HANDBOOK OF CLINICAL NEUROLOGY Series Editors
MICHAEL J. AMINOFF, FRANC¸OIS BOLLER, AND DICK F. SWAAB VOLUME 98
EDINBURGH LONDON NEW YORK OXFORD PHILADELPHIA ST LOUIS SYDNEY TORONTO 2011
ELSEVIER B.V. Radarweg 29, 1043 NX, Amsterdam, The Netherlands # 2011, Elsevier B.V. All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permissions may be sought directly from Elsevier’s Rights Department: phone: (þ1) 215 239 3804 (US) or (þ44) 1865 843830 (UK); fax: (þ44) 1865 853333; e-mail:
[email protected]. You may also complete your request on-line via the Elsevier website at http://www.elsevier.com/permissions. ISBN: 9780444520067 British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging in Publication Data A catalog record for this book is available from the Library of Congress Notice Knowledge and best practice in this field are constantly changing. As new research and experience broaden our knowledge, changes in practice, treatment and drug therapy may become necessary or appropriate. Readers are advised to check the most current information provided (i) on procedures featured or (ii) by the manufacturer of each product to be administered, to verify the recommended dose or formula, the method and duration of administration, and contraindications. It is the responsibility of the practitioner, relying on their own experience and knowledge of the patient, to make diagnoses, to determine dosages and the best treatment for each individual patient, and to take all appropriate safety precautions. To the fullest extent of the law, neither the Publisher nor the Editors assumes any liability for any injury and/or damage to persons or property arising out or related to any use of the material contained in this book. Neither the Publisher nor the Editors assume any responsibility for any loss or injury and/or damage to persons or property arising out of or related to any use of the material contained in this book. It is the responsibility of the treating practitioner, relying on independent expertise and knowledge of the patient, to determine the best treatment and method of application for the patient. The Publisher
Printed in China
Commissioning Editor: Timothy Horne/Michael Houston Development Editor: Michael Parkinson Project Manager: Janaki Srinivasan Kumar Designer: Kirsteen Wright
The Publisher's policy is to use paper manufactured from sustainable forests
Handbook of Clinical Neurology 3rd Series Available titles Vol. 79, The human hypothalamus: basic and clinical aspects, Part I, D.F. Swaab ISBN 0444513574 Vol. 80, The human hypothalamus: basic and clinical aspects, Part II, D.F. Swaab ISBN 0444514902 Vol. 81, Pain, F. Cervero and T.S. Jensen, eds. ISBN 0444519017 Vol. 82, Motor neurone disorders and related diseases, A.A. Eisen and P.J. Shaw, eds. ISBN 0444518940 Vol. 83, Parkinson’s disease and related disorders, Part I, W.C. Koller and E. Melamed, eds. ISBN 9780444519009 Vol. 84, Parkinson’s disease and related disorders, Part II, W.C. Koller and E. Melamed, eds. ISBN 9780444528933 Vol. 85, HIV/AIDS and the nervous system, P. Portegies and J. Berger, eds. ISBN 9780444520104 Vol. 86, Myopathies, F.L. Mastaglia and D. Hilton Jones, eds. ISBN 9780444518966 Vol. 87, Malformations of the nervous system, H.B. Sarnat and P. Curatolo, eds. ISBN 9780444518965 Vol. 88, Neuropsychology and behavioural neurology, G. Goldenberg and B.C. Miller, eds. ISBN 9780444518972 Vol. 89, Dementias, C. Duyckaerts and I. Litvan, eds. ISBN 9780444518989 Vol. 90, Disorders of Consciousness, G.B. Young and E.F.M. Wijdicks, eds. ISBN 9780444518958 Vol. 91, Neuromuscular Junction Disorders, A.G. Engel, ed. ISBN 9780444520081 Vol. 92, Stroke – Part I: Basic and epidemiological aspects, M. Fisher, ed. ISBN 9780444520036 Vol. 93, Stroke – Part II: Clinical manifestations and pathogenesis, M. Fisher, ed. ISBN 9780444520043 Vol. 94, Stroke – Part III: Investigations and management, M. Fisher, ed. ISBN 9780444520050 Vol. 95, History of Neurology, S. Finger, F. Boller and K.L. Tyler, eds. ISBN 9780444520081 Vol. 96, Bacterial Infections of the Central Nervous System, K.L. Roos and A.R. Tunkel, eds. ISBN 9780444520159 Vol. 97, Headache, G. Nappi and M.A. Moskowitz, eds. ISBN 9780444521392
Foreword
We spend about one-third of our life either sleeping or attempting to do so. Sleep is not only comforting, but is also essential for our normal cognitive functioning and for our survival. Yet sleep can be disturbed or abnormal in up to one-quarter of the US population. The field of sleep medicine has developed dramatically in the past few years. To reflect these advances, we are proud to introduce the present two volumes, which are a novelty in several respects. It is the first time that two Handbook volumes have been dedicated entirely to sleep and its disorders. Readers will find in these two volumes considerable emphasis on recent developments in the field. There is a new focus on diagnostic techniques, particularly imaging. Fresh attention is given to genetics and clinical aspects of sleep. Finally, there is extensive coverage of management and of new therapeutic strategies for sleep disorders. The volumes were edited by Pasquale Montagna and Sudhansu Chokroverty. As series editors, we reviewed all the chapters and made suggestions for improvement, but we are delighted that the volume editors and chapter authors produced such scholarly and comprehensive accounts of different aspects of sleep and its disorders. Hence we hope that these volumes will appeal to clinicians and neuroscientists alike. Significant new advances, particularly in terms of diagnosis and therapy, lead to new insights that demand a critical appraisal. Our goal is to provide basic researchers with the foundations for new approaches to the study of these disorders, and clinicians with a state-of-the-art reference that summarizes the clinical features and management of the many neurological manifestations of sleep disorders. In addition to the print form, the Handbook series is now available electronically on Elsevier’s Science Direct site. This should make it even more accessible to readers and should facilitate searches for specific information. We are grateful to the two volume editors and to the numerous authors who contributed their time and expertise to summarize developments in their field and helped put together these outstanding volumes. As always, we are grateful to the team at Elsevier and in particular to Mr. Michael Parkinson, Ms. Caroline Cockrell, and Mr. Timothy Horne for their unfailing and expert assistance in the development and production of these volumes. Michael J. Aminoff Franc¸ois Boller Dick F. Swaab
Preface
Sleep has been mentioned in art, literature, religion, and philosophy since antiquity, but a long period of ignorance and a lack of interest paralyzed the scientific community until recently. There has been an explosion of information about sleep medicine and sleep research in the past three decades, making it difficult to keep abreast of progress. There is therefore a need for a comprehensive book on sleep medicine and sleep science. Sleep researchers have made remarkable progress in the last century in unraveling the mysteries of sleep, including its molecular neurobiology and functional neuroanatomy. The 1930s to 1950s was an active period for sleep research, and, since the late 1990s, there has been a resurgence of interest in the neurobiology of sleep. The twenty-first century is witnessing the continuation of such progress. Advances have occurred in basic science, clinical aspects, laboratory techniques, and therapy. Advances in basic science include new understanding of the neurobiology of sleep–wakefulness, including new models of rapid eye movement (REM) sleep mechanisms; controversy about sleep states, stages, and memory consolidations; advances in the understanding of sleep–wake-dependent genes, gene products, and the circadian clock, and the role of sleep duration in mortality and morbidity; and fascinating noninvasive neuroimaging studies (particularly positron emission tomographic and single photon emission computed tomographic scans) visualizing marked changes in function in cortical and subcortical neuronal networks in different sleep states. Advances in clinical science include new understanding of the neurobiology of narcolepsy-cataplexy, restless legs syndrome, REM behavior disorders, and fatal familial insomnia. Further clinical advances have been made in our understanding of sleep apnea and heart failure, and nocturnal paroxysmal dystonia (now known as nocturnal frontal lobe epilepsy), and in describing new parasomnias and acquiring new knowledge about the genetics of sleep disorders. These clinical advances required revision of the International Classification of Sleep Disorders in 2005. New laboratory techniques (e.g., actigraphy, cyclic alternating pattern recognition and scoring in the electroencephalogram, peripheral arterial tonometry, and pulse transit time), in addition to the gold-standard techniques of polysomnography, with advances in ambulatory recordings, multiple sleep latency, and maintenance of wakefulness tests, expanded the horizon of the field of sleep medicine. Publication of the American Academy of Sleep Medicine (AASM) Manual for Scoring of Sleep and Associated Events in 2007 was a step towards standardization of the techniques. Finally, significant advances have been made in therapy, with the addition of new drugs for treating narcolepsycataplexy, insomnia, and restless legs syndrome. Considerable improvement has been made in treating central and upper-airway obstructive sleep apnea syndrome with the addition of bi-level positive airway pressure, flexible positive airway pressure, autotitrating continuous positive airway pressure, assisted servo-ventilation, and intermittent positive pressure ventilation for treating sleep-disordered breathing in neuromuscular disorders. Application of appropriately timed bright light therapy for circadian rhythm sleep disorders is also a significant therapeutic contribution of modern sleep science. It is therefore an opportune moment to produce a comprehensive volume on sleep disorders, addressing all these recent advances in basic, technical, clinical, and therapeutic issues. When we first drafted a preliminary list of topics, it immediately became obvious that a single volume, as originally conceived, would not be enough to cover the topic in the Handbook of Clinical Neurology (HCN) series. This series is widely regarded as the ultimate reference work of clinical neurology and it is found in every medical library. However, the previous two series of the HCN were organized by disease, and neither in the first nor second series was any volume specifically dedicated to sleep disorders. This absence was probably due to inadequate knowledge and awareness about sleep disorders within the context of classic neurological diseases at that time.
x
PREFACE
Despite all the progress, two vexing questions remain: What is sleep and why do we sleep? What happens if we are sleep-deprived? In animal experiments Rechtschaffen’s rats on carousel (“disk over water”), deprived of REM and non-REM sleep, lost weight despite eating excessively and died. REM-deprived rats survived longer than nonREM-deprived rats. In later experiments by other investigators using different sleep deprivation techniques, rats did not show a similar syndrome. Furthermore, adult and newborn dolphins survive with no ill effects after long periods (weeks) without sustained sleep. Awareness of the importance of sleep leads to an acceptance of sleep medicine as an independent specialty. There are new guidelines for practicing sleep medicine developed by the AASM and European Sleep Research Society. Other countries are also in the process of developing guidelines independently or in collaboration with the World Association of Sleep Medicine and other national and international organizations. In these two volumes devoted to sleep disorders, nationally and internationally known scholars, researchers, clinicians, and educators address various aspects of sleep disorders medicine to keep sleep clinicians and researchers, and all those interested in sleep, abreast of recent developments. We, the editors, owe these authors an enormous amount of gratitude for their excellent contributions, which we hope will make these two volumes authoritative reference books. They will be useful to those practicing neurology and internal medicine, especially those in pulmonary, cardiovascular, gastrointestinal, renal and endocrine specialties, and to family physicians, psychiatrists, otolaryngologists, pediatricians, dentists, psychologists, and to neurosurgeons and neuroscientists, as well as technologists, nurses, respiratory therapists, and other paraprofessionals with an interest and curiosity about the mysteries of sleep. Pasquale Montagna Sudhansu Chokroverty
Acknowledgments
We thank all of the authors for their scholarly contributions and patience in waiting to see these two volumes finally in production after a long and protracted period (beyond our control). We also thank all the authors, editors, and publishers who have granted us permission to reproduce illustrations that were published in other books and journals. We must thank Mike Parkinson, development editor for the Handbook of Clinical Neurology, for his dedication and professionalism, and the editorial and production staff at Elsevier B.V. Dr. Montagna would like to express his gratitude and love to his family and in particular to his wife, Flavia Valentini, for her continued support throughout the long time it took to edit the books, and especially for her unfailing assistance in a time of severe personal adversities. Dr. Chokroverty wishes to thank Annabella Drennan, the editorial assistant to the journal Sleep Medicine, for assisting in proofreading and corrections of many of the chapters, and, his wife, Manisha Chokroverty, MD, for her love, patience, tolerance, and continued support throughout the long period of editing and proofreading during the production of these volumes.
List of contributors
Sonia Ancoli-Israel Department of Psychiatry, University of California, San Diego, CA, USA
Chiara Cirelli Department of Psychiatry, University of Wisconsin, – Madison, WI, USA
Laurent Argaud Emergency and Intensive Care Department, Edouard Herriot Hospital, Lyon, France
Deirdre A. Conroy University of Michigan Addiction Research Center, Ann Arbor, MI, USA
Veronique Bach Laboratory DMAG-INERIS (EA 3901), Faculty of Medicine, University of Picardy Jules Verne, Amiens, France
Jana R. Cooke Division of Pulmonary and Critical Care Medicine, University of California, San Diego, CA, USA
Alexander A. Borbe´ly Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland Kirk J. Brower University of Michigan Addiction Research Center, Ann Arbor, MI, USA Peter R. Buchanan Woolcock Institute of Medical Research, University of Sydney, Department of Respiratory Medicine, Liverpool Hospital and Sleep Medicine Consultative Service, St. Vincent’s Clinic, Sydney, Australia Virginie Cardot Laboratory DMAG-INERIS (EA 3901), Faculty of Medicine, University of Picardy Jules Verne, Amiens, France
Thanh Dang-Vu Cyclotron Research Centre, University of Lie`ge, Lie`ge, Belgium Virginia de los Reyes Stanford University Sleep Medicine Program, Stanford, CA, USA Martin Desseilles Cyclotron Research Centre, University of Lie`ge, Belgium F. Dijoud Department of Pathology, Hoˆpital Femme-Me`re-Enfant, Universite´ Lyon 1, Lyon, France Alan S. Eiser Department of Neurology and Department of Psychiatry, University of Michigan Medical Center, Ann Arbor, MI, USA
Karen Chardon Laboratory DMAG-INERIS (EA 3901), Faculty of Medicine, University of Picardy Jules Verne, Amiens, France
John A. Fleetham Department of Medicine, University of British Columbia, Vancouver, Canada
Ronald D. Chervin Department of Neurology, University of Michigan, Ann Arbor, MI, USA
Nancy Foldvary-Schaefer Sleep Disorders Center, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA
xiv LIST OF CONTRIBUTORS Patrice Fort A. Kahn (deceased) UMR5167 CNRS, Institut Fe´de´ratif des Neurosciences Pediatric Sleep Unit, Children’s University Hospital, de Lyon (IFR 19), Universite´ Claude Bernard Lyon I, Free University of Brussels, Brussels, Belgium Lyon, France Ineko Kato P. Franco Department of Pediatrics, Nagoya City University Pediatric Sleep Unit, Hoˆpital Femme-Me`re-Enfant, Medical School, Nagoya, Japan SIDS Reference Center of Lyon & INSERM-628, Universite´ Lyon 1, Lyon, France Douglas B. Kirsch David Gozal Department of Pediatrics, Comer Children’s Hospital, University of Chicago, Chicago, IL, USA J. Groswasser Pediatric Sleep Unit, Children’s University Hospital, Free University of Brussels, Brussels, Belgium Ronald R. Grunstein Woolcock Institute of Medical Research, University of Sydney and Sleep Investigation Unit, Department of Respiratory and Sleep Medicine, Royal Prince Alfred Hospital, and Sleep Medicine Consultative Service, St Vincent’s Clinic, Sydney, Australia Christian Guilleminault Stanford University Sleep Medicine Program, Stanford, CA, USA Viktor Hanak Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN, USA Kristyna M. Hartse Sonno Sleep Center, El Paso, TX, USA Max Hirshkowitz Department of Medicine & Menninger Department of Psychiatry, Baylor College of Medicine, and Michael E. DeBakey VAMC Sleep Center, Houston, TX, USA Shahrokh Javaheri University of Cincinnati College of Medicine, and Sleepcare Diagnostics, Cincinnati, OH, USA
Department of Neurology, University of Michigan, Ann Arbor, MI, USA James M. Krueger Department of Veterinary and Comparative Anatomy, Pharmacology and Physiology, Washington State University, Pullman, WA, USA B. Kugener Pediatric Sleep Unit, Hoˆpital Femme-Me`re-Enfant, SIDS Reference Center of Lyon & INSERM-628, Universite´ Lyon 1, Lyon, France Carol A. Landis Department of Biobehavioral Nursing and Health Systems, University of Washington, Seattle, WA, USA Peretz Lavie Sleep Medicine Center, Rambam Hospital and Lloyd Rigler Sleep Apnea Research Laboratory, Ruth and Bruce Rappaport Faculty of Medicine, Technion- Israel Institute of Technology, Haifa, Israel P. Le´vy Pulmonary Function Test and Sleep Laboratory, Department of Rehabilitation and Physiology and HP2 Laboratory, INSERM-ERI 17, University Hospital, Grenoble, France Jean- Pierre Libert Laboratory DMAG-INERIS (EA 3901), Faculty of Medicine, University of Picardy Jules Verne, Amiens, France
Erin A. Johnson Division of Sleep Medicine, Brigham and Women’s Hospital, Boston, MA, USA
J.S. Lin INSERM-628, Institut Fe´de´ratif des Neurosciences de Lyon (IFR 19), Universite´ Lyon 1, Lyon, France
Barbara E. Jones Department of Neurology and Neurosurgery, McGill University, Montreal Neurological Institute, Montreal, Quebec, Canada
Pierre-Herve´ Luppi UMR5167 CNRS, Institut Fe´de´ratif des Neurosciences de Lyon (IFR 19), Universite´ Claude Bernard Lyon I, Lyon, France
LIST OF CONTRIBUTORS xv Jeannine A. Majde J.L. Pe´pin Department of Veterinary and Comparative Anatomy, Pulmonary Function Test and Sleep Laboratory, Pharmacology and Physiology, Washington State Department of Rehabilitation and Physiology and HP2 University, Pullman, WA, USA Laboratory, INSERM-ERI 17, University Hospital, Grenoble, France M. Mahmood Kevin R. Peters Kaiser Permanente South San Francisco Medical Department of Psychology, Trent University, Center, South San Francisco, CA, USA Peterborough, Canada Beth Malow Department of Neurology and Sleep Disorders Program, Vanderbilt University Medical Center, Nashville, TN, USA Pierre Maquet Cyclotron Research Centre, University of Lie`ge, Belgium Robert W. McCarley Neuroscience Laboratory and Harvard Department of Psychiatry, VA Boston Healthcare System, Brockton, MA, USA Enza Montemitro Department of Paediatric, Sleep Disease Centre, University of Rome “La Sapienza”-S Andrea Hospital, Rome, Italy Hawley E. Montgomery-Downs Departments of Psychology and Pediatrics, West Virginia University, Morgantown, WV, USA Tryggve Neve´us Uppsala University Children’s Hospital, Uppsala, Sweden William C. Orr Lynn Health Science Institute and Oklahoma University Health Sciences Center, Oklahoma City, OK, USA Allan I. Pack Division of Sleep Medicine and Center for Sleep and Respiratory Neurobiology, University of Pennsylvania School of Medicine, Philadelphia, PA, USA Markku Partinen Helsinki Sleep Clinic, Vitalmed Research Center, and Department of Neurology, University of Helsinki, Helsinki, Finland.
Giora Pillar Sleep Medicine Center, Rambam Hospital and Lloyd Rigler Sleep Apnea Research Laboratory, Ruth and Bruce Rappaport Faculty of Medicine, Technion- Israel Institute of Technology, Haifa, Israel A. Raoux Pediatric Sleep Unit, Hoˆpital Femme-Me`re-Enfant, SIDS Reference Center of Lyon & INSERM-628, Universite´ Lyon 1, Lyon, France David M. Rector Department of Veterinary and Comparative Anatomy, Pharmacology and Physiology, Washington State University, Pullman, WA, USA Lisa M. Richards Division of Sleep Medicine, Brigham and Women’s Hospital, Boston, MA, USA Dominique Robert Emergency and Intensive Care Department, Edouard Herriot Hospital, Lyon, France V.S. Rotenberg Department of Psychiatry, Tel Aviv University, Tel Aviv, Israel S. Scaillet Pediatric Sleep Unit, Children’s University Hospital, Free University of Brussels, Brussels, Belgium Thorsten Scha¨ffer Medical Faculty, Ruhr-University Bochum, and Institute of Clinical Physiology, Helios Klinik Hagen-Ambrock, Germany Mark S. Scher Division of Pediatric Neurology, Rainbow Babies and Children’s Hospital, University Hospitals of Cleveland, Case-Western Reserve University, Cleveland, OH, USA
xvi LIST OF CONTRIBUTORS Amir Sharafkhaneh Irene Tobler Department of Medicine, Baylor College of Medicine, Institute of Pharmacology and Toxicology, University Michael E. DeBakey VAMC Sleep Center and of Zurich, Zurich, Switzerland Methodist Hospital Sleep Diagnostic Laboratory, Houston, TX, USA Giulio Tononi Department of Psychiatry, University of Wisconsin – Carlyle Smith Madison, Madison, WI, USA Department of Psychology, Trent University, Peterborough, Canada Pierre Tourneux Laboratory DMAG-INERIS (EA 3901), Faculty of Medicine, University of Picardy Jules Verne, Amiens, Mark Solms France Department of Psychology, University of Cape Town, Rondebosch, South Africa Eus J.W. van Someren Netherlands Institute for Neuroscience, an Institute of Virend K. Somers the Royal Netherlands Society of Arts and Sciences; Division of Cardiovascular Diseases, Mayo Clinic, Department of Integrative Neurophysiology, VU Rochester, MN, USA University and Leiden Institute for the Clinical and Experimental Neuroscience of Sleep, Leiden University Alex Steiger Medical Center, The Netherlands Max Planck Institute of Psychiatry, Munich, Germany R. Tamisier Pulmonary Function Test and Sleep Laboratory, Department of Rehabilitation and Physiology and HP2 Laboratory, INSERM-ERI 17, University Hospital, Grenoble, France Frederic Telliez Laboratory DMAG-INERIS (EA 3901), Faculty of Medicine, University of Picardy Jules Verne, Amiens, France Michael J. Thorpy Sleep–Wake Disorders Center, Montefiore Medical Center, New York, NY, USA
Joyce A. Walsleben Division of Pulmonary, Critical Care and Sleep Medicine, New York University School of Medicine, New York, NY, USA John W. Winkelman Harvard Medical School and Division of Sleep Medicine, Brigham and Women’s Hospital, Boston, MA, USA
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 1
History of sleep medicine MICHAEL J. THORPY * Sleep—Wake Disorders Center, Montefiore Medical Center, and Albert Einstein College of Medicine, New York, NY, USA
Sleep; King of all the gods and of all mortals, hearken now, prithee, to my word; and if ever before thou didst listen, obey me now, and I will ever be grateful to thee all my days (Homer, 14th book of the Iliad: Mueller, 1984). Only a few physiological conditions have received as much attention from poets, novelists, scholars, and scientists as sleep. Writers from Aristotle and Ovid to Shakespeare and Dante have been fascinated by sleep and its impact upon our emotions, behavior, and health. Causes and reasons for sleep have been pondered by some of the world’s greatest minds. Regardless of what the reason is, it is likely that sleep and dreams developed in animals because they were of some evolutionary benefit. Not only has sleep evolved through the ages but the environment for sleep has also undergone a change. From communal sleeping rooms with beds of twigs, straw, or skins, the bedroom has changed in the 21st century into a private place with electronic equipment, including remote-controlled television, DVD players, internet access, and even exercise equipment. The size of bedrooms has enlarged over the years. A rudimentary understanding of insomnia and sleepiness was known in ancient times, but specific sleep disorders, such as narcolepsy, began to be recognized only in the late 19th century. Differentiation between causes of sleepiness and insomnia has reached a peak within the last 50 years since the development of sophisticated technology for the investigation of sleep. Although most sleep disorders have probably been present since humans evolved, modern society has inadvertently produced several new disorders. The electric light bulb, developed by Thomas Edison, has allowed the light of day to be extended into night so that shift work can now occur around the clock, but at the expense of circadian rhythm disruption and
*
sleep disturbance. Similarly, international jet travel has enabled the rapid crossing of time zones, which also can lead to a disruption of circadian rhythms and to sleep disturbance. Scientific investigation has produced more information on the physiology and pathophysiology of sleep in recent years than ever before. This rapid advance in sleep research and the development of sleep disorders medicine are producing answers to questions that date from antiquity.
SLEEP IN PREHISTORIC AND ANCIENT TIMES Sleep’s the only medicine that gives ease (Sophocles, Philoctetes: Lloyd Jones, 1994). The sleep patterns and sleep disorders of prehistoric humans are unknown, and therefore we must speculate from the comparative physiology of animals and from evidence of other behaviors and illnesses. Theories on the phylogenetic development of sleep stages in mammals have been developed from information available on the mammal-like reptiles. The earliest form of life developed about 600 million years ago in the pre-Cambrian period, and mammal-like reptiles evolved approximately 250 million years ago. The monotremes (egg-laying mammals) evolved as a separate line from the therian (live-bearing) mammals about 180 million years ago. It is about this time when it is believed that slow-wave sleep appeared; rapid eye movement (REM) sleep (paradoxical sleep) appeared about 50 million years later. Recent sleep research on one of the three surviving monotremes, the Australian short-nosed echidna and platypus, has provided some of the evidence for the evolution of sleep stages. The monotremes have high-voltage REM sleep, which suggests that REM sleep may have had its origin in reptilian ancestors (Karmanova, 1982; Siegel et al., 1998).
Correspondence to: Michael J. Thorpy, M.D., Sleep–Wake Disorders Center, Montefiore Medical Center, 111 East 210th Street, Bronx, NY 10467, USA. Tel: 718-920-4841, Fax: 718-798-4352, E-mail:
[email protected]
4
M.J. THORPY
The pattern of sleep and waking behavior in prehistoric humans can be deduced from studies of animal groups phylogenetically closest to humans, namely nonhuman primates, such as apes and Old World monkeys. Sleep–wake patterns in nonhuman primates consist mainly of polyphasic episodes of rest and activity with frequent (up to 12) cycles of wakeful activity throughout the 24-hour day. Humans have the most developed monophasic pattern, with one episode of consolidated sleep and one main episode of wakefulness. Some animals, e.g., the chimpanzee, have a biphasic sleep–wake pattern, with a nap taken during the daytime. The chimpanzee has a rather prolonged sleep episode from dusk to dawn of approximately 10 hours; however, during this time there are frequent, brief awakenings. The daytime is characterized by two long episodes of wakefulness and an approximately 5-hour midday nap, which also includes frequent, brief wakefulness episodes. This type of sleep pattern may have the advantage of providing some security from predators. Extrapolating from nonhuman primate studies, it seems likely that a similar polyphasic sleep pattern was likely to have been present in earliest humans (prior to the Neolithic period), particularly if they also attempted to sleep between dusk and dawn. There would have been frequent awakenings during the major sleep episode, as a single sleep episode of more than 10 hours appears unlikely. The monophasic sleep–wake pattern probably began in the latter part of the Neolithic period (since 10 000 BC). Neanderthal humans (70 000–40 000 BC) may well have been in a transitional stage between a polyphasic sleep pattern and the monophasic pattern seen today. Prehistoric humans may have attempted to treat sleep disturbances, but how early they would have done this is unknown. Therapy probably resembled that utilized by sick animals, such as the removal of infective agents, eating various plants to induce emesis, and possibly even bloodletting. Bloodletting became an increasingly frequent therapeutic means for treating disease, including sleep disorders, in more advanced ancient civilizations. Primitive societies, even today, consider many illnesses and diseases to be caused by gods, magic, and spirits, and therefore various forms of divination, such as the casting of bones, moving of beads, charms, fetishes, chanting or the use of elaborate ceremonies, are invoked for therapeutic reasons. For disturbances of sleep and wakefulness, prehistoric humans probably applied similar forms of treatment.
Ancient Egypt
which was written around 1350 BC, contains information on the interpretation of dreams. Dreams were regarded as being contrary predictions; for example, a dream of death meant a long life. However, an extensive text on a variety of medical subjects, including treatment, the Georg Ebers papyrus (1600 BC), has not been reported to contain any information on sleep disturbances. Ancient Egyptian medical practice consisted largely of praying to the gods and invoking the help of these divine healers. Thoth, who was a physician to the gods, and Imhotep were both important gods of healing at that time. The ancient Egyptians were known for their attention to hygiene and cleanliness, and it is likely that such attention was also paid to sleeping habits. Medical opinion at the time held that the body was made up of a system of channels (Metu), which conveyed air to all parts of the body. Because they believed that bodily fluids could enter this system of channels, the ancient Egyptians were particularly concerned about feces entering the Metu. Hence, purging and enemas were the treatment modalities of many illnesses of that time, which included infective illnesses, such as malaria, parasitic infections, smallpox, and leprosy. Wine and other mildly alcoholic drinks (as compared to distilled alcoholic products) were consumed in large amounts and were probably the earliest treatments for insomnia but also may have been important in its development. Medicinal plants were utilized, particularly the product of the opium poppy (Papaver somniferum), and hyoscyamine and scopolamine, derived from belladonna and nightshade (Gunther, 1959). The word “opium” is derived from the Greek word for “juice,” as the drug is derived from the juice of the poppy. Papaver somniferum was coined at a much later date; somniferum was derived from the Latin word Somnus (the Roman god of sleep). In subsequent periods in history opium (laudanum) was widely used as a treatment for insomnia, and it is likely that it was used as far back as the Sumerian age. Accordingly, opium may have been the first hypnotic medication used. Another common treatment performed by the ancient Egyptians for a variety of ailments and illnesses was bloodletting. This was likely to have been used for sleep disorders, particularly for those disorders that produced excessive sleepiness or stupor. Medical treatment by physicians was widely available during this time. In fact, the names of several hundred physicians have been documented in ancient Egypt. Herodotus (fifth century BC) wrote of the Egyptians:
Most of our current knowledge of ancient Egyptian medicine derives from the ancient medical papyruses of Egypt (Ebbell, 1937). The Chester Beatty papyrus,
Medicine with them is distributed in the following way: every physician is for one disease and not for several, and the whole country is full of
HISTORY OF SLEEP MEDICINE physicians for the eyes; others of the head; others of the teeth; others of the belly, and others of obscure diseases (Grene, 1987). It appears likely that some physicians specialized in insomnia, and possibly even in disorders that produced excessive sleepiness. There certainly were physicians who specialized in dream interpretation, for example Artemidorus of Daldis, who wrote the major work on dreams, Oneirocritica (White, 1975).
Ancient India Other civilizations, such as those of ancient India and China, developed around the same time. In India, as in Egypt, infective illnesses were common, and therefore physicians, who were largely from the Brahman or priestly caste, were viewed with great importance. Medical practice mainly consisted of magical and religious practices but also featured soundly based, rational treatments. Over 700 Indian vegetable medicines have been documented from ancient times and include the plant called Rauwolfia serpentina (reserpine). Rauwolfia was used for the treatment of anxiety (and is currently being used for hypertension in some parts of the world) among other disorders, and is likely to have been used to treat insomnia (its side-effects include drowsiness).
Ancient China The ancient Chinese viewed sleep as a state of unity with the universe: everything is one; during sleep the soul undistracted, is absorbed into the unity; when awake, distracted it sees the different beings (Chinese philosopher Chuang Tzu, 300 BC: Palmer et al., 2006). The ancient Chinese believed in the importance of the universe and environment in producing all things, including behavior and health. The basic principles of life were thought to derive from the interplay of two basic elements in nature, the active, light, dry, warm, positive, masculine yang, and the passive, dark, cold, moist, negative yin. The proportions of yin and yang determined the Tao (the way), which determined right and wrong, good and bad, health or illness. The basic yin–yang symbol is attributed to Fu Hsi (c. 2900 BC), who originated the concept of eight interacting conditions, the “Pa kua.” The yin–yang has since become the symbol for sleep and wakefulness. (This yin–yang symbol has been adopted by the American Academy of Sleep Medicine as its emblem.) Chinese views on physiology were similar to those of the ancient Greeks;
5
they also believed in a humoral system of physiology. The palpation of the pulse was important in the diagnosis of disease, as were the patient’s symptoms, the patient’s social and economic status, the weather, and particularly the patient’s dreams, as well as the dreams of other family members. These were all taken into consideration to determine whether a patient had upset the Tao. The most important medical compendium of the time was that produced by Yu Hsiung (c. 2600 BC), the Nei Ching (Canon of Medicine). There is a great deal of controversy over the authorship of this text. It mentioned five important methods of treatment: curing the spirit, nourishing the body, the administration of medications, treating the whole body, and the use of acupuncture and moxibustion (counterirritation by moxa, a combustible substance that is burned on the skin). Acupuncture and a modified form of moxibustion are used today for the treatment of insomnia and other sleep disturbances in traditional Chinese medicine. When these therapies were first established (at least since c. 2600 BC), it follows that they were most likely applied to sleep disorders as well. Massage and breathing exercises were also commonly employed for various reasons, in a manner similar to yoga – these are therapies regularly used today for the treatment of some types of insomnia. In addition to acupuncture, moxibustion, massage, and breathing exercises, the ancient Chinese had a plethora of herbal medicines. Herbal medicines consisted of extracts of virtually anything available, including minerals and metals, animal-derived products, and waste products (Gunther, 1959). Two of these herbal remedies are worth noting. One was ephedra (Ma Huang), which is believed to have been used for over 4000 years. It is a stimulant that contains ephedrine, derived from the horsetail plant and first described by the Red Emperor, Shen Nung (c. 2800 BC). Ancient Chinese physicians used it for the treatment of asthma, hayfever, and nasal and chest congestion. It is reasonable to believe that it may have been used for the treatment of other breathing disorders of sleep as well. The second common medicinal herb was ginseng (a man-shaped root), which was used for a variety of ailments, including pulmonary problems and gastrointestinal disorders. It is also thought to heighten vitality and reduce fatigue and sedation (its role in excessive somnolence due to many causes including sleep disorders is thus apparent). Acupuncture was widespread and is believed to have been developed by the Yellow Emperor (Huang Ti) around 2600 BC (Veith, 1949). Acupuncture and moxibustion were used for treating virtually every illness and symptom and therefore may well have been administered for sleep disorders.
6
M.J. THORPY
Ancient Greece Much of what we know about early Greek medicine is derived from the Iliad and Odyssey of Homer, a collection of traditions, legends, and epic poems. Homer (c. 900 BC) based his epic works on the life of the ancient Greeks in the days of the Mycenaean Citadel of about 1200 BC. The Mycenaeans, who came from mainland Greece about 1600 BC, conquered the Minoans, who had established a well-developed civilization in Crete at Knossus. This civilization was the setting for Homer’s epics, which concerned an earlier period, but his writings included medical details that were probably derived from his own era. However, Homer’s view of medicine in early Greece, called homeric medicine, is the best representation of early Greek medical practices. The quotation from the Iliad stated at the beginning of this chapter reflects the importance that Homer ascribed to good-quality sleep. The god of sleep, Hypnos, from whom the terms hypnotic and hypnotism have derived, was first reported in the 14th book of the Iliad by Homer, and was mentioned again in the Theogony of Hesiod (c. 700 BC) about two centuries later (Wittern, 1989). Also mentioned in Homer was the chieftain Asclepios and his two sons, Machaon, who in subsequent centuries became known as the father of surgery, and Podalirios, the father of internal medicine (Figure 1.1). In subsequent years, Asclepios became known as the god of healing, and temples were erected in his honor, the first being established about the sixth century BC in Thessaly or Epidauros. The Asclepieian temples were a collection of several buildings that in many cases were very elaborate and ornate. They consisted of a tholos, a round building that contained water for purification, and a main temple, which were separated by a building called the abaton. The abaton was a most important structure as it was the site where ill patients were placed for a cure. The cure consisted of an “incubation” ceremony in which the cure took place in each worshipper’s dreams. The medical ceremony began at dusk and the ill patient lay on a bed of skins to await a visit by Asclepios, the god of healing. During the night the priest would visit each patient and administer a treatment, which often consisted of medicines derived from animals such as snakes and geese. Upon awakening the next morning after dreaming of Asclepios, the patient was expected to have been cured. This treatment was clearly the forerunner of sleep therapy, which has been practiced through the ages until the present day, particularly in eastern countries. Although Asclepieian medicine was used to treat any type of illness, it was most effective for those of a psychological nature. Much of the healing was probably related to
Fig. 1.1. Asclepios.
the impressive ceremony and the relaxation that occurred in conjunction with the setting. The priestphysicians instilled faith in the cures, not only to their patients but also to themselves. However, many attempted cures were in the realm of magic and fantasy. A more rational style of medicine developed around the fifth century BC largely due to the influence of the Greek scientist-philosophers. Alcmaeon (fifth century BC), of the Crotona school of medical thought, concentrated on humans, and his basic belief was that health was harmony and disease was a disturbance of harmony (Freeman, 1966). He considered the brain essential for memory and thought, a notion that Aristotle, who believed that the mind resided in the heart, would reject 100 years later. Alcmaeon proposed what was probably the first theory on the cause of sleep, when he postulated that sleep occurred when the blood moved away from the surface of the body to the deeper vessels, including those going to the brain; withdrawal of blood from the brain and inner vessels was associated with waking. However, his major contribution to medicine
HISTORY OF SLEEP MEDICINE was the detailed description of the optic pathways at the base of brain. His much more rational concepts of medicine have led some to consider him the first true medical scientist. Around the time of Alcmaeon, a center of medicine was established in Sicily, and Empedocles (c. 493–443 BC) was credited with the original concept that all things are composed of four basic elements: water, air, fire, and earth (the importance of these four elements had been established earlier: Freeman, 1966). Empedocles believed that sleep occurs when the fire in the blood cools, thus separating one of the four elements from the others. He believed that illnesses were due either to separation of the four elements or to alterations in their balance. The principle of the balance of body humors, known as humoralism, became established medical doctrine around this time. Humoralism considered health to be due to the balance of four body fluids: blood, phlegm (water), yellow bile (“choler,” secreted by the liver) and black bile (“gall,” secreted by the spleen and kidneys). These fluids were usually seen during severe illnesses and disappeared when the crises were over. In whatever disease sleep is laborious, it is a deadly symptom (Hippocrates, Aphorisms II: Adams, 1891). Hippocrates (460–370 BC), born on the island of Cos, has had more influence upon medicine than any other individual in history. He produced many of the basic tenets that underlie the practice of modem medicine. Hippocrates produced numerous works that are gathered under the title Corpus Hippocraticum, which comprises not only his own writings but also the writings of others of the time (Chadwick et al., 1978). His approximately 72 books covered all aspects of medicine, including medical ethics, and are most widely known for the hippocratic oath. In his writings, Hippocrates discussed not only his theory of the cause of sleep, but also made suggestions on the cause of dreams, which he considered to be of “medical” origin. Hippocrates stated that: “sleep is due to blood going from the limbs to the inner regions of the body.” This statement was based upon the recognition of the importance of the blood being warmed by the inner part of the body in order to produce sleep. Hippocrates also alluded to some diseases of sleep of the time when he spoke of epilepsy (which appear to be descriptive of sleep apnea and the non-REM arousal disorders): I have known many persons in sleep groaning and crying out, some in a state of suffocation, some jumping up and fleeing out of doors, and deprived of their reason until they awaken, and
7
afterward becoming well and rational as before, although they be pale and weak; and this will happen not once but frequently (Adams, 1891). Hippocrates believed that narcotics derived from the opium poppy could be useful in treatment; therefore, they were most likely applied to treat insomnia at that time. Other philosophers, such as Diogenes (c. 480 BC) and Heraclitus (c. 450 BC), believed sleep was an incomplete “humidification of the bodily soul” and death was the complete humidification. Following these philosophers, Aristotle (384–322 BC), had an important influence upon medicine. He believed that dreams were important predictors of the future but proposed a theory of sleep based upon the effect of food ingestion (Hett, 1964; Wijsenbeek-Wijler, 1978). He proposed that food, once eaten, induced fumes that were taken into the blood vessels and then transferred into the brain where they induced sleepiness. The fumes subsequently cooled and returned to the lower parts of the body, taking heat away from the brain, thereby causing sleep onset. The sleep process continued as long as food was being digested.
Ancient Rome Greek medicine began to develop in Rome around the time of Hippocrates. Atomism, the concept that all physical objects are comprised of atoms in an infinite number that undergo random motion, was first developed by Democritus of Abdera (c. 420 BC) and Leucippus of Miletus (c. 430 BC). Leucippus regarded sleep as a state caused by the partial or complete splitting-off of atoms. Democritus considered insomnia to be the result of an unhealthy diet and daytime sleeping as being a sign of ill health. Epicurus (c. 300 BC) revived the theory of atomism and wrote extensively on sleep and dreams, although his own works have been lost. The Roman poet Titus Lucretius Carus (c. 50 BC) wrote of the teachings of Epicurus on atomism, sleep, and dreams in a poem entitled “De rerum natura.” In this poem, the loss of central control that leads to loss of peripheral muscle control and relaxation forms the foundation of a neural theory of sleep that took 2000 years to be expanded upon: And so, when the motions are changed, sense withdraws deep within. And since there is nothing which can, as it were, support the limbs, the body grows feeble, and all the limbs are slackened; arms and eyelids droop, and the hams, even as you lie down, often give way, and relax their strength (On the Nature of the Universe: Lucretius, 1994). Asclepiades of Bithynia (c. 120–70 BC), another figure in Roman medicine, believed that the physician was
8
M.J. THORPY
more important in curing disease than was nature. He used the term “phrenitis” for mental illness and invoked treatment that consisted of hygiene, opium, and wine. He was also the first to popularize the tracheostomy as a treatment for upper-airway obstruction resulting in apnea. The Greek philosopher and physician Galen (AD 129–c. 200) had a great impact on the development of medicine. Galen’s detailed writings substantially contributed to the knowledge of anatomy and he also outlined the important elements of diagnosis and treatment (Siegel, 1973, 1976). He believed bloodletting was important in the treatment of many illnesses, but he also encouraged conservative treatments, such as diet, rest, and exercise. He also spoke about dream interpretations and utilized many herbal medicines, e.g. valerian for the treatment of insomnia. In both ancient Rome and ancient Greece the similarity between death and sleep was often emphasized. Sleep and death, who are twin brothers (Homer, Iliad, c. 850 BC: Mueller, 1984). What else is sleep but the image of chill death? (Ovid, Amores 11, 43 BC–AD 17: Simpson, 2001).
Sleep in the Bible Similarly, in the Bible, death was described as being similar to sleep in that it was God who caused people to awaken from sleep; without Him they would never wake (Psalms 76:6). However, death was also contrasted with sleep in the example of a dead girl, about whom Christ said, “the little girl did not die but she is sleeping” (Matthew 9:24; Mark 5:39; Luke 8:52). This may have referred to the fact that she could be resurrected from death as one is awakened from sleep. The Bible also contains numerous references to sleep and dreams, which were largely regarded as being predictors of the future (but less significant than in previous eras) (Mackenzie, 1965). Dreams also played an important part in the Bible as a means of communication between God and mankind. The first book of the Bible, Genesis (28: 10–16), reports communication between Jacob and God: And Jacob went out from Beresheeba, and went toward Haran. And he lighted upon a certain place, and tarried there all night, because the sun was set; and he took one of the stones of that place and put them for his pillows, and laid down in that place to sleep.
And he dreamed, and behold a ladder set up on the earth, and the top of it reached to heaven: and behold the angels of God ascending and descending on it . . . And Jacob awaked out of his sleep, and he said, surely the Lord is in this place; and I knew it not. Many other examples of dreams are presented in the Bible, such as Joseph’s dream to take Mary as his wife, his dream to flee to Egypt with his family, the dream that it was safe to return home, and the dream of the Magi. Excessive sleeping was regarded as being unacceptable as it produced laziness and could subsequently lead to poverty. Laziness causes a deep sleep to fall (Proverbs 6:9–11, 10:5, 19:15, 20:13, 24:33–34).
SLEEP IN THE MIDDLE AGES AND THE RENAISSANCE Long sleep at after-noones by stirring fumes Breeds Slouth, and Agues Aking heads and Rheumes (School at Salerno, Regimen Sanitatis Salernitanum, 1095–1224: McVaugh, 1980). The time from the fall of Rome in AD 476 until the fall of Constantinople in AD 1453 is often referred to as the Middle Ages, the first 500 years being the Dark Ages. Both Ages comprise the medieval period, the Age of Faith, a time when medicine was greatly influenced by the rise of Christianity. With the spread of the word of Christianity, people were convinced that the day of judgement was about to come, and disease was considered to be God’s punishment. Prayer and good deeds were considered to be important for cures and to prevent illness. Concern for “thy neighbor” led to the establishment of facilities for the care of the ill, most of which were run with religious motives. Medicine involved strong religious mysticism, and there was a loss of the rational, clinical observation and management of disease that had begun to develop in earlier years. Although superstition and magic swept the western world, some physicians such as Avicenna, with skill in observation and deduction, slowly advanced medical knowledge. In the Muslim world, there was a similar religious approach to medicine. Although in Islam, disease was regarded as a punishment by Allah, hospitals in Muslim countries were very much better than those in the west because of their improved sanitation and better and more spacious facilities. At that time physicians
HISTORY OF SLEEP MEDICINE were largely of the Christian and Jewish faiths, but Muslim practitioners gradually helped spread medicine in the east. The Persian Razi (850–c. 923), also known as Rhazes in the west, wrote more than 200 books on many topics, including medicine (Ranking, 1914). Avicenna (980–1037 AD), who also contributed to medical understanding, was regarded both in Islam and Christendom as being of equal importance to Galen (Gruner, 1930, 1970). Included among his many contributions to medicine are the associations between epilepsy and insomnia and sleep deprivation. In the latter part of this era, Moses ben Maimon (1135–1204 AD), also known as Maimonides, emerged as the most influential Jewish physician in Arabic medicine. He appeared to combine the thoughts of Hippocrates, Galen, and Avicenna but his primary focus was on philosophy. Maimonides had his own view of how much and when a person should sleep: The day and night consist of 24 hours. It is sufficient for a person to sleep one third thereof which is eight hours. These should [preferably] be at the end of the night so that from the beginning of sleep until the rising of the sun will be eight hours. Thus he will arise from his bed before the sun rises (Mishneh Torah, Hilchoth De’oth, ch. IV, no. 4). In the 10th century AD, several medical schools came into prominence. Perhaps the first was that established at Salerno, not far from Monte Cassino. The school at Salerno developed a practical scientific approach to medicine, eschewing its neighbors’ concentration on philosophy and religious mysticism. Several universities in France, including those at Montepellier and Paris, were also highly regarded. At Paris, the school had a medical rather than a surgical bias, being more influenced by the church. At Montpellier, Greek practices were more in evidence. By AD 1000, at the end of the Dark Ages, monastic medicine began to decline as the influence of the universities increased. Many hospitals developed that are well known today, such as St. Thomas’s and St. Bartholomew’s in England and the Hoˆtel-Dieu in Paris. Diet was regarded as an important form of treatment, as were medications, particularly those derived from plant materials. One of the most commonly used medications at this time was theriac, which had been developed in the first century AD; it consisted of many substances derived from plants and animals, including snake flesh. Theriac would have been used for the treatment of a variety of sleep disorders, particularly those thought to be caused by poisons. Mysticism and astrology were important elements of medicine in the Middle Ages. Often the most important treatment to be considered
9
was exorcism; however, purgatives and bloodletting were treatments that were still commonly employed. In the 15th and 16th centuries, the works of Hippocrates were revived. Paracelsus (1493–1541), known as the father of pharmacology, began using metals in treatment, often producing some outstanding cures (Pachter, 1951). Although illnesses such as leprosy and the plague had largely disappeared, venereal diseases such as gonorrhea and syphilis were rampant. Paracelsus created a remedy that he believed to be “superior to all other heroic remedies” which he called laudanum. Laudanum was originally an extract of opium with brandy combined with other seemingly random ingredients, such as frogspawn. Among other purposes, this potion was used to induce sleep. Art and medicine became allied, as evidenced in the anatomical drawings of Michelangelo Buonarroti (1475–1564) and Albrecht Du¨rer (1471–1528). Andreas Vesalius (1514–1564) produced one of the greatest medical books in history, De Humani Corporis Fabrica (O’Malley, 1965). Its detailed anatomical drawings surpassed those of Galen and Fabricius, and it became the anatomical cornerstone of scientific medicine in the centuries to come.
SLEEP IN THE 17TH AND 18TH CENTURIES Methought I heard a voice cry, “Sleep no more! Macbeth does murder sleep,” the innocent sleep, Sleep that knits up the ravell’d sleeve of care, The death of each day’s life, sore labour’s bath, Balm of hurt minds, great nature’s second course, Chief nourisher in life’s feast (Shakespeare: Macbeth, Act II, c.1605: Coursen, 1997). In the 17th century, medicine underwent a major change from the doctrines that had influenced it up to that time, such as aristotelianism, galenism, and paracelsianism, to more scientifically directed theories, with the underlying teleological desire to accumulate knowledge on the way things work. This time was known as the Age of Scientific Revolution and included the major medical developments of Francis Bacon, William Harvey, and Marcello Malpighi. Medicine in general was now being viewed as an advancement in our control over nature and was more soundly based on scientific principles. However, it was still a time to be speculative and philosophical about medicine: He sleeps well who knows not that he sleeps ill (Francis Bacon, Omamenta Rationalia, IV; quote from Publilius Syrus, Sententiae: Wight Duff and Duff Arnold, 1994).
10
M.J. THORPY The scientific revolution began with the theories of when being abed, they betake themselves to Rene´ Descartes (1596–1650), who rejected Aristotle’s sleep, presently in the arms and legs, leapings doctrines and developed theories based on mechanisms and contractions of the tendons, and so great a (Descartes, 1632). In this regard he was similar to restlessness and tossings of their members ensue, Francis Bacon (1561–1626), who espoused experimentathat the diseased are no more able to sleep, than tion and utilitarianism. Descartes developed a hydrauif they were in a place of the greatest torture lic model of sleep, which considered that the pineal (Willis, 1684). gland maintained fullness of the cerebral ventricles Willis also discovered that laudanum, a solution of for the maintenance of alertness. The loss of “animal powdered opium, was effective in treating the spirits” from the pineal causes the ventricles to colrestless-legs syndrome. lapse, thereby inducing sleep. Despite some setbacks, a scientific approach to The chemical principles of Paracelsus were advanced medicine continued with the works of Linnaeus and in the 17th century, and medicines, including the use of von Haller. Karl von Linne (1707–1778), called Linnaeus, mercurials, began to take over from treatments such as made important contributions to the classifications of purging and bloodletting. Illness was now considered botany, zoology, and medicine (Linnaeus, 1751). He to be something that attacked the body in a distinct emphasized the importance of cyclical changes in botmanner, and the galenic and earlier concepts that disease any, which was nowhere more clearly presented than was a derangement of humors, the essential elements of in his flower clock. The flower clock was developed the body, were starting to fade. Atomism, which had upon the principle that different species of flowers been proposed by Democritus, Leucippus, and Epicurus open their leaves at various times of the day. Thereseveral centuries before the time of Christ, underwent a fore, a garden of flowers arranged in a circular patrevival in the 17th century and was supported by the findtern could give an estimate of the time of day by ings of Jan Baptista van Helmont (1577–1644), who the pattern of flower and leaf openings and closings. coined the term “gas” and recognized that air was comLinnaeus’ finding was an important early milestone in posed of a variety of gases. Robert Boyle (1627–1691) the development of the science of biological rhythms demonstrated the importance of air for life and the in plants and animals. As far back as ancient Greece effect of gases under pressure, which led to the discovthere had been some recognition of variation in the ery that the reddening of venous blood occurred because behavior of plants and animals, not only on a seaof exposure of blood to gases contained in the air. Howsonal basis but also on a daily basis. ever, the major discovery of the 17th century was that of One of the first chronobiological experiments was William Harvey (1578–1657), who was the first to demthat of Sanctorious (c. 1657), who measured the cyclionstrate that blood was pumped around the body by cal pattern of change in a number of his own physiothe heart. logical variables. His experimental apparatus has been It was against this background that the great neurolregarded as the first “laboratory for chronobiology.” ogists, Thomas Willis (1621–1675) and Thomas SydenSubsequently the intrinsic pattern of circadian activity ham (1624–1689), developed the principles and was demonstrated in the experiment performed by practice of clinical neurology. Willis made a number Jacques de Mairan in 1729, which was reported by of contributions to the knowledge of various disorders M. Marchant (de Mairan, 1729). De Mairan placed a in sleep, including restless-legs syndrome, nightmares, heliotrope plant in a darkened closet and observed and insomnia. He recognized that a component that the leaves continued to open in darkness, at the contained in coffee could prevent sleep and that sleep same time of day as they had in sunlight. This experiwas not a disease but primarily a symptom of underlyment illustrated the presence of an intrinsic circadian ing causes. His book The Practice of Physick devoted rhythm in the absence of environmental lighting confour chapters to disorders producing sleepiness and ditions. De Mairan also recognized the importance insomnia (Willis, 1684). Like Descartes, he considered of this observation for understanding the behavior of that the animal spirits contained within the body patients: undergo rest during sleep. However, he believed that those animal spirits residing in the cerebellum became this seems to be related to the sensitivity of a active during sleep to maintain a control over physiolgreat number of bed-ridden sick people, who, ogy. He believed that some of the “animal spirits” in their confinement, are aware of the differbecame intermittently unrestrained, leading to the ences of day and night. development of dreams. He also described restless-legs syndrome, which he considered to be an escape of the During the 17th and 18th centuries, medical schools animal humors into the nerves supplying the limbs: had rapidly expanded throughout Europe, with those
HISTORY OF SLEEP MEDICINE north of the French–Italian Alps beginning to gain in prominence. The Swiss-born scientist Albrecht von Haller (1708–1777), a pupil of Boerhaave of the University of Leiden, an important medical center in Europe, made major contributions to many scientific topics, including medicine. Von Haller performed numerous experiments on the nervous system and demonstrated the sensitivity of nerve and the irritability of muscle; in doing so he dispelled much of the mysticism of previous eras. Von Haller produced a major work entitled Elementa Physiologiae in which he devoted 36 pages to the physiology of sleep and proposed a theory for its cause (von Haller, 1766). In a vascular concept, similar to that of Alcmaeon in the fifth century BC, von Haller believed that sleep was caused by the flow of blood to the head, which induced pressure on the brain, thereby inducing sleep by cutting off the “animal spirits.” Von Haller derived his beliefs from the views of his mentor Hermann Boerhaave (1667–1738). Von Haller’s theory was expanded in the 19th century into the congestion theory of the causes of sleep, a theory that was still believed into the early part of the 20th century. He also considered dreams to be a symptom of disease, “a stimulating cause, by which the perfect tranquility of the sensorium is interrupted.” The late 17th century was also the time of the discovery of oxygen by Karl Scheele (1742–1786) and Joseph Priestley (1733–1804), but it was Antoine-Laurent Lavoisier (1743–1794) who coined the name “oxygen” and recognized its importance in the maintenance of living tissue. Despite the important advances in clinical medicine that occurred in the 17th century, there were very few therapeutic advances. Medications still consisted of potions developed from plant and animal tissues, and opium was still the main form of sedation, in a common formulation called “Hoffmann’s anodyne of opium.” The ancient practices of bleeding and purging continued to be widely prescribed throughout the 18th century. It was not until the late 1700s that the greatest advance was made in the development of sleep medicine. It occurred in Bologna with Luigi Galvani’s (1737–1798) demonstration of electrical activity of the nervous system. His findings led to the subsequent development of the field of electrophysiology, and the gradual destruction of the humoralist theory of nervous activity. With the development of the scientific approach to medicine, the discovery of atomism, animal electrophysiology, the advances in respiratory and cardiovascular physiology, as well as treatment advances, such as quinine for malaria and digitalis for heart disease, medicine was about to enter its modern era, the 19th century.
11
SLEEP IN THE 19TH CENTURY What probing deep Has ever solved the mystery of sleep? (Thomas Aldrich (1836–1907), Human Ignorance: Aldrich, 1876). The 19th century could be regarded as the “age of sleep theories” as some of the greatest physicians, psychologists, and physiologists turned their attention to explanations of the cause of sleep. Advances were made in the clinical recognition of sleep disorders, particularly the causes of daytime sleepiness, and several comprehensive books were written entirely on the physiological and clinical aspects of sleep. Much of what was known about insomnia and its causes, however, was only a slight expansion of earlier knowledge. There were major advances in understanding the cause of sleep, and in the latter half of the century a number of specific sleep disorders were recognized. The anatomy of sleep and wakefulness was partially revealed through the animal experiments of two outstanding neuroanatomists of the time, Luigi Rolando (1773–1831) and Marie Jean Pierre Flourens (1794–1867). Rolando in 1809 demonstrated that a state of sleepiness occurred when the cerebral hemispheres of birds were removed. His experiments were replicated by Flourens in 1824 with the ablation of the cerebral hemispheres of pigeons: Just imagine an animal which has been condemned to be permanently asleep, one that has been devoid even of the ability to dream during sleep; this is more or less the situation of the pigeon in which I had ablated the cerebral hemispheres (Flourens, 1824). The theories of the cause of sleep can be placed into four main groups: vascular (mechanical, anemic, congestive), chemical (humoral), neural (histological) and a fourth group, which explains the reason for sleep rather than the physiological cause of sleep, the behavioral (psychological, biological) theories. The vascular theories of sleep were those most widely disputed in the early part of the 19th century. They were based upon the first rational theory for the cause of sleep, proposed by Alcmaeon in ancient Greece in the fifth century BC (Wittern, 1989). Alcmaeon believed that sleep is caused by blood filling the brain and waking associated with the return of blood to the rest of the body, a concept consistent with the notions of ancient times, when it was recognized that brain disorders such as apoplexy were associated with stupor (karos). Hippocrates had an alternative theory; he believed that sleep is due to blood flowing in the opposite direction, from the limbs to the central part of the body
12 M.J. THORPY (Chadwick et al., 1978, p. 8). Von Haller, in the 18th Alexander Fleming supported the anemia theory after century, agreed with Alcmaeon’s concept and prohe performed an experiment in which he occluded the posed that blood going to the head causes the brain carotid arteries and induced a sleep-like state. One of to be pressed against the skull, thereby inducing sleep the strongest advocates for the anemia theory was by cutting off the “animal spirits.” Von Haller derived Frans Cornelius Donders (1818–1889), a professor at his beliefs from the views of his mentor, Hermann Utrecht in Holland, who carefully observed the cereBoerhaave (1667–1738), who had presented a similar bral circulation in animals through windows placed in theory a few years earlier, in 1750. These theories the skull (Donders, 1849). Donders and subsequently described the cause of sleep to be related to the blood Angelo Mosso (1826–1910), who observed the cerebral vessels, either congestion (pressure of blood) in the circulation in humans with skull defects, believed that brain or anemia (lack of blood) in the brain. Johann at sleep onset blood passed from the brain to the skin Fredreich Blumenbach (1752–1840), professor at (Mosso, 1880). Arthur Edward Durham (1833–1895), Go¨ttingen, who is regarded as the founder of modern who wrote extensively on the topic in 1860, believed anthropology, was the first to observe the brain of a that the blood passed from the brain during sleep not sleeping subject in 1795 (Blumenbach, 1795). He noted only to supply the skin but also to supply the internal that the surface of the brain was pale during sleep organs (Durham, 1860). compared with wakefulness; contrary to earlier theOne of the final advocates for the anemia theory of ories, he proposed that sleep was caused by the lack sleep was the physiologist William Henry Howell of blood in the brain. It was against this background (1860–1945). Howell believed that the change in arterial of early sleep theories that the 19th-century researchers blood pressure at the base of the brain was responsible looked for the cause of sleep. for cerebral anemia (Howell, 1897). Sir Leonard The theory that sleep was due to congestion of the Erskine Hill (1866–1952) extensively studied the cerebrain was the most accepted vascular theory in the first bral circulation, and in 1896 reported the absence of a half of the 19th century. Robert MacNish wrote a semchange in cerebral blood pressure during sleep (Hill, inal volume on sleep and its disorders, entitled 1896). He believed that the brain did not become aneThe Philosophy of Sleep (MacNish, 1830). MacNish mic or congested during sleep, and showed that intrasupported the previous concept that sleep was due cranial pressure was normal during sleep compared to pressure on the brain by blood. In 1846 Johannes with during wakefulness. By the end of the 19th cenEvangelista Purkinje (1787–1869), an outstanding neurotury the vascular sleep theories, based on congestion anatomist and professor of physiology and pathology at or anemia of the brain, were less enthusiastically supBreslau (Wroclaw, in modern Poland), proposed a ported. Subsequent research showed that changes durslightly different theory for the cause of sleep that was ing sleep of both cerebral blood flow and intracranial consistent with the congestive concept (Purkinje, 1846; pressure do occur, but it was no longer believed that Kruta, 1967). Purkinje proposed that the brain pathways these changes were responsible for the cause of sleep. (corona radiata) become compressed by blood congesThe neural theories for the cause of sleep were tion of the cell masses of the brain (basal ganglia), based upon mid-19th-century developments in the histhereby severing neural transmission and inducing tological understanding of the central nervous system. sleep. James Cappie in 1872 wrote in detail about the Camillo Golgi (1843–1926) demonstrated the first clear circulation of the brain, and was one of the last supporpicture of the nerve cell and its processes. His studies ters of the congestion theory. This theory was finally were extended by Heinrich Waldeyer (1837–1921), who contradicted by the findings of the outstanding clinical first named the nerve cell – the neuron – and demonneurologist John Hughlings Jackson (1835–1911). In strated an afferent axon and efferent dendrites. In 1863 Jackson observed the optic fundi during sleep and 1890, Rabl-Ruckhardt developed a hypothesis, called reported that the retinal arteries became pale during “neurospongium,” stating his belief that during sleep sleep, which was consistent with Blumenbach’s earlier there was a partial paralysis of the neuron prolongafindings. He therefore reasoned that brain congestion tions, which prevented communication with adjacent was not a cause of sleep. nerve cells. Subsequently, Raphael Jacques Lepine The main alternative to the congestion theory was (1840–1919) of Paris in 1894 and Marie Mathias Duval that sleep was due to insufficient blood in the brain (1844–1907) in 1895 proposed similar theories, agreeing (anemia). William Alexander Hammond (1828–1900), that sleep was produced by retraction of ameboid prothe noted American physician, in 1854 was the first in cesses of the nerve cell (Lepine, 1894; Duval, 1895). the 19th century to direct attention to the anemia theThe outstanding histologist Santiago Ramo´n y Cajal ory, after observing the brain of a patient who had a (1852–1934) proposed that small cells termed neuroglia traumatic skull injury (Hammond, 1873, p. 31). In 1855, interacted between neurons and were able to promote,
HISTORY OF SLEEP MEDICINE or inhibit, the transfer of information from one cell to another. Cajal, who in 1906 was awarded the Nobel prize along with Golgi for his work on neurohistology, suggested that the alteration in the transference of information by neuroglia could explain not only sleep but also the effect of hypnotic medications (Cajal, 1895, 1952). Ernesto Lugaro proposed an alternative histological theory that sleep was due to expansion of the neuron processes (Lugaro, 1898). He believed that neural impulses inducing sleep passed through expanded processes (gemmules) to allow transmission between cells. (In the early 20th century, the theories relating movements to parts of the neuron were largely discredited and theories based upon synaptic transmission of neurotransmitters became the prominent neural explanation for changes of sleep and wakefulness.) The chemical theories of sleep originated with Aristotle who believed that sleep was due to the effects of “fumes” taken into the blood vessels following the ingestion of food. Wilhelm Sommer in 1868 proposed that sleep was due to the lack of oxygen. Sommer’s theory (quoted in de Manace´ı¨ne, 1897) was developed from the work of Carl von Voit (1831–1908) and Max Pettenkofer (1818–1901, who had shown in 1867 that the body absorbed more oxygen during sleep than during the day. Eduard Friedrich Wilhelm Pflu¨ger (1829– 1910) became the main advocate for the oxygen hypothesis in 1875 (Pflu¨ger, 1875). Thierry Wilhelm Preyer (1841–1897) in 1877 believed that the accumulation of lactic acid during daytime fatigue led to a deficiency of oxygen in the brain at night, thereby causing hypoxemia and subsequent sleep (Preyer, 1877). This theory led to several others on the accumulation of toxic substances, which included cholesterol and other toxic waste products. Perhaps the most widely disseminated theory was that of Leo Errera of Brussels. Errera believed that the accumulation of poisonous substances called “leucomaines” induced sleep by passing from the blood to the brain (Errera, 1891). The leucomaines were believed to be gradually broken down during sleep, thereby leading to subsequent wakefulness. Raymond Emil Dubois (1818–1896) in 1895 proposed that sleep was a result of carbon dioxide toxicity, which in small amounts during wakefulness led to sleep (Dubois, 1895). Abel Bouchard (1833– 1899) in 1886 proposed that sleep was due to toxic agents, excreted in the urine during sleep, that he called “urotoxins”; he also believed that diurnally produced urine contained toxic agents that produced wakefulness. The chemical theories continued to be popular at the end of the 19th century. The behavioral theories of sleep developed from those of ancient times when general explanations were given for sleep. Although many behavioral theories
13
were proposed over the years, the inhibition theory was the most popular. This theory, first alluded to in 1889 by Charles Edouard Brown-Se´quard (1817–1894), and later expanded upon by Heubel and Ivan Pavlov, explained sleep as a process resulting from something being removed or inhibited in the brain. Brown-Se´quard, an outstanding clinical neurologist and physiologist, who believed that most glands had secretions that pass into the blood stream, is also known as the father of endocrinology. Based upon the previous work of Rolando (1809) and Flourens (1822), who had demonstrated that the removal of the cerebral cortex was accompanied by a sleep-like state (Flourens, 1824), Brown-Se´quard (1852, 1889) proposed that sleep was due to an inhibitory reflex. The inhibitory theory of sleep was advanced with the experiment of Heubel, of Kiev University in Russia, who proposed that sleep was due to the loss of peripheral sensory stimulation, which was essential for the maintenance of alertness (Heubel, 1876). Subsequently, the inhibitory theory of sleep was greatly expanded by the work of Ivan Pavlov in the early 20th century (Pavlov, 1923, 1927). Marie de Manace´¨ıne in 1897, in his book entitled Sleep: Its Physiology, Pathology, Hygiene, and Psychology, regarded sleep as being the “resting state of consciousness,” which was an appealing truism, although it provided little information on the mechanism of sleep (de Manace´ı¨ne, 1897) (Figure 1.2). A few researchers believed that a specific site in the body was capable of inducing sleep. The thyroid had been considered to be a sleep-inducing gland, until it was recognized that removal of the thyroid was not associated with insomnia. Jonathon Osborne in 1849 proposed that the choroid plexus was the “organ of sleep.” He reasoned that congestion of the choroid kept the ventricles distended to produce sleep, and that contraction of the choroid was associated with wakefulness. In the latter part of the 19th century two neurologists, Maurice Edouard Marie Gayet and Ludwig Mauthner, reported clinical findings that eventually led to the discovery of the brainstem’s role in sleep and wakefulness. In 1875 Gayet presented a patient with lethargy and associated eye movement paralysis who had upper brainstem pathology at autopsy, which led Gayet to believe that the lethargy was due to a thalamic defect that produced impaired transmission from the brainstem to the cerebral hemispheres (Gayet, 1875). Mauthner in 1890 reported a similar association between an eye movement disorder and sleepiness but placed the site of the deficit at the brainstem level. These findings received little attention at the turn of the century because of the more popular vascular and chemical sleep theories.
14
M.J. THORPY
Fig. 1.2. Title page of Sleep: Its Physiology, Pathology, Hygiene, and Psychology by Marie de Manace´¨ıne (1897).
The science of chronobiology made a few advances in the 19th century, largely through the studies of plant biologists, such as Augustin Pyramus de Candolle (1778– 1841), who demonstrated in 1832 that plants in constant conditions had a rhythm that differed slightly from 24 hours (de Candolle, 1832). Wilhelm Friedrich Phillip Pfeffer (1845–1920) in 1875 confirmed de Mairan’s finding that plants had their own intrinsic rhythm when devoid of environmental influences. In 1845 James George Davey (1813–1895) reported circadian rhythms of his own core body temperature (Davey, 1858), and in 1866 William Ogle performed similar experiments: There is a rise in the early morning while we are still asleep, and a fall in the evening while we are still awake, which cannot be explained by reference to any of the hitherto mentioned influences. They are not due to variations in light; they are probably produced by periodic variations in the activity of the organic functions. Although the theories regarding the cause of sleep were the focus of attention in the second half of the
19th century, important contributions were made to sleep disorders medicine. In 1869, Hammond, who was well known for his contributions to medicine during the Civil War, wrote a book based on his series of publications on insomnia, entitled Sleep and its Derangements (Hammond, 1873). Silas Weir Mitchell (1829–1914), a well-known and influential neurologist in America, wrote a number of clinical articles discussing the recognition of abnormal respiration during sleep, night terrors, nocturnal epilepsy, and the effect of stimulants on insomnia (Weir Mitchell, 1890). Perhaps the greatest clinical contribution in the field of sleep disorders medicine was the first description in 1880 of narcolepsy by Jean Baptiste Edouard Ge´lineau (1828–1906), who derived “narcolepsy” from the Greek words narkosis (a benumbing) and lepsis (to overtake) (Ge´lineau, 1880). The term “cataplexy,” for the emotionally induced muscle weakness (a prominent symptom of narcolepsy), was subsequently coined in 1916 by Richard Henneberg. Although Ge´lineau was the first to describe the clinical manifestations of narcolepsy clearly, several patients had previously been described by Caffe in 1862, Carl Friedrich Otto Westphal (1833–1890) in 1877 (Westphal, 1877), and Franz Fischer in 1878 (Fischer, 1878). The leading sleep disorder of the 20th century, obstructive sleep apnea syndrome, was described in 1836, not by a clinician but by the novelist Charles Dickens (1812–1870). Dickens published a series of papers entitled The Posthumous Papers of the Pickwick Club in which he described an obese boy named Joe who was excessively somnolent, a loud snorer, and who probably had right-sided heart failure (thus earning the nickname “young dropsy”: Dickens, 1836) (Figure 1.3). Mr. Lowton hurried to the door. . . The object that presented itself to the eyes of the astonished clerk was a boy – a wonderfully fat boy standing upright on the mat, with his eyes closed as if in sleep. He had never seen such a fat boy, in or out of a traveling caravan; and this, coupled with the utter calmness and repose of his appearance, so very different from what was reasonably to have been expected of the inflicter of such knocks, smote him with wonder. “What’s the matter?” inquired the clerk. The extraordinary boy replied not a word; but he nodded once, and seemed, to the clerk’s imagination, to snore feebly. “Where do you come from?” inquired the clerk. The boy made no sign. He breathed heavily, but in all other respects was motionless.
HISTORY OF SLEEP MEDICINE
15
publications. William Wadd, surgeon to the King of England, in 1816 wrote about the relationship between obesity and sleepiness. George Catlin, a lawyer, in 1872 described the breathing habits of the American Indian in his book entitled The Breath of Life; he graphically portrayed the effects of obstructed breathing during sleep (Figure 1.4). William Henry Broadbent (1835–1907) in 1871 was the first physician to report the clinical features of the obstructive sleep apnea syndrome, and William Hill in 1889 observed that upper-airway obstruction contributed to “stupidity” in children. The most notable description was by William Hughes Wells (1854–1919) in 1878; he cured several patients of sleepiness by treatment of upper-airway obstruction (Wells, 1878).
SLEEP IN THE 20TH CENTURY The interpretation of dreams is the royal road to a knowledge of the part the unconscious plays in the mental life (Freud, 1958).
Fig. 1.3. Joe, the fat boy from The Posthumous Papers of the Pickwick Club by Charles Dickens (1836).
The clerk repeated the question thrice, and receiving no answer, prepared to shut the door, when the boy suddenly opened his eyes, winked several times, sneezed once, and raised his hand as if to repeat the knocking. Finding the door open, he stared about him with astonishment, and at length fixed his eyes on Mr. Lowton’s face.
Sleep medicine advances in the 20th century were greatly affected by the development of new diagnostic means and the innovations in surgery. For the first time objective diagnostic procedures complemented the physician’s skill. X-rays were discovered in 1895 by Wilhelm Konrad Roentgen (1845–1923) and the first clinical application was reported in 1896. Widespread routine use of X-ray procedures began in the early 20th century; sophisticated brain imaging techniques such as computed axial tomography and nuclear magnetic resonance scanning began in the second half of the century. The vascular theories of the cause of sleep were no longer popular, and although the chemical theories
“What the devil do you knock in that way for?” inquired the clerk, angrily. “Which way?” said the boy, in a slow, sleepy voice. “Why, like forty hackney-coachmen,” replied the clerk. “Because master said I wasn’t to leave off knocking till they opened the door, for fear I should go to sleep” said the boy. More than 100 years followed Charles Dickens’ description before the obstructive sleep apnea syndrome became a well-recognized clinical entity. However, a number of writers in the 19th century did allude to some of the features of sleep apnea in their
Fig. 1.4. Obstructed breathing during sleep. (Reproduced from Catlin (1872).)
16
M.J. THORPY were briefly of interest due to the findings of Rene´ eye movements. Sigmund Freud in 1895, before the Legendre and Henri Pieron in 1907 (Legendre and publication of his first book on dreams in 1900, Pieron, 1907; Pieron, 1913), they were overshadowed recognized that paralysis of skeletal muscles during largely by the behavioral theory of Ivan Petrovitch dream sleep prevented the dreamer from acting out Pavlov (1849–1936). Pavlov, who is regarded as one of dreams (Freud, 1958). the greatest physiologists of all time, published his initial Sleep research, both basic and clinical, had its greatlectures on conditional reflexes in 1927 (Pavlov, 1927). est period of growth during the second half of the 20th There he expressed a belief that sleep was due to widecentury. The advances in neurochemistry, electrophysispread cortical inhibition: ology, neurophysiology, chronobiology, pathology of sleep, and sleep disorders medicine and the developSleep. . . is an inhibition which has spread over ment of sleep societies are too numerous to list, but the great section of the cerebrum, over the entire a summary is given below. hemispheres and even into the lower lying midbrain.
Neurochemistry
Pavlov’s studies on dogs showed that a continuous and monotonous stimulus would be followed by drowsiness and sleep. He reasoned that the continuous stimulus acts at a certain point of the central nervous system and leads to inhibition with resulting sleepiness. Although Pavlov’s theories on conditioning were interesting, they held little information on physiological mechanisms. Vladimir Michailovich Bekhterev (1857– 1927) published his findings on human reflexology and sleep in 1894 (translated into English in 1932). Bekhterev also believed that sleep was a general inhibition due to a loss of higher-level reflexes: [Sleep is] a reflex which has been biologically evolved for the purpose of protecting the brain from further poisoning by the products of metabolism, and which may be evoked, as an association reflex, and the conditions of fatigue. Bekhterev’s theory, similar to that of Edouard Clapare`de, who in 1905 viewed sleep as an “instinct,” was subsequently influenced by the work of Legendre and Pieron; it proposed that the biochemical processes leading to the inhibition of the brain were “hypnotoxins.” Since that time, electrophysiological studies have demonstrated that the passive, cortical inhibition proposed by Pavlov and Bekhterev does not occur; instead, the brain maintains its activity during sleep, particularly during REM sleep.
Dichotomy of sleep Since the days of ancient Greece, it had been recognized that sleep consisted of two different states, one associated with dreaming and the other with quiet sleep. Willis in the 17th century had noticed the difference, and believed that dream sleep was associated with release of the “animal spirits” from the cerebellum. However, the physiological changes of dreaming sleep were not reported until 1868 when Wilhelm Griesinger (1816–1868) noted the associated
Our studies have established that the accumulation of the hypnotoxin produces an increasing need for sleep (Pieron, 1913). Although attempts to replicate the work of Legendre and Pieron on hypnotoxin were often unsuccessful, in 1967 John Pappenheimer and colleagues induced sleep with cerebrospinal fluid obtained from sleep-deprived goats. The transmissible chemical, called “factor S,” was subsequently identified as a muramyl peptide in 1982 and is thought to act via the leukocyte monokine interleukin-1. Finding alternative sleep factors has met with mixed success; the number of putative sleep factors has grown enormously in the last 20 years. However, in 1988 Osamu Hayaishi discovered that prostaglandin PGD2, found in the preoptic muclei, was capable of inducing sleep in rats, leading to the speculation that the preoptic nucleus is the site of the perennial and elusive “sleep center.” Hypocretin/orexin was discovered independently in 1998 by two separate groups of researchers. Luis de Lecea and Thomas Kilduff and colleagues from San Diego identified two peptides derived from a single gene in the hypothalamus that had a sequence homology to secretin that they called hypocretin (de Lecea et al., 1998). At the same time, Takeshi Sakurai and Akira Amemiya and colleagues also isolated these same peptides in Texas and named them orexin (Greek for appetite) (Sakurai et al., 1998). Both groups were not investigating sleep, but were searching for novel obesity treatments. Chemelli et al. further studied hypocretin/orexin in 1999 and discovered that loss of hypocretin produced symptoms in rodents that were similar to that of cataplexy and sleep attacks as seen in humans. Emmanuel Mignot and colleagues in 1999 determined that dogs with narcolepsy had a loss of hypocretin and subsequently it was shown that most human patients with narcolepsy and cataplexy had reduced or absent cerebrospinal fluid levels of hypocretin (Lin et al., 1999).
HISTORY OF SLEEP MEDICINE
Electrophysiology Feeble currents of varying direction pass through the multiplier when electrodes are placed on two points of the external surface [of the brain] (Caton, 1875). The most useful objective diagnostic means for sleep disorders has proven to be electrophysiological techniques. Following Galvani’s demonstration of the electrical activity of the nervous system in the late 18th century, Richard Caton (1842–1926) in 1875 demonstrated action potentials in the brains of animals, an important step in the development of the electroencephalograph (Caton, 1875). In 1929, Johannes (Hans) Berger (1873–1941), the first to record electrical activity of the human brain, demonstrated differences in activity between wakefulness and sleep. Berger’s discovery led to the development of the electroencephalograph as a clinical tool for the diagnosis of brain disease. The electroencephalograph was applied to determine different sleep states in 1937, when Alfred L. Loomis, E. Newton Harvey (1887–1959), and Garret Hobart were able to classify sleep into five stages, from A to E (Loomis et al., 1935). Dream sleep was characterized in 1953 by Eugene Aserinsky and Nathaniel Kleitman, who demonstrated the occurrence of rapid eye movements during the dreaming stage of sleep, that they called “rapid eye movement (REM) sleep.” The traditional manner of producing sleep studies by using polysomnographs that used ink and paper was rapidly replaced by digital systems after the year 2000. The death knell to paper systems came at the end of 2006 when the Grass P78 polysomnograph recording paper became unavailable. In 1957 Kleitman and William Dement discovered a recurring pattern of REM sleep and non-REM sleep during overnight electroencephalographic monitoring – a finding that made it clear that sleep no longer could be regarded as a homogeneous state (Dement and Kleitman, 1957). In 1968, Allan Rechtschaffen and Anthony Kales developed a scoring manual, A Manual of Standardized Terminology, Techniques, and Scoring System for Sleep Stages of Human Subjects, which has become the standard in the field (Rechtschaffen and Kales, 1968). In 2007, a major revision of the traditional sleep-staging rules was developed by the American Academy of Sleep Medicine (Iber et al., 2007). The first report of an effective measure of daytime alertness was by Gary Richardson et al., in 1978. This study compared narcoleptics with normal individuals by applying the Multiple Sleep Latency Test (MSLT) that had been conceived and developed by Mary Carskadon, working with William Dement at Stanford University:
17
analysis of hypnogenic mechanisms has thus underlined the paramount importance of inhibition and disinhibition in the deterrnination of sleep onset and maintenance – a striking illustration of Sherrington’s visionary concepts (Bremer, 1977).
Neurophysiology In the early part of the 20th century, two schools of thought emerged regarding the neurophysiological basis of sleep and wakefulness. One characterized sleep as due to disinhibition with release of an active “sleep center,” and the other as due to a passive event, the result of inhibition of a “waking center.” The theories, proposed at the end of the 18th century by Mauthner and others, assumed an interruption of peripheral sensory stimulation, thereby allowing the cerebral cortex to produce sleep. This “deafferentation” theory had been suggested first by Purkinje in 1846. The notion of a specific sleep center did not receive much support, as illustrated by the comment of the prominent clinical neurologist Jacques Jean Lhermitte (1877–1959) in 1910 (Lhermitte, 1910): We absolutely object to the thought of the existence of a nerve center attributed to the function of sleep. The conception of a center for sleep is erroneous, as it disavows the most simple principles of physiology. Lhermitte was supported in 1914 by a pioneer of brain localization, Joseph Jules Dejerine, who said, “Sleep cannot be localized” (Dejerine and DejerineKlumpke, 1914). However, in 1929, Constantin von Economo (1876–1931) proposed a “center for regulation of sleep” based on anatomical and clinical studies of “encephalitis lethargica” at the Psychiatric Clinic of Wagner von Jauregg in Vienna (von Economo, 1923, 1929a). Viral encephalitis reached epidemic proportions between 1916 and 1920, and von Economo had the opportunity to correlate the clinical features of sleep disturbance with the central nervous system pathology. His studies demonstrated inflammatory lesions in the posterior hypothalamus in patients with excessive sleepiness and lesions in the preoptic area and anterior hypothalamus in patients with insomnia (von Economo, 1929b). Von Economo, influenced by the studies by Pieron and Pavlov, suggested that the “sleep-regulating center” was controlled by substances circulating in the blood. These substances caused the sleep center to exert an inhibitory influence on the cerebral cortex, thereby leading to sleep. The same year in Zurich, Walter Rudolph Hess (1881–1973), who was awarded the Nobel prize with Egas Moniz for his work in neuroanatomy,
18
M.J. THORPY
confirmed von Economo’s findings by demonstrating that stimulation of the central gray matter in the region of the thalamus induced sleep (Hess, 1944). Kleitman in 1939 regarded the cerebral cortex as being the source of wakefulness, and believed that sleep due to inactivity of the central nervous system was brought about by a reduction in peripheral stimulation because of fatigue. His hypothesis conformed to the “deafferentation” theory. Steven Walter Ranson (1880–1942) in 1932 demonstrated that lesions placed at the top of the brainstem produced sleepiness; experimentally, this was consistent with von Economo’s findings (Ranson and Ingram, 1932). In 1935, Fre´de´ric Bremer, of the University of Brussels, experimentally gave support to the deafferentation theory. Bremer completely transected the midbrain, producing the “cerveau isole´” preparation, an isolation of the cerebrum, and was able to show characteristic sleep patterns on the electroencephalogram. The studies up until this time were consistent with the concept that a lesion that prevented transmission of peripheral stimulation was important in the production of sleep. However, Ranson in 1939 showed that lesions of the lateral hypothalamus, in the absence of upper-brainstem lesions, were associated with sleep due to a loss of the “waking center.” A few years later, Walle Jetz Harinx Nauta demonstrated that posterior hypothalamic lesions produced sleepiness whereas anterior hypothalamic lesions produced insomnia, thereby supporting the concept of a waking center in the posterior hypothalamus and a sleep center in the anterior hypothalamus (Nauta, 1946). According to Nauta: Whereas Ranson and his collaborators held that periods of sleep were caused by more or less intrinsic periodic decreases in activity of the waking center, we are inclined to attribute these decreases to the inhibitory influence of a sleep center. Horace W. Magoun and Ruth Rhines, at the Northwestem University Medical School in Chicago, demonstrated in 1946 that the lower portion of the brainstem reticular formation was responsible for inhibiting skeletal muscle tone (Magoun and Rhines, 1946). This function of the lower brainstem had earlier been alluded to by the clinical studies of Jackson in 1898. That the lower reticular formation could have an inhibitory function through descending pathways led to Guiseppe Moruzzi and Magoun’s finding in 1949 that the brainstem reticular formation also had ascending pathways (Moruzzi and Magoun, 1949; Moruzzi, 1964). This resulted in the discovery of the “ascending reticular activating system,” which led to a new emphasis in the physiological investigation of sleep. Stimulation of
the ascending reticular activating system produced electroencephalographic patterns of wakefulness. It was now recognized that the brainstem transection studies did not produce sleep because of “deafferentation” of peripheral sensory input, but because of the loss of the wakefulness stimulus from the ascending reticular activating system. As a result, sleep became regarded as a passive phenomenon. At the beginning of the second half of the 20th century, research concentrated on determining the neurophysiological basis for non-REM and REM sleep. Following the electrophysiological documentation of REM sleep, Michel Jouvet and colleagues in 1959 demonstrated REM sleep-related muscle atonia, and in 1965 demonstrated that the brainstem serotonincontaining neurons of the raphe nuclei were important in sleep and wakefulness (Jouvet and Delorme, 1965). Subsequently, Jouvet demonstrated that the rostral raphe nucleus was important for non-REM sleep, whereas the caudal raphe nucleus was important in the maintenance of REM sleep. In 1975, Robert William McCarley and J. Allan Hobson proposed a reciprocal interaction model of REM and non-REM sleep, with rostral REM “on” cells and caudal REM “off’ cells (McCarley and Hobson, 1975). In 1996 a small group of cells, called the ventrolateral preoptic nucleus, was discovered by Sherin to be an important sleep-generating nucleus that comes as close as any cell group to being a major “sleep center” (Sherin et al., 1996).
Chronobiology Despite the multiplicity of its constituents, the circadian system often behaves like one unit which is characterized by the durability of its oscillations and its internal temporal order (Aschoff, 1981). Auguste Henri Forel (1848–1931), a Swiss physician, is credited with stimulating the investigation of circadian rhythms as important time-measuring systems. His studies in 1910 on the accurate timing system of bees were consistent with those of de Mairan in the 18th century on the opening of the flower petals at a given time of day. The circadian behavior of rodents was first reported by Curt P. Richter in his Ph.D. thesis in 1922; and Erwin Bunning in 1935 was able to demonstrate the genetic origin of circadian rhythms in plants and subsequently developed a concept of “biological clocks.” In the early 1960s Richter searched for the biological clock in extensive studies that culminated with the report in 1965 that lesions placed in the anterior ventral hypothalamus produced disruption of circadian rhythms (Richter, 1965). Two groups acting independently in 1972, Robert Y. Moore and Victor
HISTORY OF SLEEP MEDICINE 19 B. Eichler, and F.K. Stephan and Irving Zucker, discovpsychiatry. Freud’s book The Interpretation of Dreams ered the “clock” to be two small, bilateral nuclei in the (1958) led to the development of psychoanalysis, which anterior hypothalamus, which were subsequently called was applied to the treatment of insomnia. the suprachiasmatic nuclei (Moore and Eichler, 1972; Psychoactive medications became widely used with Stephen and Zucker, 1972). the introduction of the phenothiazines in the 1950s, but Jules Aschoff and Kurt Wever investigated human hypnotic medications, particularly the barbiturates, had circadian rhythms in the absence of environmental time been in common usage since barbital was introduced in cues in 1962 in an underground laboratory in Munich. 1903. The 1960s saw the introduction of the benzodiazeThey demonstrated a free-running pattern of sleep pine hypnotics, which largely replaced the barbiturates and wakefulness with a period length of greater than in the late 1970s. However, the 1980s saw a decline in 24 hours. the use of hypnotics with increased physician and public A similar free-running pattern was demonstrated in awareness of the disadvantages of chronic hypnotic field experiments (1964) by the speleologist Michel use. Insomnia became recognized as a symptom rather Siffre, who lived for 3 months in the absence of time than a diagnosis, and treatment was directed to the cues on an ice glacier deep in the Franco-Italian moununderlying physical or psychological causes. tains (Siffre, 1964). Many human biological rhythms Several books on sleep had a major influence on the have recently been discovered, such as the 24-hour epidevelopment of sleep disorders medicine. Pieron’s Le sodic secretory pattern of cortisol that was reported by problème physiologique du sommeil in 1913 summarElliot David Weitzman (1929–1983) in 1966 (Weitzman ized the scientific sleep literature at that time. A simiet al., 1966). lar approach was taken by Kleitman, who produced In 1980, Weitzman et al. demonstrated the internal his monumental treatise, Sleep and Wakefulness, in organization of temperature, neuroendocrine rhythms, 1939 (updated in 1963 to contain 4337 references) and the sleep–wake cycle in subjects who were moni(Kleitman, 1963). The Association of Sleep Disorder tored in an environment free of time cues for periods Centers classification committee, chaired by Howard of up to 6 months. Sutherland Simpson (1863–1926) Roffwarg, produced the Diagnostic Classification of and J.J. Galbraith in 1906 had demonstrated that the Sleep and Arousal Disorders in 1979; it ushered in light–dark cycle could influence mammal behavior. the modern era of sleep diagnoses and became the first However, it was not until the 1980s that Czeisler and classification to be widely used. The Principles and colleagues demonstrated the importance of the light– Practice of Sleep Disorders Medicine, edited by Meir dark cycle in the entrainment of human circadian Kryger, Thomas Roth, and William Dement in 1989, rhythms. The genetic basis for the control of circadian was the first comprehensive textbook on basic sleep rhythms was established in 1971 by R. Konopka, initiresearch and clinical sleep medicine (Kryger et al., 1989). ally in fruit flies but subsequently in humans (Konopka Increased knowledge about sleep and sleep disorand Benzer, 1971). The recognition by K. Toh in 2001 ders in general has resulted from the research of a that advanced sleep phase syndrome was associated few core sleep disorders, which include narcolepsy, with a genetic mutation of the human period gene obstructive sleep apnea syndrome, and the insomnias. two (hPer2) led to the recognition that alterations in Following Ge´lineau’s description in the late 19th centiming of the sleep–wake pattern could be controlled tury, narcolepsy was brought to general recognition in by genetic factors (Toh et al., 2001). 1926 by the Australian-born neurologist William John Adie (1886–1935) (Adie, 1926), and stimulants were first Pathology of sleep used for treatment by Otakar Janota (1898–1969) and A. Skala in 1930. In 1941 John Burton Dynes and Knox Five billion people go through the cycle of sleep H. Finley applied the electroencephalograph to the diagand wakefulness every day, and relatively few of nosis of narcolepsy (Dynes and Finley, 1941), and the them know the joy of being fully rested and fully characteristic sleep-onset REM period of night sleep alert all day long (William Dement 1988). was discovered in 1960 by Gerald Vogel. Dement and colSleep disorders were poorly described at the turn of the leagues at Stanford University developed a narcoleptic century, and, other than narcolepsy and sleeping dog colony in the 1970s, which advanced the understandsickness (African trypanosomiasis), few specific sleep ing of the biochemical and neuroanatomical bases of the disorders were recognized. In addition to general disorder. The Multiple Sleep Latency Test was applied to medical illness, environmental effects and anxiety were the diagnosis by Richardson et al. in 1978, and the docuviewed as the main causes of sleep disturbance. mentation of a strong association between the histocomHowever, a gradual recognition of the multiplicity of patability antigen HLA-DR2 and narcolepsy was made sleep diagnoses began to parallel progress in by Yutaka Honda and colleagues in 1984 (Juji et al., 1984).
20
M.J. THORPY
Following the reports of snoring, sleepiness, and obesity in the 19th century, Sir William Osler (1849– 1919) referred in 1906 to Dickens’ description of Joe (Osler, 1906): “An extraordinary phenomenon in excessively fat young persons is an uncontrollable tendency to sleep – like the fat boy in Pickwick.” Charles Sidney Burwell in 1956 brought general recognition to obstructive sleep apnea syndrome, which he called the “pickwickian syndrome” (Burwell et al., 1956), and the first objective documentation of polysomnographic features was simultaneously reported by Henri Gastaut and Jung in 1965 (Gastaut et al., 1965; Jung and Kuhlo, 1965). Although the tracheotomy had been performed since the time of Asclepiades (first century BC), Wolfgang Kuhlo and Erich Doll in 1972 reported that it provided an effective treatment of the obstructive sleep apnea syndrome. Tanenosuke Ikematsu in 1964 popularized uvulopalatopharyngoplasty surgery for the treatment of snoring, which was subsequently applied to the obstructive sleep apnea syndrome by Shiro Fujita in 1981 (Fujita et al., 1981). The same year, nasal continuous positive airway pressure treatment was described by Colin Sullivan and subsequently became the treatment of choice (Sullivan et al., 1981). Another sleep-related breathing disorder called “Ondine’s curse” was first reported by John W. Severinghaus and Robert A. Mitchell in 1962. Named after the water nymph in Jean Giraudoux’s play Ondine (1954), this disorder was characterized by the failure of automatic ventilation that could lead to fatal apnea during sleep: Live! It’s easy to say. If at least I could work up a little interest in living – but I’m too tired to make the effort. Since you left me, Ondine, all the things my body once did by itself, it now only does by special order. . . I have to supervise five senses, two hundred bones, a thousand muscles. A single moment of inattention, and I forget to breathe. He died, they will say, because it was a nuisance to breathe (Giraudoux, 1954, Act III). Insomnia received more interest in earlier centuries than in the first half of the 20th century, probably because of the availability of effective hypnotic medications. Frederick Snyder in the 1960s recognized and promoted the importance of psychiatric disorders in sleep medicine, especially depression: “Troubled minds have troubled sleep, and troubled sleep causes troubled minds” (Snyder, 1969). The polysomnograph was applied to the investigation of patients with insomnia following the discovery of obstructive sleep apnea in 1965, and objective
measures of hypnotic effectiveness were developed by Kales et al. in 1969. The concept of a conditioned insomnia (psychophysiological insomnia) was first presented in the Diagnostic Classification of Sleep and Arousal Disorders (Association of Sleep Disorder Centers, 1979), and subsequently became recognized as a common form of primary insomnia. The behavioral technique “stimulus control” developed by Richard Bootzin in 1972 was an effective treatment of insomnia, as was “sleep restriction therapy,” developed by Arthur Spielman in 1987 (Spielman et al., 1987). Circadian rhythm sleep disorders were recognized in the late 1970s, partly due to recognition of the chronobiological features of “jet lag” and “shift work.” Thomas A. Edison, who was responsible for the development of the electric light bulb, which stimulated the development of shift work, had his own views on sleep: In my opinion sleep is a habit, acquired by the environment. Like all habits it is generally carried to extremes. The man that sleeps four hours soundly is better off than a dreamy sleeper of eight hours (Baldwin, 1995). The atypical, sleep-onset insomnia called the “delayed sleep phase syndrome,” discovered by Weitzman and colleagues in 1981, led to a radically different form of treatment called “chronotherapy,” which was based on chronobiological principles (Czeisler et al., 1981; Weitzman et al., 1981). Many other sleep disorders have been discovered in the 20th century, including REM sleep behavior disorder by Carlos Schenck et al. in 1986; paroxysmal nocturnal dystonia in 1981 by Lugaresi & Cirignotta and fatal familial insomnia in 1986 by Lugaresi et al.; and food allergy insomnia by Andre Kahn et al. in 1985. General and medical awareness of sleep disorders has dramatically increased since the 1970s through the contributions of sleep disorders clinicians and the sleep societies. In addition to those mentioned, a few of the many who have contributed to this recognition include: Roger Broughton, Michel Billiard, Christian Guilleminault, Peter Hauri, J. David Parkes, the late Pierre Passouant, and Bedrich Roth.
Sleep disorders medicine we have created a new clinical specialty, sleep disorders medicine! whose task is to watch over all of us while we are asleep (William Dement 1985). Organized sleep disorders medicine in the USA began with the founding of the Association for the
HISTORY OF SLEEP MEDICINE 21 Psychophysiological Study of Sleep in 1961, an associamainly psychologists but also physicians, in behavioral tion comprised of sleep researchers, many with clinical sleep medicine. interests. Sleep research led to the investigation of In 2005, a fellowship training program was sleep disorders, which resulted in the establishment in approved by the American College of Graduate Medithe early 1970s of clinical sleep disorder centers for cal Education for eligibility to take a board certificathe diagnosis and treatment of patients. In 1976, the tion examination in sleep medicine. The first Association of Sleep Disorder Centers (ASDC) was examination was held in 2007. This examination of founded. The first sleep disorder center to be engaged the Board on Internal Medicine is open to physicians in active patient evaluations and treatment was that who have been board-certified by one of the specialty established at Stanford University in California by boards of the American Board of Psychiatry and Dement. An accreditation process for sleep disorders Neurology, the Board of Internal Medicine, the centers was established by the ASDC, and the first to American Board of Pediatrics, or the American Board be accredited in 1977 was the Sleep–Wake Disorders of Otolaryngology, and who have completed 1 year Unit, headed by Weitzman, at Montefiore Medical of sleep medicine fellowship training. Until 2011 Center in New York. physicians trained in sleep medicine who meet certain In 1978, the Association of Polysomnographic Techcriteria of training are eligible to sit the Board of nologists, founded by Peter Anderson McGregor, set Sleep Medicine examination despite not having standards of practice for polysomnographic technolocompleted 1 year of American College of Graduate gists. In 2007 the association changed its name to the Medical Education-certified training. American Association of Sleep Technologists. A sleep-related foundation, the National Sleep In 1983 the Association for the Psychophysiology Foundation, was created in 1990 by the American Sleep Study of Sleep was renamed the Sleep Research SociDisorders Association, and subsequently became indeety and in 1984 the Clinical Sleep Society was founded pendent of the association. The National Sleep Foundaas the membership branch of the Association of Sleep tion is an independent nonprofit organization Disorder Centers. In 1986, the Association of Sleep dedicated to improving public health and safety by Disorder Centers, the Clinical Sleep Society, the achieving understanding of sleep and sleep disorders, Sleep Research Society, and the Association of Polyand by supporting sleep-related education, research, somnographic Technologists formed a federation and advocacy. The National Sleep Foundation relies called the Association of Professional Sleep Societies. on voluntary contributions, including grants from The Association of Sleep Disorder Centers was foundations, corporations, government agencies, and renamed as the American Sleep Disorders Association other organizations to support its programs. Another in 1987. Subsequently the name was again changed in foundation, the American Sleep Medicine Foundation 1999 to the American Academy of Sleep Medicine. (formerly the Sleep Medicine Education and Research In 1978, the medical journal Sleep was created to Foundation) was established by the American Academy present research and clinical articles on sleep, and in of Sleep Medicine Board of Directors in March 1998 to 1979 a complete issue was devoted to the diagnostic promote education and fund research. classification of sleep and arousal disorders (AssociaWith the increased recognition of the importance of tion of Sleep Disorder Centers, 1979). The Internasleep disorders medicine many international sleep tional Classification of Sleep Disorders manual was societies have been founded, beginning with the Europroduced in 1990 and a second edition was produced pean Sleep Research Society in 1971, the Japanese Sociin 1997 (American Sleep Disorders Association, 1990, ety for Sleep Research in 1978, the Belgian Association 1997). Several other sleep journals were created, includfor the Study of Sleep in 1982, the Scandinavian Sleep ing Sleep Medicine Reviews (1997), Sleep Medicine Research Society in 1985, the Latin American Sleep (2000), Behavioral Sleep Medicine (2003), and the Society in 1986, the Sleep Society of Canada in 1986, Clinical Journal of Sleep Medicine (2005), the official and the British Sleep Society in 1989. Sleep medicine journal of the American Academy of Sleep Medicine. has become a major branch of medicine with practiClinicians who were trained in sleep medicine were tioners in nearly every country of the world. eligible to take a certification examination that was first held in 1978. The examination was open to both The woods are lovely, dark, and deep, physicians and other doctoral clinicians. With the recBut I have promises to keep, ognition of the importance of behavioral treatments And miles to go before I sleep, in sleep medicine, especially in insomnia, a board And miles to go before I sleep. examination was developed in 2003 for clinicians, (Robert Frost, 1923).
22
M.J. THORPY
REFERENCES Adams F (1891). The Genuine Works of Hippocrates. William Wood, New York. Adie WJ (1926). Idiopathic narcolepsy, a disease sui generis, with remarks on the mechanism of sleep. Brain 49: 257–306. Aldrich TB (1876). Flower And Thorn: Later Poems. James R. Osgood, Boston, MA. American Sleep Disorders Association (1997). International Classification of Sleep Disorders, revised: Diagnostic and Coding Manual. American Sleep Disorders Association, Rochester, MN. American Sleep Disorders Association Diagnostic Classification Steering Committee (1990). International Classification of Sleep Disorders: Diagnostic and Coding Manual. American Sleep Disorders Association, Rochester, MN. Aschoff J (1981). Biological Rhythms. Plenum Press, New York. Aschoff J, Wever R (1962). Spontanperiodik des Menschen bei Ausschluss aller Zeitgeber. Naturwissenschaften 49: 337–342. Aserinsky E, Kleitman N (1953). Regularly occurring periods of eye motility, and concomitant phenomena during sleep. Science 118: 273–274. Association of Sleep Disorder Centers (1979). Diagnostic classification of sleep and arousal disorders. Sleep Disorders Classification Committee. Sleep 2: 1–137. Baldwin N (1995). Edison: Inventing the Century. Hyperion, New York. Bekhterev VM (1932). General Principles of Human Reflexology. Translated by E Murphy, W Murphy. International Publishers, New York. Berger H (1929). Uber das Elektrenkephalogram des Menschen. Archiv fu¨r Psychiatrie und Nervenkrankheiten 87: 527–570. Blumenbach J (1795). Anfangs Grande de Physiologie. J.C. Dieterich, Go¨ttingen. Bootzin RR (1972). Stimulus control treatment for insomnia. Programs and abstracts of the 80th Annual Convention of the American Psychological Association; September 2; Honolulu, HI. Bouchard A (1886). Sur les variations de la toxicite´ urinaire pendant la vielle, et pendant le sommeil. C R Acad Sci 102: 727. Bremer F (1935). Cerveau isole´ et physiologe du sommeil. C Roy Soc Biol 118: 1235–1241. Bremer F (1977). Cerebral hypnogenic centers. Ann Neurol 2: 1. Broadbent WH (1871). Cheyne–Stokes respiration in cerebral hemorrhage. Lancet 1: 307–309. Brown-Se´quard E (1852). On the causes of the torpidity of the tenrec. The Medical Examiner 93: 549–550. Brown-Se´quard C (1889). Le sommeil normal, comme le sommeil hypnotique, est le re´sultat d’une inhibition de l’activite´ intellectuelle. Arch Physiol Norm Path 1: 333–335. Bunning E (1935). Zur Kenntnis der erblichen Tagesperiodizta¨t bei den Primarblattern von Phaseous Multiflorus. Jahrb Wiss Bot 81: 411–418.
Burwell CS, Robin ED, Whaley RJ et al. (1956). Extreme obesity associated with alveolar hypoventilation – a Pickwickian syndrome. Am J Med 21: 811–818. Caffe P (1862). Maladie du sommeil. Journal des connaissances me´dicales pratiques et de pharmacologie 29: 323. Cajal RY (1895). Hipotesis Sobre el Mecanismo Histolo´gico de la Associacio´n del Suevo y del Estado Vigil. Madrid. Cajal RY (1952). Histologie du syste`me nerveux, vol II. Translated and reprinted from first Spanish edition, vol. 1, 1899; vol. 2, 1904. Instituto Ramo´n y Cajal, Madrid. Cappie J (1872). The causation of sleep. A physiological essay. James Thin, Edinburgh. Catlin G (1872). The Breath of Life. John Wiley, New York. Caton R (1875). The electrical currents of the brain. Br Med J 2: 278. Chadwick J, Mann WN, Withington ET et al. (translators) (1978). Hippocratic Writings. Penguin, London. Chemelli RM, Willie JT, Sinton CM et al. (1999). Narcolepsy in orexin knockout mice: molecular genetics of sleep regulation. Cell 98 (4): 437–451. Clapare`de E (1905). Esquisse d’une the´orie biologique du sommeil. Arch Psychol 4: 246–349. Coursen H (1997). Macbeth. Greenwood Press, Westport. Czeisler CA, Richardson GS, Coleman RM et al. (1981). Chronotherapy: resetting the circadian clock of patients with delayed sleep phase insomnia. Sleep 4: 1–21. Davey JG (1858). The Ganglionic Nervous System. Its Structure, Functions, and Diseases. Churchill, London. de Candolle A (1832). Physiologie ve´ge´tale, vol. 2. Becket Jeune, Paris. Dejerine JJ, Dejerine-Klumpke AM (1914). Se´miologie des affections du syste`me nerveux. Masson, Paris. de Lecea L, Kilduff TS, Peyron C et al. (1998). The hypocretins: hypothalamus-specific peptides with neuroexcitatory activity. Proc Natl Acad Sci U S A 95 (1): 322–327. de Mairan J (1729). Observation botanique: histoire de 1’Acade´mie Royal des Sciences. Paris. de Manace´¨ıne M (1897). Sleep: Its Physiology, Pathology. Hygiene and Psychology. Walter Scott, London. Dement W, Kleitman N (1957). The relation of eye movements during sleep to dream activity: an objective method for the study of dreaming. J Exp Psychol 53: 339–346. Descartes R (1632). Treatise of Man. Reprinted in 1972. TS Hall, Ed. Harvard University Press, Cambridge, MA. Dickens C (1836). The Posthumous Papers of the Pickwick Club. Chapman and Hall, London. Donders F (1849). De bewegingen der hersenen en de veranderinger der vaatvulling van de pia mater. Nederlandsch Lancet 12: 521–553. Dubois R (1895). Autonarcose carbon-acetone´mique ou sommeil hivernal de la marmotte. C R Soc Biol 47: 149–150. Durham A (1860). The physiology of sleep. Guys Hosp Rep 3rd Series VI: 149–173. Duval M (1895). Hypothe`se sur la physiologie des centres nerveux: the´orie histologique du sommeil. C R Soc Biol 47: 86–87.
HISTORY OF SLEEP MEDICINE Dynes JB, Finley KH (1941). The electroencephalograph as an aid in the study of narcolepsy. Arch Neurol Psychiatry 46: 598–612. Ebbell B (1937). The Papyrus Ebers. Humphrey Milford, London. Errera L (1891). Note sur la the´orie toxique du sommeil. C R Soc Biol 43: 508. Fischer F, Jr (1878). Epileptoide Schlafzustande. Arch f Psychiatr 8: 203. Flourens P (1824). Recherches experimentales sur les proprie´te´s et les fonctions du syste`me nerveux dans les animaux verte`bres. Crevort, Paris. Forel A (1910). Die Trinksitten, ihre hygienische und soziale Bedeutung. 9th edn. Basel. Freeman K (1966). The pre-Socratic Philosophers. Harvard University Press, Cambridge, MA. Freud S (1958). The Interpretation of Dreams. Translated by J Strachey. Hogarth Press, London. Frost R (1923). Stopping by Woods on a Snowy Evening, in New Hampshire. Henry Holt, New York, p. 87. Fujita S, Conway W, Zorick F et al. (1981). Surgical correction of anatomic abnormalities in obstructive sleep apnea syndrome: uvulopalatopharyngoplasty. Otolaryngol Head Neck Surg 89: 923–934. Gastaut H, Tassinari CA, Duron B (1965). E´tude polygraphique des manifestations e´pisodique (hypnique et respiratoires), diurnes et nocturne, du syndrome de Pickwick. Rev Neurol 112: 568–579. Gayet M (1875). Affection encephalique. Arch Physiol Norm Pathol 2nd ser 7: 341–351. Ge´lineau J (1880). De la narcolepsie. Gazette des Hoˆpitaux 53: 626–628, 635–637. Giraudoux J (1954). Ondine. Adapted by M Valency. Random House, New York. Grene D (1987). The History, by Herodotus. University of Chicago Press, Chicago, IL. Griesinger W (1868). Physio-psychologische Selbstbeobachtungen. Arch Psychiatr Nervenkr 1: 200–204. Gruner OC (1930). A Treatise on the Canon of Medicine of Avicenna. Luzac, London. Gruner OC (1970). A Treatise on the Canon of Medicine of Avicenna. M Kelley, New York. Gunther RT (1959). The Greek Herbal of Dioscorides. Hafner, New York. Hammond W (1873). Sleep and its Derangements. Lippincott, Philadelphia. Hayaishi O (1988). Sleep–wake regulation by prostaglandins D2 and E2. J Biol Chem 263 (29): 14593–14596. Henneberg R (1916). Uber genuine Narkolepsie. Neurol Zbl 35: 282–290. Hess W (1944). Das Schlafsyndrom als Folge dienzephaler Reizung. Helv Physiol Pharmacol Acta 2: 305–344. Hett WS (1964). Aristotle: Parva Naturalia. Harvard University Press, Cambridge, MA. Heubel E (1876). Die Abha¨ngigkeit des wachen Gehirnzhstandes von ausseren Erregungen. Pflugers Arch XIV. Hill W (1889). On some cases of backwardness and stupidity in children. Br Med J (Clin Res Ed) 2: 711–712.
23
Hill L (1896). The physiology and pathology of the cerebral circulation: an experimental research. J. & A. Churchill, London. Howell W (1897). A contribution to the theory of sleep. J Exp Med 2: 313–345. Iber C, Ancoli-Israel S, Chesson AL et al. (2007). The AASM Manual for the Scoring of Sleep and Associated Events: Rules, Terminology, and Technical Specifications. American Academy of Sleep Medicine, Westchester, IL. Ikematsu T (1964). Study of snoring, 4th report. Therapy [in Japanese]. Jpn Otorhinolaryngol 64: 434–435. Jackson H (1863). Ophthalmoscopic examination of sleep. Ophthalmic Hospital Reports, London 4: 35–37. Jackson JH (1898). Remarks on the relations of different divisions of the central nervous system to one another and to parts of the body. Delivered before the Neurological Society, December 8th, 1897. Br Med J 65. Janota O, Skala A (1930). Proceedings of the staff meetings of the Mayo Clinic. Jouvet M, Delorme JF (1965). Locus coeruleus et sommeil paradoxal. C Roy Soc Biol (Paris) 159: 859–899. Jouvet M, Michel F, Courjon J (1959). [On a stage of rapid cerebral electrical activity in the course of physiological sleep.]. C R Seances Soc Biol Fil 153: 1024–1028. Juji T, Satake M, Honda Y et al. (1984). HLA antigens in Japanese patients with narcolepsy. All the patients were DR2 positive. Tissue Antigens 24 (5): 316–319. Jung R, Kuhlo W (1965). Neurophysiological studies of abnormal night sleep and the pickwickian syndrome. Prog Brain Res 18: 140–159. Kahn A, Mozin MJ, Casimir G et al. (1985). Insomnia and cow’s milk allergy in infants. Pediatrics 76: 880–884. Kales A, Scharf MB, Allen C (1969). Effectiveness of sleep medications: all night studies of hypnotic drugs. Electroencephalogr Clin Neurophysiol 27 (7): 710–711. Karmanova I (1982). Evolution of Sleep. Karger, Basel. Kleitman N (1963). Sleep and Wakefulness. Revised edn. 1963. University of Chicago Press, Chicago. Konopka RJ, Benzer S (1971). Clock mutants of Drosophila melanogaster. Proc Natl Acad Sci U S A 68 (9): 2112–2116. Kruta VJE (1967). Purkyne’s conception of the physiological basis of wakefulness and sleep [in Czech]. Scr Med Fac Med Brun 40: 281–290. Kryger M, Roth T, Dement W (1989). The Principles and Practice of Sleep Medicine. WB Saunders, Philadelphia. Kuhlo W, Doll E (1972). Pulmonary hypertension and the effect of tracheotomy in a case of Pickwickian syndrome. Bull Physiopathol Respir (Nancy) 8 (5): 1205–1216. Legendre R, Pieron H (1907). Le rapport entre les conditions physiologiques et les modifications histologiques des cellules ce´re´brales dans l’insomnie experimentale. C R Soc Biol 62: 312. Lepine R (1894). In: Revue de Medicine, Paris p. 727. Lhermitte J (1910). Les narcolepsies. Rev de Psychiat et de Psychol Exper 14: 265. Lin L, Faraco J, Li R et al. (1999). The sleep disorder canine narcolepsy is caused by a mutation in the hypocretin (orexin) receptor 2 gene. Cell 98 (3): 365–376.
24
M.J. THORPY
Linnaeus C (1751). Philosophia Botanica. Godofr Kiesewetter, Stockholm. Lloyd-Jones, H (Ed.) (1994). Sophocles. Ajax. Electra. Oedipus Tyrannus. Harvard University Press, Harvard, MA. Loomis AL, Harvey EN, Hobart G (1935). Potential rhythms of the cerebral cortex during sleep. Science 71: 597–598. Lucretius (1994). On the Nature of the Universe. Translated by RE Latham. Penguin Books, London. Lugaresi E, Cirignotta F (1981). Hypnogenic paroxysmal dystonia: epileptic seizure or a new syndrome? Sleep 4 (2): 129–138. Lugaresi E, Medori R, Montagna P et al. (1986). Fatal familial insomnia and dysautonomia with selective degeneration of thalamic nuclei. N Engl J Med 315 (16): 997–1003. Lugaro E (1898). Sulle modificazioni morfologiche funzionali dei dendriti delle cellule nervose. Rivista di Patologia Nervosa e Mentale, 3: 337–359. McCarley R, Hobson J (1975). Neuronal excitability modulation over the sleep cycle: a structural and mathematical model. Science 189: 55–58. Mackenzie N (1965). Dreams and Dreaming. Vanguard Press, New York. MacNish R (1830). The Philosophy of Sleep. WR M’Phun, Glasgow. McVaugh M (1980). History of Medicine: Dictionary of the Middle Ages. Charles Scribners Sons, New York. Magoun HW, Rhines R (1946). An inhibitory mechanism in the bulbar reticular formation. J Neurophysiol 9: 165–171. Mauthner L (1890). Pathologie und Physiologie des Schlafes. Wien Klin Wochenschr 3: 445–446. Mishneh Torah, Sefer HaMada, Hilchoth De’oth. Ch IV: No. 4: 1180 (translated by A Lesley). Baltimore Hebrew University, Baltimore. Moore RY, Eichler VB (1972). Loss of a circadian adrenal corticosterone rhythm following suprachiasmatic lesions in the rat. Brain Res 42: 201–206. Moruzzi G (1964). The historical development of the deafferentation hypothesis of sleep. Proc Am Philos Soc 108: 19–28. Moruzzi G, Magoun HW (1949). Brain stem reticular formation and activation of the EEG. EEG Clin Neurophysiol 1: 455–473. Mosso A (1880). Sulla circolazione del sangue nel cervello dell’uomo. Mem Real Acc Lincei 5: 237–358. Mueller M (1984). The Iliad, by Homer. Unwin Critical Library. Allen & Unwin, London. Nauta W (1946). Hypothalamic regulation of sleep in rats: an experimental study. J Neurophysiol 9: 285–316. O’Malley CD (1965). Andreas Vesalius. University of California Press, Los Angeles. Osborne J (1849). Tending to prove that the choroid plexus is the organ of sleep. J Pract Med 977–982. Osler W (1906). The Principle and Practice of Medicine: Designed for the Use of Practitioners and Students of Medicine. 6th edn. Apple, New York. Pachter HM (1951). Paracelsus. Magic into Science. Schuman, New York. Palmer M, Breuilly E, Chang Wei Ming et al. (translators) (2006). The Book of Chuang Tzu. Penguin Books, London.
Pavlov IP (1923). On the identity of inhibition as a constant factor in the waking state with hypnosis and sleep. Q J Exp Physiol 13 bis: 39–43. Pavlov I (1927). Lecture XV. Internal inhibition and sleep as one and the same process. Conditioned refexes: an investigation of the physiological activity of the cerebral cortex. Translated by GV Anrep. Oxford University Press, Cambridge, England. Pfluger E (1875). Theorie des Schlafes. Arch Gesamte Physiol 10: 468–478. Pieron H (1913). Le proble`me physiologique du sommeil. Masson, Paris. Preyer T (1877). Ueber die Ursache des Schlafes. Stuttgart bei Enke, Vortrag. Purkinje JE (1846). Wachen, Schlaf, Traum und verwandte Zustande. Handworterbuch der Physiologie mit Rucksicht auf physiologische Pathologic. In: R Wagner III (Ed.), Bd Abth, 2: 412–480. Rabl-Ruckhardt H (1890). Sind die Ganglienzellen Amo¨boid? Neurologisches Centralblatt 9: 199–200. Ranking GS (1914). The Life and Works of Rhazes. Frowde, London. Ranson S (1939). Somnolence caused by hypothalamic lesions in the monkey. Arch Neurol Psychiatry 41: 1–23. Ranson S, Ingram WR (1932). Catalepsy caused by lesions between the mammillary bodies and third nerve in the cat. Am J Physiol 101: 690–696. Rechtschaffen A, Kales A (1968). A Manual of Standardized Terminology, Techniques, and Scoring System for Sleep Stages of Human Subjects. National Institutes of Health, Washington, DC. Richardson G, Carskadon M, Flagg W et al. (1978). Excessive daytime sleepiness in man: multiple sleep latency measurements in narcoleptic and control subjects. Electroencephalogr Clin Neurophysiol 45: 621–627. Richter CP (1922). A behavioristic study of the activity of the rat. Comp Psych Monographs 1: 1–55. Richter CP (1965). Biological Clocks in Medicine and Psychiatry. Charles C Thomas, Springfield, IL. Roentgen WK (1896). On a New Kind of Rays, read before the Wu¨rzburg Physical and Medical Society, 1895. Translated by Arthur Stanton. Nature 53: 274. Rolando L (1809). Saggio sopra la vera strattura del cervello dell’uomo e degli animalie sopra la funzioni del sistema nervoso. Stamperie di S.S.R.M. privilegiata, Sassari. Sakurai T, Amemiya A, Ishii M et al. (1998). Orexins and orexin receptors: a family of hypothalamic neuropeptides and G protein-coupled receptors that regulate feeding behavior. Cell 92 (4): 573–585. Schenck CH, Bundlie SR, Ettinger MG et al. (1986). Chronic behavioral disorders of human REM sleep: a new category of parasomnia. Sleep 9 (2): 293–308. Severinghaus JW, Mitchell RA (1962). Ondine’s curse – failure of respiratory automaticity while awake. Clin Res 10: 122. Sherin JE, Shiromani PJ, McCarley RW et al. (1996). Activation of ventrolateral preoptic neurons during sleep. Science 271 (5246): 216–219.
HISTORY OF SLEEP MEDICINE Siegel R (1973). Galen on Psychology, Psychopathology, and Function and Diseases of the Nervous System. Karger, Basel. Siegel R (1976). Galen on the Affected Parts. Translation from the Greek text with explanatory notes. Karger, Basel. Siegel JM, Manger PR, Nienhuis R et al. (1998). Monotremes and the evolution of rapid eye movement sleep. Philos Trans R Soc Lond B Biol Sci 353 (1372): 1147–1157. Siffre M (1964). Beyond time. H Briffault. Edited and translated by McGraw-Hill, New York. Simpson M (2001). The Metamorphoses of Ovid. University of Massachusetts Press, Amherst. Simpson S, Galbraith JJ (1906). Observations on the normal temperature of the monkey and its diurnal variation, and on the effect of changes in the daily routine on this variation. Trans Roy Soc Edinburgh 45: 65–106. Snyder F (1969). Dynamic aspects of sleep disturbance in relation to mental illness. Biol Psychiatry 1 (2): 119–130. Sommer W (1868). Neue Theorie des Schla¨fes. Zeitsch. f. Rationelle Medicine, Bd. XXXIII: 214ff. Spielman AJ, Saskin P, Thorpy MJ (1987). Treatment of chronic insomnia by restriction of time in bed. Sleep 10: 45–56. Stephen FK, Zucker I (1972). Circadian rhythms in drinking behavior and locomotor activity of rats are eliminated by hypothalamic lesions. Proc Natl Acad Sci U S A 69: 1583–1586. Sullivan CE, Issa FG, Berthon-Jones et al. (1981). Reversal of obstructive sleep apnea by continuous positive airway pressure applied through the nares. Lancet i: 862–865. Toh KL, Jones CR, He Y et al. (2001). An hper2 phosphorylation site mutation in familial advanced sleep phase syndrome. Science Feb 9; 291 (5506):1040–1043. Veith I (1949). Huang Ti Nei – The Yellow Emperor’s Classic of Internal Medicine. Williams and Wilkins, Baltimore. Vogel G (1960). Studies in psychophysiology of dreams, III. The dream of narcolepsy. Arch Gen Psychiatry 3: 421–428. von Economo C (1923). Encephalitis lethargica. Wien Med Wochenschr 73: 777–782.
25
von Economo C (1929a). Schlaftheorie. Ergeb Physiol 28: 312–339. von Economo C (1929b). Die Encephalitis lethargica, ihre Nachrankheiten und ihre Behandlung. Urban and Schwarzenberg, Berlin. Von Haller A (1766). Elementa Physiologiae Corporis Humani. 8 vols. sumptibus. M. Bousquet et sodorurn, Lausannae. Wadd W (1816). Cursory Remarks on Corpulence. 3rd edn. London. Weir Mitchell S (1890). Some disorders of sleep. Am J Med Sci 100: 190–227. Weitzman ED, Schaumburg H, Fishbein W (1966). Plasma 17-hydoxy-corticosteroid levels during sleep in man. J Clin Endocrinol Metab 26: 121–127. Weitzman ED, Czeisler CA, Zimmerman JC et al. (1980). Sleep duration, sleep stages and waking time are related to circadian phase in young and older men during nonentrained conditions. Trans Am Neurol Assoc 105: 371–374. Weitzman ED, Czeisler CA, Coleman RM et al. (1981). Delayed sleep phase syndrome. Arch Gen Psychiatry 38: 737–746. Wells W (1878). Some nervous and mental manifestations occurring in connection with nasal disease. Am J Med Sci 677–682. Westphal C (1877). Eigenthumliche mit Einschlafen verbundene Anfalle. Arch Psychiatr Nervenkr 7: 631–635. White R (1975). The Interpretation of Dreams: The Oneircriticon by Artemidorus. Noyes Press, Park Ridge, NJ. Wight Duff J, Duff Arnold M (1994). Minor Latin Poets, vol. i. Publilius Syrus. Harvard University Press, Harvard, MA. Wijsenbeek-Wijler H (1978). Aristotle’s Concept of Soul, Sleep and Dreams. Adolf M Hakkert, Amsterdam. Willis T (1684). Practice of Physick. T. Dring, C. Harper, and J. Leigh, London. Wittern R (1989). Sleep theories in the antiquity and in the Renaissance. In: JA Horne (Ed.), Sleep ’88. Fischer Verlag, Stuttgart, pp. 11–22.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 2
Normal sleep-recording and scoring techniques MAX HIRSHKOWITZ 1 * AND AMIR SHARAFKHANEH 2 Department of Medicine & Menninger Department of Psychiatry, Baylor College of Medicine and Michael E. DeBakey VAMC Sleep Center, Houston, TX, USA
1
2
Department of Medicine, Baylor College of Medicine, Michael E. DeBakey VAMC Sleep Center and Methodist Hospital Sleep Diagnostic Laboratory, Houston, TX, USA
EEG AND EOG CORRELATES OF NORMAL HUMAN SLEEP Overview Sleep is a state associated with inactivity and decreased responsiveness to environmental stimuli. Unlike coma, sleep is rapidly reversible. Furthermore, sleep is an active process and not a passive consequence of brainstem and cortical metabolic depression (Hirshkowitz and Sharafkhaneh, 2005). Humans characteristically sleep during the dark photoperiod and the timing of sleep onset generally coincides with declining core body temperature. Sleep is often conceptualized as a brain process. Furthermore, our tendency to dichotomize the world would erroneously consider sleep as a single process contrasting with wakefulness. Sleep is actually composed of several distinct processes that are different both quantitatively and qualitatively. Each type of sleep has its own unique characteristics, regulatory mechanisms, and mental correlates. Deprivation of one particular sleep process will lead to selective rebound of that type of sleep when the individual is subsequently allowed to sleep ad lib. Because sleep is a brain process, an electroencephalographic (EEG) technique for recording brain activity was adopted for sleep research soon after its discovery at the beginning of the 20th century (Berger, 1930). Hans Berger, the father of EEG, himself made the first EEG sleep recording. He noted that the alpha rhythm (a 8–13 cycle per second (cps) waveform), prominent during eyes-closed relaxed wakefulness, would disappear and be replaced by low-voltage, mixed-frequency activity when an individual fell asleep. Nearly a century later, this EEG correlate is still used as a marker for *
sleep onset. Closer scrutiny of EEG reveals that alpha rhythm frequency may slow slightly and amplitude increase just before sleep onset. Furthermore, blinking and saccadic eye movements disappear and may be replaced by slow, rolling eye movements.
Traditional recording technique The traditional EEG sleep-recording technique employed high-gain, analog, differential bioamplifiers to record continuous ink pen tracings on fan-fold paper driven by a mechanical chart drive. The bioamplifiers would magnify the voltage difference between two gold or silver disk electrodes attached to the surface of the skin or scalp (Gibbs and Gibbs, 1950). Electrode placement varied from laboratory to laboratory until a standardized technique was developed (Jasper, 1958). An ad hoc committee was formed by the Sleep Research Society and an amazing collection of content-expert thought leaders began meeting under the chairmanship of Drs. Allan Rechtschaffen and Anthony Kales in the late 1960s. Differences of opinion were hashed out (in some cases after raucous disagreement, shouting, and recrimination, as I’ve been told by committee members in attendance) and consensus was finally reached. Someone once told me that Dr. Rechtschaffen physically barred the exit door at one point and threatened: “no one leaves until we all agree.” I wrote about the incident as an example of the mythos that develops surrounding pivotal events in the history of any field, but in this case Dr. Rechtschaffen phoned me after reading my article and said that it was true and really happened. As
Correspondence to: Max Hirshkowitz, Ph.D., Michael E. DeBakey VAMC Sleep Center 111 i, 2002 Holcombe Blvd, Building 100, Suite 6C-344, Houston 77030, USA. Tel: (713) 794-7562, Fax: (713) 794-7558, E-mail:
[email protected]
30
M. HIRSHKOWITZ AND A. SHARAFKHANEH
realized by the chairman, reaching consensus was really the key issue. It was the single most important element that allowed A Manual of Standardized Terminology, Techniques and Scoring System for Sleep Stages of Human Subjects (Rechtshaffen and Kales, 1968) to succeed and endure for over four decades. R&K (as it is commonly called, after the chairmen’s initials) was not particularly innovative nor did it depart much from already-established techniques. Its genius was in the consensus achieved. If everyone had returned to their respective laboratories and continued doing things their own way, the project would have failed and it is unlikely that sleep research would have advanced as rapidly with a common set of terms, recording techniques, and data reduction procedure. R&K firmly established making a so-called monopolar recording from a central EEG derivation. By referencing an electrode at either C3 or C4 to a (relatively) inactive site (the earlobe or mastoid), the amplified potential difference between the two sites would reflect the electrical activity over the brain’s central lobes on the scalp. Furthermore, the signal is conditioned using high- and low-pass analog filters that reduce (roll off) amplitude by a known percentage per octave. This could be described in terms of the frequency at which some fraction (e.g. one-half) of the amplitude was attenuated. Another way of looking at analog filtering relates to the fact that EEG amplifiers are alternating current (AC)-coupled. This simply means that the amplifier signal output gravitates to ground (0 V) at a set rate. That is, the instantaneous potential difference between two electrodes is sensed, amplified, sent to the pen’s electromagnets, and produces a deflection that is recorded on a moving paper strip. Within a set period of time, that pen point will fall to 0 V and the rate at which it falls amounts to filtering (expressed as a fall time constant). For
example, a rapid fall time constant would attenuate the ability to display slow waves. Aserisnky and Kleitman’s (1953) discovery of “regularly occurring periods of eye motility” during somnolence made recording eye movements during overnight sleep studies de rigueur. The same recording principles used for EEG apply to making eye movement recordings. Traditional technique recommended making two monopolar recordings displayed on separate channels. Electrodes placed just outside the outer canthus of each eye were referenced to the earlobe or mastoid. In this manner, horizontal eye movements would produce deflections in opposite directions on the two channels as the positive corneal potentials moved toward the electrode on one eye and away from the electrode on the other. In order to detect vertical eye movements, the electrodes at the outer canthi were displaced vertically 1 cm above on one eye’s midline and 1 cm below midline on the other. Filtering could be constricted to a tighter bandwidth because the range of relevant activity is narrower for electro-oculograms (EOG) than for EEG. However, filters were set to preserve low frequencies because many sleep researchers used EOG to visualize slow-wave activity from eye leads because they are proximal to the frontal lobe. Jouvet’s description of near electromyographic (EMG) atonia in skeletal muscles during paradoxical (rapid eye movement (REM)) sleep completed our outline of major bioelectrical correlates during sleep (Jouvet et al., 1959). Consequently, a submentalis electromyogram (i.e., chin EMG) was added to many investigators’ routine recording montage. Thus, the standard recording technique described in R&K required a minimum of four channels (Table 2.1) for overnight sleep recordings. The term “polysomnogram” emerged to designate recordings made in this manner and the recording process itself became known as “polysomnography”
Table 2.1 Traditional sleep-scoring technique parameters* Label
Derivation
Specification origin
Reference
EEGC EOGL EOGR EMGSM EEGO
C3–A2 or C4–A1 LOC-A2 or LOC-M2 ROC-A2 or ROC-M2 Chin EMG O3–A2 or O4–A1
Rechtshaffen and Kales Rechtshaffen and Kales Rechtshaffen and Kales Rechtshaffen and Kales Bonnet et al. (1992)
EEGF
F3–A2 or F4–A1
R&K R&K R&K R&K American Sleep Disorders Association (ASDA) American Academy of Sleep Medicine (AASM)
C:Central, L:Left, R:Right, S:Submental, O:Occipital, F:Frontal.
Iber et al. (2007)
(1968) (1968) (1968) (1968)
NORMAL SLEEP-RECORDING AND SCORING TECHNIQUES (Keenan 2009). This amalgam of Greek and Latin terminology (painful to the ears of some) quickly became standard parlance (preferred over the linguistically purer polyhypnogram or multisomnoscript).
Waveforms OVERVIEW EEG activity contains both ongoing background activity and specific events that stand out from the background. As a continually oscillating voltage fluctuation, one way to categorize EEG is based on its frequency. Fairly consistent bandwidths of activity occur across individuals and are designated with Greek letters (Table 2.2). Another way to label EEG activity is based on morphology (Niedermeyer and Lopes da Silva, 1987). Particular waveforms are usually given fairly descriptive names (Table 2.2).
Table 2.2 Normal electroencephalogram waveforms in humans Designation
Description
a (alpha)
8–13 cps rhythm associated with relaxed wakefulness when eyes are closed. Alpha activity is normally most prominent in occipital leads. Bursts of alpha lasting 3 seconds, or longer, are used to define arousal from nonrapid eye movement sleep. Alpha activity may be intermixed with slow wave in patients suffering from or experiencing pain >13 cps waveform occurring both during alert, vigilant wakefulness and to a lesser extent during sleep. Sometimes during sleep it will be seen as bursts or “brushes” riding in or on other activity. Increased beta activity is known to occur during sleep in patients with major depressive disorders and in individuals taking certain drugs (e.g., barbiturates) 4–8 cps activity usually most prominent in central and temporal leads. A unique variant commonly occurs during rapid eye movement sleep and is called sawtooth theta, owing to its notched appearance, reminiscent of a buzz saw’s blade 3.5 cps activity that is usually highamplitude. Delta activity at the lower end of the spectrum (<2 cps) is often called slow waves
b (beta)
y (theta)
D (delta)
31
Table 2.2 Continued Designation
Description
m (mu)
Mu waves are also called wickets, owing to their similarity in shape to the wickets used in the game croquet. They occur rhythmically and are rounded on the top and sharp at the bottom. Often asymmetric, not blocked by eye opening, they disappear with contralateral arm movements and are most prominent in central leads l (lambda) Triangular symmetric waves that occur bilaterally and most prominently in occipital leads. Often seen when an individual stares at a featureless array but also seen during reading. Quite similar to POSTS POSTS Diphasic or triphasic waves most prominent in occipital regions. These positive occipital sharp transients of sleep have a triangular appearance and are similar in appearance to lambda but occur during stage 1 and 2 sleep, usually early in the night BETS Benign epileptic transients of sleep. Small sharp waves occurring asynchronously most prominently in temporal and frontal leads. They disappear in deeper stages of sleep Vertex sharp Also called V waves, this sharply waves contoured wave stands out from background activity and occurs most prominently in central leads placed near the midline. V waves are usually seen at or near sleep onset K complex The K complex was recently redefined in the new AASM Manual (Iber et al., 2007) as: “an EEG event consisting of a well-delineated negative sharp wave immediately followed by a positive component standing out from the background EEG with total duration 0.5 seconds, usually maximal in amplitude over the frontal regions” Sleep spindles The sleep spindle is a 0.5-second burst of 11–16 cps waves most prominent in central leads. Spindles are the product of thalamocortical discharge and can be increased by sedative–hypnotic compounds. The waveform’s name derives from the fact that the envelope is “spindle”-shaped POSTS, positive occipital sharp transients of sleep; AASM, American Academy of Sleep Medicine; EEG, electroencephalogram.
32
M. HIRSHKOWITZ AND A. SHARAFKHANEH
Some waveforms occur in combination (e.g., alpha– delta sleep) and/or may form a background activity while others clearly stand out from that background (e.g., K complex). Some combinations are common (low-voltage, mixed-frequency activity) while others are rare (saw-tooth theta and sleep spindles). Specific waveforms may come in bursts (phasic) or be ongoing (tonic). Finally, some waveforms are used to define sleep stages while others are nonspecific.
THE
TRANSITION FROM WAKEFULNESS TO SLEEP
Most, but not all, individuals produce EEG alpha activity when sitting quietly awake with their eyes closed. A sudden attenuation of alpha activity occurs when the eyes are opened or when the person becomes engaged in a strenuous mental task (e.g., counting backwards by 7s beginning with the number 943). Alpha activity will also cease when sleep onset occurs (Figure 2.1, panel A); however, it does not dwindle. There may be a slight slowing of waveform frequency and increase in amplitude just before it disappears and is replaced by EEG theta and/or low-voltage mixed-frequency activity. There may even be a vertex sharp wave or two. As sleep becomes entrenched, spindles and K complexes will appear. Awakening an individual during this type of sleep may or may not elicit a self-report of being asleep. Mental content
ranges from meager, to repetitive and ruminative, to full-blown hypnagogic hallucinations containing vivid dreamlike images. Some individuals produce little or no alpha activity. In such cases, determining the moment of sleep onset can be quite difficult. This problem has long been known. In fact, Loomis and colleagues (1937) in their discussion of sleep onset admit that the “nonalpha type of individual passes into the same state of sleep as the alpha type but it is much more difficult to distinguish states A and B. State B is characterized by less high-frequency potentials. In general the nonalpha type of record looks much alike, awake or asleep, until the later stages of spindles or random appear.” Alternative criteria for sleep onset that does not rely on alpha activity have also been used (e.g., the appearance of the first spindle).
THE
MAIN BODY OF SLEEP
More than 50% of the time spent sleeping is associated with EEG that is fairly low-voltage, mixed-frequency activity (Williams et al., 1974; Hirshkowitz et al., 1992). This background activity may be punctuated by sleep spindles, K complexes, or an occasional delta wave. The eyes are mostly stationary. Although EMG activity is lower than during wakefulness, the level can vary across a wide range. Awakening individuals
E1-M2 E2-M2 EMGSM F4-M1 C4-M1
A
O2-M1 E1-M2 E2-M2 EMGSM F4-M1 C4-M1
B
O2-M1 E1-M2 E2-M2 EMGS F4-M1 C4-M1
C
O2-M1
Fig. 2.1. Transitions between sleep and wakefulness. Panel A illustrates sleep onset, panel B shows sleep termination, and panel C depicts a brief arousal from sleep (momentary wakefulness) followed by an immediate return to sleep. E1 (left outer canthus); E2 (right outer canthus); M1 (left mastoid); M2 (right mastoid); EMGSM (electromyogram: submentalis); F4 (right frontal); C4 (right central); O2 (right occipital).
NORMAL SLEEP-RECORDING AND SCORING TECHNIQUES from this type of sleep reveals a paucity of mental activity; however, they usually acknowledge that they were sleeping. The intensity of a stimulus required to awaken an individual varies during this type of sleep with the threshold being higher when presented concurrently with a sleep spindle. The K complex can be a harbinger of arousal. The likelihood of awakening occurring within 2 minutes of a K complex is higher than its incidence during the 2 minutes before.
SLOW-WAVE
SLEEP
During the first hour to hour and a half of sleep, most individuals produce a gradually increasing quantity of high-amplitude delta activity. It begins with a few slow waves and then longer trains of slow waves, and may reach a point when the low-voltage, mixed-frequency activity is completely replaced by high-voltage synchronized waves. Spindle activity may persist, occurring concurrently with slow-wave activity. This type of spindle activity has been described as riding on the slow waves. Arousability is very depressed (high arousal threshold) during this type of sleep and awakening an individual from slow-wave sleep reveals a paucity of mental content and often amnesia about having been awakened. Eyes are immobile and EMG level is usually low.
EPISODIC
CORTICAL ACTIVATION WITH SACCADIC
EYE MOVEMENTS
Episodes of low-voltage, mixed-frequency activity that are devoid of spindles and K complexes occur approximately every 90 minutes. This background activity is remarkably similar to wakefulness; however, the overall frequency is slower and saw-tooth theta activity
33
occasionally appears. Saccadic REMs accompany these episodes and awakening the individual reveals concurrent fully developed dream mentation. Research suggests the eye movements correspond to direction of gaze in the dreams. Arousal threshold is very high during the eye movement bursts but only moderately elevated at other times during this type of sleep. Skeletal muscle tone is absent and the individual sleeps in a state of functional paralysis; however, there may be twitching, and changes in facial expression.
AWAKENINGS,
AROUSALS, AND THE CYCLIC
ALTERNATING PATTERN
EEG criteria for scoring an awaking from sleep require that alpha activity persist for 15 seconds, or more (Figure 2.1, panel B). However, most sleep disturbances fall short of this duration criterion; therefore, an additional, more sensitive technique was needed to detect transient sleep disturbances. An American Sleep Disorders Association task force was formed to develop criteria for scoring central nervous system arousals (Bonnet et al., 1992). Arousals were defined in terms of EEG speeding, which involves sudden shifting from ongoing sleep EEG to faster-frequency waveforms (e.g., a shift from low-voltage, mixed-frequency activity to alpha rhythm) for more than 3 but less than 15 seconds (Figure 2.1, panel C). During the type of sleep marked by saccadic REM, to qualify as arousal there has to be both EEG speeding and increased skeletal muscle activity. Another group of sleep researchers, independently exploring the issue of transient sleep disturbance, focused on the episodic sequences of alternating EEG bursts and quiescence that occur during overnight sleep recording (Figure 2.2). This cyclic alternating
E1-M2 E2-M2 EMGSM F3-M2 F4-M1 C3-M2 C4-M1 O1-M2 O2-M1
Fig. 2.2. The cyclic alternating pattern (CAP). E1 (left outer canthus); E2 (right outer canthus); M1 (left mastoid); M2 (right mastoid); EMGSM (electromyogram: submentalis); F4 (right frontal); C4 (right central); O2 (right occipital); F3 (left frontal); C3 (left central); O1 (left occipital).
34
M. HIRSHKOWITZ AND A. SHARAFKHANEH
pattern consists of an A phase, that can be a vertex sharp wave; a K complex; a K alpha; a burst of highamplitude, low-frequency waves; a burst of polymorphic waves; or a burst of high-amplitude theta or alpha activity, followed by quiescent B phase (Terzano et al., 2002). The oscillation has a period of 20–40 seconds and there are three types of A phases. The first (A1) does not meet criteria for scoring an arousal; however, the other two (A2 and A3) include EEG frequency shifts to the alpha bandwidth that constitutes EEG speeding in most cases (A1). In fact, A3 meets arousal criteria more than 95% of the time.
Data reduction by staging OVERVIEW Data reduction is the raison d’être for sleep staging. At its foundation, it is a time domain analysis. Sleep stage scoring involves applying a set of rules in order to classify polysomnographic activity occurring over a defined period of time into one or another category. The time period is referred to as an epoch and the categories are sleep stages. There have been a number of sleep-scoring systems over the years and each also has variants. Loomis and colleagues (1936), who made the first continuous overnight recordings, developed the first such system. Dement and Kleitman (1957) updated sleep staging after Aserinsky had discovered REM sleep. R.L. Williams, in 1959, developed another convention that considered EEG activity in frontal, central, and occipital derivations and proceeded to compile normative data (Williams et al., 1974). In 1968 the Sleep Research Society’s ad hoc committee developed the standardized Manual (aka R&K: Rechtschaffen and Kales, 1968). In addition to defining recording technique and terminology, R&K included a sleep stage-scoring system which did indeed become the standard for the next 40 years. Most recently, the American Academy of Sleep Medicine (AASM), as part of a project to provide scoring guidelines for all major clinical aspects of polysomnography, had a taskforce revisit and update R&K (Iber et al., 2007). The revision was expected to help make scoring more reproducible and applicable to clinical recordings. This latest system, from The AASM Manual for the Scoring of Sleep and Associated Events, will be described in the following paragraphs with explanatory notes on how it differs from R&K. First, AASM’s updated scoring system also firmly establishes epoch length at 30 seconds, without alternatives. Secondly, the revised system abolishes the designation MT (movement time). The scorer must assign one stage designation (N1, N2, N3, R or W, as defined below) to each epoch in the recording based on its
EEG, EOG, and EMG characteristics (Table 2.3). In general, when an epoch contains features of more than one stage, classification should represent the stage characterizing the majority of that epoch. To some degree, the new AASM system’s recommended recording montage is a throwback to the Williams system. Recommended derivations include frontal, central, and occipital EEG. Specifically, F4–M1, C4–M1, and O2–M1 with backup electrodes placed at F3, C3, O1, and M2 are specified. An alternative montage is also endorsed: Fz–Cz, Cz–Oz, and C4–M1. This differs from R&K’s single monopolar EEG lead recorded from C3 or C4. Eye movement recording technique remains the same as in R&K, with altered naming conventions: “E” is used to designate eye, rather than ROC and LOC for right and left outer canthi. Also, the more accurate “M” designation for mastoid replaces the older label “A.” Thus, recommended eye movement recording placements are E1–M2 and E2–M2, with E1 placed 1 cm below LOC and E2 placed 1 cm above ROC (or vice versa). An alternative montage is allowed if one wishes to accentuate vertical eye movements (E1–Fpz and E2–Fpz, where both E1 and E2 are placed 1 cm below the outer canthus of each eye).
WAKEFULNESS Stage W (wakefulness) is scored when an epoch contains 15 or more seconds of EEG alpha activity (while eyes are closed). For individuals who do not produce EEG alpha activity, the presence of fast-activity (EEG beta), blinking, saccadic eye movements, and high EMG accompanies wakefulness (Figure 2.3).
NREM
SLEEP
Stage N1, previously called stage 1, is scored when an epoch contains less than 15 seconds of EEG alpha activity but also does not include K complexes, spindles, or REM. For individuals who have little or no alpha activity, identifying N1 can be difficult. EEG waveform content is generally low-voltage with mixed frequencies; however, vertex sharp waves (V waves) may stand out from that background. Slow rolling eye movements may occur but they are not specific to N1 in that they are also known to occur in wakefulness (Figure 2.4, panel A). Stage N2, previously called stage 2, is scored when sleep spindles and/or K complexes are present in an epoch that has a low-voltage, mixed-frequency activity background. Delta and/or slow waves may occur; however, their total duration (of waves with amplitude >75 mV) must neither equal nor exceed 6 seconds during an epoch. Under normal circumstances, neither rapid nor slow eye movements accompany N2 (Figure 2.4, panel B).
Table 2.3 Electroencephalographic (EEG), electro-oculographic, and electromyographic (EMG) characteristics of each sleep stage Brain wave activity
Delta
Theta
Alpha
Beta
Spindle
K complex
EMs
EMG
Mentation
W
15-second a activity in a 30-second epoch <15-second a activity. Background activity is lowvoltage with mixed frequency. Vertex sharp waves may be present Sleep spindles and K complexes occurring on a low-voltage, mixed-frequency background EEG with <6 seconds of >75 mV delta activity Increased EEG synchrony with 6 seconds of >75 mV delta activity Low-voltage mixedfrequency activity with saw-tooth theta activity
þþ
þ
Slow and rapid
"
Thoughts
þ
þ
Slow
#
Hypnagogic
þ
þ
þþ
þþ
None
#
-
þþ
þ
þ
None
#
-
þ
þ
þ
Rapid
Dreams
N1
N2
N3
R
NORMAL SLEEP-RECORDING AND SCORING TECHNIQUES
Stage
EMs, eye movements.
35
36
M. HIRSHKOWITZ AND A. SHARAFKHANEH E1-M2 E2-M2 EMGSM F4-M1 C4-M1 O2-M1
Fig. 2.3. Stage W. E1 (left outer canthus); E2 (right outer canthus); M1 (left mastoid); M2 (right mastoid); EMGSM (electromyogram: submentalis); F4 (right frontal); C4 (right central); O2 (right occipital).
E1-M2 E2-M2 EMGSM F4-M1 C4-M1
A
O2-M1 E1-M2 E2-M2 EMGSM F4-M1 C4-M1
B
O2-M1 E1-M2 E2-M2 EMGSM F4-M1 C4-M1 O2-M1
C Fig. 2.4. Stages N1 (panel A), N2 (panel B), and N3 (panel C). E1 (left outer canthus); E2 (right outer canthus); M1 (left mastoid); M2 (right mastoid); EMGSM (electromyogram: submentalis); F4 (right frontal); C4 (right central); O2 (right occipital).
Stage N3, previously called either stage 3 or stage 4, is scored when an epoch contains 6 seconds or more of greater than 75 mV delta or slow waves in the EEG derived from frontal sites. It should be noted, however, that the AASM manual does allow for an alternative to monopolar frontal lead recording and the specified bipolar derivation (Fz–Cz) will produce lower-amplitude signals (Figure 2.4, panel C). Unfortunately, the current version of the new system does not indicate how amplitude
criteria should be adjusted to avoid staging differences produced as an artifact of differences in recording technique.
REM
SLEEP
Stage R, previously called REM sleep, is scored when REM and muscle atonia accompanying an N1-like EEG pattern (Figure 2.5). Stage R is accompanied by
NORMAL SLEEP-RECORDING AND SCORING TECHNIQUES
37
E1-M2 E2-M2 EMGSM F4-M1 C4-M1
A
O2-M1
E1-M2 E2-M2 EMGSM F4-M1 C4-M1 O2-M1
B Fig. 2.5. Stage R. Examples of both phasic (panel A) and tonic (panel B) rapid eye movement sleep are illustrated. E1 (left outer canthus); E2 (right outer canthus); M1 (left mastoid); M2 (right mastoid); EMGSM (electromyogram: submentalis); F4 (right frontal); C4 (right central); O2 (right occipital).
Patterns across the night GENERAL
DESCRIPTION
Normal sleep stage architecture across the night is fairly consistent between individuals (Figure 2.6). A healthy young adult good sleeper will spend 7–8 hours in bed and sleep 85–90% of that time (Williams et al., 1974; Hirshkowitz et al., 1992). Normal entry into sleep
W Sleep stage
low-voltage, mixed-frequency EEG, low chin EMG levels, and saccadic eye movements. Not every epoch of stage R must contain eye movement activity. Once stage R has commenced, it continues regardless of the presence of eye movements until: (1) stage W occurs; (2) stage N3 occurs; (3) chin EMG increases and criteria for N1 are met; (4) an arousal or large body movement occurs, followed by N1-like EEG and slow eye movements; and (5) a sleep spindle or K complex occurs in the first 15 seconds of an epoch that does not contain subsequent REM. Researchers have sometimes distinguished stage R epochs with concomitant eye movement bursts from epochs lacking eye movements with the terms phasic REM sleep versus tonic REM sleep, although neither of these designations is sanctioned by the AASM scoring system.
R N1 N2 N3 0
1
2
3 4 5 6 7 Total recording time (in hours)
8
9
Fig. 2.6. Full night histogram showing sleep macroarchitecture.
for an adult may take 5–15 minutes and wakefulness usually gives way to stage N1. After a few minutes, N2 commences and it in turn is followed by N3. N3 continues either continuously or punctuated by N2 over the next hour and finally relents with the onset of stage R (occurring approximately 90 minutes from the initial sleep onset). The first stage R episode is usually brief, lasting 5–15 minutes. The end of the first stage R episode completes the first N–R (NREM–REM) cycle. Young adults will usually go back into N2 and N3 for the next 90 minutes, with stage R recurring to finalize the second N–R cycle. The second stage R episode is usually of longer duration than the first but the cycle’s N3 duration is decreased. As the sleep period progresses, succeeding N–R cycles generally have less stage N3, more N2, and longer stage R durations.
38
M. HIRSHKOWITZ AND A. SHARAFKHANEH
Table 2.4 Generalizations about normal sleep stage architecture 1 2
3 4 5 6 7 8 9 10
We enter sleep through stage N1 or N2 Latency to sleep onset is about 5–15 minutes; however, it may be much longer when sleeping in the laboratory, especially when sleeping there for the first time Stage N1 occupies usually <5% of total sleep time, occurring mainly at sleep–wake transitions Stage N2 occupies approximately 50% of a night’s sleep Stage N3 occupies approximately 13–20% of total sleep time The majority of stage N3 occurs during the first third of the night Stage R occupies approximately 20–25% of a night’s sleep The majority of stage R occurs during the second half of the night Stage R comes in 4–6 discrete episodes occurring approximately 90 minutes apart Men and women will not differ much in sleep stage percentages; however, women may have slightly more stage N3 as age advances
A prototypical night’s sleep has 10 general features that are enumerated in Table 2.4.
SLOW
WAVES, SLOW-WAVE SLEEP, AND PROCESS
S
Perhaps the most apparent feature of sleep architecture is the large amount of delta activity at the beginning of the night and its progressive diminution as the sleep period progresses. A typical sleep recording has delta and slow-wave EEG predominating during the first hour to hour and a half of sleep. After a brief episode of lowvoltage, mixed-frequency activity, delta and slow-wave activity again predominates, but usually with less intensity, duration, or amplitude than in the first N–R cycle. As sleep continues, each N portion of the N–R cycle is marked by progressively less delta activity. Homeostatic drive is one of the fundamental mechanisms postulated as regulating the sleep–wake cycle. The drive to sleep (process S) is hypothesized to increase as a function of the duration of prior wakefulness (Borbely, 1994). One would expect that, after a prolonged wakeful episode, this homeostatic drive would discharge, initially with great intensity and thereafter at a gradually decreasing rate as drive diminished. The similarity of this predicted pattern with the progression of slow-wave sleep (stages 3 and 4 sleep, now collectively referred to as stage N3) across the night led sleep theorists to posit delta activity as a marker for sleep homeostatic drive. Sophisticated
computerized measures of delta power (an index that combines amplitude and duration) have been studied in order to understand better the behavior of this aspect of sleep–wake regulation.
Patterns associated with aging OVERALL
TRENDS
One of the most dramatic age-related changes in sleep architecture involves stage R during the interval from birth to adolescence. At birth, stage R occupies as much as 50% of total sleep time. It quickly declines, reaching adult levels by approximately age 3 years (Roffwarg et al., 1966). It then remains fairly stable until very late in life, when it may decrease again. Another obvious change in sleep stage architecture across the lifespan is the progressive decrease in both the amplitude and duration of stage N3 sleep. In fact, stage N3 sleep may completely disappear late in life. It is also noteworthy that, in the second half of life, total sleep time gradually decreases. This decline in total sleep time can be associated with increasing sleep fragmentation produced by accumulated pathologies that adversely affect sleep. However, some sleep deterioration may relate to agerelated weakening in the underlying neurophysiological sleep-promoting mechanism. Regardless of the source of these changes, we usually spend more time in bed but less time sleeping as we get older.
NORMATIVE
DATA
In 1959 the sleep laboratories at the University of Florida, College of Medicine in Gainesville began compiling polysomnographic recordings in normal, healthy individuals. Drs. Robert L. Williams and “Bernie” Webb reasoned that to understand sleep disorders one first must define normal sleep. Polysomnograms from both male and female children, adolescents, teenagers, young adults, adults, and seniors were systematically collected, culminating in the compilation of normal values published as the EEG of Human Sleep: Clinical Applications (Williams et al., 1974). Figure 2.7 illustrates sleep stage composition for normal subjects at different ages, extrapolated from the archived data set recorded by Williams et al.
THE EVOLUTION OF RECORDING TECHNOLOGY Analog amplifiers and paper tracings AMPLIFIER
SETTINGS AND CALIBRATION
Traditional recording technique revolved around producing a paper recording. Amplifiers were set in such a manner as to produce a tracing that had uniform
NORMAL SLEEP-RECORDING AND SCORING TECHNIQUES N3 N2
Legend (clockwise
13–15 yrs
N1 R W
from top) 1%
3–5 yrs
21% 16–19 yrs
26%
1% 23% 40–49 yrs
39
4% 10% 25%
4% 7%
54%
46% 22%
2%
5% 8%
23% 50–59 yrs 22%
31% 4%
6%
2% 45% 6–9 yrs
1% 28%
21% 20–29 yrs
27%
59%
49% 1% 19% 60–69 yrs
8% 5% 22%
4%
2%
10–12 yrs
1% 27%
21% 30–39 yrs
9%
49%
48% 25%
2% 13%
70–79 yrs
6%
19%
5%
3%
14%
56%
55%
48%
8%
53%
Fig. 2.7. Sleep composition across the lifespan.
characteristics. Setting up equipment before making an overnight sleep recording was an involved process because, once made, the recording was immutable. Amplifiers were calibrated to reflect actual voltage levels in magnitude of pen deflection by inputting a known voltage through the amplifier and adjusting the pen’s driver circuit to provide a set rise and/or fall distance from baseline (Butkov, 1996). For example, a 50-mV signal might be set to produce a pen movement that would rise 10 mm above baseline. In this manner, an individual looking at the paper recording could determine when EEG delta activity exceeded 75 mV or what the peak amplitude was for a particular sleep spindle.
FILTER
SETTINGS
As previously mentioned, once a paper recording was made it could not be changed. However, if the polysomnogram was simultaneously recorded on to magnetic tape, the signals could be altered in subsequent reproductions. Under normal circumstances, the fixed nature of these recordings meant that it was critical to produce a high-quality, clean record. Electrophysiological signals were therefore filtered to remove artifact and accentuate only the activity within the bandwidth of interest (Table 2.5). Ultimately, stage scoring would be derived from each page of the paper tracing. If a paper tracing contained extraneous activity, artifacts, drifting baselines, electrical interference, or other irregularities, scorers had to do their best
notwithstanding these problems. Filtering allowed for decreasing signal amplitude of waveforms below or above relevant physiological frequencies. Except in the case of notch filters, usually used to remove the narrow bandwidth associated with electrical (50 or 60 cps) artifact, the amplitude roll-off was gradual and smooth. Consequently, the resulting signals would retain their sinusoidal characteristics and smooth appearance. The physical effects of pen inertial damping also contributed to the signal smoothness.
PAPER
SPEED
To make traditional paper recordings, the continuously oscillating signals representing EEG, EOG, and EMG activity were routed to galvanometers that electromagnetically produced arc-shaped rotary deflections at the base of an attached pen. The pen, usually provided with ink from a reservoir via capillary action, marks a continuous strip of paper driven by motorpowered pinch rollers. The polysomnograph’s chart drive that controlled paper movement speed typically had several settings. This mechanism employed heavy magnets, motors, and paper path feed guides and contributed largely to the overall bulk, weight, and expense of equipment. The most popular speed used in polysomnography was 10 mm/second; consequently, 30 seconds of recording would use one 30-cm (approximately 12-inches) wide, fan-fold page. A box of paper usually had 1000 sheets and thereby could easily
40
M. HIRSHKOWITZ AND A. SHARAFKHANEH
Table 2.5 Analog amplifier and digital computer settings for recording sleep Parameter
EEG and EOG
EMG and snoring
EKG
Respiration channels
Oximetry
Sampling rate: Desirable Sampling rate: Minimum Low-frequency setting High-frequency setting
500
500
500
100
25
200
200
200
25
10
0.3
10
0.3
0.1
n/a
35
100
70
15
n/a
All values are in cycles per second. Respiration channels include airflow, nasal pressure, esophageal pressure, ribcage movement, and abdominal movement. Body position should be sampled once per second or more. EEG, electroencephalogram; EOG, electro-oculogram; EMG, electromyogram; EKG, electrocardiogram.
accommodate 8⅓ hours of polysomnography. Laboratories (such as ours for many years) with chart drives running at 15 mm/second produced 20 second pages and would use up a box of paper in approximately 5½ hours. To summarize polysomnographic activity in the time domain, sleep staging rules were developed. The time domain is defined by a set period called an epoch that traditionally was 15, 20, 30, or 60 seconds in duration (largely determined by page length or multiples thereof).
Computerization BASICS As mundane as it may seem, the main catalyst driving sleep laboratory automation was the elimination of paper tracings. At first computer systems were interfaced with analog polysomnographic systems and signals were routed through analog-to-digital converters and stored as computer data files. These files could then be retrieved subsequently for video display from which scoring, interpretation, and analysis proceeded. As digital amplifiers became readily available they also became comparatively inexpensive. Digital amplifiers were also more compact and lightweight. Over time, technologists and sleep specialists became accustomed to scoring and reviewing polysomnograms on video screens, which eliminated the need to produce paper recording. As a result of these factors, hybrid analog–digital systems evolved into completely digital systems. This transition produced significant collateral damage, including the disappearance of high-quality amplifiers, the departure of selector panels, and an overall decline in signal quality. All of these changes occurred in the absence of any guidelines or standards
from the scientific and clinical sleep societies. By the end of the millennium, the paper polysomnogram was all but extinct. Furthermore, the last major supplier of polysomnographic paper recently went out of business. The great expectation from computerization was to provide reliable automatic sleep stage scoring and to enhance our ability to understand physiologic information in new, clinically useful ways; however, we are still waiting for these hopes to be realized.
ADVANTAGES While eliminating paper recordings certainly alleviated the – not insignificant – storage problem all sleep laboratories faced, it inadvertently had a much larger consequence. Using digitized media to view, score, and interpret sleep studies altered every aspect of sleep laboratory operations. First and foremost, the polysomnogram was no longer unchangeable. With the proper programming, a single page display could be the traditional 30 seconds or range from 1 second to the entire night. Recorded signals could be rearranged on the page, rescaled, filtered differently and redisplayed, hidden, and colorized. The background could also be modified to be blank, monochromatic, or color-shaded; have gridlines at any desired interval, in any color, at any amplitude demarcation; or even have amplitude guides provided to facilitate scoring. With the proper programming, digital systems can show an individual what the night technologist was seeing when he or she recorded the polysomnogram, what the scorer was seeing when he or she scored an event or sleep stage, or what the polysomnographer looked at when he or she reviewed the recording. The computer can potentially turn pages or horizontally scroll line tracings at any speed (up to the limit set by its processor and memory
NORMAL SLEEP-RECORDING AND SCORING TECHNIQUES retrieval speeds). Ultimately, a fully evolved system could automate a large part of the scoring process. Eliminating paper (and ink) decreased both operating and storage costs. Thirty years ago, one could usually determine there was a sleep laboratory nearby from the telltale 5-foot-high stacks of paper recordings leaning against the walls in corridors and hallways. The ability to store several overnight studies (with digital video) on a single DVD disc reduced the required storage space needed for a year’s worth of recordings to a file cabinet drawer (compared to entire rooms, in the past). Paperless polysomnography also meant an end to pen and ink well cleaning, flushing, and unclogging, as well as no more carpet stains and ink-spattered clothing. Realize also that paper and ink cost comprised the bulk of consumable supply expense.
DISADVANTAGES The principal setback associated with digital polysomnography is the erosion of signal quality. Three factors contribute to this regression: the first is the use of lower-quality amplifiers and in some cases inadequate sampling frequency. Secondly, the digital filtering techniques require further development. Finally, many systems do not provide the night technologist with proper tools to facilitate recording quality. Most notable is the disappearance of the selector panel that allowed remontaging on the fly in order to eliminate artifact. The confluence of these factors results in polysomnograms that look “choppy” and are riddled with avoidable artifact. Sharp-edged, steep roll-off, and “notch” filters commonly used for digital polysomnography produce spikier waveforms that are more difficult to read. By contrast, analog roll-off filters created EEG, EOG, and EMG signals of a quality yet unmatched by digital systems. The good news is that all of these difficulties can be resolved with improved programming.
Current technique AASM
RECOMMENDATIONS
Until this past year, digital sleep system developers had no official guidance from scientific or clinical organizations. No a priori standards existed; consequently, system designers relied on recommendations from individuals who sometimes provided good advice and sometimes not. Compromises were sometimes made due to microcomputer system limitations; however, personal computers are more than up to the task with lightning-fast central processing units, gigabytes of memory, terabytes of disk storage, high-definition large-format video screens, and super high-capacity DVD writers.
41
Several years ago, the AASM formed a digital polysomnography taskforce as part of the larger AASM Manual development project (Iber et al., 2007). The digital polysomnography taskforce was co-chaired by myself (MH) and Thomas Penzel. With the help of other content experts, we reviewed the literature so that recommendations could be provided for digital polysomnography. When published literature was not adequate to make recommendations, taskforce members participated in a series of polls conducted according to the RAND appropriateness method. The most basic technical specifications involved recording details. It was easy to agree that at least 12 bits were needed to represent amplitude. The recommendations concerning temporal resolution were more difficult but both minimal and desirable sampling rates were specified for each recording channel, as well as filter frequencies (Table 2.5).
OTHER
CONSIDERATIONS
The taskforce also created a list of possible recommendations about specific operational characteristics of digital polysomnographic systems. Using available literature and the RAND appropriateness method, the taskforce’s wish list was refined, with some items becoming recommendations and others becoming options (Table 2.6). While the AASM manual provides a good starting point for creating digital polysomnography standards, it is far from complete. Several major issues were sidestepped on the grounds that they were not within the purview of the current project. Others were considered premature, too controversial, or trivial. Crucial topics unfortunately considered outside the project’s purview included: (1) making recommendations about multiple window display capabilities; (2) creating standard benchmarks for validating a digital systems automatic scoring; and (3) defining a standard format for data storage. Many systems already have multiple windowing. In many instances, it is convenient to display a slowtrace window for one set of signals synchronized to another standard 30-second page. However, it may also improve quality assurance and provide a safer operating environment. Using dual windowing with respiration signals on a slow trace facilitates accurate split-night criteria assessment and better determination of a positive airway pressure’s efficacy during titration. In situations where arrhythmias are occurring, it is helpful to have one window that can be manually scrolled back and forth while another window continues to scroll. This allows the technologist and/or the physician on call to examine the waveforms carefully but not miss seeing new events as they occur.
42
M. HIRSHKOWITZ AND A. SHARAFKHANEH
Table 2.6 American Academy of Sleep Medicine Digital Taskforce list of recommended and optional features for computerized polysomnographic systems Designation
Digital polysomnography feature being considered
Recommended
Video resolution must be high-resolution (1600 1200, or higher) Sampling rates must be independently controllable for each recording channel High- and low-pass filters must be independently controllable for each recording channel Filter design must be improved to the level that they can functionally simulate analog-type roll-offs rather than distorting the signal by removing all activity and harmonics within a bandwidth Notch filtering for alternating current electrical interference (i.e., 50/60 cps) must be independently controllable for each recording channel The end-user must be able to toggle on and off an on-screen display of a calibration signal (a standard negative 50-mV direct current signal) A method must be incorporated so that the impedance for each channel can be checked against a reference Systems must be able to adjust the timescale on a single display page with a range from 5 seconds to the entire night Systems must be able to display an all-night histogram with sleep stage, breathing events, periodic leg movements, Sao2, and arousals. The end-user must be able to point and click anywhere on the histogram and have the system jump to that page. The system must identify whether sleep stage scoring was performed manually or automatically The system must have an audit trail for recording. That is, the end-user must be able to recall “what was the night technologist seeing when the recording was made?” There should be a “complete history” of filter settings, resolutions, and other adjustments The system must have an audit trail for scoring. That is, the end-user must be able to recall “what was the scorer seeing when this event was scored?” Video recordings made during the sleep study must be synchronized and have a temporal resolution of 1 frame/second or more Systems should have some form of digital electrode selector panel that provides an ability to select or change channel inputs The end-user should be able to display or hide each channel independently (preferably with a software toggle switch or control key) The end-user should be able to display as recorded or invert each channel independently (preferably with a software toggle switch or control key) The end-user should be able to display the setup profile (including colors) at any time (preferably with a software toggle switch or control key) The end-user should be able to reposition channels with a click–drag–drop procedure The system should be able to turn pages automatically or horizontally scroll data. Although it was not specified in the manual, the rate of paging or scrolling should be adjustable Any polysomnographic event that is automatically scored should be identified as such and the patterns used to perform the scoring highlighted on demand by the end-user. This includes staging (e.g., highlighting spindles, K complexes, alpha, etc.), sleep-disordered breathing events, arousals, and leg movements) The system should be able to perform a frequency analysis (fast Fourier transform or some other sort of power spectrum) on an end-user-specified window (omitting data segments marked as artifact)
Optional
It could be argued that the greatest current need for digital polysomnography is to have a standard set of benchmarks to help system developers design new event detection algorithms and facilitate system performance evaluations. Furthermore, if a standard set of recordings were available, performance comparisons would be possible. Recordings from different patient groups, from individuals in different age groups, and of varying technical quality could help determine the strengths and weaknesses of particular
polysomnographic systems. Composite recordings could be constructed to test a system’s ability to deal appropriately with a wide range of artifacts, both common and rare. Not far behind in terms of importance to the field would be the standardization of an adequate data file format for storing polysomnograms. This would enhance file flexibility and exchange data exchange between systems. Such a file could be read, written, and even possibly used as its primary file by a system.
NORMAL SLEEP-RECORDING AND SCORING TECHNIQUES Having a standardized file would help assure subsequent systems would be downward-compatible and in this manner protect your archival data collection from irretrievability due to incompatibility. European data format (EDF) has become the de facto standard for raw data archiving and polysomnographic data exchange. In fact, any data collected and stored in EDF from any of the six different laboratories I work with (MH), each of which has a different manufacturer’s system, can be viewed on any computer using a public domain reader. The main limitation is that EDF definitions only cover digitized recorded raw data and not the results of scoring (staging, arousal scoring, sleep-disordered breathing, etc.). However, a number of formats have extended beyond EDF and are possible candidates for a next-generation standard. The decision to take file format definition off the AASM digital taskforce’s agenda may turn out to be an important missed opportunity. Under the heading of controversy falls the protectionist schemes employed as antipirating measures. The most egregious of these is the use of a plug-in USB, magnetic card, or I/O port dongle that prevents the program from operating unless it is inserted. While this may be reasonable to include on the data collection systems, it is inconvenient, problematic, and abusive to implement on systems used merely to view the recording. Impediments should not be placed between clinicians and their own patients’ data. Such practices should be outlawed either by official mandate or boycott. In summary, digital polysomnography has come a long way. Within the next few years, with the establishment of rudimentary standards, we should see significant improvement in data recording, display, and processing. The situation with automatic scoring validation and data file incompatibility will have to continue to evolve on its own. There is a rapidly changing landscape and the pace and direction of digital system development will depend largely on economic factors related mostly to clinical polysomnography.
REFERENCES Aserinsky E, Kleitman N (1953). Regularly occurring periods of eye motility, and concomitant phenomena. Science 118: 273–274. Berger H (1930). Ueber das Elektroenkephalogramm des Menschen. J Psychol Neurol 40: 160–179. Bonnet M, Carley D, Carskadon M et al. (1992). ASDA Report. EEG arousals: scoring rules and examples. Sleep 15: 173–184.
43
Borbely AA (1994). Sleep homeostasis and models of sleep regulation. In: MH Kryger, T Roth, WC Dement (Eds.), Principles and Practice of Sleep Medicine. W.B. Saunders, Philadelphia, pp. 309–320. Butkov N (1996). Atlas of Clinical Polysomnography, vol. 1. Synapse Media, Ashland, OR. Dement W, Kleitman N (1957). Cyclic variation in EEG during sleep and their relation to eye movements, body motility, and dreaming. Clin Neurophysiol 9: 673–690. Gibbs F, Gibbs E (1950). Atlas of Electroencephalography. I: Methodology and Normal Controls. Addison-Wesley, Cambridge, MA. Hirshkowitz M, Sharafkhaneh A (2005). The physiology of sleep. In: C Guilleminault (Ed.), Handbook of Clinical Neurophysiology, vol. 6. Elsevier, New York, pp. 3–20. Hirshkowitz M, Moore CA, Hamilton CR et al. (1992). Polysomnography of adults and elderly: sleep architecture, respiration, and leg movements. J Clin Neurophysiol 9: 56–62. Iber C, Ancoli-Israel S, Chesson A et al. for the American Academy of Sleep Medicine (2007). The AASM Manual for the Scoring of Sleep and Associated Events: Rules, Terminology and Technical Specifications. American Academy of Sleep Medicine, Westchester, IL. Jasper HH (1958). The ten/twenty electrode system of the International Federation. EEG and Clin Neurophysiol 10: 371. Jouvet M, Michel F, Courjon J (1959). Sur un stade d’activite´ e´lectrique ce´re´brale rapide au cours du sommeil physiologique. C R Soc Biol (Paris) 153: 1024–1028. Keenan S (2009). Polysomnographic technique: an overview. In: S Chokroverty (Ed.), Sleep Disorders Medicine: Basic Science, Technical Considerations and Clinical Aspects. 3rd edn. Saunders/Elsevier, Philadelphia, pp. 137–156. Loomis AI, Harvey EN, Hobart G (1936). Electrical potentials of the human brain. J Exp Psychol 19 (3): 249–279. Loomis AL, Harvey N, Hobart GA (1937). Cerebral states during sleep, as studied by human brain potentials. J Exp Psychol 21: 127–144. Niedermeyer E, Lopes da Silva F (Eds.) (1987). Electroencephalography: Basic Principles, Clinical Applications and Related Fields. Urban and Schwarzenberg, Baltimore. Rechtschaffen A, Kales A (1968). A Manual of Standardized Terminology, Techniques and Scoring System for Sleep Stages in Human Subjects. NIH Publication No. 204. US Government Printing Office, Washington DC. Roffwarg HP, Muzio JN, Dement WC (1966). Ontogenetic development of the human sleep–dream cycle. Science 152: 604–619. Terzano MG, Parrino L, Smerieri A et al. (2002). Atlas, rules, and recording technique for scoring of cyclic alternating pattern (CAP) in human sleep. Sleep Med 3: 187–199. Williams RL, Karacan I, Hursch CJ (1974). EEG of human sleep: clinical applications. Wiley, New York.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 3
Assessment of daytime sleepiness DOUGLAS B. KIRSCH * AND RONALD D. CHERVIN Department of Neurology, University of Michigan, Ann Arbor, MI, USA
INTRODUCTION Excessive daytime sleepiness (EDS) is a common symptom of insufficient sleep, inadequate sleep, intrinsic sleep disorders, and many other medical conditions. Defined as “a subjective report of difficulty in maintaining the alert, awake state,” sleepiness becomes excessive when it occurs during inappropriate settings (American Academy of Sleep Medicine, 2001). Patients who suffer from EDS are common in the practices of primary care physicians, many types of specialists, and particularly sleep medicine specialists. To provide an appropriate diagnosis and effective treatment options, careful assessment by history, physical examination, and other approaches is often necessary. Repeated assessments may be necessary to track changes in EDS and response to treatment over time. Perhaps in part because it is nearly a universal experience, sleepiness is often ignored or minimized by patients. A National Sleep Foundation poll in 2002 suggested that 37% of adults are so sleepy during the day that it interferes with their daily activities a few days a month or more; 16% experience this level of daytime sleepiness a few days a week or more. Fifty-one percent of the polled subjects reported driving while drowsy, and 17% have dozed off while driving. Increased subjective daytime somnolence and chronically disrupted sleep also have been associated with an increase in estimated healthcare use (Kapur et al., 2002). People with chronically insufficient or inadequate sleep may have many complaints other than “sleepiness,” such as fatigue, lack of energy, and tiredness. Though patients may not distinguish between these expressions, clinicians may find some utility in encouraging patients to be more specific. Synonyms for sleepiness may be useful, such as drowsiness, tendency to fall asleep, and decreased alertness; additional terms for fatigue are
*
weariness, weakness, and depleted energy (Pigeon et al., 2003). Sleep disorders such as obstructive sleep apnea or narcolepsy are often thought to be associated primarily with EDS. However, patients with sleep apnea often complain more about lack of energy than EDS (Chervin, 2000). Attempting to compare alternative definitions of sleepiness, Rinaldi et al. (2001) assessed tiredness, resistible sleepiness, irresistible sleepiness, and sleep attacks by questionnaire in a group of patients referred for complaints of daytime sleepiness or possible sleep-disordered breathing. Findings demonstrated that sleep attacks and irresistible sleepiness were more specific and sensitive for short mean sleep latencies on formal testing than tiredness or resistible sleepiness.
HISTORY Some patients ask to be evaluated for EDS, but many patients, after years of suffering from sleepiness, do not realize that this state is not normal. Falling asleep at work or during social activities can become commonplace for some individuals who may not come to attention unless persuaded to seek help by friends, significant others, or near-miss motor vehicle crashes. Such patients may require detailed inquiry to elicit symptoms of EDS. Areas to explore include the length of time patients have suffered from EDS, when EDS is most notable, and what life changes may have coincided with the onset of the symptom. Questions about the situations affected by EDS may also help to assess the severity. Feeling drowsy after a large lunch, while commuting on a long train ride, or at a late-night movie are less startling demonstrations of EDS than falling asleep during important presentations, in the middle of one-on-one conversations, or while operating dangerous machinery. Drowsiness while driving is particularly important to address because of the devastating consequences to patients and others
Correspondence to: Douglas B. Kirsch, Assistant Professor, UH 8D8702, Box 0117, University of Michigan Hospital, 1500 East Medical Center Drive, Ann Arbor, MI 48105, USA. Tel: (734) 647-9064, Fax: (734) 647-9065, E-mail:
[email protected]
46
D.B. KIRSCH AND R.D. CHERVIN
(Lyznicki et al., 1998). Investigation of patients’ productivity at work and quality of life at home is also warranted. Other symptoms associated with EDS can include poor concentration, impaired memory, irritability, and emotional lability (Chervin, 2003). A sleep history should be obtained both from the patient and family members and a bedpartner whenever possible. An understanding of sleep schedules and patterns is essential, as one of the most common reasons for EDS is insufficient time spent in bed. The amount of sleep needed to remain optimally alert varies considerably between individuals, but most adults require 7.5–8 hours each night (Chokroverty, 2009). Timing of sleep, a consistent sleep schedule, and good sleep hygiene are also important. Nighttime or shift-workers are often more sleepy than those who work solely during daylight hours. In one study, up to 20% of graveyard shift workers were identified to have fallen asleep during ambulatory electroencephalogram (EEG) monitoring while at work (Torsvall et al., 1989). Circadian rhythm disturbances may lead to sleepiness during waking hours,
either in the morning or the evening, depending on the type of phase shift. Bed partners sometimes provide critical diagnostic clues, such as information about snoring, apneic spells, or leg movements during sleep. Other common medical causes of sleep fragmentation include urinary frequency, pain, and medication side-effects, any of which can be the main cause of EDS. Narcolepsy often presents with severe EDS as the primary complaint, but other informative symptoms can include cataplexy, hypnagogic or hypnopompic hallucinations, sleep paralysis, and disrupted nighttime sleep. Idiopathic hypersomnolence involves nonimperative sleepiness, long unrefreshing naps, prolonged nighttime sleep, difficulty reaching full wakefulness after sleep, and sleep drunkenness (Bassetti and Aldrich, 1997). A review of the patient’s medical history may reveal specific conditions that commonly contribute to sleepiness or fatigue: depression, cancer, and multiple sclerosis are common examples, but many others exist (Table 3.1) (Dittner et al., 2004). Many medications can cause sleepiness (Table 3.2). The family history occasionally assists in
Table 3.1 Conditions potentially causing excessive daytime somnolence Intrinsic sleep disorders Sleep-disordered breathing Periodic limb movement disorder Idiopathic hypersomnia Narcolepsy cataplexy Recurrent hypersomnia: Kleine–Levin syndrome Menstrual-related hypersomnia Extrinsic sleep disorders Insufficient sleep syndrome Environmental sleep disorder Adjustment sleep disorder Circadian rhythm disturbance Time zone change syndrome Shift work sleep disorder Irregular sleep–wake pattern Delayed sleep phase syndrome Advanced sleep phase syndrome Non 24-hour sleep–wake syndrome Medical conditions (may cause insomnia, excessive daytime sleepiness, or both) Sleeping sickness (protozoan infection) Chronic obstructive pulmonary disease Sleep-related asthma Posttraumatic hypersomnia Genetic disorders Niemann–Pick type C Norrie’s disease Prader–Willi syndrome Adapted from American Academy of Sleep Medicine (2001, 2005).
Myotonic dystrophy Moebius syndrome Fragile X syndrome Central nervous system (CNS) lesions Parkinsonism CNS tumors Vascular lesions CNS infections Sarcoidosis Cerebral degenerative disorders Dementia Endocrine disorders (e.g., hypothyroidism) Toxic–metabolic disorders Hepatic encephalopathy Chronic renal insufficiency Adrenal pancreatic insufficiency Toxic exposures Pregnancy-associated sleep disorder Hypersomnia due to drug or substance Stimulants Benzodiazepines Barbiturates Alcohol Gammahydroxybutyric acid Antiepileptic medications Psychiatric conditions (nonorganic hypersomnia) Psychosis Mood disorders
ASSESSMENT OF DAYTIME SLEEPINESS
47
Table 3.2 Selected common medications with listed adverse effects of drowsiness, sleepiness, or somnolence Benzodiazepines Alprazolam Clonazepam Diazepam Anticonvulsants Carbamazepine Fosphenytoin Gabapentin Phenobarbital Topiramate Valproic acid Lamotrigine Antidepressants Amitriptyline Fluoxetine Citalopram Lamotrigine Paroxetine Sertraline Trazodone Venlafaxine Antipsychotics Chlorpromazine Clozapine Haloperidol Olanzapine Quetiapine Risperidone Antihypertensives Amlodipine Atenolol Clonidine Enalapril Lisinopril Losartan Nicardipine Antibiotics/fungal/viral Azithromycin Ciprofloxacin Cytarabine Efavirenz Ganciclovir
Ketoconazole Nevirapine Antiparkinson Amantadine Levodopa/carbidopa Pergolide Pramipexole Ropinirole Antireflux Nitazidine Omeprazole Ranitidine Medications for pain Hydrocodone Morphine Fentanyl Oxycodone Tramadol Muscle relaxants Cyclobenzaprine Baclofen Medications for dementia Donezepil Galantamine Memantine Rivastigmine Tacrine Nonsteroidal anti-inflammatory Diclofenac Naproxen Misoprostol Indomethacin Ketorolac Antiallergy Brompheniramine Diphenhydramine Fexofenadine Loratadine Nonbenzodiazepine hypnotics Zaleplon Zolpidem
Adapted from Micromedex medical database (www.micromedex.com), searched March, 2005.
diagnosis; causes of EDS that can be familial include obstructive sleep apnea, narcolepsy, restless-legs syndrome, and advanced sleep phase syndrome (Taheri, 2004). Alcohol, caffeine use, herbal supplementation, or illegal drugs may alter sleep patterns or level of alertness.
PHYSICAL EXAMINATION Frequently, the physical examination of the patient with EDS reveals no specific findings. Patients with severe sleepiness may fall asleep in a waiting room or nod off
during a lull in conversation. Other behavioral signs of sleepiness may include yawning, ptosis, reduced activity, lapses in attention, and head-nodding (Roehrs et al., 2000). Dark or baggy circles under the eyes are often thought to represent a sign of sleepiness, but few studies have been performed to evaluate, confirm, or explain these changes. Examination findings of elevated body mass index, increased neck circumference, and crowding of the oropharynx are suggestive of obstructive sleep apnea. Abnormal neurological examination findings may lead to diagnoses of conditions
48
D.B. KIRSCH AND R.D. CHERVIN
such as myotonic dystrophy or brain tumors, which have been associated with excessive somnolence (Gibbs et al., 2002; Rosen et al., 2003). Psychiatric evaluation may reveal depression, which can have dramatic effects on sleep patterns and is probably one of the most common causes of sleepiness (Fava, 2004). Blood work is seldom used in the workup of EDS. Blood counts and thyroid-stimulating hormone may be helpful on occasion. More than 85% of narcoleptics with cataplexy share the human leukocyte antigen (HLA) allele DQB1*0602, but this finding is not necessary for diagnosis and 12–38% of the general population also carry this allele (Mignot, 1998). The cerebrospinal fluid hypocretin level is substantially reduced or undetectable in narcolepsy with cataplexy, and if it is reduced below 110 pg/ml, it may aid in diagnosis of narcolepsy without cataplexy or narcolepsy due to another medical condition (American Academy of Sleep Medicine, 2005).
SUBJECTIVE TESTING Several standardized methods for assessment of daytime sleepiness exist, but the most commonly used is the Epworth Sleepiness Scale (ESS) (Table 3.3). The ESS evaluates a patient’s self-report of sleepiness by asking about the likelihood of a patient dozing in eight different sedentary situations. The Likert response scale ranges from 0 (“would never doze”) to 3 (“high chance of dozing”). The sum of the eight item responses then quantifies subjective sleep propensity “in recent times” (Johns, 1991). This ESS is popular in part because of its ease of use and low cost. The ESS frequently appears on websites, for public use, with little explanation and variable interpretations (Avidan and Chervin, 2002). However, results should not be expected to match those obtained from objective laboratory tests. The initial publication on validity of the ESS (Johns, 1991) demonstrated a correlation with Multiple Sleep Latency Test (MSLT) results that was statistically significant but only low to moderate in magnitude. High ESS scores (>15) were observed in patients with narcolepsy, idiopathic hypersomnolence, or moderate/severe obstructive sleep apnea (Johns, 1991). In a population-based sample, subjects with intermediate and high ESS scores, in comparison to those with low scores, had only a 30% and 69% increased risk, respectively, for sleep onset during the MSLT (Punjabi et al., 2003). In a study of 237 referred patients with suspected or confirmed sleep-disordered breathing, the ESS score did not reflect mean sleep latency on the MSLT or severity of sleep apnea as measured by the apnea–hypopnea index or minimum oxygen saturation (Chervin and
Table 3.3 The Epworth Sleepiness Scale Name: ____________________________________ Today’s date: ________ Your age (years): ________ Your sex (male ¼ M; female ¼ F): _______________ How likely are you to doze off or fall asleep in the following situations, in contrast to feeling just tired? This refers to your usual way of life in recent times. Even if you have not done some of these things recently try to work out how they would have affected you. Use the following scale to choose the most appropriate number for each situation: 0 1 2 3
¼ ¼ ¼ ¼
would never doze slight chance of dozing moderate change of dozing high chance of dozing
Situation Sitting and reading Watching TV Sitting, inactive in a public place (e.g. a theater or a meeting) As a passenger in a car for an hour without a break Lying down to rest in the afternoon when circumstances permit Sitting and talking to someone Sitting quietly after a lunch without alcohol In a car, while stopped for a few minutes in the traffic
Chance of dozing ___________ ___________ ___________ ___________ ___________ ___________ ___________ ___________
Thank you for your cooperation
Aldrich, 1999). Another study of 102 patients at a sleep disorders center also found no significant association between ESS score and mean sleep latency on MSLT (Benbadis et al., 1999). Some of the discrepancy may arise from underestimation or lack of awareness of sleep propensity: in one study nearly 20% of the subjects underestimated their risk of dozing off (Reyner and Horne, 1998). These results suggest that, in practice, the ESS is best used to assess subjective sleepiness in a standardized manner, and to complement rather than replace other neurophysiological measures. Use of ESS scores longitudinally for individual patients may prove helpful in tracking symptom evolution or treatment response. The Stanford Sleepiness Scale provides a validated, subjective measure of instantaneous sleepiness on a seven-point scale (Hoddes et al., 1972; Herscovitch and Broughton, 1981). This scale, in contrast to the ESS, can be used by the same patient many times in one day. Similarly, the older Karolinska scale and a more recent cartoon face scale are alternative methods
ASSESSMENT OF DAYTIME SLEEPINESS 49 of tracking the acute level of sleepiness in a given and increased sleep efficiency. In a study of 147 patient (Akerstedt and Gillberg, 1990; Maldonado referred patients, the only factor among demographic et al., 2004). information, polysomnographic data, and subjective The Sleep–Wake Activity Inventory (SWAI) is a assessments that was found to correlate significantly multidimensional self-report of sleepiness. The EDS with mean sleep latency on the MSLT was sleep factor was demonstrated to be a valid predictor of latency on overnight polysomnography (Chervin et al., mean sleep latency on an MSLT and also appeared to 1995). Arousals or hypoxia from sleep apnea or, less separate pathological levels of sleepiness from normal often, periodic leg movements during sleep may be alertness. The EDS factor improved in patients with an indicator of the root cause of the EDS. However, sleep-disordered breathing who were effectively treapolysomnography is not generally used as an objective ted (Rosenthal et al., 1993). When a large population measure of EDS. sample was analyzed, the SWAI results appeared to demonstrate a “natural break” in EDS scores. Scores MULTIPLE SLEEP LATENCY TEST were below 10 (less sleepy) when nocturnal sleep time The MSLT is considered the standard, for objective was at or above 7 hours and above 10 when less sleep assessment of EDS, to which all other measures are was obtained (Johnson et al., 1999). compared. Developed by Carskadon & Dement in the The impact of EDS on activities of daily living can 1970s at Stanford University, this test was described be assessed by the Functional Outcomes of Sleep Quesas a test of physiological sleep tendency. The MSLT tionnaire. Initially, this questionnaire was validated to measures the speed with which a patient is able to fall discriminate between normal subjects and those seekasleep in a controlled environment at time points ing medical attention for a sleep problem (Weaver spread throughout the day (Carskadon and Dement, et al., 1997). In an older sample, significant reductions 1977). The guidelines for the tests were later revised in functioning, for a broad range of activities, were in 1986 and some pretest conditions have been evalunoted among sleepier patients, particularly those with ated recently. In January 2005, the American Academy several medical conditions or more than four medicaof Sleep Medicine published practice parameters for tions (Gooneratne et al., 2003). the clinical use of the MSLT (Carskadon et al., 1986; Adult questionnaires are unlikely to be optimal for Thorpy, 1992; Bonnet and Arand, 1998; Littner et al., use with children and adolescents. For these age groups, 2005). one of the first parental EDS assessments to be validated The technical guidelines for recording an MSLT are is contained within the Pediatric Sleep Questionnaire similar to those for nocturnal polysomnography, and at (PSQ). The PSQ and four-item sleepiness subscale have minimum utilize the Rechtschaffen and Kales (1968) proved useful in research conducted in general pediatric recording montage required to stage sleep. Included waiting rooms (Chervin et al., 2000; Archbold et al., in the montage are a referential EEG from a central 2002). Another instrument also used primarily for (C3 or C4) location, two horizontal electro-oculograms research is the Children’s Sleep Habits Questionnaire, (left and right) at the outer canthi, and a mental or subwhich screens children aged 4–10 years for sleep promental electromyogram. One or two occipital EEG blems and includes a subscale on daytime sleepiness leads are often helpful to determine sleep onset, as (Owens et al., 2000). The Pediatric Daytime Sleepiness reflected by loss of alpha activity. Other helpful leads Scale is a 13-question survey suitable for assessment of include an electrocardiogram, a microphone for respiEDS in middle-school-age children (Drake et al., 2003). ratory noise, a measure of nasal–oral airflow, and belts Finally, the ESS also has been modified and used in chilfor the detection of chest and abdominal movement. dren for research purposes (Melendres et al., 2004). None Measures of airflow and chest movement may, for of these questionnaires have been validated against example, reveal that sleep-disordered breathing interMSLT results, except for the PSQ sleepiness subscale feres with sleep onset. (Chervin et al., 2006). This subscale correlates with Preparation for the MSLT ideally begins with a 1- or MSLT findings to a limited extent, similar to that gener2-week sleep log kept by the patient, to assist with ally observed between subjective and objective sleepiness interpretation of the study. It has been recommended measures in adults. that the sleep–wake cycle be standardized for at least 7 days before the test (American Academy of Sleep NOCTURNAL POLYSOMNOGRAPHY Medicine, 2005). Medications that affect sleep, rapid The overnight polysomnogram often plays a central eye movement (REM) sleep, or sleepiness should be role in the diagnostic process. Findings that may help discontinued, if safe to do so, at least 15 days or five assess the severity of EDS include a short sleep latency half-lives before testing (American Academy of Sleep
50
D.B. KIRSCH AND R.D. CHERVIN
Medicine, 2005). Records of other substances that may change sleep, such as caffeine products, alcohol, or illegal drugs, should also be obtained, and these agents should not be used during the test (though withdrawal from higher doses of caffeine may also modify test results) (Carskadon et al., 1986). Optimally, a nocturnal polysomnogram should be performed during the patient’s usual hours of sleep, before beginning the MSLT. This allows interpretation of MSLT results with full understanding of the quality and amount of sleep on the previous night. The nap attempts should take place in a bedroom that is dark and quiet, at the patient’s desired temperature. The subject wears regular street clothes. Four or five nap opportunities begin 1.5–3 hours after the end of the polysomnogram and continue at 2-hour intervals. Prior to each attempt, the subject lies in bed and is told to “allow yourself to fall asleep” or “not to resist falling asleep.” No sleeping is allowed between the tests, nicotine use is avoided 30 minutes before each test, and vigorous activity is suspended 15 minutes before each trial (Carskadon et al., 1986). If sleep occurs at any time during one of the 20-minute trials, 15 additional minutes of recording time are allowed to see whether “sleep-onset” REM sleep occurs. If no sleep occurs, the nap attempt is terminated and a sleep latency of 20 minutes is recorded for the trial. The sleep latencies from all four or five nap attempts are averaged to obtain the mean sleep latency. Interpretation of the MSLT result must take place within the clinical context. A mean sleep latency of less than 8 minutes in adults is generally considered to reflect severe, pathological sleepiness. Values of 8 minutes or less are commonly found in patients with disorders that cause EDS (American Academy of Sleep Medicine, 2005). In a recent meta-analysis, narcoleptics had a mean sleep latency of 3.1 2.9 minutes, and patients with idiopathic hypersomnia had a mean sleep latency of 6.2 3.0 minutes (Littner et al., 2005). Normal adults typically have sleep latencies between 10 and 20 minutes. Roehrs and Roth (1992) suggest that a sleep latency of 9 minutes or more may be normal, based on studies of older patients. Other studies have also demonstrated changes in sleep latency normative values based on age: college students had a mean latency of 9.9 minutes, adults 18–29 years old 11.1 minutes, and adults 30–80 years old 12.5 minutes (Levine et al., 1988). Children tend to have substantially longer sleep latencies; for instance, a preadolescent may have an average sleep latency of 19 minutes (Hoban and Chervin, 2001). The MSLT has been used to demonstrate EDS in several types of sleep disorders, most notably narcolepsy, obstructive sleep apnea, and experimentally induced sleep deprivation (Carskadon and Dement, 1981; Mitler
et al., 1987). In addition to shortened sleep latency, many patients with narcolepsy (at least 80%) show REM sleep on two or more MSLT naps (van den Hoed et al., 1981). However, other chronic sleep disorders and especially obstructive sleep apnea can also cause similar sleep-onset REM periods (Chervin and Aldrich, 2000). Therefore, clinical information and the preceding polysomnogram are essential to an interpretation of MSLT results. The MSLT also may be used to assess response to treatment of EDS, though the utility of this measurement is uncertain, as patients may have a better clinical response than improvement in objective sleep latency (Thorpy, 1992). In clinical practice, the MSLT is useful to confirm narcolepsy with cataplexy; essential to make a diagnosis of narcolepsy without cataplexy; sometimes useful to identify narcolepsy secondary to another medical condition; and often useful to distinguish idiopathic hypersomnolence from narcolepsy. The MSLT is not routinely indicated in the assessment of patients for obstructive sleep apnea or its response to treatment, insomnia, circadian rhythm disorders, or medical or neurological causes of sleepiness (Littner et al., 2005).
MAINTENANCE OF WAKEFULNESS TEST The Maintenance of Wakefulness Test (MWT) is a variation of the MSLT designed to assess an individual’s ability to remain awake during sleep-inducing circumstances. The patient, seated in bed within a dimly lit and quiet room, is told to “sit still and remain awake” rather than to “try to fall asleep,” as in an MSLT. As initially described, the subject is monitored for sleep onset during five sessions, each lasting 20 or 40 minutes, scheduled at 2-hour intervals, beginning 2 hours after awakening from a prior polysomnogram. The recording guidelines from a polysomnographic perspective resemble those for an MSLT. More recent recommendations have included a light source of 0.1 lux, room temperature adjusted for patient comfort, and light meals 1 hour before the first nap and immediately after the noon nap. Patients should not be allowed to use extraordinary measures to stay awake, such as slapping their own face (Mitler et al., 1982; Doghramji et al., 1997). When MWT sleep latencies are compared to MSLT latencies in control subjects, the MWT sleep latencies are longer by approximately 300%. Patients with narcolepsy have shorter sleep latencies than control patients. Though fewer data exist for the MWT in comparison to the MSLT, evidence supports use of the MWT to monitor treatment effects in some sleep disorders (Mitler et al., 1982; Poceta et al., 1992). Initially, controversy existed due to the wide variety of protocols used (nap length, number of naps) and the lack of normative data.
ASSESSMENT OF DAYTIME SLEEPINESS However, some normative data were published by Doghramji et al. (1997) for both 20- and 40-minute nap length. The lower limit for normal sleep latency (first epoch of sleep scored) was considered 2 standard deviations below the mean: for a 20-minute MWT, the limit is 10.9 minutes (mean ¼ 18.1 3.6 minutes); for a 40-minute MWT, the lower limit is 12.9 minutes (mean 32.6 9.9 minutes). These data showed no clear evidence that age or sex affected MWT sleep latency (Mitler et al., 2000). One advantage of the MWT is that it has face value as a measure of the ability to stay awake under sedentary circumstances, which could have relevance for safety, concentration, or job performance. The MWT has been used by the Federal Aviation Administration to aid in determination of whether pilots with treated sleep apnea are alert enough to fly (Office of Aerospace Medicine, 2003). Some have suggested that patients should not be allowed to drive if their MWT is less than 15 minutes (1 standard deviation below the mean for sleep apnea patients in one series) (Poceta et al., 1992). However, no clear standard has been set for the MWT sleep latency for operators of any vehicle type, including drivers involved with public transportation (Poceta et al., 1992). Furthermore, neither the MWT nor the MSLT has been validated prospectively as an effective predictor of motor vehicle crashes or other accidents related to sleepiness.
OTHER TESTING Pupillometry measures the spontaneous variation of the pupil diameter and the pupillary light reflex. Sleepiness-related alterations in spontaneous pupil behavior in a dark environment were described by Lowenstein & Loewenfeld in 1958. Later, Yoss et al. (1969) discovered pupillary changes in patients with narcolepsy. More recent studies have confirmed these earlier reports, and have attempted to increase the objectivity of pupillometry (Wilhelm et al., 1998). Increase in spontaneous pupil variation has been observed in patients with hypersomnolence, including those with narcolepsy, sleep apnea, and increased sleep disruption (Cluydts et al., 2002). Many pupillometric variables correlate with mean sleep latency on MSLT, but not to the extent that they can be used effectively to predict the mean sleep latency (McLaren et al., 2002). Pupillometry remains expensive, complex, and rarely performed for assessment of sleepiness. Vigilance testing examines subjects’ performance on a monotonous task, which may be particularly relevant to sedentary work over long periods. One example of a practical vigilance test is a driving simulator; patients with narcolepsy and sleep apnea perform worse on a 30-minute test than do subjects without sleep disorders (Findley et al., 1995). Combination of a driving simulator
51
with a simultaneous cognitive task may be even more sensitive for sleepiness (Rupp et al., 2004). The Performance Vigilance Test, a monotonous, simple reaction time test, is sensitive to insufficient sleep and also improves after treatment for obstructive sleep apnea (Kribbs et al., 1993; Dinges et al., 1997). The Oxford Sleep Resistance Test monitors similar responses to a repeating stimulus and is used to point at which responses cease to determine sleep latency. Subjects with severe untreated sleep apnea clearly perform worse than normal controls (Bennett et al., 1997). Many other cognitive tests, including those of attention and memory, also may differentiate patients with sleep disorders from healthy subjects (Fulda and Schulz, 2001). Evoked potentials have been investigated for potential use in the assessment of sleepiness. Brainstem auditory evoked responses measured during sleep in apneic patients and narcoleptics are normal. Long-latency cortical potentials, both auditory and sensory, appear more sensitive to sleepiness, but have large individual variability, causing difficulty with interpretation. Event-related potentials, most commonly the auditory P300, have been used to distinguish between subjects with sleep apnea from normal controls, based on wave amplitude and latency. However, the wave alterations generally remain within physiological limits, and treatment of sleep apnea with positive airway pressure may not shorten this mildly prolonged latency (Bastuji and Garcia-Larrea, 1999). In narcolepsy, some studies have suggested that the amplitude of the auditory P300 is diminished, though other authors have not found this abnormality (Broughton et al., 1988; Sangal and Sangal, 1995).
PRACTICAL APPLICATIONS Although most patients referred to a sleep disorders clinic have a chief complaint of EDS, assessment of this problem by a careful history is usually sufficient to estimate the severity and impact. Most of the diagnostic challenge centers on the determination of underlying causes. An ESS can provide a quick, inexpensive, and repeatable quantification of subjective sleepiness. A nocturnal polysomnogram is often indicated to identify root causes for abnormal sleepiness, when such causes are not readily apparent from the history. In practice, most polysomnograms are obtained to identify or quantify any underlying sleep-disordered breathing. An MSLT is required when cataplexy is absent but narcolepsy is still in the differential diagnosis. Clinicians sometimes obtain an MSLT when an objective measure of sleepiness may help to resolve conflicting historical reports (for example, from family members and the patient); motivate treatment of sleepdisordered breathing that by history may not be severe;
52
D.B. KIRSCH AND R.D. CHERVIN
distinguish mood disorder-related sleepiness, often associated with normal sleep latencies, from other causes; or provide objective support for consequential decisions or recommendations (relating to surgery, for example). An MWT may be useful when the main clinical question concerns the ability of the patient to maintain wakefulness during sedentary situations. However, despite intuitive appeal and reasonable demonstrations of validity, neither the MSLT nor other tests of sleepiness have been adequately demonstrated to predict future motor vehicle crashes or other morbidity. Confounds, such as anxiety, can affect test results, which therefore tend to be more useful when they confirm or detect severe sleepiness than when they fail to demonstrate short sleep latencies. Negative MSLT findings generally should not be used to discount reliable subjective reports of excessive sleepiness. No single test can provide a complete assessment of excessive sleepiness, which often must involve integration of clinical, subjective, and objective laboratory data.
REFERENCES Akerstedt T, Gillberg M (1990). Subjective and objective sleepiness in the active individual. Int J Neurosci 52: 29–37. American Academy of Sleep Medicine (2001). International Classification of Sleep Disorders, revised: Diagnostic and Coding Manual. AASM, Chicago. American Academy of Sleep Medicine M (2005). International Classification of Sleep Disorders. 2nd edn. Diagnostic and Coding Manual. AASM, Chicago. Archbold KH, Pituch KJ, Panahi P et al. (2002). Symptoms of sleep disturbances among children at two general pediatric clinics. J Pediatr 140: 97–102. Avidan A, Chervin RD (2002). ESS dot com. Sleep Med 3 (5): 405–410. Bassetti C, Aldrich MS (1997). Idiopathic hypersomnia: a series of 42 patients. Brain 120: 1423–1435. Bastuji H, Garcia-Larrea L (1999). Evoked potentials as a tool for the investigation of human sleep. Sleep Med Rev 3 (1): 23–45. Benbadis SR, Mascha E, Perry M et al. (1999). Association between the Epworth sleepiness scale and the multiple sleep latency test in a clinical population. Ann Intern Med 130: 289–292. Bennett LS, Stradling JR, Davies RJO (1997). A behavioural test to assess daytime sleepiness in obstructive sleep apnoea. J Sleep Res 6: 142–145. Bonnet MH, Arand DL (1998). Sleepiness as measured by modified multiple sleep latency testing varies as a function of preceding activity. Sleep 21: 477–483. Broughton R, Aguirre M, Dunham W (1988). A comparison of multiple and single sleep latency and cerebral evoked potentials (P300) measures in the assessment of excessive daytime sleepiness in narcolepsy-cataplexy. Sleep 11 (6): 537–545.
Carskadon MA, Dement WC (1977). Sleep tendency: an objective measure of sleep loss. Sleep Res 6: 200. Carskadon MA, Dement WC (1981). Cumulative effects of sleep restriction on daytime sleepiness. Psychophysiology 18: 107–113. Carskadon MA, Dement WC, Mitler MM et al. (1986). Guidelines for the multiple sleep latency test (MSLT): a standard measure of sleepiness. Sleep 9: 519–524. Chervin RD (2000). Sleepiness, fatigue, and lack of energy in obstructive sleep apnea. Chest 118: 372–379. Chervin RD (2003). Assessment of daytime sleepiness. In: S Chokroverty, WA Hening, AS Walters (Eds.), Sleep and Movement Disorders. Elsevier, Philadelphia, pp. 132–143. Chervin RD, Aldrich MS (1999). The Epworth sleepiness scale may not reflect objective measures of sleepiness or sleep apnea. Neurology 52: 125–131. Chervin RD, Aldrich MS (2000). Sleep onset REM periods during multiple sleep latency tests in patients evaluated for sleep apnea. Am J Respir Crit Care Med 161 (2 Pt 1): 426–431. Chervin RD, Kraemer HC, Guilleminault C (1995). Correlates of sleep latency on the multiple sleep latency test in a clinical population. Electroencephalogr Clin Neurophysiol 95 (3): 147–153. Chervin RD, Hedger K, Dillon JE et al. (2000). Pediatric sleep questionnaire (PSQ): validity and reliability of scales for sleep-disordered breathing, snoring, sleepiness, and behavioral problems. Sleep Med 1: 21–32. Chervin RD, Weatherly RA, Ruzicka DL et al. (2006). Subjective sleepiness and polysomnographic correlates in children scheduled for adenotonsillectomy vs. other surgical care. Sleep 29: 495–503. Chokroverty S (2009). An overview of sleep. In: S Chokroverty (Ed.), Sleep Disorders Medicine. 2nd edn. Saunders/ Elsevier, Philadelphia, pp. 5–21. Cluydts R, De Valck E, Verstaeten E et al. (2002). Daytime sleepiness and its evaluation. Sleep Med 6 (2): 83–96. Dinges DF, Pack F, Williams K et al. (1997). Cumulative sleepiness, mood disturbance, and psychomotor vigilance performance decrements during a week of sleep restriction to 4–5 hours per night. Sleep 20 (4): 267–270. Dittner AJ, Wessely SC, Brown RG (2004). The assessment of fatigue: a practical guide for clinicians and researchers. J Psychosom Res 56: 157–170. Doghramji K, Mitler MM, Sangal RB et al. (1997). A normative study of the maintenance of wakefulness test. Electroencephalogr Clin Neurophysiol 103: 554–562. Drake C, Nickel C, Burduvali E et al. (2003). The pediatric daytime sleepiness scale (PDSS): sleep habits and school outcomes in middle-school children. Sleep 26 (4): 455–458. Fava M (2004). Daytime sleepiness and insomnia as correlates of depression. J Clin Psychiatry 65 (Suppl. 16): 27–32. Findley L, Unverzagt M, Guchu R et al. (1995). Vigilance and automobile accidents in patients with sleep apnea or narcolepsy. Chest 108: 619–624.
ASSESSMENT OF DAYTIME SLEEPINESS Fulda S, Schulz H (2001). Cognitive dysfunction in sleep disorders. Sleep Med Rev 5 (6): 423–445. Gibbs JW 3rd, Ciafaloni E, Radtke RA (2002). Excessive daytime somnolence and increased rapid eye movement pressure in myotonic dystrophy. Sleep 25: 672–675. Gooneratne NS, Weaver TE, Cater JR et al. (2003). Functional outcomes of excessive daytime sleepiness in older adults. J Am Geriatr Soc 51 (5): 642–649. Herscovitch J, Broughton R (1981). Sensitivity of the Stanford sleepiness scale to the effects of cumulative partial sleep deprivation and recovery oversleeping. Sleep 4: 83–91. Hoban TF, Chervin RD (2001). Assessment of sleepiness in children. Semin Pediatr Neurol 8 (4): 216–228. Hoddes E, Dement W, Zarcone V (1972). The development and use of the Stanford sleepiness scale (SSS). Psychophysiology 9: 150. Johns MW (1991). A new method for measuring daytime sleepiness: the Epworth sleepiness scale. Sleep 13: 540–545. Johnson EO, Breslau N, Roth T et al. (1999). Psychometric evaluation of daytime sleepiness and nocturnal sleep onset scales in a representative community sample. Biol Psychiatry 45 (6): 764–770. Kapur VK, Redline S, Nieto FJ et al. (2002). The relationship between chronically disrupted sleep and healthcare use. Sleep 25: 289–296. Kribbs NB, Pack AI, Kline LR et al. (1993). Effects of one night without nasal CPAP treatment on sleep and sleepiness in patients with obstructive sleep apnea. Am Rev Respir Dis 147 (5): 1162–1168. Levine B, Roehrs T, Zorick F et al. (1988). Daytime sleepiness in young adults. Sleep 11: 39–46. Littner MR, Kushida C, Wise M et al. (2005). Practice parameters for clinical use of the multiple sleep latency test and the maintenance of wakefulness test. Sleep 28: 113–121. Lowenstein O, Loewenfeld IE (1958). Electronic pupillography: a new instrument and some clinical applications. Arch Ophthalmol 59: 352–363. Lyznicki JM, Doege TC, Davis RM et al. (1998). Sleepiness, driving, and motor vehicle crashes. JAMA 279: 1908–1913. McLaren JW, Hauri PJ, Lin SC et al. (2002). Pupillometry in clinically sleepy patients. Sleep Med 3: 347–352. Maldonado CC, Bentley AJ, Mitchell D (2004). A pictorial sleepiness scale based on cartoon faces. Sleep 27 (3): 541–548. Melendres MC, Lutz JM, Rubin ED et al. (2004). Daytime sleepiness and hyperactivity in children with suspected sleep-disordered breathing. Pediatrics 114 (3): 768–775. Mignot E (1998). Genetic and familial aspects of narcolepsy. Neurology 50 (2): S16–S22. Mitler MM, Gujavarty KS, Browman CP (1982). Maintenance of wakefulness test: a polysomnographic technique for evaluation of treatment efficacy in patients with excessive somnolence. Electroencephalogr Clin Neurophysiol 53: 658–661. Mitler MM, Nelson S, Hajdukovic R (1987). Narcolepsy: diagnosis, treatment, and management. Psychiatr Clin North Am 11: 307–317.
53
Mitler MM, Doghramji K, Shapiro C (2000). The maintenance of wakefulness test: normative data by age. J Psychosom Res 49: 363–365. National Sleep Foundation (2002). Sleep in America Poll. NSF, Washington, DC. Office of Aerospace Medicine (2003). Guide for Aviation Medical Examiners. Available online at: http://www.faa.gov Owens JA, Spirito A, McGuinn M (2000). The children’s sleep habits questionnaire (CSHQ): psychometric properties of a survey instrument for school-aged children. Sleep 23 (8): 1–9. Pigeon W, Sateia M, Ferguson R (2003). Distinguishing between excessive daytime sleepiness and fatigue: toward improved detection and treatment. J Psychosom Res 54: 61–69. Poceta JS, Timms RM, Jeong DU et al. (1992). Maintenance of wakefulness test in obstructive sleep apnea syndrome. Chest 101: 893–897. Punjabi NM, Bandeen-Roche K, Young T (2003). Predictors of objective sleep tendency in the general population. Sleep 26 (6): 678–683. Rechtschaffen A, Kales A (1968). A Manual of Standardized Terminology, Techniques, and Scoring System for Sleep Stages of Human Subjects. Brain Information Service/ Brain Research Institute, Los Angeles. Reyner LA, Horne JA (1998). Falling asleep whilst driving: are drivers aware of prior sleepiness? Int J Legal Med 111: 120–123. Rinaldi R, Vignatelli L, D’Alessandro R et al. (2001). Validation of symptoms related to excessive daytime sleepiness. Neuroepidemiology 20: 248–256. Roehrs T, Roth T (1992). Multiple sleep latency test: technical aspects and normal values. J Clin Neurophysiol 9 (1): 63–67. Roehrs T, Carskadon M, Dement W et al. (2000). Daytime sleepiness and alertness. In: M Kryger, T Roth, W Dement (Eds.), Principles and Practice of Sleep Medicine. 3rd edn. W.B. Saunders, Philadelphia, pp. 43–52. Rosen GM, Bendel AE, Neglia JP (2003). Sleep in children with neoplasms of the central nervous system: case review of 14 children. Pediatrics 112 (1): 46–54. Rosenthal L, Roehrs TA, Roth T (1993). The sleep–wake activity inventory: a self-report measure of daytime sleepiness. Biol Psychiatry 34 (11): 810–820. Rupp T, Arnett JT, Acebo C et al. (2004). Performance on a dual driving simulation and subtraction task following sleep restriction. Percept Mot Skills 99: 739–753. Sangal RB, Sangal JM (1995). P300 latency: abnormal in sleep apnea with somnolence and idiopathic hypersomnia, but normal in narcolepsy. Clin Electroencephalogr 26: 146–153. Taheri S (2004). The genetics of sleep disorders. Minerva Med 95 (3): 203–212. Thorpy MJ (1992). The clinical use of the multiple sleep latency test: the Standards of Practice Committee of the American Sleep Disorders Association. Sleep 15 (3): 268–276. Torsvall L, Akerstedt T, Gillander K et al. (1989). Sleep on the night shift: 24h EEG monitoring of spontaneous sleep/wake behavior. Psychophysiology 26: 352–358.
54
D.B. KIRSCH AND R.D. CHERVIN
van den Hoed J, Kraemer H, Guilleminault C et al. (1981). Disorders of excessive daytime somnolence: polygraphic and clinical data for 100 patients. Sleep 4: 23–37. Weaver TE, Laizner AM, Evans LK et al. (1997). An instrument to measure functional status outcomes for disorders of excessive sleepiness. Sleep 20 (10): 835–843.
Wilhelm B, Wilhelm H, Ludtke H et al. (1998). Pupillographic assessment of sleepiness in sleep-deprived healthy subjects. Sleep 21 (3): 258–265. Yoss RE, Moyer NY, Ogle KN (1969). The pupillogram and narcolepsy: a method to measure decreased levels of wakefulness. Neurology 19: 921–928.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 4
Actigraphic monitoring of sleep and circadian rhythms EUS J.W. VAN SOMEREN * Netherlands Institute for Neuroscience, an Institute of the Royal Netherlands Society of Arts and Sciences; Department of Integrative Neurophysiology, VU University and Leiden Institute for the Clinical and Experimental Neuroscience of Sleep, Leiden University Medical Center, The Netherlands
INTRODUCTION Although polysomnography, the continuous monitoring of multiple physiological parameters during sleep, as described in Chapter 2, is the golden standard for the objective assessment of sleep and its disturbances, there may be circumstances that ask for a different approach. For example, one may want to evaluate a large number of nights, or subjects who comply poorly with wearing electrodes for hours, as may be the case in children, or in dementia. Actigraphy provides a cost-effective method of estimating the occurrence of periods of sleep and wakefulness from information on the timing, duration, and intensity of movements for multiple days, weeks, or even months. Actigraphy is the continuous long-term assessment of activity-induced acceleration by means of a small solid-state recorder. Technical progress has enabled the integration of an acceleration sensor, amplifier, filter, microprocessor, and digital memory into a case the size of a wristwatch. Like a wristwatch, these so-called actigraphs are usually worn on the wrist. After the first report on the relation of wrist movement to sleep (Kupfer et al., 1974), the first actigraphs were soon described (Colburn et al., 1976; McPartland et al., 1976) and validated for use in sleep research (Kripke et al., 1978; Mullaney et al., 1980; Webster et al., 1982). Since then, actigraphs of decreasing size and increasing capacity have become commercially available, of which an example is shown in Figure 4.1. The present chapter discusses their application in clinical
*
and experimental research on sleep and its day–night rhythm.
APPLICATIONS Actigraphy has been applied in a variety of clinical and research fields which include sleep disorders, obesity, depression, hyperactivity, and movement disorders, including periodic leg movements during sleep (reviewed in Tryon, 1991). The most extensive use has been in sleep research in healthy subjects, where it has even been suggested as an alternative for the costly and time-consuming gold standard of polysomnography. The reliability of actigraphy in the clinical evaluation of sleep disorders is a matter of debate, mostly focusing on the question whether actigraphy can replace polysomnography (Pollak et al., 2001; Tryon, 2004). There is no doubt, however, that actigraphic recordings can give valuable insights into a patient’s sleep and sleep–wake rhythms, whether or not a further investigation with polysomnography is required. Practice parameters for the use of actigraphy in the clinical assessment of sleep disorders have been published by the Board of Directors of the American Academy of Sleep Medicine in 1995 (Sadeh et al., 1995). In 2003, the practice parameters were updated (Littner et al., 2003), with an accompanying review paper on the role of actigraphy in the study of sleep and circadian rhythms (Ancoli-Israel et al., 2003). The present chapter focuses on the use of actigraphy in estimating sleep parameters and in obtaining the rest– activity rhythm over multiple days.
Correspondence to: Prof. Eus J.W. Van Someren, Head Dept. Sleep and Cognition, Netherlands Institute for Neuroscience, Meibergdreef 33, 1105 AZ Amsterdam, The Netherlands. Tel: þ 31 20 566 5500, Fax: þ 31 20 6961006, E-mail: e.van.
[email protected]
56
E.J.W. VAN SOMEREN
Fig. 4.1. Example of an actigraph worn on the wrist (Actiwatch, Cambridge Neurotechnology, Cambridge, UK).
THE ACCELERATION SIGNAL: MOVEMENT AND ARTIFACT The movement-induced signal that actigraphs utilize is picked up by a piezoelectric element, which generates small voltages if accelerations occur. It is important to realize that actigraphy data may contain artifacts. Artifacts that may affect the signal mostly during wakefulness include externally imposed movement from riding in vehicles (Ancoli-Israel et al., 1997; Pollak et al., 2001). An artifact that may be of more importance during sleep is that very sensitive accelerometers can pick up chest movements associated with breathing, if the wrist is positioned on the chest. In addition to these artifactual signalgenerating events, there may be artifactual absence of signal if an actigraph has (temporarily) not been worn. The artifacts mentioned above generate faults in the presence or absence of activity. In addition, there is the risk of an artifact that strongly affects the strength, i.e., amplitude, of the movement-induced acceleration signal. This artifact is due to the earth’s gravitational field. More specifically, the mere rotation of the wrist from upwards to downwards will induce an acceleration signal change of 2 g. This signal is a strong overestimate of the energy involved in the arm movement, because it would take much more muscle effort to induce a signal of 2 g with a wrist movement that does not change the orientation of the accelerometer in the gravitational field. The frequency range that is most affected by such gravitational artifacts depends on the speed of rotation of the wrist. Detailed investigations have demonstrated that most of these artifacts occur in the frequency range below 0.5 Hz (Van Someren et al., 1996b). These artifacts have led early studies to suggest that most of the activity-induced accelerations occur around 0.25 Hz (Redmond and Hegge, 1985), which resulted in low-pass filtering at 2 Hz in early actigraphs. However, later work demonstrated that frequency components of up to about 11 Hz are prominently present in movementinduced acceleration signals, while relatively few truly movement-induced accelerations occur below 0.5 Hz
(Van Someren et al., 1996b). Thus, although it is not possible to prevent gravitational artifacts completely with single-site accelerometer signal, a band-pass filter of 0.5–11 Hz is presently advocated and will yield a more acceptable estimate than the early filter settings of 0.25–2 Hz. After filtering, a data reduction step is necessary to allow for storage of long-term activity data in the limited memory of actigraphs. This may be accomplished in several ways, and some actigraphs leave the choice to the user. The following methods have been applied. First, one may reduce the data by measuring the time that the acceleration signal exceeds a certain threshold just above the noise floor of the device, generating a “time above threshold” number, to be stored in every 30-second or 1-minute epoch. Longer epochs are not advocated for reliable sleep detection. Alternatively, one may integrate the acceleration signal over the time it exceeds the threshold, generating a so-called area under the curve. Yet another approach is to count the number of threshold crossings, often referred to as “zero crossings.” For the remainder of this chapter we will refer to any such output as “activity level.” Depending on the mode of recording, it may be necessary to fine-tune the algorithms used to derive estimates of sleep and wakefulness from the 30-second or 1-minute epochs of activity levels.
PLACEMENT OF THE ACTIGRAPH Actigraphs have mostly been placed on the nondominant wrist, but may also be placed on the dominant wrist, the ankles, or the trunk. During active daytime wakefulness, the dominant wrist shows most motor activity (Middelkoop et al., 1997). The effect of using the dominant versus nondominant wrist on the validity of the nocturnal sleep–wake estimates is equivocal (Van Hilten et al., 1993; Nagels et al., 1996). Assessment from other places on the body generally gives results that differ only marginally from wrist-assessed movements (Meijer et al., 1992; Middelkoop et al., 1997). However, in sleep–wake rhythm research, the dominant wrist may be the preferred site in subjects who are virtually nonambulatory and sedentary, as is the case in some demented elderly patients. In conclusion, placement on the wrist is recommended, and whereas the effect of placement on the dominant or nondominant site is equivocal, it should be standardized for all subject groups within a study.
ESTIMATING SLEEP^WAKE STATE AND SLEEP PARAMETERS During sleep, the activity level is low and periods of immobility last much longer than during quiet wakefulness. Based on these simple premises, algorithms have
ACTIGRAPHIC MONITORING OF SLEEP AND CIRCADIAN RHYTHMS been developed to estimate from a time series of activity counts whether a subject is awake or asleep (Cole et al., 1992; Sadeh et al., 1994). The algorithms require storage of activity level in 30-second or 1-minute intervals, and do not work well if the data have been acquired and stored with a lower time resolution, i.e., aggregated over longer time intervals. In general, the classification of an epoch as representing “sleep” or “wakefulness” is based on a weighted sum of the activity level in the current epoch and of the activity levels and their standard deviation in a time window of a few minutes surrounding the current epoch. If this sum exceeds a certain threshold, the epoch is scored as wakefulness, and if not, as sleep. This results in a sequence of sleep and wake epochs for each recorded night, from which parameters like sleep latency, sleep duration, wakefulness after sleep onset, sleep efficiency, and several fragmentation indexes can be derived. An example of how such algorithms translate activity levels into sleep estimates is shown in Figure 4.2. Several studies (Pilsworth et al., 2001) investigated the reliability of actigraphic sleep estimate by means of a one-to-one comparison of actigraphy epochs classified as sleep versus wakefulness and equivalent polysomnography epochs classified as sleep versus wakefulness by the gold standards of Rechtschaffen
Mon 21-Nov-2005
00:00
01:00
02:00
57
and Kales (1968). In healthy subjects, actigraphy is a sensitive method: nearly 100% of the epochs classified as sleep by polysomnography are also identified as sleep by actigraphy. The specificity, however, is poor: actigraphy correctly identifies only about 40% of the epochs classified as wakefulness using polysomnography. Because healthy subjects have only a limited amount of wakefulness during their major sleep period, the overall accuracy is still high: about 90% of the epochs obtain the same classification from actigraphy and polysomnography. The reliability and validity of the actigraphy-derived sleep parameters are a matter of debate. As a result of the low sensitivity for wakefulness during the nocturnal sleep period, actigraphy tends to underestimate intermittent wakefulness and overestimate the total sleep time and sleep efficiency (Mullaney et al., 1980; Cole et al., 1992; De Souza et al., 2003). The precision of the sleep parameter estimates, and especially the precision of the sleep onset latency estimate, is very sensitive to even small deviations in the reported times of lights out and getting up, because these times have to be entered into the sleep-scoring software and determine the start and stop time of the analysis. Usually, these times are obtained from a sleep–wake diary the subject is asked to fill out daily. However, even healthy subjects may make considerable mistakes, and a
Tue 22-Nov-2005
03:00
04:00
05:00
06:00
07:00
Fig. 4.2. Example of the steps taken to derive the sleep–wake state and sleep parameters. The upper panel shows the first 2 days of a typical activity recording, where every bar represents the activity level in 1 minute. The gray part of the time series is zoomed in on in the middle panel, to provide more detail in the alternating periods of activity and rest. Based on a sleep– wake diary, the times of lights out (23:53 hours) and getting out of bed (6:47 hours) have to be entered into the software. They are shown as small dark gray bars just below the second panel. Subsequently an algorithm is run to estimate sleep onset (23:58 hours) and offset (6:47 hours), shown as small light gray bars just below the middle panel, as well as the momentary sleep– wake state over the night, which is shown in the third (thin) panel as alternating gray (wakefulness) and white (sleep) periods. Sleep parameters can be calculated from this sequence. Note, in the present example, that the subject appears to sleep soundly for the first sleep cycle of about 80 minutes, then experiences much wakefulness for more than an hour, after which sleep is once more rather sound. For the example given, a total sleep time of 5:47 hours results, and a sleep efficiency of 84%. Usually, such sleep parameters are calculated and averaged over multiple nights. (Sleep Analysis software, Cambridge Neurotechnology, Cambridge, UK.)
58
E.J.W. VAN SOMEREN
1200
Activity
In bed
Lights out
900 600 300 0 12:00
15:00
18:00
21:00
00:00
03:00
06:00
09:00
12:00
Fig. 4.3. A bedside monitoring system, consisting of a miniature logger equipped with a light sensor, a pressure-sensitive mat switch, and a software algorithm can be used to determine automatically bedtime, lights-out time, and rise time. The precision of these times determines the precision of actigraphic sleep estimates. Sleep diary times are prone to contain errors (Krahn et al., 1997; Usui et al., 1998; Eissa et al., 2001), which is not surprising because subjects are required to memorize precisely clock times at the very times when their cognitive abilities suffer from high sleep pressure or sleep inertia. The figure gives an example of a 24-hour (ordinate) actigraphic recording combined with the automated bedtime detection system. Black columns represent minute-by-minute activity counts (abscissa, arbitrary units). The light grey area indicates the period during which the subject is in bed and the dark grey area indicates the lights-out period.
precise sleep–wake diary may not even be feasible at all in very young subjects and patients with motor disabilities or limited cognitive capabilities. In these groups, actigraphic sleep estimates may become feasible only by combining actigraphy with a bedside monitor which records bedtimes, lights-out times and get-up times. Such a system has recently been developed in our group (Figure 4.3), allowing for sleep parameter estimates in these subjects as well as for improved reliability of sleep parameter estimates in healthy subjects.
COMPARISON WITH POLYSOMNOGRAPHY Actigraphy has some disadvantages as compared to polysomnography. Although a reasonable estimate of being awake or asleep is feasible from actigraphy recordings in healthy subjects under normal conditions, the reliability in, for example, insomniac and elderly patients may be worse: these subjects show an increase in the number of epochs where no movements are made, yet wakefulness is present (Hauri and Wisbey, 1992). Also, actigraphy cannot discriminate between sleep stages. In case of screening for sleep apnea, polysomnography can easily be extended to include sensors obtaining respiratory effort, oronasal airflow, and blood oxygen desaturation. Obviously, this is not within the scope of actigraphy. On the other hand, actigraphy also has a number of advantages as compared to polysomnography. Actigraphy is cost-effective, easily applied, less demanding for the subject, and allows several nights of recording continuously. This makes sleep studies feasible in a larger number of clinical and experimental investigations. For example, whereas polysomnography may be difficult
to attain in demented elderly individuals, actigraphy is usually well tolerated. The advantage of being able to record for several nights continuously deserves attention. It is known that two polysomnographic recordings obtained over subsequent nights may show considerable differences. This has been referred to as a “first-night effect.” In a study on the first-night effect in actigraphic recordings, no systematic difference for the first night could be found (Van Hilten et al., 1993). However, there was a considerable within-subject variation over the six nights recorded. This indicates that, in addition to systematic first-night effects, there may also be a considerable variability in sleep parameters as obtained over several nights. Acebo and colleagues (1999) have provided estimates of the reliability of sleep scores based on 1–7 nights in children. We have recently investigated the day-today variability in a systematic empirical way in elderly insomniacs and demented elderly subjects: the reliability of sleep parameter estimates continues to increase if the number of recorded nights is extended, even up to 10 nights of sleep (Van Someren, 2007). Thus, an advantage of actigraphy over polysomnography is that it is much more feasible to do such long-term investigations that allow for improved sleep parameter estimates as well as insight into the variability of the sleep parameters. This advantage has not yet been fully exploited, since clinicians and researchers have often relied on three nights of recording, the minimum advised in the practice parameters for the use of actigraphy in the clinical assessment of sleep disorders, as published by the Board of Directors of the American Academy of Sleep Medicine (Littner et al., 2003). Figure 4.4 shows how the reliability of an actigraphic estimate of the percentage of wakefulness after sleep
Absolute difference (mean±s.e.m.) of two estimates of % wake after sleep onset (WASO)
ACTIGRAPHIC MONITORING OF SLEEP AND CIRCADIAN RHYTHMS 15
12
9
6
3
0 0
2
4 6 8 Number of days analysed
10
Fig. 4.4. The reliability of an actigraphic estimate of the percentage of wakefulness after sleep onset (WASO) in a group of 12 demented elderly individuals improves with the number of recorded days. Subjects were actigraphically recorded for 20 days continuously, and actigraphic WASO estimates were derived in pairs from the day 1–10 period and from the day 11–20 period. Pairs resulted from calculating WASO twice for a single day (day 1 and day 11), twice over a period of 2 days (days 1–2 and 11–12), twice over 3 days (days 1–3 and 11–13), up to twice over 10 days (days 1–10 and 11–20). The resulting WASO estimates were averaged over the number of days. The figure shows how the average ( SEM, abscissa) absolute difference between two separate actigraphic estimates of WASO, derived from assessments only 10 days apart, decreases with the number of days (ordinate) included to obtain the estimate.
onset (WASO) in a group of 12 demented elderly individuals improves with the number of recorded days.
CIRCADIAN AND DIURNAL RHYTHMS Circadian rhythms, i.e., rhythms with a period of about 24 hours, are present in most physiological and behavioral parameters, including the vigilance state (sleep versus wakefulness) and activity level. Such rhythms are usually described in terms of the phase, period, and amplitude of a sinusoidal curve fitted to the data. In experimental protocols, the functionality of the circadian timing system is usually evaluated by measuring alterations in the period, phase, and/or amplitude of this curve after imposing shifts in the environmental light–dark cycle, or by putting animals or human subjects in a constantly lit environment without any time cues for a period of up to weeks or months. In the latter situation a rhythm that may deviate from 24 hours emerges, and this is called the free-running rhythm. The majority of actigraphic studies, however, are obtained under unrestrained conditions in the subject’s normal environment. Yet, information on the
59
functionality of the circadian timing system can be extracted from actigraphic recordings assessed in the subject’s usual environment. When the actigraphic data are plotted as a time series, a clear circadian rhythm can be seen, and several variables can be calculated for a quantitative description of the rhythm. A traditional way of quantifying circadian rhythms is by fitting a single or dual harmonic cosine function on the data, thus summarizing it in a mesor (a measure for the mean of a circular function), the phase of the peak, the amplitude, and the period of the rhythm. This ‘cosinor’ method of data reduction has successfully been applied to quantify the specific time course of body temperature and hormone levels. However, because the rest–activity rhythm is far from sinusoidal, the goodness of fit of such functions is usually unacceptable for application to activity data. Nonparametric methods to describe the activity time series have therefore been proposed. They outperformed several frequently used parametric variables in a comparative study on their sensitivity to the effect of bright daylight – the primary input to the biological clock of the brain – on the circadian rest–activity rhythm (Van Someren et al., 1999), and appeared sensitive as well as in other treatment studies (Van Someren et al., 1998). In addition to nonparametric equivalents of the timing and level of the peak and trough of the rest–activity rhythms, and the amplitude that results from their difference, two variables deserve some additional description. First, in most healthy subjects, the activity profiles from different 24-hour periods resemble each other to a reasonable extent. In some diseases, notably in Alzheimer patients, subsequent days may lose any such typical pattern (Figure 4.5). This phenomenon can be quantified using the interdaily stability (IS) value (Van Someren et al., 1999; Carvalho-Bos et al., 2007), essentially a normalized 24-hour value from a periodogram (Sokolove and Bushell, 1978). IS gives an indication of the strength of coupling between the rest– activity rhythm and supposedly stable environmental cues with a 24-hour pattern, also known as Zeitgebers. Second, in most healthy subjects, sleep and wakefulness are both confined to one major period of time each. If one takes a nap during the daytime, sleep and wakefulness both occur in two instead of one periods of time during 24 hours. In some diseases, notably in Alzheimer patients, periods of high and low vigilance, and consequently high and low amounts of activity, may alternate even more frequently, resulting in a fragmented rhythm (Figure 4.5). The nonparametric variable intradaily variability (IV) (Van Someren et al., 1999) gives an indication of the fragmentation of the rhythm, i.e., the frequency and extent of transitions between rest and activity.
60
E.J.W. VAN SOMEREN 250 200 150 100 50 12:00
00:00
12:00
00:00
12:00
00:00
12:00
00:00
12:00
00:00
12:00
00:00
12:00
00:00
12:00
12:00
00:00
12:00
00:00
12:00
00:00
12:00
00:00
12:00
00:00
12:00
00:00
12:00
00:00
12:00
12:00
00:00
12:00
00:00
12:00
00:00
12:00
00:00
12:00
00:00
12:00
00:00
12:00
00:00
12:00
00:00
12:00
00:00
12:00
00:00
12:00
00:00
12:00
00:00
12:00
00:00
12:00
00:00
12:00
A
12:00
0
250 200 150 100 50 0
B 250 200 150 100 50 0
C 250 200 150 100 50 0
D
Fig. 4.5. Examples of 7-day activity plots in Alzheimer patients. Each bar represents the activity counts in 1 hour. The top panel (A) shows a rhythm that does not significantly differ from rhythms of control subjects. Panel B shows the rhythm of a patient with a low interdaily stability (IS), panel C a patient with a high intradaily variability (IV), and the bottom panel (D) a patient with both low IS and high IV. (Reproduced from Van Someren et al. (1996a), with permission.)
It should be noted that, under the conditions of everyday life, the measured rest–activity rhythm does not strictly represent the function of the endogenous biological clock of the brain, located in the hypothalamic suprachiasmatic nucleus (SCN). The measurements in fact at best represent the interaction of the endogenous biological clock with the environmental 24-hour time structure, which includes social demands and the light– dark cycle – the primary input to the SCN. Such conditions are referred to as entrained conditions. Rhythms obtained under such conditions are usually referred to as diurnal rhythms, whereas rhythms obtained under experimental
conditions in the absence of any time cues are referred to as circadian rhythms. If one wants to obtain an indication of clock function in the absence of entrainment, one needs to apply dedicated laboratory protocols like constant routine and enforced sleep–wake cycles of considerably shorter or longer duration than 24 hours (ultrashort sleep–wake cycles, forced desynchrony).
PERSPECTIVES The presently available actigraphs and the accompanying software are useful tools to provide clinicians
ACTIGRAPHIC MONITORING OF SLEEP AND CIRCADIAN RHYTHMS and researchers with objective indices of sleep. They should not be regarded as a replacement for polysomnography. As has been described, actigraphy has both shortcomings and advantages as compared to polysomnography. This final section discusses a number of recent and ongoing developments that promise a further improvement of actigraphic estimates of sleep parameters. First, optimization of the estimates may be accomplished by adapting the algorithm for sleep estimates to the specific group of subjects under study. For example, lowering the activity threshold that should be surpassed in order to score wakefulness may improve sleep estimates in elderly subjects (Colling et al., 2000). While lying awake in bed elderly subjects may move less than young subjects do. Important for clinical neurology, sleep recordings in patients suffering from Parkinson’s disease may require even more significant adaptations. Thresholds may have to be lowered even more than is already the case in their matching healthy elderly control subjects, because movement-induced accelerations are of a lower amplitude (Eichhorn et al., 1996). In addition, if patients show tremor, it is important to discriminate high levels of activity due to “healthy” movements from those resulting from tremor. An actigraph doing just this has recently been developed and validated for tremor recording (Van Someren et al., 2006). Such devices are likely to provide more detailed insight into activity rhythms originating from the alteration of periods of sleep and wakefulness, and those associated with fluctuating amounts of tremor. A common characteristic of the present generation of actigraphs is that the accompanying sleep analysis software utilizes only one activity measure, be it time above threshold, area under the curve, or zero crossings. However, movements related to wakefulness and sleep, possibly even sleep stages, may differ in more than one signal dimension. Movements may differ in frequency, vigor, fragmentation, and duration. It has been noted, for example, that limb movements during rapid eye movement (REM) sleep are brief, rapid, and jerky (Chase and Morales, 1990) and Aserinsky (1986) has shown that the acceleration characteristics of eye movements are different in REM sleep and wakefulness, suggesting that twitches resulting in wrist movements associated with REM sleep might have a different acceleration profile than the awake wrist movement acceleration profile. A recent advance in the online data reduction algorithm and storage capacity of an actigraph has made it possible to obtain multiple dimensions of the acceleration signal simultaneously, i.e., the amplitude, duration, and repetitiveness (Van Someren et al., 2006). Although this novel
61
actigraph has been developed to allow for online discrimination of pathological tremor from normal movements in Parkinson’s disease, for example (Van Someren et al., 1993), it would be of considerable interest to evaluate how the different dimensions of the acceleration signal vary across wakefulness and sleep stages and could be of value in improving their discrimination. An unpublished study indeed found that amplitude, frequency, number, average duration, and total duration of movements differed significantly across wake and sleep stages. Related to the single activity measure mentioned above is the fact that actigraphy utilizes only one type of signal (activity) to estimate sleep and wakefulness, whereas the gold standard of polysomnography utilizes multiple signals. Since the multiple signals of polysomnography are not redundant, it is somewhat unlikely a priori that sleep parameter estimates derived from the single signal of actigraphy could ever reach complete agreement with polysomnographic sleep parameter estimates (Tryon, 2004). Actigraphs may be used to obtain movement signals on other sites, and process them in different ways. The most successful example of this approach is the use of actigraphs to assess periodic leg movements during sleep (King et al., 2005). Alternatively, actigraphs have been developed to obtain other measurements in addition to movement signals, e.g., heart rate and skin temperature. Heart rate variability measures may improve estimates of sleep depth (Otzenberger et al., 1997) and support the screening for obstructive sleep apnea (Roche et al., 1999) and periodic limb movements during sleep (Winkelman, 1999). A development that goes beyond actigraphy is that several research programs are presently utilizing the ongoing miniaturization of sensors and microelectronics to integrate measurement systems within the bedding of the subject under study. These developments will ultimately allow for unobtrusive assessment of signals reflecting heart rate, breathing, gross movements, and skin temperature, which together are likely to provide even better and more detailed estimates of sleep.
REFERENCES Acebo C, Sadeh A, Seifer R et al. (1999). Estimating sleep patterns with activity monitoring in children and adolescents: how many nights are necessary for reliable measures? Sleep 22: 95–103. Ancoli-Israel S, Clopton P, Klauber MR et al. (1997). Use of wrist activity for monitoring sleep/wake in demented nursing-home patients. Sleep 20: 24–27. Ancoli-Israel S, Cole R, Alessi C et al. (2003). The role of actigraphy in the study of sleep and circadian rhythms. Sleep 26: 342–392.
62
E.J.W. VAN SOMEREN
Aserinsky E (1986). Proportional jerk: a new measure of motion as applied to eye movements in sleep and waking. Psychophysiology 23: 340–347. Carvalho-Bos S, Riemersma-van der Lek RF, Waterhouse J et al. (2007). Strong association of the rest–activity rhythm with well-being in demented elderly women. Am J Geriatr Psychiatry 15: 92–100. Chase MH, Morales FR (1990). The atonia and myoclonia of active (REM) sleep. Annu Rev Psychol 41: 557–584. Colburn TR, Smith BM, Guarini JJ et al. (1976). An ambulatory activity monitor with solid state memory. Biomed Sci Instrum 12: 117–122. Cole RJ, Kripke DF, Gruen W et al. (1992). Automatic sleep/ wake identification from wrist activity. Sleep 15: 461–469. Colling E, Wright M, Lahr S et al. (2000). A comparison of wrist actigraphy with polysomnography as an instrument of sleep detection in elderly persons. Sleep 23: A378. De Souza L, Benedito-Silva AA, Pires ML et al. (2003). Further validation of actigraphy for sleep studies. Sleep 26: 81–85. Eichhorn TE, Gasser T, Mai N et al. (1996). Computational analysis of open loop handwriting movements in Parkinson’s disease – a rapid method to detect dopamimetic effects. Mov Disord 11: 289–297. Eissa MA, Poffenbarger T, Portman RJ (2001). Comparison of the actigraph versus patients’ diary information in defining circadian time periods for analyzing ambulatory blood pressure monitoring data. Blood Press Monit 6: 21–25. Hauri PJ, Wisbey J (1992). Wrist actigraphy in insomnia. Sleep 15: 293–301. King MA, Jaffre MO, Morrish E et al. (2005). The validation of a new actigraphy system for the measurement of periodic leg movements in sleep. Sleep Med 6: 507–513. Krahn LE, Lin SC, Wisbey J et al. (1997). Assessing sleep in psychiatric inpatients: nurse and patient reports versus wrist actigraphy. Ann Clin Psychiatry 9: 203–210. Kripke DF, Mullaney DJ, Messin S et al. (1978). Wrist actigraphic measures of sleep and rhythms. Electroencephalogr Clin Neurophysiol 44: 674–676. Kupfer DJ, Weiss BL, Foster G et al. (1974). Psychomotor activity in affective states. Arch Gen Psychiatry 30: 765–768. Littner M, Kushida CA, Anderson WM et al. (2003). Practice parameters for the role of actigraphy in the study of sleep and circadian rhythms: an update for 2002. Sleep 26: 337–341. McPartland RJ, Foster FG, Kupfer DJ et al. (1976). Activity sensors for use in psychiatric evaluation. IEEE Trans Biomed Eng 23: 175–178. Meijer GA, Westerterp KR, van Hulsel AM et al. (1992). Physical activity and energy expenditure in lean and obese adult human subjects. Eur J Appl Physiol 65: 525–528. Middelkoop HAM, Van Dam EM, Smilde-Van Den Doel DA et al. (1997). 45-hour continuous quintuple-site actimetry: relations between trunk and limb movements and effects of circadian sleep–wake rhythmicity. Psychophysiology 34: 199–203.
Mullaney DJ, Kripke DF, Messin S (1980). Wrist actigraphic estimation of sleep time. Sleep 3: 83–92. Nagels G, Marion P, Pickut BA et al. (1996). Actigraphic evaluation of handedness. Electroencephalogr Clin Neurophysiol 101: 226–232. Otzenberger H, Simon C, Gronfier C et al. (1997). Temporal relationship between dynamic heart rate variability and electroencephalographic activity during sleep in man. Neurosci Lett 229: 173–176. Pilsworth SN, King MA, Shneerson JM et al. (2001). A comparison between measurements of sleep efficiency and sleep latency measured by polysomnography. Sleep 24: S106. Pollak CP, Tryon WW, Nagaraja H et al. (2001). How accurately does wrist actigraphy identify the states of sleep and wakefulness? Sleep 24: 957–965. Rechtschaffen A, Kales A (1968). A Manual of Standardized Terminology, Techniques and Scoring System for Sleep Stages of Human Subjects. United States Department of Health, Education and Welfare, Bethesda. Redmond DP, Hegge FW (1985). Observations on the design and specification of a wrist-worn activity monitoring system. Behav Res Methods Instrum Comput 17: 659–669. Roche F, Gaspoz JM, Court-Fortune I et al. (1999). Screening of obstructive sleep apnea syndrome by heart rate variability analysis. Circulation 100: 1411–1415. Sadeh A, Sharkey KM, Carskadon MA (1994). Activitybased sleep–wake identification: an empirical test of methodological issues. Sleep 17: 201–207. Sadeh A, Hauri PJ, Kripke DF et al. (1995). The role of actigraphy in the evaluation of sleep disorders. Sleep 18: 288–302. Sokolove PG, Bushell WN (1978). The chi square periodogram: its utility for analysis of circadian rhythms. J Theor Biol 72: 131–160. Tryon WW (1991). Activity Measurement in Psychology and Medicine. Plenum Press, New York. Tryon WW (2004). Issues of validity in actigraphic sleep assessment. Sleep 27: 158–165. Usui A, Ishizuka Y, Obinata I et al. (1998). Validity of sleep log compared with actigraphic sleep–wake state. Psychiatry Clin Neurosci 52: 161–163. Van Hilten JJ, Braat EA, van der Velde EA et al. (1993). Ambulatory activity monitoring during sleep: an evaluation of internight and intrasubject variability in healthy persons aged 50–98 years. Sleep 16: 146–150. Van Someren EJW (2007). Improving actigraphic sleep estimates: how many nights? J Sleep Res 16: 269–275. Van Someren EJW, Van Gool WA, Vonk BFM et al. (1993). Ambulatory monitoring of tremor and other movements before and after thalamotomy: a new quantitative technique. J Neurol Sci 117: 16–23. Van Someren EJW, Hagebeuk EEO, Lijzenga C et al. (1996a). Circadian rest–activity rhythm disturbances in Alzheimer’s disease. Biol Psychiatry 40: 259–270. Van Someren EJW, Lazeron RHC, Vonk BFM et al. (1996b). Gravitational artefact in frequency spectra of movement acceleration: implications for actigraphy in young and elderly subjects. J Neurosci Methods 65: 55–62.
ACTIGRAPHIC MONITORING OF SLEEP AND CIRCADIAN RHYTHMS Van Someren EJW, Scherder EJA, Swaab DF (1998). Transcutaneous electrical nerve stimulation (TENS) improves circadian rhythm disturbances in Alzheimer’s disease. Alzheimer Dis Assoc Disord 12: 114–118. Van Someren EJW, Swaab DF, Colenda CC et al. (1999). Bright light therapy: improved sensitivity to its effects on rest–activity rhythms in Alzheimer patients by application of nonparametric methods. Chronobiol Int 16: 505–518.
63
Van Someren EJW, Pticek MD, Speelman JD et al. (2006). A new actigraph for long-term tremor recording. Mov Disord 21: 1136–1143. Webster JB, Kripke DF, Messin S et al. (1982). An activitybased sleep monitor system for ambulatory use. Sleep 5: 389–399. Winkelman JW (1999). The evoked heart rate response to periodic leg movements of sleep. Sleep 22: 575–580.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 5
Video recordings and video polysomnography NANCY FOLDVARY-SCHAEFER 1 * AND BETH MALOW 2 Sleep Disorders Center, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA
1 2
Department of Neurology and Sleep Disorders Program, Vanderbilt University Medical Center, Nashville, TN, USA
INTRODUCTION
METHODOLOGY
The differentiation of nocturnal seizures, parasomnias, arousals, and other nonepileptic sleep-related behaviors can be challenging during polysomnography (PSG). While a limited number of electroencephalogram (EEG) channels is adequate for sleep staging in routine PSG (Iber et al., 2007), the identification of seizures requires more extensive EEG monitoring (American Electroencephalographic Society, 1994a). Video PSG (VPSG) combines simultaneous PSG and video-EEG to evaluate patients with nocturnal events. This technique has several advantages over routine PSG, including the ability to analyze behavior, correlate behavior with neurophysiologic parameters, and detect epileptiform activity.
EEG/electrode placement
INDICATIONS The American Academy of Sleep Medicine Standards of Practice indications for PSG guidelines (1987) recommend the use of VPSG in patients with nocturnal behaviors in whom seizures are suspected when the clinical history and routine EEG are inconclusive. Other indications for VPSG include the evaluation of sleep-related events that are violent or potentially injurious, parasomnias with unusual or atypical features, and presumed parasomnias or seizure disorders that fail to respond to conventional therapy. The differential diagnosis of abnormal sleep-related behaviors includes epileptic seizures, nonrapid eye movement (NREM) arousal disorders, REM sleep behavior disorder, rhythmic movement disorder, and psychiatric disorders such as panic and dissociative disorder.
*
The EEG is generated by inhibitory and excitatory postsynaptic potentials of cortical neurons. EEG activity is a reflection of the summation of the potentials generated by the underlying cortex and its interactions with subcortical structures. The 10/20 system of the International Federation of Societies for EEG and Clinical Neurophysiology is the method of electrode placement used in conventional EEG (Jasper, 1958). The system is based on measurements of 10% and 20% of the distance between standard cranial landmarks. Each electrode site is identified by a letter, representing the underlying region of the brain, and a number indicating a specific position in that region, with odd numbers indicating the left hemisphere and even numbers indicating the right hemisphere (Figure 5.1). Each recording channel represents the difference in electrical potential between a pair of electrodes. Several pairs of electrodes are combined to form a montage. Additional rows of electrodes in between the coronal and sagittal rows of the 10/20 system may be placed for more precise localization of epileptiform activity. Known as the 10/10 system, this method of electrode placement is used primarily during long-term monitoring (American Electroencephalographic Society, 1994b). Additional, closely spaced scalp electrodes increase the detection of epileptiform activity (Morris et al., 1986).
Montages Montages may be either referential, in which one of the electrodes in each pair is connected to a common electrode, or bipolar, in which there is no common
Correspondence to: Nancy Foldvary-Schaefer, D.O., Sleep Disorders Center, Neurological Institute, Cleveland Clinic, FA-20, 9500 Euclid Avenue, Cleveland, OH 44195, USA. Tel: (216) 445-2990, Fax: (216) 445-6205, E-mail:
[email protected]
66
N. FOLDVARY-SCHAEFER AND B. MALOW
Fp1
Fp2
F7
F3
Fz
F4
F8
T7
C3
Cz
C4
T8
P7
P3
Pz
P4
P8
A1
O1
A2
O2
Fig. 5.1. Schematic of the 10-20 system of electrode placement.
electrode. Bipolar montages are usually arranged in a chain with a common electrode in adjacent derivations. The EEG is typically viewed on an anterior–posterior bipolar montage, although any configuration of electrodes may be used (Figure 5.2). The American Academy of Sleep Medicine (1987) guidelines recommend the use of an extended EEG montage in the evaluation of patients with nocturnal spells. The American Electroencephalographic Society (1994b) Guideline Thirteen recommends the use of
at least six EEG channels to evaluate patients with suspected seizures. Electrode placements FP1, FP2 (or other frontal placements), C3, C4, O1, O2, T7, and T8 are suggested. When limited to a few EEG channels, attempts should be made to design a montage that best addresses the clinical question. Unfortunately, too often the clinical history does not provide such detail and a limited number of EEG channels fails to exclude the diagnosis of epilepsy. Additional electromyogram (EMG) monitoring may be indicated, such as in patients with suspected REM sleep behavior disorder (Mahowald and Schenck, 1994). The optimal number and placement of EEG electrodes depend on a variety of factors, including the location, size, and characteristics of the epileptogenic focus. Commonly chosen as a reference in PSG, the auricular and mastoid electrodes (A1/A2 or M1/M2) may be active in temporal lobe seizures, making localization difficult or misleading. In a study comparing abbreviated EEG montages with a standard 18-channel bipolar montage, seizures were more readily distinguished from arousals using seven- and 18-EEG channel montages as compared to four-channel recordings (Foldvary et al., 2000). Accuracy increased progressively with the number of channels. Seven- and 18-channel montages provided significantly better accuracy for identifying temporal seizures than the four-channel montage. However, the 18-channel montage was not superior to a seven-channel montage incorporating anterior temporal electrode placements. More extensive EEG
Clinical onset C3–TP10 200 uV
C4–TP10
O1–TP10
O2–TP10
A
1 sec
Fig. 5.2. Bilateral tonic seizure in sleep in a 6-year-old female with left frontal lobe epilepsy depicted using an abbreviated electroencephalogram (EEG) montage in (A) 30-second and Continued
VIDEO RECORDINGS AND VIDEO POLYSOMNOGRAPHY
67
Clinical onset C3–TP10 200 uV
C4–TP10
O1–TP10
O2–TP10
1 sec
B Clinical onset Fp1–F7 200 uV F7–T7 T7–P7 P7–O1 Fp2–F8 F8–T8 T8–P8 P8–O2 Fp1–F3 F3–C3 C3–P3 P3–O1 Fp2–F4 F4–C4 C4–P4 P4–O2 Fz–Cz Cz–Pz
1 sec
C Fig. 5.2. Cont’d. (B) 10-second epochs, and (C) an 18-channel montage in a 10-second epoch. While altering the epoch length facilitates interpretation significantly, the seizure becomes readily apparent only on the expanded EEG montage.
68
N. FOLDVARY-SCHAEFER AND B. MALOW
montages did not increase the accuracy of frontal lobe seizure or arousal detection. In a subsequent study comparing an abbreviated montage using the recommended electrode placements of the American Electroencephalographic Society (1994a), the same investigators found an 18-channel montage superior in differentiating seizures from nonepileptic events (Foldvary-Schaefer et al., 2005). This appeared to be particularly true in frontal lobe epilepsy (Figure 5.2). Few have investigated the value of extensive EEG montages in the sleep laboratory. Among 122 patients with suspected parasomnias, VPSG provided a definite diagnosis in 35% of cases, with epilepsy being most common (Aldrich and Jahnke, 1991). In another 30% of cases, VPSG provided supportive evidence of sleep terrors or epilepsy. Sleep disorders were identified in five of 36 patients with known epilepsy. Only 34% of studies were inconclusive.
Viewing and reformatting Virtually all sleep laboratories have made the transition from analog recordings to computerized digital systems. Digital systems provide a more efficient means of data analysis, review, and storage. For the evaluation of sleep-related behaviors, current technology allows the reader to view an event in a variety of ways by altering the paper speed, filter setting, sensitivity, and montage. Readily apparent on conventional EEG paper speed (30 mm/second), isolated epileptiform discharges are virtually impossible to identify on 30-second PSG epochs (10 mm/second). In digital recordings, a sampling rate of 200 Hz is recommended to identify epileptiform discharges of short duration.
Video Video recordings are a necessary component of VPSG. Tonic-clonic motor activity, automatisms, and versive head movements are readily recognized by physicians with experience in the diagnosis of epilepsy. Minor motor features, such as brief generalized or focal tonic posturing and myoclonus, are more difficult to characterize using the clinical history alone. Negative motor activity, including behavior arrest, staring, and subtle loss of postural tone, may not be recognized even by experienced observers without video recordings and patient interaction. Sleep rooms should be equipped with adjustable cameras so that the patient is in view at all times.
The sleep technologist Technologists performing VPSG must have the skills to assess and manage patients with unexplained nocturnal behaviors. Technologists should be trained to identify behaviors that are likely to be epileptic in nature and
interact with the patient to determine level of consciousness. The degree of unresponsiveness, recollection of dream content, and presence of lateralizing signs, including postictal language deficits and Todd’s paralysis, during and immediately following nocturnal events, should be ascertained. Technologists should be capable of administering first aid to patients with generalized motor seizures, knowledgeable on the management of postictal violent or aggressive behavior, and able to recognize potentially injurious situations, including prolonged seizures and complications such as aspiration.
INTERPRETATION The interpretation of VPSG requires knowledge of the clinical and electrographic manifestations of seizures and nonepileptic parasomnias. Epileptic seizures are classified as focal or generalized based on their clinical and electrographic features. Epilepsy syndromes are constellations of specific signs and symptoms that can be used to predict the natural history of a disorder.
Generalized epilepsy Generalized epilepsy syndromes are characterized by seizures with initial activation of neurons involving both cerebral hemispheres. Most of the generalized epilepsies are characterized by interictal epileptiform discharges having a generalized, bianterior maximal distribution (F3, F4 or FP1, FP2) with progressive amplitude decay posteriorly. These discharges are typically detected when recording from frontal and central electrode placements. Consequently, they may be apparent on routine PSG. During generalized seizures, the EEG typically shows diffuse rhythmic activity or repetitive epileptiform activity, reflecting initial involvement of both cerebral hemispheres. Tonic and atonic seizures are characterized by a sudden appearance of generalized low-voltage fast activity, suppression, spike–wave complexes or rhythmic activity. Generalized polyspikes interrupted by slow waves characterize clonic seizures, producing a characteristic pattern of myogenic artifact that is relatively easy to identify even at a paper speed of 10 mm/second.
Focal epilepsy Focal or localization-related epilepsies are characterized by focal (partial) seizures that originate from a localized cortical region. The electrographic manifestations of focal epilepsy depend upon a variety of factors, including the size and location of the ictal generator, location and number of recording electrodes, and the attenuating characteristics of the skull and other intervening tissues (Jayakar et al., 1991).
VIDEO RECORDINGS AND VIDEO POLYSOMNOGRAPHY In many cases, the EEG shows interictal epileptiform discharges from the region harboring the epileptogenic lesion. The EEG may be normal in patients with epileptogenic lesions arising from deep or midline regions or show generalized epileptiform activity due to rapid propagation to the contralateral hemisphere. Most focal seizures are characterized by rhythmic activity that evolves in frequency, distribution (field), and amplitude (Sharbrough, 1993). Repetitive spikes or sharp waves and sudden attenuation of activity over one region or cerebral hemisphere are also observed. Seizures characterized by excessive motor activity may be obscured by muscle artifact, rendering the EEG uninterpretable. This is most commonly observed in patients with frontal lobe epilepsy in whom parasomnias or psychogenic seizures may be erroneously diagnosed due to the apparent lack of an EEG correlate. The EEG may be normal even during a seizure if the event is brief and the epileptogenic focus is distant from the recording electrodes, another feature of frontal lobe epilepsy. Similarly, EEG changes may not be apparent when a focal seizure remains relatively confined to a limited area. While temporal lobe
69
epilepsy is the most common of the focal epilepsies in adolescents and adults, frontal lobe epilepsy more often presents with seizures during sleep that can be difficult to differentiate from other types of nocturnal behaviors. The absence of epileptiform abnormalities does not definitively exclude the diagnosis of epilepsy.
Effect of sleep stage The stage of sleep from which nocturnal spells emerge and the time of the spell relative to sleep onset provide useful diagnostic information, particularly when evaluating patients with nonepileptic events in sleep. Sleeprelated seizures usually arise from NREM sleep. NREM arousal disorders usually arise from slow-wave sleep in the first third of the sleep period. Included in the category are somnambulism, sleep terrors, and confusional arousals (Figure 5.3). REM sleep behavior disorder typically presents in the last third of the sleep period, when REM sleep predominates. Affected individuals have vigorous or violent behavior in sleep associated with vivid dream imagery and augmented EMG activity of the chin and/or extremities. Rhythmic
Fp1–F7 50 uV F7–T7 T7–P7 P7–O1 Fp2–F8 F8–T8 T8–P8 P8–O2 Fp1–F3 F3–C3 C3–P3 P3–O1 Fp2–F4 F4–C4 C4–P4 P4–O4 LOC–Pz 100 uV ROC–Pz Air Flow–REF2 20 uV Thoracic–REF2 100 uV Abdomina–REF2 50 uv Chin–EMG1 5 uV LANT–RANT 20 uv ECG+–ECG– 100 uV
1 sec
Fig. 5.3. Video polysomnography recording from a 29-year-old woman with nocturnal wandering spells. The patient suddenly awoke from slow-wave sleep (arrow) and began to get out of bed without awareness.
70
N. FOLDVARY-SCHAEFER AND B. MALOW
movements associated with rhythmic movement disorder usually occur during sleep–wake transitions. Dissociative episodes emerge from wakefulness. Nocturnal panic attacks occur from NREM sleep, usually at the transition of stage 2 from stage 3.
Artifacts Artifacts are commonly seen in recordings of patients with nocturnal spells and must be distinguished from epileptiform activity and the EEG changes associated with parasomnias. Although artifacts may obscure the EEG, their sterotyped presentation may be supportive of the diagnosis in question. Examples of this include the EMG artifact of a tonic-clonic seizure, head or body rocking artifact in rhythmic movement disorder, and the rhythmic bitemporal myogenic artifact of bruxism. Other types of artifact that may mimic epileptiform activity include that produced by head tremor, eye movements, and tongue movements (glossokinetic artifact). Normal patterns that are occasionally misinterpreted as epileptic include positive occipital sharp transients of sleep, repetitive vertex waves of young patients, small sharp spikes, wicket spikes, and rhythmic temporal theta of drowsiness.
CONCLUSIONS VPSG combines video EEG and PSG for the evaluation of unexplained behaviors in sleep. The differential diagnosis most commonly includes epileptic seizures and parasomnias. Additional time is required for electrode placement and data analysis and more space is required on storage media. However, misdiagnosis can lead to unnecessary treatment with medications that may produce significant adverse effects and failure to make an accurate diagnosis may lead to serious, potentially fatal accidents and injuries. When VPSG fails to clarify the diagnosis, long-term video EEG monitoring should be considered.
REFERENCES Aldrich MS, Jahnke B (1991). Diagnostic value of videoEEG polysomnography. Neurology 41: 1060–1066. American Electroencephalographic Society (1994a). Guideline Fifteen. Guidelines for polygraphic assessment of sleep-related disorders (polysomnography). J Clin Neurophysiol 11: 116–124. American Electroencephalographic Society (1994b). Guideline Thirteen. Guidelines for standard electrode position nomenclature. J Clin Neurophysiol 11: 111–113. American Sleep Disorders Association Standards of Practice Committee (1987). Practice parameters for the indications for polysomnography and related procedures. Sleep 20: 406–422. Foldvary N, Caruso AC, Mascha E et al. (2000). Identifying montages that best detect electrographic seizure activity during polysomnography. Sleep 23: 221–229. Foldvary-Schaefer N, De Ocampo J, Mascha E et al. (2005). Accuracy of seizure detection using abbreviated EEG during polysomnography. J Clin Neurophysiol 23: 68c–71c. Iber C, Ancoli-Israel S, Chesson A et al. (2007). The AASM Manual for the Scoring of Sleep and Associated Events: Rules, Terminology and Technical Specifications. American Academy of Sleep Medicine, Westchester, IL. Jasper HH (1958). The 10-20 electrode system of the International Federation. Electroencephalogr Clin Neurophysiol 10: 370–375. Jayakar P, Duchowny M, Resnick TJ (1991). Localization of seizure foci: pitfalls and caveats. J Clin Neurophysiol 8: 414–431. Mahowald M, Schenck CH (1994). REM sleep behavior disorder. In: MH Kryger, T Roth, WC Dement (Eds.), Principles and Practice of Sleep Medicine. 2nd edn. W.B. Saunders, Philadelphia, pp. 574–588. Morris HH, Lu¨ders H, Lesser RP et al. (1986). The value of closely spaced scalp electrodes in the localization of epileptiform foci: a study of 26 patients with complex partial seizures. Electroencephalogr Clin Neurophysiol 63: 107–111. Sharbrough FW (1993). Scalp-recorded ictal patterns in focal epilepsy. J Clin Neurophysiol 10 (3): 262–267.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 6
Functional neuroimaging in sleep, sleep deprivation, and sleep disorders MARTIN DESSEILLES *, THANH DANG-VU, AND PIERRE MAQUET Cyclotron Research Centre, University of Lige, Belgium
INTRODUCTION The optimal management of patients with sleep disorders would require a comprehensive understanding of the underlying specific pathological mechanisms, but also an exact appreciation of the consequences of ensuing sleep disruption. The latter objective is hampered by our incomplete knowledge of normal sleep. During the last 50 years, considerable progress has been made in the understanding of the neural mechanisms by which sleep is induced, maintained, and regulated (McCarley et al., 1983; Buzsaki, 1998; Kryger et al., 2000; Saper et al., 2001; Steriade and Timofeev, 2003). Yet, at present, our understanding remains fragmentary and we are still striving for a comprehensive description of sleep mechanisms. Likewise, the functions of sleep are not yet undisputedly specified, although several hypotheses have been proposed (Maquet et al., 2003). Consequently, the effect of sleep on cerebral and bodily functions (Stickgold and Walker, 2007), as well as the consequences of sleep deprivation or fragmentation (Chee and Chuah, 2008), are not yet fully understood at the different levels of description. Neuroimaging studies conducted in sleep disorders have suffered from this fragmentary knowledge of normal sleep. For instance, they often have not been able to tease apart the pathological mechanisms of a given disorder from the consequences of the ensuing sleep disruption. Nevertheless, impressive advances have been made in some sleep disorders. In this section, our aim is to describe the present state of the art and hopefully exemplify the limitations of the available neuroimaging literature. The review begins with a short account of neuroimaging studies conducted
*
during normal sleep, because they nicely introduce the subsequent pathological sections.
NEUROIMAGING IN NORMAL HUMANS Introduction Studies using positron emission tomography (PET), single photon emission computed tomography (SPECT) or functional magnetic resonance imaging (fMRI) reviewed in this section have shown that global and regional patterns of brain activity during sleep are outstandingly different from wakefulness. These studies also demonstrated the persistence of brain responses to external stimuli during sleep as well as plastic changes in brain activity related to previous waking experience.
Nonrapid eye movement (NREM) sleep NREM sleep, when compared to wakefulness or REM sleep (Maquet et al., 1997; Maquet, 2000), is characterized by a global decrease in cerebral blood flow (CBF), and by a regional deactivation in the dorsal pons, mesencephalon, cerebellum, thalami, basal ganglia, basal forebrain and anterior hypothalamus, prefrontal cortex, anterior cingulate cortex and precuneus. This distribution of brain activity could be at least partially explained by NREM sleep generation mechanisms in mammals (Maquet et al., 1990). Taking into account that PET measurements average cerebral activity over 90 seconds to 45 minutes, decreases in CBF and metabolism during NREM are thought to reflect a change in firing pattern, characterized by synchronized bursting activity followed by long hyperpolarization periods, more than a decrease in the average neuronal firing rate (Maquet, 2000). Accordingly, as compared to wakefulness, the average
Corrrespondence to: Martin Desseilles, MD, PhD, Cyclotron Research Centre, University of Lie`ge, Baˆtiment B30, 8, alle´e du 6 Aouˆt – B-4000 Lie`ge (Belgium). Tel: þ32 4 366 23 16, Fax: þ32 4 366 29 46, E-mail:
[email protected]
72
M. DESSEILLES ET AL.
cerebral metabolism and blood flow levels begin to decrease in light (stage 1 and 2) NREM sleep (Madsen et al., 1991b; Maquet et al., 1992; Kjaer et al., 2002), and are the lowest during deep (stage 3 and 4) NREM sleep, also named slow-wave sleep (SWS) (Maquet et al., 1990; Madsen et al., 1991a). NREM sleep rhythms (spindles, delta, and slow oscillations) are generated by a cascade of events occurring in thalamoneocortical networks, initially induced by a decreased activation from the brainstem tegmentum (Steriade and Amzica, 1998). Accordingly, in humans, brainstem blood flow is decreased during light NREM sleep (Kajimura et al., 1999) as well as during SWS (Braun et al., 1997; Maquet et al., 1997; Kajimura et al., 1999; Nofzinger et al., 2002). However, during light NREM sleep, the pontine tegmentum appears specifically deactivated whereas the mesencephalon seems to retain an activity that is not significantly different from wakefulness (Kajimura et al., 1999). In SWS, both
pontine and mesencephalic tegmenta are deactivated (Maquet et al., 1997). The thalamus occupies a central position in the generation of NREM sleep rhythms like spindles and delta waves, due to the intrinsic oscillating properties of its neurons and to the intrathalamic and thalamocortico-thalamic connectivity. As expected, in humans, regional CBF decreases have been found in the thalamus during both light and deep NREM sleep (Braun et al., 1997; Maquet et al., 1997; Kajimura et al., 1999), and also in proportion to the power density of the electroencephalogram (EEG) signal in the spindle frequency range (Hofle et al., 1997). However, in a recent study, regional CBF was not correlated with delta activity in the thalamus (Dang-Vu et al., 2005), suggesting the potential active participation of the cortex in the generation of the delta rhythm recorded on the scalp (Figure 6.1). The role of the cortex in the generation of NREM sleep oscillations (e.g., slow cortical rhythm) begins to
NREMS
15 8 6
2 0
Adjusted CBF at [–2488 mm]
4
10
5
0
–5
–10 –1.5 –1 –0.5 0
0.5
1
1.5
Delta power
2
2.5
3 1
×10
Fig. 6.1. Regional cerebral blood flow (rCBF) decrease as a function of delta power during nonrapid eye movement (NREM) sleep. Left panel: rCBF decreases as a function of delta power during NREM sleep. Image sections are centered on the ventromedial prefrontal cortex. The color scale indicates the range of Z values for the relevant voxels. Right panel: Plot of the adjusted rCBF responses (arbitrary units) in the ventromedial prefrontal cortex in relation to the adjusted delta power values (mV2) during NREM sleep corresponding to left panel pictures: rCBF activity decreases when delta power increases. Each circle/cross represents one scan: green circles are stage 2 scans, red crosses are stage 3–4 scans. The blue line is the linear regression. (Reprinted from Dang-Vu et al., 2005; copyright (2005). Reprinted with permission from Elsevier.)
FUNCTIONAL NEUROIMAGING IN SLEEP, SLEEP DEPRIVATION, AND SLEEP DISORDERS 73 be understood at the microscopic system level (Steriade precuneus, posterior cingulate cortex, and parahippoet al., 1993). Their neural correlates at the macroscopic campal gyrus (Dang-Vu et al., 2008). Beside identifying system levels are less well characterized. EEG power the brain structures involved in the generation, propagadensity maps have revealed a relatively typical pretion, or modulation of NREM sleep oscillations, these dominance of the delta frequency band in the frontal studies emphasize that NREM sleep is not a state of regions whereas sigma power predominated over the brain quiescence characterized by persistent decrease vertex (Finelli et al., 2001). Human PET data similarly in brain activity, but a state during which brain activity showed that the pattern of cortical deactivation was is temporally organized in specific oscillations. not homogeneously distributed throughout the cortex. As compared to wakefulness, the least active areas in REM sleep SWS were observed in various associative cortices of In contrast to NREM sleep, REM sleep is characterthe frontal (in particular in the dorsolateral and orbital ized by a sustained neuronal activity (Steriade and prefrontal cortex), parietal, and to a lesser extent in the McCarley, 1990; Jones, 1991) and, correspondingly, by temporal and insular, lobes (Braun et al., 1997; Maquet high cerebral requirements (Maquet et al., 1990) and et al., 1997; Andersson et al., 1998; Kajimura et al., blood flow (Madsen et al., 1991a; Lenzi et al., 1999) 1999). In contrast the primary cortices were the least (Figure 6.2). In this active but sleeping brain, some deactivated cortical areas (Braun et al., 1997). A linear areas are particularly active, even more than during (inverse) relationship between delta waves and rCBF is wakefulness, while others have lower than average also found in ventromedial prefrontal regions during regional activity. NREM sleep (Dang-Vu et al., 2005). The reasons for During REM sleep, significant rCBF increases have this heterogeneous cortical distribution remain unclear. been found in the pontine tegmentum, thalamic nuclei, One hypothesis is that since polymodal association limbic and paralimbic areas (amygdaloid complexes cortices are the most active cerebral areas during (Maquet et al., 1996; Nofzinger et al., 1997), hippocampal wakefulness, and because sleep intensity is homeostatiformation (Braun et al., 1997; Nofzinger et al., 1997), and cally related to prior waking activity at the regional anterior cingulate cortex (Maquet et al., 1996; Braun level (Borbely, 2001), these cortices might be more et al., 1997; Nofzinger et al., 1997)). Posterior cortices in profoundly influenced by SWS rhythms than primary temporo-occipital areas were also found to be activated cortices (Maquet, 2000). (Braun et al., 1997; Wehrle et al., 2005), although less The predominance of slow oscillation-related rCBF consistently. In contrast, the inferior and middle dorsodecreases in ventromedial prefrontal regions may be lateral prefrontal gyri and the inferior parietal cortex functionally important since these cortical regions, were the least active brain regions (Maquet et al., 1996, known to deteriorate after a short sleep deprivation 2005; Braun et al., 1997). (Horne, 1988, 1993; Pilcher and Huffcutt, 1996; Harrison Regional brain activity in mesopontine, occipital, and and Horne, 1998, 1999), are involved in mood regulation thalamic regions during human REM sleep (Maquet and in various cognitive functions (such as planning or et al., 1996; Braun et al., 1997; Nofzinger et al., 1997; probability matching) (Harrison and Horne, 1999) that Wehrle et al., 2005) is in keeping with our current help in adapting individual behavior. Studies of the delunderstanding of sleep generation in animals. REM eterious effects of sleep deprivation on human cognisleep is generated by neuronal populations of the mesotion also pointed to an exquisite sensitivity of these pontine reticular formation that activate the thalamic association cortices to sleep deprivation (see below). nuclei which in turn activate the cortex (Steriade and Recent studies have used simultaneous EEG/fMRI McCarley, 1990). recordings during NREM sleep to characterize the neuThe activation of limbic and paralimbic structures, ral correlates of NREM sleep oscillations in healthy including amygdaloid complexes, hippocampal formahumans. In contrast to PET studies that described the tion, and anterior cingulate cortex, is constantly reported patterns of brain activity during the different sleep (Maquet et al., 1996; Braun et al., 1997; Nofzinger et al., stages or correlated with values of EEG spectral power, 1997). Animal data show that the amygdala plays a role in the better temporal resolution of fMRI allows assessREM sleep modulation. For example, ponto-geniculoment of the brain activity changes directly related to occipital (PGO) waves, a major component of REM sleep brief events such as spindles and delta waves. Spindles phasic endogenous activity, were increased in cats by have been associated with increases of brain activity in electrical stimulation of the central nucleus of amygdathe thalamus, anterior cingulate cortex, insula, and supeloid complexes (Calvo et al., 1987), while carbachol (chorior temporal gyrus (Schabus et al., 2007). Delta waves linergic agonist) injections in the same nucleus enhanced have been associated with increases of brain activity both REM sleep and PGO activity (Calvo et al., 1996). in the inferior frontal gyrus, brainstem, cerebellum,
74
M. DESSEILLES ET AL. SWS
Wakefulness
Absolute glucose metabolism
REM sleep
B2
Decreases in rCBF
B1
Increases in rCBF
A
Fig. 6.2. Cerebral glucose metabolism (CMRGlu) and regional cerebral blood flow (rCBF) during rapid eye movement (REM) sleep (first column), deep non-REM (NREM) sleep or slow-wave sleep (SWS) (second column), and wakefulness (third column). Row A: CMRGlu quantified in the same individual at 1-week interval, using 18F-fluorodeoxyglucose and positron emission tomography (PET). The three images are displayed at the same brain level using the same color scale. The average CMRGlu during deep NREM sleep (versus wakefulness) is significantly decreased. During REM sleep the CMRGlu is as high as during wakefulness. Row B1: Distribution of the highest regional brain activity, as assessed by CBF measurement using PET, during wakefulness and REM sleep. The most active regions during wakefulness are located in the polymodal associative cortices in the prefrontal and parietal lobes (both on the medial wall and convexity). During REM sleep, the most active areas are located in the pontine tegmentum, the thalami, the amygdaloid complexes, and the anterior cingulate cortex. Other data (not shown) have shown a large activity in the occipital cortices, the insula, and the hippocampus (Braun et al., 1997). Row B2: Distribution of the lowest regional brain activity, as assessed by CBF measurement using PET, during NREM and REM sleep. In both sleep stages, the least active regions are located in the polymodal associative cortices in the prefrontal and parietal lobes (convexity). During NREM sleep, the brainstem and thalami are also particularly deactivated.
Likewise, the rebound of REM sleep induced by microinjections of gamma aminobutyric acid (GABA) agonist into the periaqueductal gray matter elicited a significant increase in c-fos labeling in the amygdala (Sastre et al., 2000). The activated temporo-occipital areas during REM sleep (Braun et al., 1997) include inferior temporal cortex and fusiform gyrus, which are extrastriate cortices belonging to the ventral visual stream. Functional connectivity of these areas is also modified during REM sleep. The functional relationship between striate and extrastriate cortices, usually excitatory during wakefulness, is reversed during REM sleep (Braun et al., 1997, 1998). Likewise, the functional relationship between the amygdala and the temporal and occipital cortices is different during REM sleep than during wakefulness
or NREM sleep (Maquet and Phillips, 1998). This pattern suggests that not only the functional neuroanatomy but also the functional interactions between neuronal populations are different during REM sleep than during wakefulness. Pontine waves or PGO waves are also primary features of REM sleep. In rats, the generator of the pontine waves projects to a set of brain areas shown to be active in human REM sleep: the occipital cortex, the enthorinal cortex, the hippocampus, and the amygdala, as well as brainstem structures participating in the generation of REM sleep (Datta et al., 1998). In cats, although most easily recorded in the pons (Jouvet, 1967), the lateral geniculate bodies (Mikiten et al., 1961), and the occipital cortex (Mouret et al., 1963), PGO waves are observed in many parts of the brain,
FUNCTIONAL NEUROIMAGING IN SLEEP, SLEEP DEPRIVATION, AND SLEEP DISORDERS including limbic areas (amygdala, hippocampus, cingulate gyrus) (Hobson, 1964). Using PET, regional CBF in the lateral geniculate bodies and the occipital cortex was shown to be more tightly coupled to spontaneous eye movements during REM sleep than during wakefulness (Peigneux et al., 2001). These data are in keeping with other pieces of evidence suggesting the existence of pontine waves in humans, and have been more recently corroborated by an fMRI study (Wehrle et al., 2005). In epileptic patients, direct intracerebral recordings in the striate cortex showed monophasic or diphasic potentials during REM sleep, isolated or in bursts (Salzarulo et al., 1975). In normal subjects, surface EEG revealed transient occipital and/or parietal potentials time-locked to the REMs (McCarley et al., 1983). Source dipoles of magnetoencephalography signal were localized in the brainstem, thalamus, hippocampus and occipital cortex during REM sleep (Inoue et al., 1999; Ioannides et al., 2004).
The brain remains reactive to external stimulation during sleep Available functional neuroimaging data globally suggest that the processing of external stimuli persists during NREM sleep. A pioneering fMRI study found that during NREM sleep, as during wakefulness, several areas continue to be activated by external auditory stimulation: the thalamic nuclei, the auditory cortices, and the caudate nucleus (Portas et al., 2000). Moreover, the left amygdala and the left prefontal cortex were found to be more activated by subjects’ own name than by pure tones, and more so during sleep than during wakefulness, suggesting the persistence during sleep of specific responses for meaningful or emotionally loaded stimuli. In contrast, other groups observed that response to auditory stimulation was decreased during sleep as compared to wakefulness (Czisch et al., 2002). Intriguingly, the brain activation pattern of visual stimulation during SWS in adults showed a decrease in activity in the rostromedial occipital cortex (Born et al., 2002). This decrease was more rostral and dorsal compared to the relative regional CBF increase along the calcarine sulcus found during visual stimulation in the awake state. The origin of this negative blood oxygenation level is still unclear despite replication (Czisch et al., 2004).
NEUROIMAGING IN SLEEP DISORDERS Introduction In this section, we will mainly focus on primary sleep disorders. We will include several types of dyssomnia related to intrinsic sleep disorders (e.g., idiopathic
75
insomnia, narcolepsy, and obstructive sleep apnea), abnormal motor behavior during sleep (e.g., periodic limb movement disorder and REM sleep behavior disorder (RBD)). Sleep may also be secondarily disrupted in a number of conditions ranging from environmental causes (e.g., jet lag, shift work, noisy environment) to medical diseases (e.g., endocrine disorders, chronic pain, brain lesions) and psychiatric disorders (e.g., anxiety, depression, schizophrenia). From the latter conditions, we will only consider the sleep disorders secondary to depression. Single case reports of brain functional imaging like in recurrent hypersomnia (Nose et al., 2002) and in sleepwalking (Bassetti et al., 2000) as well as rare disorders such as fatal familial insomnia, Landau– Kleffner syndrome and the syndrome of continuous spike-and-wave discharges during slow wave sleep are not reviewed.
Idiopathic insomnia Idiopathic insomnia is a lifelong inability to obtain adequate sleep that is presumably due to an abnormality of the neurological control of the sleep–wake system (AASM, 2001). This disorder is thought to reflect an imbalance between the arousal system and the various sleep-promoting systems (AASM, 2001). In particular, hyperactivity within the arousal system is presently believed to be the final common pathway of the disorder (AASM, 2001). For instance, several studies have reported increased alertness on the multiple sleep latency test, increased heart rate during the sleep period, increased anxiety on rating scales, and increased tension during wakefulness (Stepanski et al., 1988; Bonnet and Arand, 1995, 1997). In addition, poor sleep leads to altered mood and motivation, decreased attention and vigilance, low levels of energy and concentration, and increased daytime fatigue (AASM, 2001). Quantitative EEG recordings suggest an overall cortical hyperarousal in insomnia (Perlis et al., 2001). However, it should be noticed that hyperarousal in primary insomnia was characterized by an increase in beta/gamma activity at sleep onset, followed by a decline leading to a brief period of hypoarousal (Perlis et al., 2001). Accordingly, some neuroimaging studies show a cortical hyperarousal pattern in insomnia while others report a decrease in cortical functions. In the latter, decreased metabolism might originate from the time window coincidence of the cortical hypoarousal period with neuroimaging acquisition, and therefore does not discard the hyperarousal hypothesis of primary insomnia (Smith et al., 2002). Only a small number of studies tried to characterize the functional neuroanatomy of idiopathic insomnia
76
M. DESSEILLES ET AL.
disorder (referred to as primary insomnia in these reports). Using technetium-99m-hexamethylene-propyleneamine Oxime (99mTC-HMPAO), a gamma-emitting radionuclide imaging agent, regional CBF was estimated in 5 insomniacs and 4 normal sleepers during NREM sleep. Patients with insomnia revealed major rCBF decreases in the basal ganglia, frontal medial, occipital, and parietal cortices. These results suggest that idiopathic insomnia is associated with an abnormal pattern of regional brain function during NREM sleep that particularly involves basal ganglia (Smith et al., 2002). More recently, regional cerebral glucose metabolism (CMRglu) was measured using 18F-fluorodeoxyglucose (18FDG) PET in 7 patients with idiopathic insomnia and 20 healthy age- and gender-matched subjects during waking and NREM sleep (Nofzinger et al., 2004a). Insomniac patients showed increased global CMRglu during sleep as compared to healthy subjects, suggesting an overall cortical hyperarousal in insomnia. In addition insomniac patients had a smaller decline, related to healthy subjects, in CMRglu from waking to sleep states in the ascending reticular activating system, hypothalamus, thalamus, insular cortex, amygdala, hippocampus, anterior cingulate, and medial prefrontal cortices. During wakefulness, reduced metabolism, as compared to healthy subjects, was detected in the prefrontal cortex bilaterally, in the left superior temporal, parietal, and occipital cortices and in the thalamus, hypothalamus, and brainstem reticular formation. Taken together, these findings confirm that regional brain activity does not normally progress from waking to sleep states in patients with
insomnia. Moreover, it was proposed that daytime fatigue resulting from inefficient sleep may be reflected by decreased activity in the prefrontal cortex (Nofzinger et al., 2004a) (Figure 6.3). Interestingly, 4 of the insomnia patients from the Smith’s study were rescanned after cognitive behavioral therapy (Smith et al., 2005). Sleep latency was reduced by at least 43% and there was a global 24% increase in CBF, with significant increases in the basal ganglia after this psychotherapeutic treatment. Such an increase in brain activity has been proposed to reflect the normalization of sleep homeostatic processes. These promising results will certainly inspire further investigations on the effects of psychotherapy on brain functioning in insomnia.
Depression The most common primary diagnosis in patients presenting with a complaint of insomnia is depression (Benca, 2000). Depression is a subclass of mood disorders, which are psychiatric disorders characterized by either one or more episodes of depression, or partial or full manic or hypomanic episodes. Depressive disorders include major depressive disorder, diagnosed in people who have experienced at least one major depressive episode. The Diagnostic and Statistical Manual of Mental Disorders (DSM-IV: American Psychiatric Association, 1994) provides diagnostic criteria for major depression. At least five symptoms must be present for the same 2-week period, nearly every day, and at least one symptom must be either depressed
Thalamus Ascending reticular activating system Hypothalamus
Prefrontal cortex
Mesial temporal cortex
A
Anterior cingulate cortex Insula Mesial temporal cortex Hypothalamus Ascending reticular activating system
Thalamus
B
Ascending reticular activating system
Fig. 6.3. Regional cerebral glucose metabolism (CMRGlu) in patients with insomnia assessed during both waking and nonrapid eye movement sleep states by using 18F-fluorodeoxyglucose positron emission tomography. Panel A: Brain structures that did not show decreased glucose metabolic rate from wakefulness to sleep states in patients with insomnia. Panel B: Brain structures where relative glucose metabolism during wakefulness was higher in healthy subjects than in patients with insomnia. (Reproduced from Nofzinger et al. (2004a), with permission from the American Journal of Psychiatry, Copyright 2004. American Psychiatric Association.)
FUNCTIONAL NEUROIMAGING IN SLEEP, SLEEP DEPRIVATION, AND SLEEP DISORDERS 77 mood or loss of interest or pleasure. Other symptoms suggest an increased arousal in depressed patients of major depressive episodes include insomnia or (Clark and Watson, 1991; Joiner et al., 1999), a hypothhypersomnia, significant weight loss or weight gain, esis that finds support in functional neuroimaging psychomotor activity or retardation, fatigue, feelings data. Beta activity is proposed as an EEG marker of worthlessness or excessive or inappropriate guilt, of arousal during sleep. In an 18FDG PET study (Nofzinger et al., 2000) beta power was negatively poor concentration, recurrent thoughts of death, and correlated with subjective sleep quality, in both normal recurrent suicidal ideation. The disease is classified as and depressed subjects, although depressed patients dysthymic when the full criteria for major depression exhibited increased beta activity during the night comare not met and when individuals are chronically pared to normal controls. Interestingly, beta power depressed for at least 2 years. The association between was correlated with glucose metabolism levels in the typical features of depression, insomnia, and, more ventromedial prefrontal cortex, a region amongst the rarely, excessive sleepiness (AASM, 2001) remains not most deactivated during consolidated SWS (see above) clearly understood. (Nofzinger et al., 2000). In depressed patients, modifications of sleep archiThese clinical, electrophysiological, and neuroimagtecture are characterized by reduced SWS, early onset ing studies provide some evidence in keeping with the of the first episode of REM sleep, and increased phahypothesis of increased hyperarousal in depressed sic REM sleep (Thase, 1998). patients. Nevertheless, pathophysiological mechanisms In the following sections, we will present studies linking hyperarousal with depression as well as insomconducted in depressed patients during wakefulness, nia with depression remain to be established. after sleep deprivation, during NREM, and during The physiological mechanisms underpinning the benREM sleep. eficial effects of sleep deprivation are complex and not WAKEFULNESS NEUROIMAGING IN DEPRESSION completely understood yet. It has been hypothesized that REM sleep pressure is enhanced in depressed patients. Neuroimaging studies in depressed patients during In depressed patients responding favorably to sleep depwakefulness indicate that dysfunction of the prefrontal rivation, as compared to nonresponders, baseline brain cortical and striatal systems, which normally modulate activity during wakefulness was reported to be higher limbic and brainstem structures, play an important role in the anterior cingulate cortex (Wu et al., 1992; Clark in the pathogenesis of depressive symptoms (Mayberg, et al., 2001) and/or the nearby mesial frontal cortex 1997; Drevets, 2001). Abnormalities within orbital and (Ebert et al., 1991, 1994b; Wu et al., 1999; Clark et al., medial prefrontal cortex areas persist following symp2001), then to decrease significantly after sleep deprivatom remission (Drevets, 2000). These findings involve tion as compared to wakefulness. A similar pattern of interconnected neural circuits in which dysfunction of brain activity was observed in elderly depressed patients, neurotransmission may result in the depressive sympincluding normalization after total sleep deprivation toms (Drevets, 2000, 2001). associated with antidepressant treatment (Smith et al., The Hamilton Depression Rating Scale (HDRS) is 1999). In addition, the normalization of anterior cinguwidely used to measure the severity of depression in late metabolism persisted even after recovery sleep mood disorders. Voxelwise correlation maps have (Smith et al., 1999). Interestingly, it was also shown that shown that total HDRS score correlates with metabosleep deprivation responders, as compared to non18 lism as measured by F-FDG PET during wakefulness responders, exhibit a significant decrease in relative in a large set of cerebral areas, including limbic strucbasal ganglia D2 receptor occupancy after sleep depritures, thalamus, and basal ganglia. Moreover, sleep vation (Ebert et al., 1994a). These results suggest that disturbance, a distinct symptom cluster included in the antidepressant benefits of sleep deprivation are the HDRS, correlated positively with glucose metabocorrelated with enhanced endogenous dopamine release lism in limbic structures and basal ganglia (Milak in responders, as compared to nonresponders. These et al., 2005). results corroborate previous hypotheses of dopaminergic participation in the therapeutic action of sleep depriSLEEP DEPRIVATION IN DEPRESSION vation, and indirectly support a dopamine hypothesis of Intriguingly, sleep deprivation has rapid beneficial depression (Ebert et al., 1994a). effects in about 60% of depressed patients (WirzRecently, a preliminary work studied the effect Justice and Van den Hoofdakker, 1999). Responders of concomitant sleep deprivation and antidepressant to sleep deprivation are usually patients with high medication in 6 depressed patients (Wu et al., 2008). behavioral activation and low levels of tiredness (Szuba They were administered the serotonergic antidepreset al., 1991; Bouhuys et al., 1995). These findings sant sertraline for a week and then underwent FDG
78
M. DESSEILLES ET AL.
PET before and after total sleep deprivation. Glucose metabolism decreased in the inferior frontal gyrus and inferior frontal/orbital frontal cortex and increased in the dorsolateral prefrontal cortex, in correlation with reduced score of HDRS.
NREM
SLEEP NEUROIMAGING IN DEPRESSION
It was shown that whole-brain absolute CMRglu during NREM sleep is higher in depressed patients than in normal subjects (Ho et al., 1996). The greatest increases were observed in the posterior cingulate, the amygdala, the hippocampus, and the occipital and temporal cortex. Significant reductions of relative CMRglu were found in the prefrontal and anterior cingulate cortices, caudate nucleus, and medial thalamus. More recently, depressed patients showed smaller decreases than controls in relative regional CMRglu from presleep wakefulness to NREM sleep in the left and right laterodorsal frontal gyri, right medial prefrontal cortex, right superior and middle temporal gyri, insula, right posterior cingulate cortex, lingual gyrus, striate cortex, cerebellar vermis, and left thalamus (Germain et al., 2004b). These results suggest that transition from wakefulness to NREM sleep in depressed patients is characterized by persistent “elevated” activity in frontoparietal regions and thalamus. Intuitively, it is as if the low frontal metabolism during wakefulness could not be further decreased during NREM sleep, as is the case for normal subjects. These findings suggest that abnormal thalamocortical network function may underpin sleep abnormalities and nonrestorative sleep complaints in depressed patients (Germain et al., 2004b).
REM
SLEEP NEUROIMAGING IN DEPRESSION
Anterior paralimbic areas (anterior cingulate cortex, right insula, right parahippocampal gyrus) were shown to be less active in depressed patients than in normal subjects, during REM sleep, as compared to wakefulness (Nofzinger et al., 1999). The spatial extent of paralimbic activation from waking to REM sleep was shown to be greater in the depressed patients as compared to healthy controls (Nofzinger et al., 2004b). Moreover, from waking to REM sleep, depressed patients showed greater activation in bilateral dorsolateral prefrontal, left premotor, primary sensorimotor, and left parietal cortices, as well as in the midbrain reticular formation (Nofzinger et al., 2004b) and in the tectal area, inferior temporal cortex, amygdala, and subicular complex (Nofzinger et al., 1999). The density of REM (number of REMs per minute of REM sleep) has been correlated with the severity of the depression (Thase et al., 1997; Buysse et al., 1999).
Average REM count (an automated analog of REM density) was positively correlated with regional CMRglu bilaterally in the striate cortex, the posterior parietal cortices, and in the medial and ventrolateral prefrontal cortices in depressed patients compared to healthy controls. Moreover, it was negatively correlated with regional CMRglu in areas corresponding bilaterally to the lateral occipital cortex, cuneus, temporal cortices, and parahippocampal gyri (Germain et al., 2004a). For the authors, these results suggest that average REM count may be a marker of hypofrontality during REM sleep in depressed patients. Bupropion (an antidepressant drug) increases CMRglu in anterior cingulate, medial prefrontal cortex, and right anterior insula from waking to REM sleep. After analysis, this effect was linked to a reduction in waking relative metabolism in these structures following treatment in the absence of a significant effect on REM sleep relative metabolism (Nofzinger et al., 2001).
SUMMARY Taken together, these data suggest a close link between mood alteration and activity in limbic and paralimbic structures. Especially, it suggests that hyperactivity in the anterior cingulate cortex of depressed patients during wakefulness may hinder further increases in REM sleep. From this perspective, sleep deprivation would alleviate depression symptoms in decreasing abnormally elevated activity in the anterior cingulate cortex during wakefulness. However, available data remain limited and further studies using more detailed designs are needed to understand the causes and consequences of these mesial frontal metabolic disturbances. Overall, relationships between sleep, insomnia, and depression open a neurobiological window to the understanding of the pathophysiological mechanisms of depression which should be extensively exploited in the future.
Narcolepsy Narcolepsy is a disorder which is characterized by excessive sleepiness that is typically associated with cataplexy, sleep paralysis, and hypnagogic hallucinations (AASM, 2001). To the best of our knowledge, in narcoleptic patients, the voxelwise functional neuroanatomy of waking state, REM sleep, or SWS is not yet fully described. Nor are the neural correlates characterized of other characteristic symptoms such as cataplexy, hypnopompic/ hypnagogic hallucinations, or sleep paralysis. Early observations using 133Xe inhalation showed that, during wakefulness, brainstem and cerebellar
FUNCTIONAL NEUROIMAGING IN SLEEP, SLEEP DEPRIVATION, AND SLEEP DISORDERS blood flow was lower in narcoleptic patients than in normal subjects (Meyer et al., 1980). In contrast, after sleep onset (3 out of 13 in REM sleep), the CBF increased in all areas, and particularly in temporoparietal regions. This pattern was supposedly attributed to dreaming activity, in line with prior reports showing that regional blood flow was increased in temporoparietal areas during visual dreaming and hypnagogic hallucinations (Meyer et al., 1980, 1987). In another study, 6 narcoleptic patients underwent 99 mTC-HMPAO SPECT and showed similar HMPAO uptake in waking state and REM sleep (Asenbaum et al., 1995), suggesting a similar overall cortical activity. An activation of parietal regions during REM sleep was shown with data analysis by regions of interest (Asenbaum et al., 1995). The latter result is intriguing given the parietal deactivation usually observed by PET studies during normal REM sleep (Maquet, 2000). Overall, further studies are needed to confirm these results on a broader population. Data describing the neural correlates of cataplexy in narcoleptic patients are very scarce. One SPECT study was conducted on 2 patients during a cataplexy episode compared to REM sleep or baseline waking period (Hong et al., 2006). During cataplexy, perfusion increased in limbic areas (including amygdala) and basal ganglia, thalami, premotor cortices, sensorimotor cortices, and brainstem, whereas perfusion decreased in prefrontal cortex and occipital lobe. Increased cingulate and amygdala activity may relate to concomitant emotional processing that is usually reported as a powerful trigger of cataplexy. However, such hyperperfusion in the pons, thalami, and amygdaloid complexes was not found in a recent single case report (Chabas et al., 2007). A very recent event-related fMRI study was performed on narcoleptic patients and controls while they watched sequences of humorous pictures. This study is based on the clinical observation that cataplexy episodes are often triggered by positive emotions (e.g., hearing or telling jokes). A group comparison revealed that humorous pictures elicited reduced hypothalamic response together with enhanced amygdala response in the narcoleptic patients. These results suggest that hypothalamic hypocretin activity physiologically modulates the processing of emotional inputs within the amygdala, and that suprapontine mechanisms of cataplexy might involve a dysfunction of hypothalamic– amygdala interactions triggered by positive emotions (Schwartz et al., 2008). Another fMRI study confirmed an increase of activity in the emotional network in narcoleptic patients as compared to controls while viewing humorous cartoons (Reiss et al., 2008). Increased activity was also observed in the right inferior frontal gyri,
79
an area involved in inhibition (Aron et al., 2004). In addition a reduction in hypothalamic activity was shown in 1 subject experiencing a cataplectic attack. For authors, these findings suggest an overdrive of the emotional circuitry and possible compensatory suppression by cortical inhibitory regions in cataplexy (Reiss et al., 2008). Given the role of acetylcholine as an important neurotransmitter in the generation of REM sleep (see above), cholinergic dysfunction was hypothesized to underlie narcolepsy. However, at present, the available PET data did not show any change in muscarinic cholinergic receptors in narcoleptic patients (Sudo et al., 1998). Similarly, the dopamine system has been probed by PET in narcoleptic patients because increased dopamine D2 binding was shown in the brain of deceased narcoleptic patients (Aldrich et al., 1992; Kish et al., 1992). Results remain controversial. One SPECT study has shown that D2 receptor binding in the striatal dopaminergic system was elevated and correlates with the frequency of cataplectic and sleep attacks in 7 patients with narcolepsy (Eisensehr et al., 2003a). However, this finding was not confirmed by other PET (Rinne et al., 1995, 1996; MacFarlane et al., 1997) or SPECT (Hublin et al., 1994; Staedt et al., 1996) studies. This discrepancy might be related to the drug treatment of narcoleptic patients. Indeed, considerable increase in the uptake of 11C-raclopride, a specific D2 receptor ligand, was observed in the putamen of narcoleptic subjects older than 31 years who had undergone prolonged treatment (Khan et al., 1994). Likewise, despite the fact that the binding of iodobenzamide (IBZM, a highly selective central nervous system dopamine D2 receptor ligand) was similar in narcoleptic patients and normal controls, treatment by stimulants and/or antidepressants for 3 months significantly changed the ligand uptake in 4 out of 5 patients (Staedt et al., 1996). Collectively, these neuroimaging results suggest that the reported postmortem increase in dopamine binding might be due to the long-term effect of prior treatment rather than intrinsic modifications. Two fMRI studies assessed the effects of stimulant drugs on cerebral function in narcoleptic patients. The first one tested the effect of modafinil, a wakefulnesspromoting drug (Ellis et al., 1999). In normal subjects, larger brain responses to a multiplexed visual and auditory stimulation paradigm were found at 10.00 hours than at 15.00 hours in visual areas, but not in auditory areas, suggesting time-of-day influences. Surprisingly, the reverse pattern of activity was observed in a group of 12 narcoleptic patients, with higher activity at 15.00 hours than at 10.00 hours. Additionally, modafinil administration did not modify the average level of activation in either normal subjects or narcoleptics
80
M. DESSEILLES ET AL.
(n ¼ 8), but postdrug activation level was inversely proportional to the predrug activation level. These findings are not easy to interpret but at least suggest that modafinil can modulate brain activation to external stimuli. The second study used fMRI and assessed the effects of amphetamines in a small sample of patients with narcoleptic syndrome (n ¼ 2) (Howard et al., 1996). As compared to 3 normal control subjects, the extent of the brain response to auditory and visual stimulation decreased after amphetamine administration in normal subjects. The reverse pattern was observed in narcoleptic patients. Once again, data are very scarce, these findings remain difficult to interpret, and larger samples should be studied before any generalization can be made. Interestingly, using SPECT in 21 healthy volunteers, modafinil has been shown to increase wakefulness and regional CBF in the arousal-related systems and in brain areas related to emotion and executive function (including thalami, dorsal pons, frontopolar, orbitofrontal, superior frontal and middle frontal gyri, insular gyri, cingulate gyrus, inferior temporal gyri, and parahippocampal gyrus) (Joo et al., 2008). Despite these results, it is not clear if activity elicited by wake-promoting drug is underpinned by the same network in narcoleptic patients and healthy controls. Finally, narcolepsy has been linked to a loss of hypothalamic neurons producing orexin (hypocretin), a neuropeptide implicated in arousal systems (Lin et al., 1999). Hypocretin neurons are localized in the lateral hypothalamus and have widespread excitatory projections throughout the brainstem, basal forebrain, and spinal cord. Hypocretin neurons receive in turn inputs from excitatory (glutaminergic) and inhibitory (noradrenergic, serotonergic, and GABAergic) neurons (Baumann and Bassetti, 2005). Hypocretin neurons are hypothesized to be implicated in maintaining wakefulness (Sakurai, 2005) and regulating motor functions (locomotion, muscle tone), energy expenditure (Sakurai, 2005), and sympathetic activity (Baumann and Bassetti, 2005). In humans, postmortem autopsy studies showed a loss of hypocretin mRNA and absence of hypocretin peptides in the hypothalami of narcoleptic patients (Peyron et al., 2000; Thannickal et al., 2003). Low cerebrospinal fluid (CSF) hypocretin-1 levels are usual findings in narcolepsy with definite cataplexy (Mignot et al., 2002). In contrast, in most patients with narcolepsy without cataplexy and in other primary sleep–wake disorders (such as insomnia or restless-legs syndrome (RLS)), CSF hypocretin-1 levels are normal (Baumann and Bassetti, 2005). Moreover, the CSF hypocretin-1 levels have been found to be low in several neurological disorders, irrespective of sleep habits (see, for instance, in advanced Parkinson’s disease, Drouot et al. (2003)).
These elements suggest that hypocretin deficiency may represent in specific clinical contexts a marker of hypothalamic dysfunction rather than an immediate cause of sleep–wake disturbance (Baumann and Bassetti, 2005). Differences in brain morphology that are not identifiable in routine structural MRI can be investigated using the technique of voxel-based morphometry (VBM) that compares the brain structure of patients and controls assessed by high-quality MRI (Ashburner and Friston, 2000, 2001). At present, VBM studies have reported equivocal results in narcoleptic patients. A first study did not show any structural change in brains of patients with hypocretin-deficient narcolepsy (Overeem et al., 2003). These authors suggested that narcolepsy is either associated with microscopic changes untractable by VBM or that functional abnormalities of hypocretin neurons are not associated with structural correlates (Overeem et al., 2003). In another VBM study, however, narcoleptic patients exhibited bilateral cortical graymatter reductions predominantly in inferior temporal and inferior frontal brain regions (Kaufmann et al., 2002). Relative global gray-matter loss was independent of disease duration or medication history and there were no significant subcortical gray-matter alterations. Still another VBM study detected a significant bilateral decrease in hypothalamic gray-matter concentration in narcoleptic patients related to unaffected healthy controls (Draganski et al., 2002). Decreased gray-matter concentration was also observed in the vermis, the superior temporal gyrus, and the right nucleus accumbens. Given the major projection sites of hypocretin-1 (the hypothalamus among others) and hypocretin-2 (the nucleus accumbens among others), the decrease in gray matter was thought to reflect the secondary neuronal loss due to the destruction of specific hypocretin projections (Draganski et al., 2002). This study was corroborated by another VBM study (Buskova et al., 2006). Another VBM study found significant gray-matter loss in the right prefrontal and frontomesial cortex of patients with narcolepsy (Brenneis et al., 2005). For the authors, the volume reduction of gray matter in narcoleptic patients could indicate a disease-related atrophy. Several factors can explain these controversial results, such as possible bias due to inhomogeneous patient groups, prestatistical image processing, or history of treatment (Brenneis et al., 2005). VBM studies with large sample of drug-naive patients should be performed to advance further in this very complex physiopathology. Proton magnetic resonance spectroscopy (1H-MRS) was used in order to assess the N-acetylaspartate (NAA) content in the ventral pontine areas (Ellis et al., 1998) and the hypothalamus of narcoleptic
FUNCTIONAL NEUROIMAGING IN SLEEP, SLEEP DEPRIVATION, AND SLEEP DISORDERS patients (Lodi et al., 2004). In both studies, an analysis of spectral peak area ratios revealed a decrease in the NAA/creatine-phosphocreatine ratio in narcoleptic patients compared with control subjects. These results were interpreted as a neuronal loss or damage in the ventral pontine area and in the hypothalamus of the narcoleptic patients. Another 1H-MRS study in 17 narcoleptics patients showed a higher GABA concentration in the medial prefrontal cortex, which was more prominent in patients without nocturnal sleep disturbance (Kim et al., 2008). The authors suggest it might be a compensatory mechanism to reduce nocturnal sleep disturbances in narcolepsy. The results of the Lodi study (Lodi et al., 2004) were confirmed by an 18FDG PET study that was used to measure relative difference between CMRGlu of 24 narcoleptic patients and 24 normal controls during wakefulness (Joo et al., 2004) (Figure 6.4). Narcoleptic patients had reduced CMRGlu in bilateral precuneus, bilateral posterior hypothalami, and mediodorsal thalamic nuclei (Joo et al., 2004). This study prevails over a SPECT study that was subsequently conducted (Yeon Joo et al., 2005).
Obstructive sleep apnea syndrome Obstructive sleep apnea syndrome (OSAS) is characterized by repetitive episodes of upper-airway obstruction that occur during sleep, generally associated with a reduction in blood oxygen saturation (AASM, 2001). Population-based epidemiologic studies revealed a high prevalence (1–5% of adult men) of OSAS. These studies also associate OSAS with significant morbidity, such as hypertension, cardiovascular disease, stroke, or motor vehicle accidents (Young et al., 2002). OSAS has a complex pathophysiology which is not yet completely understood. Several studies suggest that
81
OSAS in all age groups is due to a combination of both anatomic airway narrowing and abnormal upperairway neuromotor tone. Besides the known anatomic factors, such as craniofacial anomalies, obesity, and adenotonsillar hypertrophy, that contribute to OSAS, clear anatomical contributing factors cannot always be identified (AASM, 2001). This suggests that alterations in upper-airway neuromuscular tone also play an important role in the etiology of OSAS (Arens and Marcus, 2004). The pathophysiology of OSAS also includes enhanced chemoreflex sensitivity and an exaggerated sympathetic response during hypoxemic episodes (Caples et al., 2005). Furthemore, it is still a matter of debate whether the cognitive consequences of OSAS are reversible or not (Aloia et al., 2004; Brown, 2005). Functional impairments are often associated with neuropsychological deficits which are often thought to be reversible with appropriate treatment (Aloia et al., 2004; Brown, 2005). In contrast, structural alterations may indicate irreversible cerebral changes and would underpin permanent cognitive impairments (Alchanatis et al., 2004), although this proposal remains a matter of debate in the literature (Gale and Hopkins, 2004). In addition, the specific consequences of sleep fragmentation and hypoxia on cognition and brain function have still to be teased apart and thoroughly characterized. We will present successively an overview of cognitive alterations, changes in brain structure and function, and finally neuroimaging studies exploring ventilatory control in OSAS.
OVERVIEW
OF COGNITIVE ALTERATIONS
Alterations of mental process, behavior, and interpersonal relations are a common observation in OSAS patients (Brown, 2005). Moreover OSAS has been associated with distinct cognitive alterations in various
Fig. 6.4. Cerebral glucose metabolism (CMRGlu) in the hypothalamus and thalamus in narcoleptic patients during wakefulness. Bilateral posterior hypothalami and mediodorsolateral thalamic nuclei show hypometabolism in narcoleptic patients compared to controls. (Reproduced with permission from Joo et al. (2004), Copyright 2004. Wiley-Liss, Inc., A Wiley Company.)
82
M. DESSEILLES ET AL.
domains. Both fragmented sleep and hypoxemia are proposed as the main factors leading to neurocognitive impairment during wakefulness (Berry et al., 1986; Findley et al., 1986, 1995; Bedard et al., 1991; Cheshire et al., 1992; Bonnet, 1993; George et al., 1996; Young et al., 1997). Several studies emphasized the deterioration of executive functions in OSAS patients, including the inability to initiate new mental processes (Naegele et al., 1995; Feuerstein et al., 1997), deficits in working memory (Greenberg et al., 1987; Naegele et al., 1995), contextual memory (Harrison et al., 2000), selective attention (Kotterba et al., 1998), continuous attention (Kotterba et al., 1998), and analysis and synthesis (Greenberg et al., 1987; Naegele et al., 1995). A metaanalysis showed that untreated patients with OSAS had a negligible impairment of intellectual and verbal functioning but a substantial impairment of vigilance and executive functioning (Beebe et al., 2003). In addition, a “cognitive reserve” could be protective against OSAS-related cognitive decline (Alchanatis et al., 2005). Most studies suggest that cognitive impairments improve with nasal continuous positive airway pressure (nCPAP) treatment but evidence suggests that some changes may be permanent (Aloia et al., 2004; Brown, 2005). For instance, after nCPAP, OSAS patients improved attention / vigilance in most studies and did not improve constructional abilities or psychomotor functioning (Aloia et al., 2004). Intrinsic neural dysfunction related to these deleterious factors would add to daytime sleepiness to explain the neuropsychological deterioration of OSAS patients (Beebe and Gozal, 2002). Interestingly, several studies have linked OSAS and depression (Schroder and O’Hara, 2005). Moreover, several authors have demonstrated improvement in depression scores and overall psychopathology by using nCPAP therapy (Engleman et al., 1997).
STRUCTURAL
CHANGES
Using VBM in 21 patients with OSAS and in 21 control subjects, structural changes in brain morphology were assessed (Macey et al., 2002). Diminished regional and often unilateral gray-matter loss was apparent in patients with OSAS in multiple brain sites involved in motor regulation of the upper airway as well as in various cognitive functions, including the frontal and parietal cortex, temporal lobe, anterior cingulate, hippocampus, and cerebellum. Another VBM study conducted in 7 OSAS patients and 7 controls showed a significantly lower gray-matter concentration solely within the left hippocampus in the OSAS patients (Morrell et al., 2003). There was no difference in total gray-matter volume between the two groups. In
a more recent VBM study (27 OSAS patients and 24 controls), it has been found that there are no graymatter volume deficits or focal structural changes in severe OSAS patients. Whole-brain volume decreases without focal changes after 6 months of cPAP treatment (O’Donoghue et al., 2005). Another study compared both neuropathological and neuropsychological effects of hypoxia in patients with either carbon monoxide poisoning or OSAS (Gale and Hopkins, 2004). Brain imaging showed a hippocampal atrophy in both groups even though a linear relationship between hippocampal volume and memory performance was found for only a subset of selected tests (the delayed recall or the Rey–Osterrieth Complex Figure Design and Trial 6 of the Rey Auditory Verbal Learning Test, among others), and only in the OSAS group. Hippocampal volume was related to performance on nonverbal information processing (Wechsler Adult Intelligence Scale – Revised Block Design). Further data will be necessary to delineate better the specificity and contribution of hippocampal atrophy in OSAS.
CHANGES
IN BRAIN FUNCTION
As described earlier, cognitive executive functions, associated with specific prefrontal-subcortical brain circuits, are dysfunctional in OSAS patients (Alchanatis et al., 2004). Another study, using single-voxel 1HMRS, attempted to demonstrate that OSAS can induce axonal loss or dysfunction and myelin metabolism impairment in the frontal periventricular white matter. Magnetic resonance spectra were obtained from prefrontal cortex, parieto-occipital and frontal periventricular white matter. NAA-to-creatine and cholineto-creatine ratios were significantly lower in the frontal white matter of OSAS patients when compared to controls. Absolute concentrations of NAA and choline were also significantly reduced in the frontal white matter of OSAS patients (Alchanatis et al., 2004). These findings may offer an explanation for the sometimes irreversible cognitive deficits associated with OSAS. Despite these results, which suggest an implication of frontal-lobe white-matter lesion in daytime cognitive dysfunction, it still lacks a direct relationship between frontal dysfunction and cognitive impairments. Likewise, some clarification is needed to show the respective roles (in cognitive alterations supposed to be frontal) of hypoxia, sleep fragmentation, or sleep deprivation which occur during OSAS. Another 1H-MRS study in OSAS patients showed that, in the left hippocampal area, the N-acetyl-containing/ creatine-containing compounds ratio was significantly increased (Bartlett et al., 2004). Analysis indicated that this was probably due to a decrease in creatine-containing
FUNCTIONAL NEUROIMAGING IN SLEEP, SLEEP DEPRIVATION, AND SLEEP DISORDERS 83 compounds which was correlated with worse OSAS the estimates of cardiovascular variability (Kryger severity and neurocognitive performance. Authors suget al., 2000). Several important regulatory mechanisms gest that the metabolic changes in the hippocampal area in cardiovascular homeostasis seem to be impaired in represent adjustments to brain bioenergetics and may OSAS patients. Specific chemoreceptors seem to be reflect the different susceptibility of this tissue to hypimplicated in the pathophysiology of OSAS (Mateika oxic damage in OSAS, as in ischemic preconditioning. and Ellythy, 2003). For instance, the ventilatory An earlier and less reflective 1H-MRS study in 23 response to carbon dioxide is elevated in OSAS OSAS patients showed that the NAA-to-choline ratio patients (Mateika and Ellythy, 2003). The partial presin cerebral white matter was significantly lower in sure of carbon dioxide that delimits the carbon dioxide patients with moderate to severe OSAS than in patients ventilatory recruitment threshold is elevated in patients with mild OSAS and healthy subjects (Kamba et al., with OSAS (Mateika and Ellythy, 2003). An altered 1997). This finding suggests the presence of cerebral autonomic balance has been suggested as one possible damage, probably caused by repeated apneic episodes. pathogenic factor. This autonomic dysfunction has In addition, a study by Halbower et al. (2006) showed been thought to be implicated in the subsequent devela decrease in the NAA-to-choline ratio in the left opment of cardiovascular diseases in patients with hippocampus and in the right frontal cortex using the OSAS. Several fMRI studies have been conducted in same technique in a pediatric population with OSAS. OSAS patients to characterize the neural correlates of Together VBM and spectroscopy studies point to integrated afferent airway signals with autonomic outan atrophy and/or dysfunction of hippocampal regions flow and airway motor response (Harper et al., 2003; in OSAS. Henderson et al., 2003; Macey et al., 2003, 2006). For Long-term consequences of OSAS have been more instance, altered neuronal response after Valsalva rarely assessed after nCPAP treatment. An early maneuver was shown in cerebellar, limbic, and motor 99 mTC-HMPAO SPECT study in 14 adult OSAS areas involved in the control of diaphragmatic and patients (Ficker et al., 1997) reported a marked frontal upper-airway muscles (Figure 6.5). Enhanced sympahyperperfusion in 5 patients. In distinction, regional thetic outflow after a forehead cold pressor challenge analysis showed a reduced perfusion in the left parietal results in both diminished and exaggerated responses region. It is noteworthy that all these changes were in limbic area, cerebellar, frontal cortex, and thalamus. completely reversed by effective nCPAP therapy, sugAn fMRI study evaluated the brain activity changes gesting that the main deleterious effects of OSAS on during baseline and expiratory loading conditions in 9 brain activity are reversible. The authors suggest that OSAS patients and 16 controls (Macey et al., 2003). there might be an apnea-associated effect of local vasReduced neural signals emerged in OSAS patients cular autoregulation mechanisms acting to compensate within the frontal cortex, anterior cingulate, cerebellar systemic blood flow alterations or blood gas changes dentate nucleus, dorsal pons, anterior insula, and lentiin OSAS. Using 1H-MRS, a study showed that NAA in form nuclei. Signal increases in OSAS over control the parietal-occipital cortex was significantly reduced subjects developed in the dorsal midbrain, hippocammore in 14 OSAS patients than in controls, but this pus, quadrangular cerebellar lobule, ventral midbrain, reduction persisted after nCPAP therapy despite clinical, and ventral pons. Fastigial nuclei and the amygdala neuropsychological, and neurophysiological normalizashowed substantially increased variability in OSAS tion (Tonon et al., 2007). In addition, mandibular subjects. No group differences were found in the thaladvancement led to decreased fMRI response in the amus. Both groups developed similar expiratory loadleft cingulate gyrus and the bilateral prefrontal cortices ing pressures, but appropriate autonomic responses in 12 healthy subjects during induced respiratory stress did not emerge in OSAS patients. A more recent fMRI (Hashimoto et al., 2006). Simultaneously, the subjective study evaluated the brain activity changes during baseeffects of this treatment were assessed by a visual line and inspiratory loading in 7 OSAS patients and analog scale and confirmed successful reduction of 11 controls (Macey et al., 2006). A number of cortical respiratory stress. and subcortical areas mediating sensory and autonomic processes, and motor timing were affected. Altered signals appeared in primary sensory thalamus CHANGES IN VENTILATORY CONTROL and sensory cortex, supplementary motor cortex, cerIn OSAS patients, apnea has considerable hemodyebellar cortex and deep nuclei, cingulate, medial temnamic consequences that are mediated by a complex poral, and insular cortices, right hippocampus, and cascade of physiological events. Repetitive episodes midbrain (Macey et al., 2006). of apnea trigger marked fluctuations in both blood These altered brain activation patterns, during pressure and heart rate, with consequent effects on waking, could reflect neural dysfunctions that mediate
84
M. DESSEILLES ET AL. Inferior parietal cortex Right view
Precentral gyrus
Left view
Superior temporal gyrus Cerebellar cortex
Superior frontal gyrus
Front view
Fig. 6.5. Neural response (cerebral blood flow) during Valsalva maneuvers in obstructive sleep apnea syndrome using functional magnetic resonance imaging. There are areas of significant difference in signal intensity between controls and obstructive sleep apnea syndrome (OSAS) patients during Valsalva maneuver in cortical regions. Voxels are color-coded for depth from the surface and rendered on to the cortex of an average anatomical image set of all control and OSAS patients. (Reproduced from Henderson et al. (2003), with permission from the Journal of Applied Physiology, Copyright 2003. American Physiological Society.)
the prominently diminished upper-airway tone which occurs in OSAS patients during sleep.
SUMMARY Altogether, these findings suggest that neuropsychological damage in OSAS is brought about by various alterations in prefrontal cortex, hippocampal and parietal cortex. Even if abnormal brain activations are reversible under nCPAP, several studies have suggested that not all neuropsychological damage disappears after nCPAP (Bedard et al., 1993; Feuerstein et al., 1997; Naegele et al., 1998). Accordingly, structural brain changes have been reported in OSAS patients. Although the basic pathophysiological mechanisms are not completely understood, a dysregulation in the autonomic regulation seems to have an important role in these mechanisms. However, it is important to notice that peripheral factors may confound the deficits observed in studies focused on OSAS patients, including exaggerated body mass index and
motivational problems (Tasali and Van Cauter, 2002; Spiegel et al., 2004).
Abnormal motor behaviors during sleep Abnormal motor behaviors during sleep include the periodic limb movements and RBD, a specific parasomnia syndrome associated with REM sleep. Abnormal motor behaviors are a common cause of sleep disturbance and the understanding of the underlying physiopathology should be useful in the management (diagnostic and prognostic information) of insomnia (Montplaisir et al., 1994).
PERIODIC
LIMB MOVEMENTS
Periodic limb movement disorder during sleep (PLMS) and RLS are distinct but overlapping syndromes. PLMS is characterized by periodic episodes of repetitive and highly stereotyped limb movements that occur during sleep (ASDA, 1990). RLS is a disorder
FUNCTIONAL NEUROIMAGING IN SLEEP, SLEEP DEPRIVATION, AND SLEEP DISORDERS characterized by uncomfortable leg sensations, usually prior to sleep onset, that cause an almost irresistible urge to move the legs (ASDA, 1990). The diagnosis of PLMS requires the presence of PLMS on polysomnography as well as an associated sleep complaint. RLS, however, is essentially made on clinical grounds. Moreover, PLMS are themselves nonspecific, occurring both with RLS and with other sleep disorders (e.g., narcolepsy, sleep apnea syndrome, RBD) as well as in normal individuals (Tan and Ondo, 2000). Thus, the diagnosis of PLMS requires the exclusion of other potential causes for the associated sleep complaint (Lesage and Hening, 2004). Structural cerebral abnormalities have been reported in patients with idiopathic RLS (Etgen et al., 2005). High-resolution T1-weighted MRI of 51 patients and 51 controls analyzed using VBM revealed a bilateral gray-matter increase in the pulvinar in patients with idiopathic RLS. These authors suggest that changes in thalamic structures are either involved in the pathogenesis of RLS or may reflect a consequence of chronic increase in afferent input of behaviorally relevant information. Finally, an fMRI study also attempted to localize some cerebral generators of leg discomfort and periodic limb movements in RLS (Bucher et al., 1997). The leg discomfort study showed a bilateral activation of the cerebellum and contralateral activation of the thalamus in patients. During a second condition, combining periodic limb movements and sensory leg discomfort, patients also showed activity in the cerebellum and thalamus with additional activation in the red nuclei and brainstem close to the reticular formation. Interestingly, when subjects were asked to imitate PLMS voluntarily, there was no activation in the brainstem, but rather additional activation in the globus pallidus and motor cortex. These results suggest an involuntary mechanism of induction and a subcortical origin for RLS. In addition, a recent VBM study examining 14 patients with idiopathic RLS detected a slightly increased gray-matter density in the ventral hippocampus and in the middle orbitofrontal gyrus (Hornyak et al., 2007). Recently, 45 idiopathic RLS patients and 30 healthy controls were studied using quantitative whole-brainbased diffusion tensor imaging (Unrath et al., 2008). In the RLS group, regional fractional anisotropy used as a quantitative marker of white-matter integrity was reduced in several subcortical areas, including areas in the proximity of motor and somatosensory cortices, the right hemispheric thalamus (posterior ventral lateral nucleus), in motor projectional fibers, and adjacent to the left anterior cingulum. In addition, high-resolution three-dimensional MRI was performed in 63 idiopathic RLS patients using optimized VBM (Unrath et al.,
85
2007). As compared to controls, regional decreases of gray-matter volume were shown in primary somatosensory cortex and primary motor areas. Clusters in both areas correlated with the severity of RLS symptoms and with disease duration. Together these results show a neocortical and subcortical network of area involving sensorimotor impairment. Incongruent results might be due to differences in populations examined, such as treatment-induced effects on cerebral morphology in RLS, duration of the illness, or methodological issues (size of the samples). A suprasegmental release of inhibition of descending inhibitory pathways implicating dopaminergic, adrenergic, and opiate systems is thought to be involved in PLMS pathogenesis (Wetter and Pollmacher, 1997). This is supported by the observation of PLMS during spinal anaesthesia (Watanabe et al., 1987), for instance. Patients’ condition worsens when dopamine antagonists are given (Akpinar, 1982), whereas dopaminergic drugs have been shown to relieve PLMS (Brodeur et al., 1988; Montplaisir et al., 1991, 2000). Staedt et al. have tested the hypothesis of decreased dopaminergic activity in PLMS patients. In a series of SPECT studies, they report a decreased IBZM striatal uptake, indicating a lower D2 receptor occupancy in PLMS patients (Staedt et al., 1993, 1995a, b; Happe et al., 2003). Treating patients with dopamine replacement therapy increased the IBZM binding and improved the sleep quality in these patients (Staedt et al., 1995a). One study evaluated the striatal pre- and postsynaptic dopamine status in 10 drug-naive patients suffering from both RLS and PLMS and 10 age-matched controls, by means of 123I methyl 3 beta-(4-iodophenyl) tropane-2 beta-carboxylate (123I beta-CIT), a ligand of dopamine transporter, and 123I-IBZM SPECT respectively (Michaud et al., 2002). There was no difference in DA transporter (123I-beta-CIT) binding between RLS-PLMS patients and controls. The study of the striatal D2 receptor binding (123I-IBZM) revealed again a significantly lower binding in patients as compared with controls. Numerous mechanisms may be responsible for this decrease in D2 receptor binding. Since 123 I-beta-CIT binding is normal, a decreased number of D2 receptors or a decreased affinity of D2 receptors for 123I-IBZM is more likely than a downregulation of D2 receptors due to an increased level of synaptic dopamine (Michaud et al., 2002). Fourteen patients with idiopathic RLS and PLMS successfully treated by dopaminergic (e.g., ropinirole) and nondopaminergic (e.g., gabapentin) treatment were investigated while off medication by using 123I-IBZM and SPECT (Tribl et al., 2004). They were compared to 10 healthy sex- and age-matched control subjects. The patients presented with sleep disturbances, severe
86
M. DESSEILLES ET AL.
PLMS, and severe RLS symptoms during the period of scanning while off medication and did not show any significant differences in striatal to frontal 123I-IBZM binding to D2 receptors compared to controls, in contrast to the previous study. The authors suggest that the dopaminergic system in these patients might be affected elsewhere, possibly in the diencephalospinal part of the dopaminergic system (Tribl et al., 2004). These studies support the hypothesis that a central dopamine dysfunction is involved in the physiopathology of RLS-PLMS, although more recent studies specifically implicate the cerebral metabolism of iron (Allen, 2004). Iron and the dopaminergic system are linked since iron is an important cofactor for tyrosine hydroxylase, the step-limiting enzyme in dopamine synthesis, and also plays a major role in the functioning of postsynaptic D2 receptors (Kryger et al., 2000). A neuropathologic study (7 RLS brain and 5 normal brain) has shown a marked decrease in H-ferritin (ferritin heavy chain) and iron staining in RLS subtantia nigra. Transferrin receptor staining on neuromelanincontaining cells was decreased in RLS brains compared to normal brains, whereas transferrin staining in these cells was increased (Connor et al., 2003). Using a special MRI measurement (R2*), Allen et al. (2001) assessed regional brain iron concentrations in 10 subjects (5 with RLS, 5 controls). R2* was significantly decreased in the substantia nigra, and somewhat less significantly in the putamen, both in proportion to RLS severity. These results show that this R2* MRI measurement may prove useful in the management of RLS, and also indicate that brain iron insufficiency may occur in RLS patients in some brain regions. In addition, another study found diminished iron concentration across 10 brain regions in early-onset RLS but not in late-onset RLS when compared to controls (Earley et al., 2006). These convergent observations seem to show that RLS may be a functional disorder resulting from impaired iron metabolism (i.e., impaired regulation of transferring receptors) (Connor et al., 2003). Interestingly, altered iron metabolism in lymphocytes was shown in 24 subjects with RLS as compared with controls. Lymphocytes showed an increase in ferroportin (a transmembrane protein that transports iron from the inside to the outside of a cell), implying increased cellular iron excretion, in the face of increased iron need (Earley et al., 2008).
REM
SLEEP BEHAVIOR DISORDER
RBD is characterized by brisk movements of the body associated with dream mentation that usually disturbs sleep continuity (Schenck et al., 1986). During the nocturnal spells, patients behave as if they are acting out
their dream (ASDA, 1997). This disease may be idiopathic (up to 60%) or associated with other neurologic disorders. A sizeable proportion of patients with RBD will develop extrapyramidal disorders (Schenck et al., 1996; Gagnon et al., 2002, 2004), Lewy body dementia (Fantini et al., 2005), and multiple system atrophy (Plazzi et al., 1997; Gilman et al., 2003). More recently, a strong association between RBD and alpha-synucleinopathies has been observed, with the parasomnia often preceding the clinical onset of the neurodegenerative disease (Fantini et al., 2005; Boeve et al., 2007). Worthy of note, lesions in the mesopontine tegmentum of cats can lead to the disappearance of muscle atonia during REM sleep together with dream enactment behavior (Sakai et al., 1979). A study combining MRI and 123I-IMP SPECT in 20 RBD patients and 7 healthy controls during REM sleep reported significantly decreased blood flow in the upper portion of both sides of the frontal lobe and pons in patients with RBD, in comparison with normal elderly subjects (Shirakawa et al., 2002). Another SPECT study in 8 RBD patients during waking rest showed decreased activity in frontal and temporoparietal cortices but found increased activity in the pons, putamen, and right hippocampus (Mazza et al., 2006). In addition, brainstem function was evaluated by 1H-MRS in a 69-year-old man with idiopathic RBD. An analysis of spectral peak area ratios revealed an increase in the choline/creatine ratio. This change suggests that brainstem neurons have functional impairment at the cell membrane level (Miyamoto et al., 2000). In contrast, one group using 1H-MRS in 15 patients with idiopathic RBD and 15 matched control subjects failed to reveal any difference in metabolic peaks of NAA/creatine, choline/creatine and myoinositol/creatine ratios in the pontine tegmentum and the midbrain (Iranzo et al., 2002). This result does not support the hypothesis of marked mesopontine neuronal loss or 1 H-MRS detectable metabolic disturbances in idiopathic RBD. Despite these equivocal results, 1H-MRS may provide for noninvasive metabolic evaluation of brainstem neuronal function in RBD and find application in the differentiation of secondary RBD with neurodegenerative disorders from idiopathic disorders. Using SPECT and (N)-(3-iodopropene-2-yl)-2betacarbomethoxy-3beta-(4-chlorophenyl) tropane labeled with iodine-123 (IPT), a ligand of striatal presynaptic dopamine transporters), IPT binding in RBD patients (n ¼ 5) during wakefulness was found to be lower than in normal controls but higher than in Parkinson patients (n ¼ 14) (Eisensehr et al., 2000, 2003b). These results suggest that the number of presynaptic dopamine transporters is decreased in both Parkinson and RBD patients. Other studies probed the density of striatal dopaminergic terminals using PET and 11C-dihydrotetrabenazine (11C-DTBZ, a monoamine vesicular transporter
FUNCTIONAL NEUROIMAGING IN SLEEP, SLEEP DEPRIVATION, AND SLEEP DISORDERS inhibitor used as an in vivo marker for dopamine nerve terminals). Significant reductions in striatal 11C-DTBZ binding characterized 6 elderly subjects with chronic idiopathic RBD, as compared to 19 age-matched controls, particularly in the posterior putamen (Albin et al., 2000). Likewise 11C-DTBZ binding in the striatum was decreased in 13 patients with multiple-system atrophy (MSA) (Gilman et al., 2003). Striatal 11C-DTBZ uptake was inversely correlated with the severity of symptoms in this MSA group. Moreover 123I-iodobenzovesamiol (123I-IBVM) binding was reduced in the thalamus in this MSA population. 123I-IBVM is a radiotracer that selectively binds to the intraneuronal storage vesicles of cholinergic nerve endings, and is used as a highly specific marker for cerebral cholinergic neurons. It remains to be shown whether these alterations play a causal role in the pathophysiology of RBD or reflect functional consequences and adaptations to the pathological conditions. Although there is evidence that some Parkinson patients do show excessive nocturnal movements (Trenkwalder, 1998; Happe et al., 2003), it is interesting that only a small percentage of Parkinson patients develop full-blown RBD. This suggests that modifications of other systems of neurotransmission are probably necessary for full-blown RBD to occur.
CONCLUSIONS Brain functional imaging provides unprecedented possibilities to explore brain function during normal and pathological sleep. Nevertheless, brain functional imaging in sleep is still in its infancy, at present mostly restricted to research purposes. As shown in this review, brain functional imaging in patients affected by sleep disorders may address different kinds of issues. The first topic is the characterization of the cerebral aftermath of sleep disruption due to intrinsic sleep disorders or to extrinsic environmental or medical causes. The second, more ambitious, aim would be to characterize better the primary physiopathological mechanisms of sleep disorders, or at least their cerebral correlates. This attempt is hampered by several factors. Scanning patients during their sleep is not at all easy, for practical and methodological reasons. It requires some adjustment in the imaging environment and it is never guaranteed that the participant will sleep during data acquisition opportunities. Clinical manifestations in sleep disorders are often unpredictable and transient (e.g., sleepwalking, RBD); thus one cannot predict whether the pathological event will occur during the scanning period. In the same manner, most clinical manifestations induce large movements. These pathological movements during sleep may lead to image
87
artifacts and misinterpretation of brain activation, making their study in functional neuroimaging very difficult. In this respect, SPECT is probably the most appropriate procedure for the reason that the radiotracer can be simply administered during the clinical events, well before the brain images are acquired. A example of such a study pertains to sleepwalking (Bassetti et al., 2000). Finally, and not least, the theoretical framework necessary for designing the protocol of clinical neuroimaging studies is not necessarily available for all sleep disorders. For instance, the discovery of the hypocretin system and its role in narcolepsy in the late 1990s (Lin et al., 1999) has indubitably changed how experimental designs should be run in neuroimaging in narcoleptic patients. Nevertheless, alternative approaches are available, as the functional and structural consequences of these sleep disorders can also be assessed during wakefulness, as seen above. A third area of interest is the establishment of a nosography of sleep disorders. For instance, neuroimaging could help classify different subtypes of insomnia in terms of their underlying characteristic patterns of regional brain activity, an approach that may prove complementary to the clinical observation. Finally, functional neuroimaging can also be used to assess the effects of hypnotic drugs on regional brain function. This may enlighten our understanding of their effects, assuming that hypnotic medications inducing typical patterns of brain activation might rely on cellular mechanisms similar to those prevailing in normal sleep. Although substantial progress in methodology has been made, a large research effort is still needed to characterize better pathophysiological mechanisms of sleep disorders, teasing apart their causes from their consequences. Optimally, brain functional imaging should be helpful in order to assess, in an individual patient, the functional and structural consequences of long-term sleep disruption. These considerations argue for closer collaboration and partnership between basic neuroscientist sleep researchers, sleep clinicians, and neuroimagers in designing and conducting more informative (multimodal) experiments in a large number of sleep disorders.
ACKNOWLEDGMENTS The authors are supported by the Fonds National de la Recherche Scientifique (FNRS) (Belgium; grant number 3.4516.05 to Martin Desseilles). This work was additionally supported by the research funds of the University of Lie`ge, the Queen Elisabeth Medical Foundation, and the Interuniversity Attraction Pole program.
88
M. DESSEILLES ET AL.
REFERENCES AASM (2001). International Classification of Sleep Disorders. Diagnostic and Coding Manual. American Academy of Sleep Medicine, Chicago, IL. Akpinar S (1982). Treatment of restless legs syndrome with levodopa plus benserazide. Arch Neurol 39 (11): 739. Albin RL, Koeppe RA, Chervin RD et al. (2000). Decreased striatal dopaminergic innervation in REM sleep behavior disorder. Neurology 55 (9): 1410–1412. Alchanatis M, Deligiorgis N, Zias N et al. (2004). Frontal brain lobe impairment in obstructive sleep apnoea: a proton MR spectroscopy study. Eur Respir J 24 (6): 980–986. Alchanatis M, Zias N, Deligiorgis N et al. (2005). Sleep apnea-related cognitive deficits and intelligence: an implication of cognitive reserve theory. J Sleep Res 14 (1): 69–75. Aldrich MS, Hollingsworth Z, Penney JB et al. (1992). Dopamine-receptor autoradiography of human narcoleptic brain. Neurology 42 (2): 410–415. Allen R (2004). Dopamine and iron in the pathophysiology of restless legs syndrome (RLS). Sleep Med 5 (4): 385–391. Allen RP, Barker PB, Wehrl F et al. (2001). MRI measurement of brain iron in patients with restless legs syndrome. Neurology 56 (2): 263–265. Aloia MS, Arnedt JT, Davis JD et al. (2004). Neuropsychological sequelae of obstructive sleep apnea-hypopnea syndrome: a critical review. J Int Neuropsychol Soc 10 (5): 772–785. American Psychiatric Association (1994). Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR). APA Press, Washington DC. Andersson JL, Onoe H, Hetta J et al. (1998). Brain networks affected by synchronized sleep visualized by positron emission tomography. J Cereb Blood Flow Metab 18 (7): 701–715. Arens R, Marcus CL (2004). Pathophysiology of upper airway obstruction: a developmental perspective. Sleep 27 (5): 997–1019. Aron AR, Robbins TW, Poldrack RA et al. (2004). Inhibition and the right inferior frontal cortex. Trends Cogn Sci 8 (4): 170–177. ASDA (1990). International Classification of Sleep Disorders. Diagnostic and Coding Manual. American Sleep Disorders Association, Rochester, MN. ASDA (1997). International Classification of Sleep Disorders and Codign Manual. American Sleep Disorders Association, Rochester, MN. Asenbaum S, Zeithofer J, Saletu B et al. (1995). Technetium99m-HMPAO SPECT imaging of cerebral blood flow during REM sleep in narcoleptics. J Nucl Med 36 (7): 1150–1155. Ashburner J, Friston KJ (2000). Voxel-based morphometry – the methods. Neuroimage 11 (6 Pt 1): 805–821. Ashburner J, Friston KJ (2001). Why voxel-based morphometry should be used. Neuroimage 14 (6): 1238–1243. Bartlett DJ, Rae C, Thompson CH et al. (2004). Hippocampal area metabolites relate to severity and cognitive function in obstructive sleep apnea. Sleep Med 5 (6): 593–596.
Bassetti C, Vella S, Donati F et al. (2000). SPECT during sleepwalking. Lancet 356 (9228): 484–485. Baumann CR, Bassetti CL (2005). Hypocretins (orexins): clinical impact of the discovery of a neurotransmitter. Sleep Med Rev 9 (4): 253–268. Bedard MA, Montplaisir J, Richer F et al. (1991). Obstructive sleep apnea syndrome: pathogenesis of neuropsychological deficits. J Clin Exp Neuropsychol 13 (6): 950–964. Bedard MA, Montplaisir J, Malo J et al. (1993). Persistent neuropsychological deficits and vigilance impairment in sleep apnea syndrome after treatment with continuous positive airways pressure (CPAP). J Clin Exp Neuropsychol 15 (2): 330–341. Beebe DW, Gozal D (2002). Obstructive sleep apnea and the prefrontal cortex: towards a comprehensive model linking nocturnal upper airway obstruction to daytime cognitive and behavioral deficits. J Sleep Res 11 (1): 1–16. Beebe DW, Groesz L, Wells C et al. (2003). The neuropsychological effects of obstructive sleep apnea: a metaanalysis of norm-referenced and case-controlled data. Sleep 26 (3): 298–307. Benca RM (2000). Mood disorders. In: MH Kryger, T Roth, WC Dement (Eds.), Principles and Practice of Sleep Medicine. Elsevier, Saunders, pp. 1040–1057. Berry DT, Webb WB, Block AJ et al. (1986). Nocturnal hypoxia and neuropsychological variables. J Clin Exp Neuropsychol 8 (3): 229–238. Boeve BF, Silber MH, Saper CB et al. (2007). Pathophysiology of REM sleep behaviour disorder and relevance to neurodegenerative disease. Brain 130 (Pt 11): 2770–2788. Bonnet MH (1993). Cognitive effects of sleep and sleep fragmentation. Sleep 16 (8 Suppl): S65–S67. Bonnet MH, Arand DL (1995). 24-Hour metabolic rate in insomniacs and matched normal sleepers. Sleep 18 (7): 581–588. Bonnet MH, Arand DL (1997). Hyperarousal and insomnia. Sleep Med Rev 1 (2): 97–108. Borbely AA (2001). From slow waves to sleep homeostasis: new perspectives. Arch Ital Biol 139 (1–2): 53–61. Born AP, Law I, Lund TE et al. (2002). Cortical deactivation induced by visual stimulation in human slow-wave sleep. Neuroimage 17 (3): 1325–1335. Bouhuys AL, van den Burg W, van den Hoofdakker RH et al. (1995). The relationship between tiredness prior to sleep deprivation and the antidepressant response to sleep deprivation in depression. Biol Psychiatry 37 (7): 457–461. Braun AR, Balkin TJ, Wesenten NJ et al. (1997). Regional cerebral blood flow throughout the sleep–wake cycle. An H2(15)O PET study. Brain 120 (Pt 7): 1173–1197. Braun AR, Balkin TJ, Wesensten NJ et al. (1998). Dissociated pattern of activity in visual cortices and their projections during human rapid eye movement sleep. Science 279 (5347): 91–95. Brenneis C, Brandauer E, Frauscher B et al. (2005). Voxelbased morphometry in narcolepsy. Sleep Med 6: 531–536. Brodeur C, Montplaisir J, Godbout R et al. (1988). Treatment of restless legs syndrome and periodic movements during sleep with L-dopa: a double-blind, controlled study. Neurology 38 (12): 1845–1848.
FUNCTIONAL NEUROIMAGING IN SLEEP, SLEEP DEPRIVATION, AND SLEEP DISORDERS Brown WD (2005). The psychosocial aspects of obstructive sleep apnea. Semin Respir Crit Care Med 26 (1): 33–43. Bucher SF, Seelos KC, Oertel WH et al. (1997). Cerebral generators involved in the pathogenesis of the restless legs syndrome. Ann Neurol 41 (5): 639–645. Buskova J, Vaneckova M, Sonka K et al. (2006). Reduced hypothalamic gray matter in narcolepsy with cataplexy. Neuro Endocrinol Lett 27 (6): 769–772. Buysse DJ, Tu XM, Cherry CR et al. (1999). Pretreatment REM sleep and subjective sleep quality distinguish depressed psychotherapy remitters and nonremitters. Biol Psychiatry 45 (2): 205–213. Buzsaki G (1998). Memory consolidation during sleep: a neurophysiological perspective. J Sleep Res 7 (Suppl 1): 17–23. Calvo JM, Badillo S, Morales-Ramirez M et al. (1987). The role of the temporal lobe amygdala in ponto-geniculooccipital activity and sleep organization in cats. Brain Res 403 (1): 22–30. Calvo JM, Simon-Arceo K, Fernandez-Mas R et al. (1996). Prolonged enhancement of REM sleep produced by carbachol microinjection into the amygdala. Neuroreport 7 (2): 577–580. Caples SM, Gami AS, Somers VK et al. (2005). Obstructive sleep apnea. Ann Intern Med 142 (3): 187–197. Chabas D, Habert MO, Maksud P et al. (2007). Functional imaging of cataplexy during status cataplecticus. Sleep 30 (2): 153–156. Chee MW, Chuah LY (2008). Functional neuroimaging insights into how sleep and sleep deprivation affect memory and cognition. Curr Opin Neurol 21 (4): 417–423. Cheshire K, Engleman H, Deary I et al. (1992). Factors impairing daytime performance in patients with sleep apnea/ hypopnea syndrome. Arch Intern Med 152 (3): 538–541. Clark LA, Watson D (1991). Tripartite model of anxiety and depression: psychometric evidence and taxonomic implications. J Abnorm Psychol 100 (3): 316–336. Clark CP, Frank LR, Brown GG et al. (2001). Sleep deprivation, EEG, and functional MRI in depression: preliminary results. Neuropsychopharmacology 25 (5 Suppl): S79–S84. Connor JR, Boyer PJ, Menzies SL et al. (2003). Neuropathological examination suggests impaired brain iron acquisition in restless legs syndrome. Neurology 61 (3): 304–309. Czisch M, Wetter TC, Kaufmann C et al. (2002). Altered processing of acoustic stimuli during sleep: reduced auditory activation and visual deactivation detected by a combined fMRI/EEG study. Neuroimage 16 (1): 251–258. Czisch M, Wehrle R, Kaufmann C et al. (2004). Functional MRI during sleep: BOLD signal decreases and their electrophysiological correlates. Eur J Neurosci 20 (2): 566–574. Dang-Vu TT, Desseilles M, Albouy G et al. (2005). Dreaming: a neuroimaging view. Swiss Archives of Neurology and Psychiatry 156 (8): 415–425. Dang-Vu TT, Schabus M, Desseilles M et al. (2008). Spontaneous neural activity during human slow wave sleep: an EEG/fMRI study. Proc Natl Acad Sci U S A 105: 15160–15165.
89
Datta S, Siwek DF, Patterson EH et al. (1998). Localization of pontine PGO wave generation sites and their anatomical projections in the rat. Synapse 30 (4): 409–423. Draganski B, Geisler P, Hajak G et al. (2002). Hypothalamic gray matter changes in narcoleptic patients. Nat Med 8 (11): 1186–1188. Drevets WC (2000). Neuroimaging studies of mood disorders. Biol Psychiatry 48 (8): 813–829. Drevets WC (2001). Neuroimaging and neuropathological studies of depression: implications for the cognitiveemotional features of mood disorders. Curr Opin Neurobiol 11 (2): 240–249. Drouot X, Moutereau S, Nguyen JP et al. (2003). Low levels of ventricular CSF orexin/hypocretin in advanced PD. Neurology 61 (4): 540–543. Earley CJBBP, Horska A, Allen RP et al. (2006). MRIdetermined regional brain iron concentrations in earlyand late-onset restless legs syndrome. Sleep Med 7 (5): 458–461. Earley CJ, Ponnuru P, Wang X et al. (2008). Altered iron metabolism in lymphocytes from subjects with restless legs syndrome. Sleep 31 (6): 847–852. Ebert D, Feistel H, Barocka A et al. (1991). Effects of sleep deprivation on the limbic system and the frontal lobes in affective disorders: a study with Tc-99m-HMPAO SPECT. Psychiatry Res 40 (4): 247–251. Ebert D, Feistel H, Barocka A et al. (1994a). Single photon emission computerized tomography assessment of cerebral dopamine D2 receptor blockade in depression before and after sleep deprivation–preliminary results. Biol Psychiatry 35 (11): 880–885. Ebert D, Feistel H, Kaschka W et al. (1994b). Increased limbic blood flow and total sleep deprivation in major depression with melancholia. Psychiatry Res 55 (2): 101–109. Eisensehr I, Linke R, Noachtar S et al. (2000). Reduced striatal dopamine transporters in idiopathic rapid eye movement sleep behaviour disorder. Comparison with Parkinson’s disease and controls. Brain 123 (Pt 6): 1155–1160. Eisensehr I, Linke R, Tatsch K et al. (2003a). Alteration of the striatal dopaminergic system in human narcolepsy. Neurology 60 (11): 1817–1819. Eisensehr I, Linke R, Tatsch K et al. (2003b). Increased muscle activity during rapid eye movement sleep correlates with decrease of striatal presynaptic dopamine transporters. IPT and IBZM SPECT imaging in subclinical and clinically manifest idiopathic REM sleep behavior disorder, Parkinson’s disease, and controls. Sleep 26 (5): 507–512. Ellis CM, Simmons A, Lemmens G et al. (1998). Proton spectroscopy in the narcoleptic syndrome. Is there evidence of a brainstem lesion? Neurology 50 (2 Suppl 1): S23–S26. Ellis CM, Monk C, Simmons A et al. (1999). Functional magnetic resonance imaging neuroactivation studies in normal subjects and subjects with the narcoleptic syndrome. Actions of modafinil. J Sleep Res 8 (2): 85–93. Engleman HM, Martin SE, Deary IJ et al. (1997). Effect of CPAP therapy on daytime function in patients with
90
M. DESSEILLES ET AL.
mild sleep apnoea/hypopnoea syndrome. Thorax 52 (2): 114–119. Etgen T, Draganski B, Ilg C et al. (2005). Bilateral thalamic gray matter changes in patients with restless legs syndrome. Neuroimage 24 (4): 1242–1247. Fantini ML, Ferini-Strambi L, Montplaisir J et al. (2005). Idiopathic REM sleep behavior disorder: toward a better nosologic definition. Neurology 64 (5): 780–786. Feuerstein C, Naegele B, Pepin JL et al. (1997). Frontal loberelated cognitive functions in patients with sleep apnea syndrome before and after treatment. Acta Neurol Belg 97 (2): 96–107. Ficker JH, Feistel H, Moller C et al. (1997). Changes in regional CNS perfusion in obstructive sleep apnea syndrome: initial SPECT studies with injected nocturnal 99mtc-HMPAO]. Pneumologie 51 (9): 926–930. Findley LJ, Barth JT, Powers DC et al. (1986). Cognitive impairment in patients with obstructive sleep apnea and associated hypoxemia. Chest 90 (5): 686–690. Findley L, Unverzagt M, Guchu R et al. (1995). Vigilance and automobile accidents in patients with sleep apnea or narcolepsy. Chest 108 (3): 619–624. Finelli LA, Borbely AA, Achermann P et al. (2001). Functional topography of the human nonrem sleep electroencephalogram. Eur J Neurosci 13 (12): 2282–2290. Gagnon JF, Bedard MA, Fantini ML et al. (2002). REM sleep behavior disorder and REM sleep without atonia in Parkinson’s disease. Neurology 59 (4): 585–589. Gagnon JF, Fantini ML, Bedard MA et al. (2004). Association between waking EEG slowing and REM sleep behavior disorder in PD without dementia. Neurology 62 (3): 401–406. Gale SD, Hopkins RO (2004). Effects of hypoxia on the brain: neuroimaging and neuropsychological findings following carbon monoxide poisoning and obstructive sleep apnea. J Int Neuropsychol Soc 10 (1): 60–71. George CF, Boudreau AC, Smiley A et al. (1996). Simulated driving performance in patients with obstructive sleep apnea. Am J Respir Crit Care Med 154 (1): 175–181. Germain A, Buysse DJ, Wood A et al. (2004a). Functional neuroanatomical correlates of eye movements during rapid eye movement sleep in depressed patients. Psychiatry Res 130 (3): 259–268. Germain A, Nofzinger EA, Kupfer DJ et al. (2004b). Neurobiology of non-REM sleep in depression: further evidence for hypofrontality and thalamic dysregulation. Am J Psychiatry 161 (10): 1856–1863. Gilman S, Koeppe RA, Chervin RD et al. (2003). REM sleep behavior disorder is related to striatal monoaminergic deficit in MSA. Neurology 61 (1): 29–34. Greenberg GD, Watson RK, Deptula D et al. (1987). Neuropsychological dysfunction in sleep apnea. Sleep 10 (3): 254–262. Halbower AC, Degaonkar M, Barker PB et al. (2006). Childhood obstructive sleep apnea associates with neuropsychological deficits and neuronal brain injury. PLoS Med 3 (8): e301. Happe S, Pirker W, Klosch G et al. (2003). Periodic leg movements in patients with Parkinson’s disease are
associated with reduced striatal dopamine transporter binding. J Neurol 250 (1): 83–86. Harper RM, Macey PM, Henderson LA et al. (2003). fMRI responses to cold pressor challenges in control and obstructive sleep apnea subjects. J Appl Physiol 94 (4): 1583–1595. Harrison Y, Horne JA (1998). Sleep loss impairs short and novel language tasks having a prefrontal focus. J Sleep Res 7 (2): 95–100. Harrison Y, Horne JA (1999). One night of sleep loss impairs innovative thinking and flexible decision making. Organ Behav Hum Decis Process 78 (2): 128–145. Harrison Y, Horne JA, Rothwell A et al. (2000). Prefrontal neuropsychological effects of sleep deprivation in young adults – a model for healthy aging? Sleep 23 (8): 1067–1073. Hashimoto K, Ono T, Honda E et al. (2006). Effects of mandibular advancement on brain activation during inspiratory loading in healthy subjects: a functional magnetic resonance imaging study. J Appl Physiol 100 (2): 579–586. Henderson LA, Woo MA, Macey PM et al. (2003). Neural responses during Valsalva maneuvers in obstructive sleep apnea syndrome. J Appl Physiol 94 (3): 1063–1074. Ho AP, Gillin JC, Buchsbaum MS et al. (1996). Brain glucose metabolism during non-rapid eye movement sleep in major depression. A positron emission tomography study. Arch Gen Psychiatry 53 (7): 645–652. Hobson JA (1964). [The phasic electrical activity of the cortex and thalamus during desychonized sleep in cats.]. C R Seances Soc Biol Fil 158: 2131–2135. Hofle N, Paus T, Reutens D et al. (1997). Regional cerebral blood flow changes as a function of delta and spindle activity during slow wave sleep in humans. J Neurosci 17 (12): 4800–4808. Hong SB, Tae WS, Joo EY et al. (2006). Cerebral perfusion changes during cataplexy in narcolepsy patients. Neurology 66 (11): 1747–1749. Horne JA (1988). Sleep loss and “divergent” thinking ability. Sleep 11 (6): 528–536. Horne JA (1993). Human sleep, sleep loss and behaviour. Implications for the prefrontal cortex and psychiatric disorder. Br J Psychiatry 162: 413–419. Hornyak M, Ahrendts JC, Spiegelhalder K et al. (2007). Voxel-based morphometry in unmedicated patients with restless legs syndrome. Sleep Med 9 (1): 22–26. Howard RJ, Ellis C, Bullmore ET et al. (1996). Functional echoplanar brain imaging correlates of amphetamine administration to normal subjects and subjects with the narcoleptic syndrome. Magn Reson Imaging 14 (9): 1013–1016. Hublin C, Launes J, Nikkinen P et al. (1994). Dopamine D2receptors in human narcolepsy: a SPECT study with 123I-IBZM. Acta Neurol Scand 90 (3): 186–189. Inoue S, Saha U, Musha T et al. (1999). Spatio-temporal distribution of neuronal activities and REM sleep. In: B Mallick, S Inoue (Eds.), Rapid Eye Movement Sleep. Narosa Publishing House, New Delhi, pp. 214–230. Ioannides AA, Corsi-Cabrera M, Fenwick PB et al. (2004). MEG tomography of human cortex and brainstem
FUNCTIONAL NEUROIMAGING IN SLEEP, SLEEP DEPRIVATION, AND SLEEP DISORDERS activity in waking and REM sleep saccades. Cereb Cortex 14 (1): 56–72. Iranzo A, Santamaria J, Pujol J et al. (2002). Brainstem proton magnetic resonance spectroscopy in idopathic REM sleep behavior disorder. Sleep 25 (8): 867–870. Joiner TE Jr, Steer RA, Beck AT et al. (1999). Physiological hyperarousal: construct validity of a central aspect of the tripartite model of depression and anxiety. J Abnorm Psychol 108 (2): 290–298. Jones BE (1991). Paradoxical sleep and its chemical/ structural substrates in the brain. Neuroscience 40 (3): 637–656. Joo EY, Tae WS, Kim JH et al. (2004). Glucose hypometabolism of hypothalamus and thalamus in narcolepsy. Ann Neurol 56 (3): 437–440. Joo EY, Tae WS, Kim JH et al. (2008). Cerebral blood flow changes in man by wake-promoting drug, modafinil: a randomized double blind study. J Sleep Res 17 (1): 82–88. Jouvet M (1967). Neurophysiology of the states of sleep. Physiol Rev 47 (2): 117–177. Kajimura N, Uchiyama M, Takayama Y et al. (1999). Activity of midbrain reticular formation and neocortex during the progression of human non-rapid eye movement sleep. J Neurosci 19 (22): 10065–10073. Kamba M, Suto Y, Ohta Y et al. (1997). Cerebral metabolism in sleep apnea. Evaluation by magnetic resonance spectroscopy. Am J Respir Crit Care Med 156 (1): 296–298. Kaufmann C, Schuld A, Pollmacher T et al. (2002). Reduced cortical gray matter in narcolepsy: preliminary findings with voxel-based morphometry. Neurology 58 (12): 1852–1855. Khan N, Antonini A, Parkes D et al. (1994). Striatal dopamine D2 receptors in patients with narcolepsy measured with PET and 11C-raclopride. Neurology 44 (11): 2102–2104. Kim SJ, Lyoo IK, Lee YS (2008). Increased GABA levels in medial prefrontal cortex of young adults with narcolepsy. Sleep 31 (3): 342–347. Kish SJ, Mamelak M, Slimovitch C et al. (1992). Brain neurotransmitter changes in human narcolepsy. Neurology 42 (1): 229–234. Kjaer TW, Law I, Wiltschiotz G et al. (2002). Regional cerebral blood flow during light sleep-a H(2)(15)O-PET study. J Sleep Res 11 (3): 201–207. Kotterba S, Rasche K, Widdig W et al. (1998). Neuropsychological investigations and event-related potentials in obstructive sleep apnea syndrome before and during CPAP-therapy. J Neurol Sci 159 (1): 45–50. Kryger MH, Roth T, Dement WC et al. (2000). Principles and Practice of Sleep Medicine. 3rd edn. W.B. Saunders, Philadelphia. Lenzi P, Zoccoli G, Walker AM et al. (1999). Cerebral blood flow regulation in REM sleep: a model for flow-metabolism coupling. Arch Ital Biol 137 (2–3): 165–179. Lesage S, Hening WA (2004). The restless legs syndrome and periodic limb movement disorder: a review of management. Semin Neurol 24 (3): 249–259. Lin L, Faraco J, Li R et al. (1999). The sleep disorder canine narcolepsy is caused by a mutation in the hypocretin (orexin) receptor 2 gene. Cell 98 (3): 365–376.
91
Lodi R, Tonon C, Vignatelli L et al. (2004). In vivo evidence of neuronal loss in the hypothalamus of narcoleptic patients. Neurology 63 (8): 1513–1515. McCarley RW, Winkelman JW, Duffy FH et al. (1983). Human cerebral potentials associated with REM sleep rapid eye movements: links to PGO waves and waking potentials. Brain Res 274 (2): 359–364. Macey KE, Macey PM, Woo MA et al. (2006). Inspiratory loading elicits aberrant fMRI signal changes in obstructive sleep apnea. Respir Physiol Neurobiol 151 (1): 44–60. Macey PM, Henderson LA, Macey KE et al. (2002). Brain morphology associated with obstructive sleep apnea. Am J Respir Crit Care Med 166 (10): 1382–1387. Macey PM, Macey KE, Henderson LA et al. (2003). Functional magnetic resonance imaging responses to expiratory loading in obstructive sleep apnea. Respir Physiol Neurobiol 138 (2–3): 275–290. MacFarlane JG, List SJ, Moldofsky H et al. (1997). Dopamine D2 receptors quantified in vivo in human narcolepsy. Biol Psychiatry 41 (3): 305–310. Madsen PL, Schmidt JF, Wildschiodtz G et al. (1991a). Cerebral oxygen metabolism and cerebral blood flow in man during light sleep (stage 2). Brain Res 557 (1–2): 217–220. Madsen PL, Schmidt JF, Holm S et al. (1991b). Cerebral O2 metabolism and cerebral blood flow in humans during deep and rapid-eye-movement sleep. J Appl Physiol 70 (6): 2597–2601. Maquet P (2000). Functional neuroimaging of normal human sleep by positron emission tomography. J Sleep Res 9 (3): 207–231. Maquet P, Phillips C (1998). Functional brain imaging of human sleep. J Sleep Res 7 (Suppl 1): 42–47. Maquet P, Dive D, Salmon E et al. (1990). Cerebral glucose utilization during sleep-wake cycle in man determined by positron emission tomography and [18F]2-fluoro-2-deoxyD-glucose method. Brain Res 513 (1): 136–143. Maquet P, Dive D, Salmon E et al. (1992). Cerebral glucose utilization during stage 2 sleep in man. Brain Res 571 (1): 149–153. Maquet P, Peters J, Aerts J et al. (1996). Functional neuroanatomy of human rapid-eye-movement sleep and dreaming. Nature 383 (6596): 163–166. Maquet P, Degueldre C, Delfiore G et al. (1997). Functional neuroanatomy of human slow wave sleep. J Neurosci 17 (8): 2807–2812. Maquet P, Smith C, Stickgold R et al. (2003). Sleep and Brain Plasticity. Oxford University Press, Oxford. Maquet P, Ruby P, Maudoux A et al. (2005). Human cognition during REM sleep and the activity profile within frontal and parietal cortices. A reappraisal of functional neuroimaging data. Prog Brain Res 150: 219–227. Mateika JH, Ellythy M (2003). Chemoreflex control of ventilation is altered during wakefulness in humans with OSA. Respir Physiol Neurobiol 138 (1): 45–57. Mayberg HS (1997). Limbic-cortical dysregulation: a proposed model of depression. J Neuropsychiatry Clin Neurosci 9 (3): 471–481.
92
M. DESSEILLES ET AL.
Mazza S, Soucy JP, Gravel P et al. (2006). Assessing whole brain perfusion changes in patients with REM sleep behavior disorder. Neurology 67 (9): 1618–1622. Meyer JS, Sakai F, Karacan I et al. (1980). Sleep apnea, narcolepsy, and dreaming: regional cerebral hemodynamics. Ann Neurol 7 (5): 479–485. Meyer JS, Ishikawa Y, Hata T et al. (1987). Cerebral blood flow in normal and abnormal sleep and dreaming. Brain Cogn 6 (3): 266–294. Michaud M, Soucy JP, Chabli A et al. (2002). SPECT imaging of striatal pre- and postsynaptic dopaminergic status in restless legs syndrome with periodic leg movements in sleep. J Neurol 249 (2): 164–170. Mignot E, Lammers GJ, Ripley B et al. (2002). The role of cerebrospinal fluid hypocretin measurement in the diagnosis of narcolepsy and other hypersomnias. Arch Neurol 59 (10): 1553–1562. Mikiten T, Niebyl P, Hendley C et al. (1961). EEG desynchronization during behavioural sleep associated with spike discharges from the thalamus of the cat. Fed Proc (20): 327. Milak MS, Parsey RV, Keilp J (2005). Neuroanatomic correlates of psychopathologic components of major depressive disorder. Arch Gen Psychiatry 62 (4): 397–408. Miyamoto M, Miyamoto T, Kubo J et al. (2000). Brainstem function in rapid eye movement sleep behavior disorder: the evaluation of brainstem function by proton MR spectroscopy (1H-MRS). Psychiatry Clin Neurosci 54 (3): 350–351. Montplaisir J, Lorrain D, Godbout R et al. (1991). Restless legs syndrome and periodic leg movements in sleep: the primary role of dopaminergic mechanism. Eur Neurol 31 (1): 41–43. Montplaisir J, Lapierre O, Lavigne G et al. (1994). [Movement disorders during sleep: attempt at classification.] Neurophysiol Clin 24 (2): 155–159. Montplaisir J, Denesle R, Petit D et al. (2000). Pramipexole in the treatment of restless legs syndrome: a follow-up study. Eur J Neurol 7 (Suppl 1): 27–31. Morrell MJ, McRobbie DW, Quest RA et al. (2003). Changes in brain morphology associated with obstructive sleep apnea. Sleep Med 4 (5): 451–454. Mouret J, Jeannerod M, Jouvet M et al. (1963). [Electrical activity of the visual system during the paradoxical phase of sleep in the cat.] J Physiol (Paris) 55: 305–306. Naegele B, Thouvard V, Pepin JL et al. (1995). Deficits of cognitive executive functions in patients with sleep apnea syndrome. Sleep 18 (1): 43–52. Naegele B, Pepin JL, Levy P et al. (1998). Cognitive executive dysfunction in patients with obstructive sleep apnea syndrome (OSAS) after CPAP treatment. Sleep 21 (4): 392–397. Nofzinger EA, Mintun MA, Wiseman M et al. (1997). Forebrain activation in REM sleep: an FDG PET study. Brain Res 770 (1–2): 192–201. Nofzinger EA, Nichols TE, Meltzer CC et al. (1999). Changes in forebrain function from waking to REM sleep in depression: preliminary analyses of [18F]FDG PET studies. Psychiatry Res 91 (2): 59–78.
Nofzinger EA, Price JC, Meltzer CC et al. (2000). Towards a neurobiology of dysfunctional arousal in depression: the relationship between beta EEG power and regional cerebral glucose metabolism during NREM sleep. Psychiatry Res 98 (2): 71–91. Nofzinger EA, Berman S, Fasiczka A et al. (2001). Effects of bupropion SR on anterior paralimbic function during waking and REM sleep in depression: preliminary findings using. Psychiatry Res 106 (2): 95–111. Nofzinger EA, Buysse DJ, Miewald JM et al. (2002). Human regional cerebral glucose metabolism during non-rapid eye movement sleep in relation to waking. Brain 125 (Pt 5): 1105–1115. Nofzinger EA, Buysse DJ, Germain A et al. (2004a). Functional neuroimaging evidence for hyperarousal in insomnia. Am J Psychiatry 161 (11): 2126–2128. Nofzinger EA, Buysse DJ, Germain A et al. (2004b). Increased activation of anterior paralimbic and executive cortex from waking to rapid eye movement sleep in depression. Arch Gen Psychiatry 61 (7): 695–702. Nose I, Ookawa T, Tanaka J et al. (2002). Decreased blood flow of the left thalamus during somnolent episodes in a case of recurrent hypersomnia. Psychiatry Clin Neurosci 56 (3): 277–278. O’Donoghue FJ, Briellmann RS, Rochford PD et al. (2005). Cerebral structural changes in severe obstructive sleep apnea. Am J Respir Crit Care Med 171 (10): 1185–1190. Overeem S, Steens SC, Good CD et al. (2003). Voxel-based morphometry in hypocretin-deficient narcolepsy. Sleep 26 (1): 44–46. Peigneux P, Laureys S, Fuchs S et al. (2001). Generation of rapid eye movements during paradoxical sleep in humans. Neuroimage 14 (3): 701–708. Perlis ML, Smith MT, Andrews PJ et al. (2001). Beta/gamma EEG activity in patients with primary and secondary insomnia and good sleeper controls. Sleep 24 (1): 110–117. Peyron C, Faraco J, Rogers W et al. (2000). A mutation in a case of early onset narcolepsy and a generalized absence of hypocretin peptides in human narcoleptic brains. Nat Med 6 (9): 991–997. Pilcher JJ, Huffcutt AI (1996). Effects of sleep deprivation on performance: a meta-analysis. Sleep 19 (4): 318–326. Plazzi G, Corsini R, Provini F et al. (1997). REM sleep behavior disorders in multiple system atrophy. Neurology 48 (4): 1094–1097. Portas CM, Krakow K, Allen P et al. (2000). Auditory processing across the sleep–wake cycle: simultaneous EEG and fMRI monitoring in humans. Neuron 28 (3): 991–999. Reiss AL, Hoeft F, Tenforde AS et al. (2008). Anomalous hypothalamic responses to humor in cataplexy. PLoS ONE 3 (5): e2225. Rinne JO, Hublin C, Partinen M et al. (1995). Positron emission tomography study of human narcolepsy: no increase in striatal dopamine D2 receptors. Neurology 45 (9): 1735–1738. Rinne JO, Hublin C, Partinen M et al. (1996). Striatal dopamine D1 receptors in narcolepsy: a PET study with [11C] NNC 756. J Sleep Res 5 (4): 262–264.
FUNCTIONAL NEUROIMAGING IN SLEEP, SLEEP DEPRIVATION, AND SLEEP DISORDERS Sakai K, Sastre JP, Karacan I et al. (1979). Tegmentoreticular projections with special reference to the muscular atonia during paradoxical sleep in the cat: an HRP study. Brain Res 176 (2): 233–254. Sakurai T (2005). Roles of orexin/hypocretin in regulation of sleep/wakefulness and energy homeostasis. Sleep Med Rev 9 (4): 231–241. Salzarulo P, Lairy GC, Bancaud J et al. (1975). Direct depth recording of the striate cortex during REM sleep in man: are there PGO potentials? Electroencephalogr Clin Neurophysiol 38 (2): 199–202. Saper CB, Chou TC, Scammell TE et al. (2001). The sleep switch: hypothalamic control of sleep and wakefulness. Trends Neurosci 24 (12): 726–731. Sastre JP, Buda C, Lin JS et al. (2000). Differential c-fos expression in the rhinencephalon and striatum after enhanced sleep–wake states in the cat. Eur J Neurosci 12 (4): 1397–1410. Schabus M, Dang-Vu TT, Albouy G et al. (2007). Hemodynamic cerebral correlates of sleep spindles during human non-rapid eye movement sleep. Proc Natl Acad Sci U S A 104 (32): 13164–13169. Schenck CH, Bundlie SR, Ettinger MG et al. (1986). Chronic behavioral disorders of human REM sleep: a new category of parasomnia. Sleep 9 (2): 293–308. Schenck CH, Bundlie SR, Mahowald MW et al. (1996). Delayed emergence of a parkinsonian disorder in 38% of 29 older men initially diagnosed with idiopathic rapid eye movement sleep behaviour disorder. Neurology 46 (2): 388–393. Schroder CM, O’Hara R (2005). Depression and obstructive sleep apnea (OSA). Ann Gen Psychiatry 4: 13. Schwartz S, Ponz A, Poryazova R et al. (2008). Abnormal activity in hypothalamus and amygdala during humour processing in human narcolepsy with cataplexy. Brain 131: 514–522. Shirakawa S, Takeuchi N, Uchimura N et al. (2002). Study of image findings in rapid eye movement sleep behavioural disorder. Psychiatry Clin Neurosci 56 (3): 291–292. Smith GS, Reynolds CF 3rd, Pollock B et al. (1999). Cerebral glucose metabolic response to combined total sleep deprivation and antidepressant treatment in geriatric depression. Am J Psychiatry 156 (5): 683–689. Smith MT, Perlis ML, Chengazi VU et al. (2002). Neuroimaging of NREM sleep in primary insomnia: a Tc-99HMPAO single photon emission computed tomography study. Sleep 25 (3): 325–335. Smith MT, Perlis ML, Chengazi VU et al. (2005). NREM sleep cerebral blood flow before and after behavior therapy for chronic primary insomnia: preliminary single photon emission computed tomography (SPECT) data. Sleep Med 6 (1): 93–94. Spiegel K, Tasali E, Penev P et al. (2004). Brief communication: sleep curtailment in healthy young men is associated with decreased leptin levels, elevated ghrelin levels, and increased hunger and appetite. Ann Intern Med 141 (11): 846–850.
93
Staedt J, Stoppe G, Kogler A et al. (1993). Dopamine D2 receptor alteration in patients with periodic movements in sleep (nocturnal myoclonus). J Neural Transm Gen Sect 93 (1): 71–74. Staedt J, Stoppe G, Kogler A et al. (1995a). Nocturnal myoclonus syndrome (periodic movements in sleep) related to central dopamine D2-receptor alteration. Eur Arch Psychiatry Clin Neurosci 245 (1): 8–10. Staedt J, Stoppe G, Kogler A et al. (1995b). Single photon emission tomography (SPET) imaging of dopamine D2 receptors in the course of dopamine replacement therapy in patients with nocturnal myoclonus syndrome (NMS). J Neural Transm Gen Sect 99 (1–3): 187–193. Staedt J, Stoppe G, Kogler A et al. (1996). [123I]IBZM SPET analysis of dopamine D2 receptor occupancy in narcoleptic patients in the course of treatment. Biol Psychiatry 39 (2): 107–111. Stepanski E, Zorick F, Roehrs T et al. (1988). Daytime alertness in patients with chronic insomnia compared with asymptomatic control subjects. Sleep 11 (1): 54–60. Steriade M, Amzica F (1998). Coalescence of sleep rhythms and their chronology in corticothalamic networks. Sleep Res Online 1 (1): 1–10. Steriade M, McCarley RW (1990). Brainstem Control of Wakefulness and Sleep. Plenum Press, New York. Steriade M, Timofeev I (2003). Neuronal plasticity in thalamocortical networks during sleep and waking oscillations. Neuron 37 (4): 563–576. Steriade M, Nunez A, Amzica F et al. (1993). Intracellular analysis of relations between the slow (< 1 Hz) neocortical oscillation and other sleep rhythms of the electroencephalogram. J Neurosci 13 (8): 3266–3283. Stickgold R, Walker MP (2007). Sleep-dependent memory consolidation and reconsolidation. Sleep Med 8 (4): 331–343. Sudo Y, Suhara T, Honda Y et al. (1998). Muscarinic cholinergic receptors in human narcolepsy: a PET study. Neurology 51 (5): 1297–1302. Szuba MP, Baxter LR Jr, Fairbanks LA et al. (1991). Effects of partial sleep deprivation on the diurnal variation of mood and motor activity in major depression. Biol Psychiatry 30 (8): 817–829. Tan EK, Ondo W (2000). Restless legs syndrome: clinical features and treatment. Am J Med Sci 319 (6): 397–403. Tasali E, Van Cauter E (2002). Sleep-disordered breathing and the current epidemic of obesity: consequence or contributing factor? Am J Respir Crit Care Med 165 (5): 562–563. Thannickal TC, Siegel JM, Nienhuis R et al. (2003). Pattern of hypocretin (orexin) soma and axon loss, and gliosis, in human narcolepsy. Brain Pathol 13 (3): 340–351. Thase ME (1998). Depression, sleep, and antidepressants. J Clin Psychiatry 59 (Suppl 4): 55–65. Thase ME, Buysse DJ, Frank E et al. (1997). Which depressed patients will respond to interpersonal psychotherapy? The role of abnormal EEG sleep profiles. Am J Psychiatry 154 (4): 502–509.
94
M. DESSEILLES ET AL.
Tonon C, Vetrugno R, Lodi R et al. (2007). Proton magnetic resonance spectroscopy study of brain metabolism in obstructive sleep apnoea syndrome before and after continuous positive airway pressure treatment. Sleep 30 (3): 305–311. Trenkwalder C (1998). Sleep dysfunction in Parkinson’s disease. Clin Neurosci 5 (2): 107–114. Tribl GG, Asenbaum S, Happe S et al. (2004). Normal striatal D2 receptor binding in idiopathic restless legs syndrome with periodic leg movements in sleep. Nucl Med Commun 25 (1): 55–60. Unrath A, Juengling FD, Schork M (2007). Cortical grey matter alterations in idiopathic restless legs syndrome: an optimized voxel-based morphometry study. Mov Disord 22 (12): 1751–1756. Unrath A, Muller HP, Ludolph AC et al. (2008). Cerebral white matter alterations in idiopathic restless legs syndrome, as measured by diffusion tensor imaging. Mov Disord 23 (9): 1250–1255. Watanabe S, Sakai K, Ono Y et al. (1987). Alternating periodic leg movement induced by spinal anesthesia in an elderly male. Anesth Analg 66 (10): 1031–1032. Wehrle R, Czisch M, Kaufmann C et al. (2005). Rapid eye movement-related brain activation in human sleep: a functional magnetic resonance imaging study. Neuroreport 16 (8): 853–857. Wetter TC, Pollmacher T (1997). Restless legs and periodic leg movements in sleep syndromes. J Neurol 244 (4 Suppl 1): S37–S45.
Wirz-Justice A, Van den Hoofdakker RH (1999). Sleep deprivation in depression: what do we know, where do we go? Biol Psychiatry 46 (4): 445–453. Wu JC, Gillin JC, Buchsbaum MS et al. (1992). Effect of sleep deprivation on brain metabolism of depressed patients. Am J Psychiatry 149 (4): 538–543. Wu J, Buchsbaum MS, Gillin JC et al. (1999). Prediction of antidepressant effects of sleep deprivation by metabolic rates in the ventral anterior cingulate and medial prefrontal cortex. Am J Psychiatry 156 (8): 1149–1158. Wu JC, Gillin JC, Buchsbaum MS et al. (2008). Sleep deprivation PET correlations of Hamilton symptom improvement ratings with changes in relative glucose metabolism in patients with depression. J Affect Disord 107 (1–3): 181–186. Yeon Joo E, Hong SB, Tae WS et al. (2005). Cerebral perfusion abnormality in narcolepsy with cataplexy. Neuroimage 28: 410–416. Young T, Blustein J, Finn L et al. (1997). Sleep-disordered breathing and motor vehicle accidents in a populationbased sample of employed adults. Sleep 20 (8): 608–613. Young T, Peppard PE, Gottlieb DJ et al. (2002). Epidemiology of obstructive sleep apnea: a population health perspective. Am J Respir Crit Care Med 165 (9): 1217–1239.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 7
The phylogeny of sleep KRISTYNA M. HARTSE * Sonno Sleep Center, El Paso, TX, USA
INTRODUCTION Why do we sleep? Despite a voluminous body of scientific and clinical literature, the definitive answer to this fundamental question has yet to be found. To the insomnia patient with unrelenting chronic sleeplessness, the answer is painfully and viscerally obvious. Sleep prevents feelings of sleepiness and dysphoria during the day. To the scientist and clinician, however, this answer, although responsive to the universally acknowledged effects of sleep loss, does not address the specific biological or functional reasons for sleep (Rechtschaffen, 1998). All mammals and birds studied to date exhibit unambiguous signs of sleep. Furthermore, an array of specific human sleep disorders, including sleep apnea, narcolepsy, periodic limb movements, restless legs, and insomnia, correlate with deficits in health and well-being. These consequences of disturbed sleep in conjunction with the universality of sleep in mammalian organisms imply that sleep serves an important life-enhancing or even life-sustaining function. Correlations, however, do not prove causality. Whether the function of sleep can be discovered by studying human sleep disorders or more generally by studying neurologically and biochemically complex mammalian species is questionable. A different approach to discovering the origins and functions of sleep would be through the study of nonmammalian organisms which have remained relatively unchanged from their ancient fossil ancestors and which may provide clues about the origins of sleep. The presence of behavioral and electrophysiological signs of sleep in living mammals and birds suggests that sleep has been perpetuated in evolution from ancient origins. A behavior such as sleep, of course, does not leave a fossil record, which severely limits
*
the extent to which definitive statements can be made about the origin of sleep. However, by studying living, phylogenetically ancient organisms such as insects, fish, amphibians, reptiles, and primitive mammals, clues to the function of sleep might be revealed. This phylogenetic approach to investigating the origins of sleep has not been without controversy, and there is disagreement in the literature about the presence or absence of sleep in nonmammals. There is general agreement that most nonmammalian organisms exhibit behavioral sleep or rest. However, the electrophysiological signs of sleep in nonmammalian organisms may be very different from that of mammals. This observation has led some authors to conclude that, by definition, nonmammalian species do not sleep because mammalian electrophysiological correlates of sleep are not present (Walker and Berger, 1973). These issues will be reviewed as we examine evidence for the origins of sleep.
THE DEFINITION OF SLEEP Sleep is defined by both behavioral and electrophysiological criteria. The well-established behavioral criteria include: (1) a species-specific posture; (2) behavioral quiescence; (3) elevated arousal thresholds; and (4) rapid state reversibility with moderately intense stimulation to distinguish sleep from hypothermia, torpor, or coma (Flanigan et al., 1974). Sleep homeostasis, the compensatory rebound in sleep after deprivation of quiescent states, is an additional feature in the definition of sleep (Tobler, 2005). In mammals and birds, there are distinctive electrophysiological correlates that accompany behavioral sleep. As a result of the close relationship between behavior and electrophysiology, electrophysiological correlates are almost universally substituted for behavioral observation to define the
Correspondence to: Kristyna M. Hartse, Ph.D., Clinical Director, Sonno Sleep Center, 1400 George Dieter, Suite 210, El Paso TX 79936, USA. Tel: 915-533-8499, E-mail:
[email protected]
98
K.M. HARTSE
presence of sleep. Slow-wave sleep (SWS) is marked by high-amplitude neocortical slow waves. Cyclically alternating with SWS is rapid eye movement (REM) sleep (also called paradoxical sleep), characterized by lowvoltage brain activity similar to that of waking, skeletal muscle inhibition, and REMs. Although the distribution and amounts of non-REM (NREM) and REM sleep vary widely among mammals and birds (Zeplin et al., 2005), the electrophysiology of these two states is well established except in cetaceans (whales and dolphins) and a monotreme, the echidna, a primitive egg-laying mammal (Mukhametov, 1987; Siegel et al., 1996; Lyamin et al., 2002, 2004, 2005). The electrophysiological correlates associated with nonmammalian behavioral sleep have received considerable attention. No change in brain activity during behavioral quiescence, slow waves during waking which diminish with behavioral sleep, both the presence and absence of SWS, and both the presence and absence of REM sleep have all been reported. However, some of the most rigorous studies, particularly in reptiles, have revealed the presence of a high-voltage spike which is prominent during behavioral sleep and minimally present during behavioral wakefulness (Flanigan, 1973, 1974; Flanigan et al., 1973, 1974). The spikes increase in a homeostatic response following enforced wakefulness, and both spikes in reptiles and SWS in mammals respond similarly to pharmacological agents (Hartse and Rechtschaffen, 1974, 1982). These
findings have suggested that the spikes are a nonmammalian electrophysiological correlate of SWS. Persuasive evidence for REM sleep in nonmammalian organisms is not strong. Because the appearance of the reptilian spike is substantially different from the neocortical slow waves recorded in mammals (Figure 7.1), these findings have led some investigators to conclude that the spike is not an electrophysiological marker of sleep (Walker and Berger, 1973). Further studies in the rat and cat, however, have revealed the presence of a spike recorded from the ventral hippocampus (VH) during SWS which is similar to the reptilian spikes (Metz and Rechtschaffen, 1976; Hartse et al., 1979). VH spikes and reptilian spikes have a similar morphology: they both show a rebound following enforced wakefulness, and they both respond similarly to pharmacological agents. Additional support for a relationship between hippocampal spikes and neocortical slow waves is the finding that hippocampal sharp waves are modulated by neocortical activity during SWS (Sirota et al., 2003). The generation of slow waves requires neocortical development, and slow-wave activity recorded from brain surface electrodes is easily observed in mammals that have extensive neocortical development. However, the rudimentary neocortex of fish, amphibians, and reptiles in comparison to mammals would seem to preclude on anatomical grounds the observation of slow waves in these species (Nieuwenhuys, 1994). In addition, it has recently been convincingly argued that the
CAT HIPPOCAMPUS 100 mv HIPPOCAMPUS –INTEGRATION
1s
1s
TORTOISE LIMBIC AREA 50 mv LIMBIC AREA –INTEGRATION
1s
1s
Fig. 7.1. Comparison of mammalian ventral hippocampus spikes in the cat with reptilian spikes in the tortoise. In each recording the upper tracing shows the raw, unfiltered record. The lower tracing shows the signal after it has been passed through a bandpass filter set for 30–1000 Hz, a 60-Hz notchfilter, and a Beckman 9852 integrator coupler. Both spikes are shown at slow and fast speeds. (Reprinted with permission from Hartse and Rechtschaffen, 1982.)
THE PHYLOGENY OF SLEEP presence of the mammalian neocortex per se is not necessarily the most critical element in the electrophysiological expression of slow waves, but rather it is the advanced development of palliopallial connectivity in mammals and birds which accounts for the presence of slow waves in these species (Rattenborg, 2006a). This position has also spurred debate (Rattenborg, 2007; Rial et al., 2007b). In contrast to the findings of SWS associated with mammalian and avian quiescence, some investigators have reported the presence of slow waves during reptilian waking which diminish during behavioral sleep. This observation has been interpreted as suggesting that reptilian wakefulness, and not reptilian sleep, is the precursor of mammalian SWS (De Vera et al., 1994; Rial et al., 2007a). This position, however, has not been widely adopted based upon the preponderance of evidence (Rattenborg et al., 2007). As we can see, the task of identifying sleep in nonmammalian organisms has not been a straightforward one. Besides the imposition of mammalian criteria for sleep on nonmammalian organisms, additional constraints in studying nonmammalian species include technical difficulties in evaluating organisms which inhabit unusual arboreal or aquatic environments not conducive to electrophysiological recording, an absence of stereotaxic atlases to assure comparable electrode placements between species, and a sparsity of data which establish homologous brain structures between mammals and nonmammals (Hartse, 1994). Nonetheless, even given these constraints as well as the contradictory findings of nonmammalian studies, the most general conclusion that can be made is that behavioral quiescence is a universal phenomenon in living organisms.
INVERTEBRATES In comparison to the many studies on sleep in vertebrates, the literature on sleep behavior and electrophysiology in invertebrates, organisms without backbones, is exceedingly sparse. The exception, as we shall see, is a growing body of work in insects, specifically the fruit fly, Drosophila melanogaster, which suggests that these organisms may serve as a model for studying the molecular basis for mammalian sleep (Hendricks et al., 2000b). Invertebrates which have been studied to date meet the behavioral criteria for a sleep-like state. The sea slug (Aplysia californica) exhibits periods of nocturnal behavioral quiescence and decreased motor activity (Strumwasser, 1971). In addition a rise in 5-hydroxytryptophan (5-HT) secretion in the hemolymph during the dark portion of the 24-hour cycle, corresponding to periods of decreased locomotor activity, suggests that behavioral sleep is accompanied by mammalian-like
99
neurochemical changes (Levenson et al., 1999). Using time lapse video, preliminary studies in the pond snail, Lymnaea stagnalis, have identified a resting state which is associated with reduced responsiveness to an appetitive stimulus and an increase in quiescence following rest deprivation (R. Stephenson, personal communication). Two ocean-dwelling gastropods, the cuttlefish (Sepia pharonis) and octopus (Octopus vulgaris), meet the criteria for behavioral sleep, and both exhibit rebounds in behavioral sleep following periods of enforced wakefulness (Duntley et al., 2002; Brown et al., 2006). Electrophysiological recordings from above the vertical lobe in the brain of the octopus have revealed trains of high-amplitude spikes associated with behavioral quiescence, suggesting a correspondence to the spikes observed during reptilian behavioral quiescence (Flanigan, 1973, 1974). A recent study in the crayfish (Procambarus clarkii) also documented clear signs of behavioral sleep as well as a rebound in recovery sleep following enforced wakefulness (Ramon et al., 2004; Mendoza-Angeles et al., 2007). However, in contrast to findings in the octopus, continuous fast spikes occurred during behavioral wakefulness. With the onset of distinctive quiescent postures, “continuous slow waves” in the 15–20-Hz bandwidth were observed. This frequency range is substantially higher than the 0.5–4.0-Hz frequency range typically associated with mammalian SWS. Thus, although these recent studies are in agreement about the presence of behavioral sleep, there is significant divergence in the electrophysiological findings.
INSECTS Some of the most promising clues to the function of sleep have come from a new and rapidly growing body of work on sleep in insects, specifically D. melanogaster (for a recent review, see, Hartse, 2009). In early observational studies both in the field and in the laboratory, wasps, bees, flies, butterflies, and moths were observed to exhibit state-reversible behavioral sleep associated with species-specific postures as well as increased arousal thresholds (Rau and Rau, 1916; Andersen, 1968). The honey bee (Apis mellifera) exhibits distinctive antennae and head postures correlated with behavioral sleep and waking (Figure 7.2). During behavioral sleep decreases in locomotor activity, decreases in thoracic temperature, decreases in neck muscle activity, and increases in thresholds to infrared stimuli are present (Kaiser, 1988). Following 12 hours of sleep deprivation, a significant increase in antenna immobility in sleep-deprived as compared to control bees is present in a homeostatic response to deprivation (Sauer et al., 2004). The electrophysiological
100
K.M. HARTSE
Fig. 7.2. A quiescent bee. (Courtesy of Cheryl Moorehead.)
correlates of sleep in the bee are unknown, but single cell recordings from directionally sensitive optomotor interneurons reveal a circadian rhythmicity with decreased sensitivity to a pattern stimulus at night, corresponding to times of decreased locomotor activity and behavioral sleep (Kaiser and Steiner-Kaiser, 1983). Delivery of a puff of air reversed this decreased sensitivity, indicating neuronal state reversibility. Three species of scorpion (Tobler and Stadler, 1988) as well as the cockroach (Tobler, 1983; Tobler and Neuner-Jehle, 1992) all meet the behavioral criteria for sleep. A recent study in the cockroach (Stephenson et al., 2007) has elegantly demonstrated a similarity to the results in mammals following sleep deprivation. Deprivation of cockroach behavioral quiescence led to both an increased metabolic rate without a change in body mass and increased mortality in comparison to controls. These results are remarkably similar to the findings of increased metabolic rate and increased mortality in the rat following sustained sleep deprivation (Rechtschaffen and Bergmann, 2002). The fruit fly, D. melanogaster, has been proposed as a model for the study of mammalian sleep, and the similarities between characteristics of sleep in the fruit fly and in mammalian species are striking (Hendricks et al., 2000b; Cirelli, 2006). The well-studied genetic mapping, the short life cycle which permits rapid assessment of genetic manipulations in subsequent generations, and the relative ease of maintaining large experimental colonies make the fruit fly an excellent candidate for studying the molecular and genetic aspects of sleep. Initial studies provided convincing evidence that behavioral rest in Drosophila is analogous to mammalian sleep (Hendricks et al., 2000a; Shaw et al., 2000). Similar to mammals, Drosophila exhibits increased arousal thresholds and an increase in quiescence following enforced wakefulness that is independent of the circadian clock. Behavioral wakefulness occurs in
response to the administration of caffeine, metamphetamine, and modafinil whereas behavioral quiescence is induced following antihistamine administration (Shaw et al., 2000; Hendricks et al., 2003; Andretic et al., 2005). There are age-related changes across the lifespan with increased quiescence in immature organisms and a decline in quiescence as well as a fragmentation of rest periods with age (Shaw et al., 2000; Koh et al., 2006). A decrease in spike-like local field potentials with quiescence suggests an electrophysiological correlate of behavioral sleep (Nitz et al., 2002), and chemical lesioning as well as stimulation of the mushroom bodies have identified a specific neuroanatomical locus for the control of sleep in the fly brain (Joiner et al., 2006; Pitman et al., 2006). One of the major advantages in utilizing Drosophila is its well-known genetic profile and the identification of mutant strains with specific alterations in normal patterns of quiescence (Cirelli, 2003; Kume et al., 2005). A mutation in the dopamine transporter gene has been identified in a near-sleepless mutant ( fumin) (Kume et al., 2005). Significantly increased motor activity across the light–dark cycle independent of the circadian clock, decreased arousal thresholds, and an absence of rebound in response to rest deprivation were associated with normal lifespans and an absence of obvious morphological, reproductive, or developmental abnormalities. Other mutant strains exhibiting reduced sleep amounts, however, also have decreased lifespans (Cirelli et al., 2005). These findings not only suggest an important role for dopamine in the control of sleep expression, but also that some forms of sleeplessness may have a genetic basis which is not necessarily associated with adverse consequences for survival. Recent studies of specific protein manipulations also suggest that Drosophila may provide new insights into the functional molecular basis of sleep (Foltenyi et al., 2007; Naidoo et al., 2007). In summary, quiescent states, which meet the criteria for behavioral sleep, are present in invertebrate species. The electrophysiology of invertebrate sleep is not well known, although there is evidence that distinctive electrophysiology may exist. In addition, studies in Drosophila are rapidly advancing understanding of the detailed molecular and genetic structure of sleep mechanisms that may provide fruitful clues to sleep function in mammals.
FISH AND AMPHIBIANS Behavioral sleep has been described in both fish and amphibians. Very few electrophysiological studies have been conducted in these organisms primarily as the result of significant technical problems in obtaining
THE PHYLOGENY OF SLEEP 101 reliable recordings in an aquatic environment. Several plays a major role in the regulation of mammalian species of Bermuda reef fish and freshwater fish sleep and wakefulness, and hypocretin deficits are (Peyrethon and Dusan-Peyrethon, 1967; Siegmund, 1969; now well known to be the major neurochemical defect Tauber and Weitzman, 1969; Shapiro and Hepburn, in patients with narcolepsy (for a review see Mignot, 1976; Tobler and Borbely, 1985) exhibit behavioral sleep. 2005). In contrast to narcoleptic patients who exhibit Eye movements have been observed during periods of excessive daytime sleepiness and cataplexy (a sudden behavioral quiescence in Bermuda reef fish, suggesting loss of muscle tone in response to emotional stimuli), the presence of REM sleep (Tauber and Weitzman, mutant zebrafish lacking the hypocretin receptor did 1969). Other studies, however, have failed to replicate not demonstrate an increase in daytime sleep or the this finding (Peyrethon and Dusan-Peyrethon, 1967; development of cataplexy-like behaviors. They did, Shapiro and Hepburn, 1976), leading these authors to however, exhibit an increase in nocturnal sleep–wake conclude that REM sleep is not present in these species. transitions and an increase in nocturnal sleep fragmenThere is evidence for a rebound in resting behavior foltation. Although zebrafish hypocretin receptors were lowing enforced behavioral wakefulness in the perch not found in proximity to the monoaminergic neuro(Cichlosoma nigrofasciatum) and goldfish (Carassius transmitter systems regulating mammalian sleep and auratus), indicating the presence of homeostatic regulatwaking, these receptors did colocalize with GABAergic ing mechanisms, similar to those in mammals (Tobler neurons in the anterior hypothalamus, suggesting that and Borbely, 1985). these neurons rather than monoaminergic systems are An emerging body of work has suggested that the important for sleep regulation in zebrafish. This study zebrafish, Danio rerio, may also serve as a model is of significance not only because it suggests that the organism for understanding the genetic and molecular zebrafish may be an important organism for underregulation of sleep. Zebrafish meet the criteria for standing the underlying molecular basis of sleep, but behavioral sleep, and in addition, quiescent states are also that nonmammalian species must be meticulously induced by sleep-promoting substances such as melatoevaluated, using rigorous methodology, since there nin, diazepam, and sodium pentobarbital (Zhdanova may be important and significant differences which et al., 2001). Genetic and immunohistochemistry studlimit the generalization of findings to mammals. ies demonstrate that the cholinergic, aminergic, and The evidence for electrophysiological correlates of orexin/hypocretin systems of the zebrafish show striking sleep in fish is meager. Recordings in the tench (Tinca similarities to mammals (Zhdanova et al., 2001; Kaslin tinca) did not reveal distinctive electrophysiology assoet al., 2004; Prober et al., 2006). However, a recent ciated with behavioral sleep (Peyrethon and Dusandetailed study also suggests important differences Peyrethon, 1967). Slow waves with superimposed between sleep in zebrafish and sleep in mammals spike-like activity occurring during behavioral sleep (Yokogawa et al., 2007). The behavioral characteristics have been observed in the catfish (Karmanova and of sleep in zebrafish were observed in this study, but Lazarev, 1978). Neither of these studies reported the homeostatic response to sleep deprivation exhibited electrophysiological evidence for REM sleep. striking differences in comparison to mammals. FollowAlso of note are descriptions of “sleep swimming” ing 6 hours of sleep deprivation induced by electrical zooplanktivorous fish which increase the frequency stimulation, there was an expected rebound in quiesof nocturnal dorsal, pectoral, and caudal fin strokes cence when fish were released into darkness at the while maintaining a stereotypic nocturnal position in end of the deprivation period. However, sleep-deprived the coral reef (Goldshmid et al., 2004). The measurable fish which were released into light following deprivabeneficial effects to the coral reef resulting from this tion did not exhibit a homeostatic sleep rebound. Also behavior include enhanced water replenishment and of note is that there was virtually a complete suppresincreased oxygenation. It could be argued that, by defsion of sleep by maintaining the zebrafish under condiinition, behavioral sleep is not present in these fish tions of constant illumination. No sleep rebound since they are obviously not quiescent. On the other occurred following this light-induced sleep suppreshand, the increased activity of nocturnal fin movesion, but sleep gradually reemerged after several days. ments occurring with a stereotypic body posture may This suppression of sleep under conditions of constant be a unique variation on quiescent behavior. Such illumination may be similar to the marked decrease in unique manifestations of “nonquiescent sleep” could sleep which occurs in migrating birds (Rattenborg also exist in other organisms which have been judged et al., 2004; Rattenborg, 2006b). In contrast to mamas not exhibiting sleep by current definitions. mals, there was not a close localization between either The amphibians are of interest because they reprelarval or adult zebrafish hypocretin receptors and the sent the basal stock from which land vertebrates monoaminergic and cholinergic systems. Hypocretin developed (Romer, 1966). Detailed sleep studies in
102
K.M. HARTSE
Fig. 7.3. A sleeping frog. (Courtesy of Roy Smith.)
amphibians are sparse, and reports of electrophysiological correlates associated with sleep-like states have, once again, been variable. Clear signs of behavioral sleep were not observed in either the bullfrog, Rana catesbiana, or the western toad, Bufo boreas (Hobson, 1967; Huntley et al., 1978) (Figure 7.3). However, the tree frog, Hyla squirella and H. cinerea, exhibited signs of behavioral rest, but distinctive electrophysiology associated with this behavioral rest was not present (Hobson et al., 1968). Slow waves in the South American toad and spike-like activity in the frog R. temporaria during behavioral sleep have both been reported (Segura, 1966; Lazarev, 1978). Similar to some studies in frogs, no distinctive electrophysiological correlates of behavioral sleep have been found in the salamander, and variations in heart rate did not correlate with activity and inactivity (McGinty, 1972). However, spectral analysis did reveal electroencephalogram frequency increases during arousal (Lucas et al., 1969). In summary, the data from amphibian studies are quite variable, but support the existence of behavioral sleep with possible electrophysiological correlates.
Fig. 7.4. An American alligator dozing in late afternoon. (Courtesy of Kristyna M. Hartse.)
these findings, no signs of behavioral or electrophysiological sleep, independent of ambient temperature, were found in the American alligator (Alligator mississipiensis) (Van Twyver, 1973) (Figure 7.4). SWS, but not paradoxical sleep, has been reported to occur in the caiman (Warner and Huggins, 1978; Meglasson and Huggins, 1979). Although spikes and sharp waves were observed in this study, this electrophysiology was not correlated with degrees of progressive postural relaxation. Behavioral quiescence associated with highamplitude electrical activity that disappeared with behavioral waking has been reported in a snake, Python saebe (Peyrethon and Dusan-Peyrethon, 1969). Findings in other reptiles have been equally diverse. SWS has not been reported in lizards (Figure 7.5), but two studies have suggested the presence of paradoxical sleep alternating with periods of quiet sleep not marked by slow waves (Tauber et al., 1968; AyalaGuerrero and Mexicano, 2008). In iguanas, spikes and
REPTILES The first stem reptiles from which modern reptiles originated are seen in the fossil record during the carboniferous period approximately 30 million years ago (Romer, 1966). Reptilian sleep has been more extensively studied than sleep in most other nonmammalian species. Although there is general agreement that reptiles exhibit signs of behavioral sleep and wakefulness, the electrophysiological findings and their interpretation have been variable and often in sharp disagreement. In the caiman (Caiman sclerops), behavioral quiescence accompanied by high-voltage spiking, which disappeared during behavioral waking, was first reported by Flanigan et al. (1973). There was no convincing evidence for SWS or paradoxical sleep. In contrast to
Fig. 7.5. A monitor lizard sleeps on a branch. (Courtesy of Kathleen Andersen.)
THE PHYLOGENY OF SLEEP 103 sharp waves occurring during behavioral quiescence and (Hartse, 1994). Some may be due to true species differdisappearing during behavioral waking have been docuences. Some may be due to variations in the meticulousmented (Flanigan et al., 1973). Turtles and tortoises also ness and consistency with which recording procedures exhibit spikes during behavioral sleep which disappear were performed. Some may be due to the biased impoduring behavioral wakefulness. A rebound in spikes sition of mammalian criteria for sleep on nonmammaoccurred following enforced wakefulness. There was lian organisms which have a very different palette of no convincing evidence, however, for the presence of electrophysiology and behavior from that of mammals. either SWS or paradoxical sleep in turtles and tortoises However, the most persuasive evidence supports the (Flanigan, 1974; Flanigan et al., 1974). Further supporting presence of behavioral sleep with an electrophysiological the position that reptiles do not exhibit REM sleep are correlate, the high-amplitude spike, in reptiles. single-unit studies in the brainstem of freely moving turtles (Eiland et al., 2001). Bursting patterns characterBIRDS AND MAMMALS istic of reticular formation neurons in the mammalian In contrast to invertebrates and nonmammalian vertebrainstem were not observed during behavioral quiesbrates, sleep in birds and mammals has been studied cence, nor were cyclically occurring periods of eye extensively (for reviews, see Amlander and Ball, movements and phasic muscle bursts typical of mam1994; Zeplin et al., 2005). Birds exhibit both SWS and malian REM sleep. paradoxical sleep, although paradoxical sleep differs Pharmacological studies in the tortoise, demonstrating from mammalian paradoxical sleep in that it occurs a similar response of the reptilian spike and the cat VH as short bouts lasting from a few seconds to a few spike to amphetamine, Nembutal, parachlorophenylalaminutes in duration. It is also well known that, unlike nine, and alpha methyl-tyrosine do, however, indicate a most mammals, with a few exceptions described similarity between the reptilian spikes and mammalian below, birds exhibit unihemispheric SWS, i.e., one SWS (Hartse and Rechtschaffen, 1982). In another study hemisphere shows clear SWS and the other hemisphere high-voltage spike activity was associated with behavioral exhibits clear waking with eye closure contralateral to quiescence in the tortoise, but the lack of the spike’s assothe sleeping hemisphere. It has been proposed that uniciation with elevated arousal thresholds in this study as hemispheric sleep may have evolved in response to the well as the modulating effect of temperature upon the risk of predation by allowing parts of the cerebrum to presence of the spike led these investigators to conclude be differentially alert (Lima et al., 2005). that the spikes are not an electrophysiological manifestaThe question of whether migrating birds sleep has tion of “true” sleep (Walker and Berger, 1973). In conrecently received attention (Rattenborg, 2006b). Migratrast, only mammalian-like SWS, but not paradoxical tions occurring over a period of several days suggest sleep, has been reported in the tortoise, Testudo margineither that birds sleep in flight or that sleep requirements ata (Hermann et al., 1964), and both SWS and paradoxical are drastically reduced during this time. No electrophyssleep have been reported in the European pond turtle, iological recordings of sleep have been made during Emys orbicularis, as well as in the tortoise, Gopherus flaactual migration. However, in the laboratory, the white vomarginatus (Vasilescu, 1970; Ayala-Guerrero et al., crowned sparrow, a migrating songbird, spends 63% 1988). No electrophysiological correlates of behavioral less time sleeping during the migratory season as comsleep and wakefulness as well as an absence of a homeopared to the no-migratory season (Rattenborg et al., static response to enforced waking in the sea turtle, Car2004). As pointed out by Rattenborg (2006b), by strict etta caretta L., led to the conclusion that this species does definition birds in flight do not sleep because they are not sleep (Susic, 1972). Finally, observations of highnot quiescent, even though it seems unlikely that sleep amplitude slow-wave activity during waking in the lizard does not occur for several days. Avian unihemispheric have prompted one group of investigators to conclude SWS may allow some sleep in flight, but it seems that reptilian waking is the precursor to mammalian unlikely that REM sleep, which is typically sensitive to SWS (Rial et al., 2007a). environmental disruption, occurs under these conditions. The often contradictory findings in the reptile literThe finding that sleep amounts are drastically reduced ature have raised an important issue. If REM sleep is during the migratory season suggests that birds may absent in reptiles, this suggests that REM may not have have a periodically reduced sleep need in response to been present in stem reptiles ancestral to birds and the demand of migration (Rattenborg, 2006b). Further mammals and as a result REM sleep may have evolved research with new technologies that permit in-flight independently in birds and mammals rather than being electrophysiological recordings is clearly required to perpetuated from a common ancient ancestor. There resolve the question of whether or not birds sleep in are a number of parameters that could account for flight (Figures 7.6 and 7.7). the differences in findings from the reptile studies
104
K.M. HARTSE
Fig. 7.6. A sleeping water fowl. (Courtesy of Berit Watkin.)
Fig. 7.7. Dozing flamingos. (Courtesy of Kathleen Andersen.)
The features of sleep in mammals are well known through the use of a wide variety of electrophysiological and neurochemical techniques (for a review, see Zeplin et al., 2005). Like birds, mammals, with the exception of some cetaceans (whales and dolphins), exhibit both NREM and REM sleep in a predictable cyclically alternating fashion (Figure 7.8). The presence
Fig. 7.8. A sleeping lion. (Courtesy of Kathleen Andersen.)
of NREM and REM sleep in both birds and mammals is of interest since the absence of REM sleep in reptiles would suggest that REM sleep is a more recent development in the phylogenetic history of land-dwelling organisms. Utilizing data primarily from mammals, several different theories have been advanced to explain the function of sleep. Some of the most persuasive data support an energy conservation hypothesis, and there is a positive correlation between basal metabolic rate (BMR) and total sleep time (Zeplin and Rechtschaffen, 1974; Zeplin et al., 2005). That is, animals with higher metabolic rates spend more time asleep. However, recent path model analyses have found a significant negative correlation between BMR and total sleep time in mammals (Lesku et al., 2006). In contrast to the mammalian data, similar path model analyses in birds have not revealed a relationship between BMR and either SWS or REM sleep. The only statistically significant relationship in avian species was an inverse relationship between SWS time and risk of predation, suggesting different, independently evolved functions for sleep in mammals and birds (Roth et al., 2006). It has also recently been proposed that “mammalian sleep has no function apart from the rest of simple organisms” (Rial et al., 2007a). Although the simplicity of this theory is attractive, there is meager support for this position when the totality of data from phylogenetic studies is examined (Rattenborg et al., 2007). Furthermore, a recent metabolic study in the desert iguana, Dipsosaurus dorsalis, supports the position that sleep contributes to energy conservation, even in poikilothermic organisms (Revell and Dunbar, 2007). Under controlled laboratory conditions, the mean metabolic rate of sleeping iguanas was 27.6% less in comparison to waking across temperature ranges of 20–40 C. However, a larger metabolic saving accrued during wakefulness at cooler temperatures than during sleep at warmer temperatures, suggesting that the energy conservation function of sleep in poikilotherms may be less significant than the impact of behavioral thermoregulation upon energy conservation. One group of animals which may shed light upon the origins of REM sleep are the living monotremes, primitive egg-laying mammals representing an early branch in mammalian evolution (Figure 7.9). The first study in the short-beaked echidna, Tachyglossus aculeatus, revealed the presence of NREM sleep, but unambiguous REM sleep could not be conclusively identified (Allison et al., 1972). More recent studies have utilized single-cell recordings from the echidna midbrain reticular formation and pons, structures known to have a distinctive bursting pattern of activity during REM sleep, to clarify whether or not REM
THE PHYLOGENY OF SLEEP
Fig. 7.9. The short-beaked echidna in its Australian habitat. (Courtesy of Ian Michael Thomas.)
sleep is present in these organisms (Siegel et al., 1996). A unique electrophysiological pattern of brainstem unit discharge variability accompanied by highamplitude forebrain slow waves was observed (Siegel et al., 1996). This brainstem single-unit activity was not typical of the bursting pattern present in the mammalian reticular formation during REM sleep, and phasic motor activity or eye movements did not occur in concert with this unit activity. These findings may be interpreted to support the hypothesis that sleep in the echidna is an amalgam of cortex-synchronized NREM and brainstemactivated REM sleep which was subsequently differentiated during evolution into separate NREM and REM states (Siegel et al., 1998). A subsequent study in the echidna has identified unambiguous REM sleep based upon the usual mammalian criteria for this stage (Nichol et al., 2000). In contrast to these findings, the platypus (Ornithorhynchus anatinus), another monotreme, exhibits abundant amounts of REM sleep characterized by muscle atonia, eye movements, and phasic twitching. Similar to the echidna, these elements of REM sleep occurred in the presence of high-voltage slow waves (Siegel et al., 1999). Differences between the echidna and the platypus in the expression of REM sleep may be the result of adaptation to the vulnerability of their sleeping environments (Siegel et al., 1998). The only group of mammals in which REM sleep has not been clearly identified is the cetaceans (whales and dolphins). Like birds, these mammals exhibit unihemispheric SWS with eye closure contralateral to the sleeping hemisphere (Mukhametov, 1987; Lyamin et al., 2000, 2002, 2004). No arousal threshold studies have been performed, and a variable rebound in unihemispheric sleep following unihemispheric sleep deprivation has been reported in one study of the dolphin (Oleksenko et al., 1992). No evidence for unambiguous
105
REM sleep has been revealed in cetaceans, although jerking movements similar to the phasic twitches of mammalian REM sleep have been observed in the gray whale (Lyamin et al., 2000). It should not necessarily be concluded from these studies, however, that aquatic mammals do not have REM sleep. Current techniques for the detection of REM sleep in cetaceans may not be adequate or, alternatively, REM sleep in the aquatic environment may be present in a form different from that observed in terrestrial environments. Not only is the questionable absence of REM sleep in cetaceans different from sleep in land-dwelling mammals, the pattern of behavioral sleep and wakefulness in newborn cetacean calves is also different from the young of land-dwelling mammals (Lyamin et al., 2005). Unlike most mammalian infants which spend significant periods of the 24-hour-day sleeping, dolphin and killer whale neonates exhibited virtually no periods of behavioral rest or eyelid closure, which is correlated with the presence of sleep, for several months after birth. In concert with their infants, mothers also exhibited almost no resting behavior for several months postpartum. These findings challenge the concept that a basal amount of sleep, as it is currently defined by electrophysiological and behavioral criteria, is necessary for normal growth and development in all mammals.
THE PHYLOGENY OF SLEEP AND HUMAN SLEEP DISORDERS Phylogenetic sleep studies unquestionably provide clues to our understanding of human sleep mechanisms, and more importantly, these data form a nexus of evidence for ultimately understanding the functionality of sleep in humans. How does the study of sleep in organisms as diverse as the fruit fly and the whale contribute to our understanding of human sleep?
Assessing the effects of sleep loss Although the insomnia patient is frequently advised that lack of sleep is not harmful or life-threatening, studies in Drosophila demonstrate that sleep loss can affect lifespan, aging, and gene expression (Cirelli, 2006; Koh et al., 2006). By extension, these findings imply that the impact of sleep loss in humans may have greater physiological significance than has been previously appreciated. Epidemiological data support a correlation between shortened as well as extended sleep and decreased lifespan, indicating that less-thanoptimal sleep amounts are likely to be deleterious to longevity in humans (Kripke et al., 2002; Hublin et al., 2007). There is also evidence that some strains of genetically short-sleeping Drosophila, akin to the
106
K.M. HARTSE
normal human “short sleeper,” do not experience deleterious effects of sleep loss such as decreased longevity (Kume et al., 2005), although other studies have demonstrated decreased longevity in short-sleeping flies (Cirelli, 2006). By using the fruit fly as a model for the study of sleep, the relationship between sleep duration, lifespan, and aging can be dissected with greater precision.
Models for treatment If the molecular consequences of reduced sleep can be assessed by using the Drosophila model, then additional precision may be gained in assessing the molecular effects of pharmacological treatments for insomnia or excessive daytime sleepiness. Caffeine, amphetamine, and antihistaminics have already been demonstrated to have effects on behavioral sleep and waking in Drosophila which are similar to the effects on sleep in humans (Shaw et al., 2000). Modafinil, a treatment for human narcolepsy, produces a similar alerting response in fruit flies and in humans (Hendricks et al., 2003). Recently a specific biomarker for sleepiness in humans, salivary amylase, has been identified directly as the result of work in Drosophila (Seugnet et al., 2006). Ideally, the future development of effective new compounds to enhance sleepiness and/or alertness in humans could be potentially assessed on a molecular level in a model such as Drosophila for efficacy, safety, and side-effects.
The genetics of sleep The studies in nonmammalian organisms, specifically Drosophila and zebrafish, have tremendously advanced our understanding of sleep genetics. Although the genetics of humans sleep disorders are not well understood, delayed sleep phase syndrome (Toh et al., 2001), narcolepsy (Mignot, 2005), and periodic limb movements (Stefansson et al., 2007) have all recently been identified as having a genetic basis. The identification of mutant strains of Drosophila, for example shortsleeping flies, may shed light on the mechanisms for the origins and perpetuation of some sleep disorders in humans.
CONCLUSIONS Our original question, “Why do we sleep?”, has not been answered by this review. However, simple behavioral observations as well as correlations between surface brain activity and behavior in unstudied, interesting nonmammalian organisms are no longer adequate to advance our understanding of the function of sleep from a phylogenetic perspective. The same
rigorous and innovative neurophysiological and molecular methodologies which have been applied to the study of mammalian sleep must also be applied to nonmammalian species. Conversely, the application of molecular techniques developed in Drosophila to the study of sleep in mammalian organisms may provide further insight into the function or functions of sleep in humans and other mammals. Clearly, there are many fruitful avenues of research to pursue which have the potential to unravel the complex relationships between sleep function and species survival.
REFERENCES Allison T, Van Twyver H, Goff WR (1972). Electrophysiological studies of the echidna, Tachyglossus aculeatus. I. Waking and sleep. Arch Ital Biol (110): 145–184. Amlander CJ, Ball NJ (1994). Avian sleep. In: MH Kryger, T Roth, WC Dement (Eds.), Principles and Practice of Sleep Medicine. 2nd edn. WB Saunders, Philadelphia, pp. 81–94. Andersen FS (1968). Sleep in moths and its dependence on the frequency of stimulation in Anagasta kuehniella. Opusc Ent 33: 15–24. Andretic R, van Swindern B, Greenspan RJ (2005). Dopaminergic modulation of arousal in Drosophila. Curr Biol 15: 1165–1175. Ayala-Guerrero F, Calderon A, Perez MC (1988). Sleep patterns in a chelonian reptile (Gopherus flavomarginatus). Physiol Behav 44: 333–337. Ayala-Guerrero F, Mexicano G (2008). Sleep and wakefulness in the green iguanid lizard (Iguana iguana). Comp Biochem Physiol A Mol Integr Physiol 151: 305–312. Brown R, Piscopo S, DeStefan R et al. (2006). Brain and behavioral evidence for rest activity cycles in Octopus vulgaris. Behav Brain Res 172: 355–359. Cirelli C (2003). Searching for sleep mutants of Drosophila melanogaster. BioEssays 25: 940–949. Cirelli C (2006). Sleep disruption, oxidative stress, and aging: new insights from fruit flies. Proc Natl Acad Sci 103: 13901–13902. Cirelli C, Bushey D, Hill S et al. (2005). Reduced sleep in Drosophila shaker mutants. Nature 434: 1087–1092. De Vera L, Gonzalez J, Rial RV (1994). Reptilian waking EEG: slow waves, spindles and evoked potentials. Electroencephal Clin Neurophysiol 90: 298–303. Duntley SP, Uhles M, Feren S (2002). Sleep in the cuttlefish Sepia pharonis. Sleep 25: A159. Eiland MM, Lyamin OI, Siegel JM (2001). State-related discharges of neurons in the brainstem of freely moving box turtles, Terrapene carolina major. Arch Ital Biol 139: 23–36. Flanigan WF (1973). Sleep and wakefulness in iguanid lizards, Ctenosaura pectinata and Iguana iguana. Brain Behav Evol 8: 401–436. Flanigan WF (1974). Sleep and wakefulness in chelonian reptiles. II. The red-footed tortoise, Geochelone carbonaria. Arch Ital Biol 112: 253–277.
THE PHYLOGENY OF SLEEP Flanigan WF, Wilcox RH, Rechtschaffen A (1973). The EEG and behavioral continuum of the crocodilian, Caiman sclerops. Electroenceph Clin Neurophysiol 34: 521–538. Flanigan WF, Knight CP, Hartse KM et al. (1974). Sleep and wakefuness in chelonian reptiles. I. The box turtle, Terrapene carolina. Arch Ital Biol 112: 227–252. Foltenyi K, Greenspan RJ, Newport JW (2007). Activation of EGFR and ERK by rhomboid signaling regulates the consolidation and maintenance of sleep in Drosophila. Nat Neurosci 10: 1160–1167. Goldshmid R, Holzman R, Weihs D et al. (2004). Aeration of corals by sleep swimming fish. Limnol Oceanogr 49: 1832–1839. Hartse KM (1994). Sleep in insects and nonmammalian vertebrates. In: MH Kryger, T Roth, WC Dement (Eds.), Principles and Practice of Sleep Medicine. 2nd edn. WB Saunders, Philadelphia, pp. 95–104. Hartse KM (2009). Sleep in isects. In: P McNamara, RA Barton, CL Nunn (eds.) Evolution of Sleep: Phylogenetic and functional Perspectives. Cambridge University Press, New York, pp. 34–56. Hartse KM, Rechtschaffen A (1974). Effect of atropine sulfate on the sleep-related EEG spike activity of the tortoise, Geochelone carbonaria. Brain Behav Evol 9: 81–94. Hartse KM, Rechtschaffen A (1982). The effect of amphetamine, Nembutal, alpha-methyl-tyrosine, and parachlorophenylalanine on the sleep-related spike activity of the tortoise, Geochelone carbonaria, and on the cat ventral hippocampus spike. Brain Behav Evol 21: 199–222. Hartse KM, Eisenhart SF, Bergmann BM et al. (1979). Hippocampal spikes during sleep, wakefulness, and arousal in the cat. Sleep 1: 231–246. Hendricks JC, Finn SM, Panckeri KA et al. (2000a). Rest in Drosophila is a sleep-like state. Neuron 25: 129–138. Hendricks JC, Sehgal A, Pack AI (2000b). The need for a simple animal model to understand sleep. Prog Neurobiol 61: 339–351. Hendricks JC, Kirk D, Panckeri K et al. (2003). Modafinil maintains waking in the fruit fly, Drosophila melanogaster. Sleep 26: 139–146. Hermann H, Jouvet M, Klein M (1964). Analyse polygraphique du sommeil de la tortue. C R Hebd Seances Acad Sci 258: 2175–2178. Hobson JA (1967). Electrographic correlates of behavior in the frog with special reference to sleep. Electroencephalogr Clin Neurophysiol 22: 113–121. Hobson J, Goin O, Goin C (1968). Electrographic correlates of behaviour in tree frogs. Nature 220: 386–387. Hublin C, Partinen M, Koskenvuo M et al. (2007). Sleep and mortality: a population-based 22-year follow-up study. Sleep 30: 1245–1253. Huntley AC, Donnelly M, Cohen HB (1978). Sleep in the western toad, Bufo boreas. Sleep Res 7: 141. Joiner WJ, Crocker A, White BH et al. (2006). Sleep in Drosophila is regulated by adult mushroom bodies. Nature 441: 757–760. Kaiser W (1988). Busy bees need rest too. J Comp Physiol A 163: 565–584.
107
Kaiser W, Steiner-Kaiser J (1983). Neuronal correlates of sleep, wakefulness and arousal in a diurnal insect. Nature 301: 707–709. Karmanova IG, Lazarev SG (1978). Neurophysiological characteristics of primary sleep in fish and amphibians. In: Sleep 1978. Fourth European Congress on Sleep Research. S Karger, Basel, pp. 437–442. Kaslin J, Nystedt JM, Ostergard M et al. (2004). The orexin/hypocretin system in zebrafish is connected to the aminergic and cholinergic systems. J Neurosci 24: 2678–2689. Koh K, Evans JM, Hendricks JC et al. (2006). A Drosophila model for age-associated changes in sleep:wake cycles. Proc Nat Acad Sci (103): 13843–13847. Kripke DF, Garfinkel L, Wingard DL et al. (2002). Mortality associated with sleep duration and insomnia. Arch Gen Psychiatr (50): 131–136. Kume K, Kume S, Park SK et al. (2005). Dopamine is a regulator of arousal in the fruit fly. J Neurosci (25): 7377–7384. Lazarev SG (1978). Electrophysiological analysis of wakefulness and primary sleep in the frog Rana temporaria [in Russian]. Zh Evol Biokhim Fiziol (14): 379–388. Lesku JA, Roth TC, Amlaner CJ et al. (2006). A phylogenetic analysis of sleep architecture in mammals: the integration of anatomy, physiology, and ecology. Am Nat 168: 441–453. Levenson J, Byrne JH, Eskin A (1999). Levels of serotonin in the hemolymph of Aplysia are modulated by lightdark cycles and sensitization training. J Neurosci 19: 8094–8103. Lima SL, Rattenborg NC, Lesku JA et al. (2005). Sleeping under the risk of predation. Anim Behav (70): 723–736. Lucas EA, Sterman MB, McGinty DJ (1969). The salamander EEG: a model of primitive sleep and wakefulness. Psychophysiology 6: 230. Lyamin OI, Manger PR, Mukhametov LM et al. (2000). Rest and activity states in a gray whale. J Sleep Res 9: 261–267. Lyamin OI, Mukhametov IM, Siegel JM et al. (2002). Unihemispheric slow wave sleep and the state of the eyes in a white whale. Behav Brain Res 129: 125–129. Lyamin OI, Mukhametov IM, Siegel JM (2004). Relationship between sleep and eye state in cetaceans and pinnipeds. Arch Ital Biol 142: 557–568. Lyamin OI, Pryaslova J, Lace V et al. (2005). Continuous activity in cetaceans after birth. Nature 435: 1177. McGinty D (1972). Sleep in amphibians. In: MH Chase (Ed.), The Sleeping Brain. Brain Information Service, Los Angeles, pp. 7–10. Meglasson MD, Huggins SE (1979). Sleep in a crocodilian, Caiman sclerops. Comp Biochem Physiol 63A: 561–567. Mendoza-Angeles K, Cabrera A, Hernandez-Falcon J et al. (2007). Slow waves during sleep in crayfish: a time– frequency analysis. J Neurosci Methods 162: 264–271. Metz J, Rechtschaffen A (1976). Hippocampus spikes during sleep in rats. Sleep Res 5: 28. Mignot E (2005). Narcolepsy: pharmacology, pathophysiology, and genetics. In: MH Kryger, T Roth, WC Dement
108
K.M. HARTSE
(Eds.), Principles and Practice of Sleep Medicine. Elsevier Saunders, Philadelphia, pp. 761–779. Mukhametov LM (1987). Unihemispheric slow-wave sleep in the Amazonian dolphin, Inia geoffrensis. Neurosci Lett 79: 128–132. Naidoo N, Casiano V, Cater J et al. (2007). A role for the molecular chaperone protein bip/GRP78 in Drosophila sleep homeostasis. Sleep 30: 557–656. Nichol S, Andersen NA, Phillips NH et al. (2000). The echidna manifests typical characteristics of rapid eye movement sleep. Neurosci Lett (283): 49–52. Nieuwenhuys R (1994). The neocortex: an overview of its evolutionary development, structural organization, and synaptology. Anat Embryol 190: 307–337. Nitz D, von Swinderen B, Tononi G et al. (2002). Electrophysiological correlates of rest and activity in Drosophila melanogaster. Curr Biol 12: 1934–1940. Oleksenko AI, Mukhametov IM, Polyakova IG et al. (1992). Unihemispheric sleep deprivation in bottlenose dolphins. J Sleep Res (1): 40–44. Peyrethon J, Dusan-Peyrethon D (1967). Etude polygraphique du cycle veille–sommeil d’un teleoste´en (Tinca tinca). C R Seances Soc Biol Fil 161: 2533–2537. Peyrethon J, Dusan-Peyrethon D (1969). Etude polygraphique due cycle veille–sommeil chez trois genres de reptiles. C R Seances Soc Biol Fil 163: 181–186. Pitman JL, McGill JJ, Keegan KP et al. (2006). A dynamic role for the mushroom bodies in promoting sleep in Drosophila. Nature 441: 753–756. Prober DA, Rihel J, Onah AA et al. (2006). Hypocretin/ orexin overexpression induces an insomnia-like phenotype in zebrafish. J Neurosci 26: 13400–13410. Ramon F, Hernandez-Falcon J, Nguyen B et al. (2004). Slow wave sleep in crayfish. Proc Natl Acad Sci U S A 101: 11857–11861. Rattenborg NC (2006a). Evolution of slow-wave sleep and palliopallial connectivity in mammals and birds: a hypothesis. Brain Res Bull (69): 20–29. Rattenborg NC (2006b). Do birds sleep in flight? Naturwissenschaften 93: 413–425. Rattenborg NC (2007). Response to commentary on evolution of slow-wave sleep and palliopallial connectivity in mammals and birds: a hypothesis. Brain Res Bull 72: 187–193. Rattenborg NC, Mandt BH, Obermeyer WH et al. (2004). Migratory sleeplessness in the white-crowned sparrow (Zonotrichia leucophrys gambelii). PloS Biol 2: 924–936. Rattenborg NC, Lesku JA, Martinez-Gonzalez D et al. (2007). The non-trivial functions of sleep. Sleep Med Rev 11: 405–409. Rau P, Rau N (1916). The sleep of insects: an ecological study. Ann Entomol Soc Am 9: 227–274. Rechtschaffen A (1998). Current perspectives on the function of sleep. Perspect Biol Med 41: 359–390. Rechtschaffen A, Bergmann B (2002). Sleep deprivation in the rat: an update of the 1989 paper. Sleep 25: 18–24. Revell TK, Dunbar SG (2007). The energetic savings of sleep versus temperature in the desert iguana (Dipsosaurus
dorsalis) at three ecologically relevant temperatures. Comp Biochem Physiol A 148: 393–398. Rial RV, Nicolau MC, Gamundi A et al. (2007a). The trivial function of sleep. Sleep Med Rev 11: 311–325. Rial RV, Nicolau MC, Gamundi A et al. (2007b). Comments on evolution of sleep and the palliopallial connectivity in mammals and birds. Brain Res Bull (72): 183–186. Romer AS (1966). Vertebrate Paleontology. University of Chicago Press, Chicago. Roth TC, Lesku JA, Amlaner CJ et al. (2006). A phylogenetic analysis of the correlates of sleep in birds. J Sleep Res (15): 395–402. Sauer S, Hermann E, Kaiser W (2004). Sleep deprivation in honey bees. J Sleep Res 13: 145–152. Segura ET (1966). Estudios electroencefalograficos en anfibios. Acta Physiol Lat Am (16 Suppl): 277–282. Seugnet L, Boero J, Gottschalk L et al. (2006). Identification of a biomarker for sleep drive in flies and humans. Proc Natl Acad Sci U S A 103: 19913–19918. Shapiro CM, Hepburn HR (1976). Sleep in a schooling fish, Tilapia mossambica. Physiol Behav 16: 613–615. Shaw PJ, Cirelli C, Greenspan RJ et al. (2000). Correlates of sleep and waking in Drosophila melanogaster. Science 287: 1834–1837. Siegel JM, Manger PR, Nienhuis R et al. (1996). The echidna Tachyglossus aculeatus combines REM and non-REM aspects in a single sleep state: implications for the evolution of sleep. J Neurosci 15: 3500–3506. Siegel JM, Manger PR, Nienhuis R et al. (1998). Monotremes and the evolution of rapid eye movement sleep. Phil Trans R Soc Lond B 353: 1147–1157. Siegel JM, Manger PR, Nienhuis R et al. (1999). Sleep in the platypus. Neurosci (91): 391–400. Siegmund VR (1969). Lokomotorische Aktivitat und Ruheverhalten bei einheimischen Subwasser-fischen (Pices: Percidae, cyprinidae). Biol Zbl 88: 295–312. Sirota A, Csicsvari J, Buhl D et al. (2003). Communication between neocortex and hippocampus during sleep in rodents. Proc Natl Acad Sci U S A 100: 2065–2069. Stefansson H, Rye D, Hicks A et al. (2007). A genetic risk factor for periodic limb movements in sleep. N Eng J Med (357): 639–647. Stephenson R, Chu K, Lee J (2007). Prolonged deprivation of sleep like rest raises metabolic rate in the pacific beetle cockroach, Diploptera punctata (Eschscholtz). J Exp Biol 210: 2540–2547. Strumwasser F (1971). The cellular basis of behavior in Aplysia. J Psychiat Res 8: 237–257. Susic V (1972). Electrographic and behavioural correlations of the rest–activity cycle in the sea turtle, Caretta caretta L. J Exp Mar Biol Ecol (10): 81–87. Tauber ES, Weitzman ED (1969). Eye movements during behavioral inactivity in certain Bermuda reef fish. Comm Behav Biol A 3: 131–135. Tauber ES, Rojas-Ramirez J, Hernandez Peon R (1968). Electrophysiological and behavioral correlates of wakefulness and sleep in the lizard, Ctenosaura pectinata. Electroencephalogr Clin Neurophys (24): 424–433.
THE PHYLOGENY OF SLEEP Tobler I (1983). Effect of forced locomotion on the rest– activity cycle of the cockroach. Behav Brain Res 8: 351–360. Tobler I (2005). Phylogeny of sleep regulation. In: MH Kryger, T Roth, WC Dement (Eds.), Principles and Practice of Sleep Medicine. Elsevier Saunders, Philadelphia, pp. 77–90. Tobler I, Borbely AA (1985). Effect of rest deprivation on motor activity of fish. J Comp Physiol A 157: 817–822. Tobler I, Stadler J (1988). Rest in the scorpion – a sleep like state? J Comp Physiol A 163: 227–235. Tobler I, Neuner-Jehle M (1992). 24-h variation in vigilance in the cockroach. J Sleep Res (4): 231–239. Toh KL, Jones CR, He Y et al. (2001). An hper2 phosphorylation site mutation in familial advanced sleep phase syndrome. Science (291): 1040–1043. Van Twyver H (1973). Polygraphic studies of the American alligator. Sleep Res (2): 87. Vasilescu E (1970). Sleep and wakefulness in the tortoise (Emys orbicularis). Rev Roum Biol (Ser Zool) 15: 177–179.
109
Walker JM, Berger RJ (1973). A polygraphic study of the tortoise (Testudo denticulata): absence of electrophysiological signs of sleep. Brain Behav Evol 8: 453–467. Warner BF, Huggins BF (1978). An electroencephalographic study of sleep in young caimans in a colony. Comp Biochem Physiol (59A): 139–144. Yokogawa T, Marin W, Faraco J et al. (2007). Characterization of sleep in zebrafish and insomnia in hypocretin receptor mutants. PloS Biol (5): 2379–2397. Zeplin H, Rechtschaffen A (1974). Mammalian sleep, longevity, and energy metabolism. Brain Behav Evol (10): 425–470. Zeplin H, Siegel JM, Tobler I (2005). Mammalian sleep. In: MH Kryger, T Roth, WC Dement (Eds.), Principles and Practice of Sleep Medicine. Elsevier Saunders, Philadelphia, pp. 91–100. Zhdanova IV, Wang SY, Leclair OU et al. (2001). Melatonin promotes sleep-like state in zebrafish. Brain Res 903: 263–268.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 8
Ontogeny of EEG sleep from neonatal through infancy periods MARK S. SCHER* Division of Pediatric Neurology, Rainbow Babies and Children’s Hospital, University Hospitals of Cleveland, Case-Western Reserve University, Cleveland, OH, USA
Electrographic and polygraphic recordings of newborns and infants have been performed for almost a half-century. Pioneering studies by multiple researchers worldwide offer neurophysiologic information concerning the developing central nervous system (Ellingson, 1964; Anders et al., 1971; Parmelee and Stern, 1972; Prechtl, 1974; Dreyfus-Brisac, 1979; Lombroso, 1989; Hrachovy et al., 1990; Pope et al., 1992). Earlier investigations predated the creation of the modern neonatal intensive care unit (NICU); however, these seminal works described for the first time electrographic patterns and physiologic behaviors which define the rudimentary state of the preterm neonate. Given the higher rate of neonatal mortality, particularly in the premature infant, the clinical neurophysiologist had a more limited consultative role in the neurologic care of the sick neonate. With the creation of the modern-day tertiary care NICU, the sophistication of medical care, including technological improvements in physiologic recordings, now offers the neurological consultant a more active role in neonatal neurophysiological assessments for medical care. The decline in neonatal morbidity and mortality has concentrated renewed attention on the neurological performance during both the acute and convalescent periods in the days to weeks after birth for the highrisk newborn. Given the immature clinical repertoire of the newborn and infant, as well as limited access to neonates in a busy intensive care setting, electroencephalographic (EEG) polygraphic studies can extend the clinician’s abilities to document functional brain maturation, as well as the presence and severity of encephalopathic states. Serial EEG sleep analyses have a significant impact on documenting aberrant functional
brain maturation (i.e., dysmaturity) (Scher et al., 2003a). Quantitative estimates of brain dysmaturity using computer analyses are being refined as research tools to develop objective measures for detecting subtle expressions of encephalopathy as well as predicting outcome. Neonatal survivors also require close supervision after discharge over successive stages in brain maturation during infancy and later childhood. Maturation of neonatal and infant behavior requires careful evaluation of both waking and sleep behaviors. Combined neurophysiological monitoring with systematic behavioral assessments can better evaluate functional brain maturation. The clinician can apply knowledge of sleep ontogeny to the evaluation of different pediatric populations who are at risk for developmental delay, as suggested by altered behaviors during sleep or wakefulness. Computer-assisted analysis tools will extend our abilities to examine physiologic relationships between cerebral and noncerebral measures, and explore associations with selected outcome measures (AjmoneMarsan, 1986; Scher et al., 1990, 2005b).
CAVEATS CONCERNING NEUROPHYSIOLOGIC INTERPRETATION OF STATE A number of caveats will assist the neurophysiologist in an understanding of the application of sleep interpretation from the neonatal through infancy periods. Maturational changes of EEG polygraphic patterns emerge at successively older postmaturational ages (PMA): neurophysiologic maturity of a neonate can
*Correspondence to: Mark S. Scher, M.D., Rainbow Babies and Children’s Hospital, 11100 Euclid Ave., M/S 6090, Cleveland, OH 44106-6090, USA. Tel: (216) 844-3691, Fax: (216) 844-8444, E-mail:
[email protected]
112
M.S. SCHER
be estimated within 2 weeks for the preterm infant (i.e., < 37 weeks PMA) and 1 week for the full-term infant, reflecting the PMA of the infant independent of birth weight. Temporal coincidence or concordance among physiologic sleep behaviors emerges with increasing maturity, similar to fetal behavioral states documented by abdominal sonography. Significant functional reorganization of state occurs at 30, 36, and 48 weeks’ PMA, reflecting cortical-subcortical neuronal networks that subserve sleep. Finally, serial neurophysiologic studies rather than a single recording more accurately document normal ontogeny or the evolution of delayed or abnormal changes reflective of a brain disorder. Subsequent developmental stages also occur during infancy regarding sleep reorganization principally after 3, 9, and 12 months of age. The clinician needs to develop a confident style of neurophysiologic pattern recognition and clinical correlation by repetitive experiences with a wide variety of EEG polygraphic recordings. Before an accurate interpretation can be offered to the referring clinician, knowledge of the child’s PMA as well as the range of behavioral phenomena that are anticipated at that age during the recording are needed; this requires close communication between the electrodiagnostic technologist and the neurophysiologist. Ongoing discussion with the neonatologist results in continual re-evaluation of the neurophysiologic interpretations within the clinical context.
GENERAL COMMENTS ON RECORDING TECHNIQUES AND INSTRUMENTATION FOR NEONATES AND INFANTS Appropriate recording techniques will yield highquality EEG polygraphic studies. The neurophysiologist should apply a minimum of 10 EEG electrodes in addition to a full complement of noncerebral polygraphic electrodes, given that specific regional and hemispheric electrographic patterns need to be correlated with other noncerebral physiologic behaviors. Placement of electrodes by either paste or collodion must be achieved with ease and efficiency by the technologist who must always be cognizant of the fragile state of the neonate within the busy NICU environment. While double interelectrode distances may be preferred for the infant <36 weeks’ estimated gestational age to visualize electrographic patterns better, a more complete set of electrodes will be advantageous for monitoring the full-term newborn and older infant. Adjustments in sensitivity, paper speed, and filter settings will facilitate electrographic/polysomnographic interpretation. Sensitivity settings should begin with standard 7 mV/mm, but may need to be periodically
adjusted during the recording. Lower-frequency filter settings between 0.25 and 0.5 Hz are preferred for neonatal recordings, to avoid the elimination of commonly occurring slow-frequency wave forms. Slower paper speeds (such as 15 mm/s) will permit easier visualization of slowly recurring normal features, such as EEG discontinuity and asynchrony, or abnormal features such as seizures and periodic discharges. Adjustment to a lower filter setting of 1 Hz and a paper speed of 30 mm/s may be preferred for infants after 6–8 weeks of age. State-of-the-art digital equipment facilitates these adjustments when viewed offline, following the completion of the study. Motility, cardiorespiratory, and eye movements are essential noncerebral physiologic behaviors to record for sleep analysis. Non-EEG physiologic observations are relevant for both state identification as well as corroboration of a clinical observation that may have prompted the request for the study. Documentation of transcutaneous PO2 and CO2 may be needed. Sources of artifact are also more readily identified and eliminated with the consistent use of non-EEG channels, supplemented by the technologist’s comments. Frequent and accurate annotations by the technologist throughout the study are strongly advised. Eye opening and eye closure as well as repositioning of the patient’s head are common annotations that are essential for proper interpretation. Information from the medical record should be recorded by the technologist for the physician’s use regarding the child’s gestational and PMA, as well as states of arousal, medications, and medical procedures. Skull defects, vital signs, and pertinent laboratory studies should all be described since certain factors may affect neurophysiologic interpretation.
MATURATION OF ELECTROGRAPHIC PATTERNS IN THE NEONATE A number of principles should be applied by the neurophysiologist for an accurate interpretation of a neonatal EEG sleep study. The neurophysiologist’s ability to interpret expected age-appropriate neurophysiologic patterns is essential before recognition of encephalopathic features (Scher, 1994a-h). Changes in EEG polygraphic patterns occur for neonates at increasing PMA up to term and into early infancy. PMA is calculated simply as the infant’s estimated gestational age at birth plus the number of weeks of postnatal life (i.e., estimated gestational age at birth plus postnatal age equals PMA in weeks). The neurophysiologist should approximate the electrical maturity of the preterm infant within 2 weeks of other estimates of maturity, and 1 week for a term infant. Preterm neonates recorded
ONTOGENY OF EEG SLEEP FROM NEONATAL THROUGH INFANCY PERIODS at PMA up to term will express EEG patterns similar to a child born at that comparable level of maturity; subtle differences may also be expressed because of functional brain adaptation to prematurity, as will be discussed in a subsequent section (i.e., physiologic dysmaturity). Two studies exemplify how neurophysiologic estimates of gestational maturity can be achieved by pattern recognition of EEG sleep recordings for either healthy or sick preterm cohorts (Scher and Barmada, 1987; Scher et al., 1994a). Such neurophysiologic estimates of maturity were offered even without accurate clinical examination criteria, fetal sonographic data, or other obstetrical information regarding gestational maturity; for both the healthy and sick preterm groups, assessments of neurophysiologic gestational maturity were as accurate as clinical and/or anatomical estimates. Such neurophysiologic information may be essential in problematic situations in which gestational maturity is not accurately assessed by other methods. This is particularly the case in high-risk pregnancies with intrauterine growth restriction, which may lack accurate information with respect to correct gestational maturity; in symptomatic infants who are too medically ill to assess postural tone or levels of arousal; or in infants too premature who do not exhibit postural tone, primitive reflexes, or behavioral alterations during state transition to estimate brain maturity accurately. Regional and hemispheric electrographic patterns for the preterm and fullterm neonate will be initially discussed, emphasizing major features at successively older PMA. Since brain regions also mature in an asymmetric manner in subtle degrees, interpretations of regional cerebral patterns will be helpful. Specific aspects of temporal, spatial, and state organization of EEG polygraphic recordings are subsequently highlighted, but this brief review should be supplemented by more detailed discussions in standard texts (Anders et al., 1971; Dreyfus-Brisac, 1979; Lombroso, 1989; Hrachovy et al., 1990; Pope et al., 1992; Curzi-Dascalova and Mirmiran, 1996).
EEG discontinuity Alternating segments of EEG activity and inactivity (i.e., quiescence) commonly occur in preterm neonates, and have been described as EEG discontinuity or tracé discontinu (Dreyfus-Brisac, 1968). For the child less than 30 weeks’ PMA, neonatal recordings consist of predominantly discontinuous EEG patterns. Varying durations of interburst intervals define this quiescence and have been described by various authors (Hughes et al., 1983, 1987; Connell et al., 1987; Eyre et al., 1988; Benda et al., 1989). For the healthy preterm infant,
113
an interburst interval should follow the “30–20 rule”: an interburst interval should not exceed 30 seconds in duration on multiple occasions for the child less than 30 weeks’ estimated gestational age. As the child matures beyond 30 weeks’ postconceptional age, the interburst interval should be less than 20 seconds in duration. Longer periods of EEG continuity interrupt quiescent intervals after 28 weeks’ PMA. For the preterm infant less than 30 weeks’ PMA, electrographic activities predominate in the vertex central and occipital regions; bitemporal attenuation is commonly observed and reflects underdeveloped frontal and temporal regions of the brain at that level of brain maturity (Figure 8.1).
Synchrony/asynchrony The electrophysiologic description known as asynchrony (Lombroso, 1985) refers to similarly appearing EEG waveforms in homologous head regions (e.g., left and right temporal regions) that are separated by at least 1.5 seconds in time. Healthy preterm neonates typically express varying degrees of physiologic asynchrony. While less than 30 weeks’ PMA, extremely low-birthweight neonates commonly exhibit “hypersynchrony,” given their extreme cortical immaturity. Physiologic asynchrony emerges after 30 weeks’ PMA and persists until 36 weeks’ PMA. Asynchrony in the child at 30–32 weeks for example may be as much as 50% of the discontinuous portion of the sleep cycle. However, after 36 weeks’ PMA the occurrence of asynchrony rapidly drops to 0% by postmaturational term age.
Delta brush patterns An admixture of fast and slow rhythms appears in the preterm EEG record as morphologically discrete waveforms that are identified with preterm neonates at varying PMA. Random or briefly rhythmic 0.3–1.5 Hz delta activity of 50–250 mV is associated with a superimposed rhythm of low- to moderate-amplitude faster frequencies of 10–20 Hz. Historically, different authors have described these complexes as spindle delta bursts, brushes, spindle-like fast waves or ripples of prematurity. For infants less than 28 weeks’ PMA, delta brush patterns are seen in the central and midline locations with only occasional expression in the occipital regions. After 28 weeks’ PMA, brushes appear more abundantly in the occipital followed by the temporal regions. Brushes can be asynchronous or asymmetric, while at other times they may be symmetrical. By term PMA, brush patterns are occasionally noted during the nonREM quiet sleep or transitional sleep segments. Persistent expression or attenuation of brush rhythms in one region or hemisphere may reflect structural lesions.
114
M.S. SCHER
FP3 - T3 T3 - O1 FP4 - T4 T4 - O2 FP3 - C3 C3 - O1 FP4 - C4 C4 - O2 T3 - C3 C3 - CZ CZ - C4 C4 - T4 FZ - CZ CZ - PZ T3 - CZ T4 - CZ EMGCHIN LOC - A1 ROC - A2 RESP. EKG
26wk / 5D/O
26wk ? 1D/O
E/C - head on right
E/C - head on right
on ventilator
on ventilator Rt Leg Mvt 50µv
50µv
2sec
2sec
Fig. 8.1. Segments of electroencephalograms of two preterm infants less than 26 weeks 5 days old and 26 weeks 1 day old respectively. Note the prominent bitemporal attenuation (arrowheads both panels), the rhythmic delta with superimposed delta brushes in the central regions (panel 1 arrow), and the hypersynchronous burst in the second panel. Isolated occipital delta with superimposed occipital theta are also noted in the second panel (arrow).
Occipital theta/alpha rhythms Other patterns can help estimate gestational maturity. Monorhythmic alpha and theta activities are located in the occipital regions of neonates less than 28 weeks’ PMA, commonly referred to as the STOP rhythm (Hughes et al., 1990). This pattern usually persists for 6–10 seconds, can be asynchronous or asymmetric, but also may be synchronous (Figure 8.2). Such a pattern, together with midline/central brushes, is an electrographic feature associated with extremely premature infants.
Temporal theta rhythm A third useful developmental marker which estimates brain maturity is the theta burst, consisting of rhythmic 4.5–6 Hz activities noted in the mid temporal regions. Temporal theta bursts are rarely apparent in infants less than 28 weeks’ PMA but become maximally expressed between 28 and 32 weeks’ PMA (Figure 8.3). Historically, this feature has been described as a “temporal sawtooth wave” (Dreyfus-Brisac, 1979), with amplitudes ranging from 20 to 200 mV. After 32 weeks’ PMA, its incidence rapidly diminishes (Scher et al., 1994b).
FP3 - T3
24wk / 4D/O
T3 - O1 FP4 - T4 T4 - O2 FP3 - C3 C3 - O1 FP4 - C4 C4 - O2 T3 - C3 C3 - CZ CZ - C4 C4 - T4 FZ - CZ CZ - PZ T3 - CZ T4 - CZ EMGCHIN LOC - A1 ROC - A2 RESP. EKG
20µv 2sec
Fig. 8.2. An electroencephalogram segment of a 24-week 4-day-old female with prolonged occipital theta alpha that is asymmetric in amplitude (arrows), characteristic of the STOP rhythm.
ONTOGENY OF EEG SLEEP FROM NEONATAL THROUGH INFANCY PERIODS FP3 - T3
115
28wk ? 7D/O
28wk / 11D/O
T3 - O1 FP4 - T4 T4 - O2 FP3 - C3 C3 - O1 FP4 - C4 C4 - O2 T3 - C3 C3 - CZ CZ -C4 C4 - T4 FZ - CZ CZ - PZ T3 - CZ T4 - CZ EMGCHIN LOC - A1 ROC - A2 RESP. EKG
E/C head on right
E/C head on right
50µv
50µv 2sec
2sec
Fig. 8.3. Segments of electroencephalograms of two preterm infants approximately 29 weeks’ postmaturational age, depicting abundant delta in multiple head regions as well as temporal theta activity (first panel: arrow), temporo-occipital, vertex and central brush patterns (first and second panels: arrowheads), and rhythmic occipital delta (second panel: arrow).
Delta wave patterns Rhythmic waveforms consisting of delta activity can also help estimate gestational maturity of the asymptomatic preterm neonate. Delta patterns in the central or midline locations are predominant for the infant less than 28 weeks’ gestation together with bitemporal attenuation, as previously described. Other delta rhythms occur in the temporal and occipital locations, particularly after 28 weeks’ gestation (Figures 8.4 and 8.5). Between 30 and 34 weeks’ PMA, temporal and occipital delta rhythms become quite prominent and rhythmic, with durations that may exceed 30 seconds to 1 minute (Figures 8.2 and 8.3).
FP3 - T3
30wk ? 5D/O
T3 - O1 FP4 - T4 T4 - O2 P3 - C3 C3 - O1 FP4 - C4 C4 - O2 T3 - C3 C3 - CZ CZ - C4 C4 - T4 FZ - CZ CZ - PZ T3 - CZ T4 - CZ EMGCHIN
Midline theta/alpha activity This waveform pattern (Hayakawa et al., 1987) appears in recordings of both preterm and full-term infants, particularly during transitional or quiet sleep segments (Figure 8.6). This commonly observed pattern is sharply contoured and usually of low to moderate amplitude (Figure 8.7) in the alpha or theta ranges. Although it is morphologically similar to a sleep spindle, classical spindles do not appear in the central regions until 2–4 months of age (Lenard, 1970). While
On Ventilator
LOC - A1
E/C
Head Right
ROC - A2 RESP. EKG
50µv 2sec
Fig. 8.4. An electroencephalogram (EEG) segment of a nearly 30-week 5-day-old postmaturational age male, depicting the onset of continuous EEG segment with a left temporal theta burst, (arrow), prominent delta, and superimposed delta brushes in the temporal regions (arrowhead). Note that the temporal delta is more rhythmic than in Figure 8.3.
116
M.S. SCHER FP3 - T3
29wk ? 3D/O
T3 - O1 FP4 - T4 T4 - O2 FP3 - C3 C3 - O1 FP4 - C4 C4 - O2 T3 - C3 C3 - CZ CZ - C4 C4 - T4 FZ - CZ CZ - PZ T3 - CZ T4 - CZ EMGCHIN Jerk
LOC - A1 ROC - A2
Tongue Mvt E/C head on right
RESP. EKG
50µv 2sec
Fig. 8.5. An electroencephalogram (EEG) segment of a 29-week 3-day-old male with a shifting asymmetry between the left temporal-central region (arrow) and the right temporal region (arrowhead), characteristic of physiologic interhemispheric asynchrony. Also note the prominent temporal theta and brushes as well as diffuse delta slowing during this discontinuous portion of the EEG.
this pattern may appear sharply contoured, this ageappropriate electrographic rhythm does not reflect a pathological or encephalopathic state, and might be expressed despite significant lack of other ageappropriate background rhythms.
MATURATION OF NON-EEG PHYSIOLOGIC BEHAVIORS WHICH DEFINE STATE IN THE PRETERM INFANT State transitions in preterm infants less than 36 weeks’ PMA are not as easily identified as with the term infant. Sleep reorganization is expected to occur at, or around, 36 weeks’ PMA, which is similar to the coalescence of physiologic behaviors documented on abdominal sonography of temporally synchronous fetal behaviors of both primates and humans (Myers et al., 1995). As a rule, state organization in the preterm infant remains rudimentary and underdeveloped
(Curzi-Dascalova et al., 1988, 1998) at less than 36 weeks’ PMA. The following summary serves as an introduction to a discussion of specific physiologic behaviors which highlight state differentiation in the preterm infant with increasing PMA. Rapid eye movements (REMs) represent one of the main identifying features of rudimentary active sleep in the preterm infant. Eye movement phenomena become consistently time-locked to continuous EEG activities as early as 30–31 weeks’ gestation (CurziDascalova et al., 1988). However, neonates as premature as 24 weeks’ PMA already have a fixed and reciprocal occurrence with EEG discontinuity with an interval of approximately 1 hour (Scher et al., 2005a). Using fetal sonography (Prechtl and Nijhuis, 1983), eye movements of the fetus are noted during active sleep. REM activities are not random and occur in a predictable interval despite brain immaturity (Dittrichova´ et al., 1972; Scher et al., 2005a). Various classes of
ONTOGENY OF EEG SLEEP FROM NEONATAL THROUGH INFANCY PERIODS 34wk / 23D/O
FP3 - T3 T3 - O1 FP4 - T4 T4 - O2 FP3 - C3 C3 - O1 FP4 - C4 C4 - O2 T3 - C3 C3 - CZ CZ - C4 C4 - T4 FZ - CZ CZ - PZ T3 - CZ T4 - CZ EMGCHIN
E/C head on right
LOC - A1 ROC - A2 RESP.
50µv
EKG
2sec
Fig. 8.6. An electroencephalogram segment for a 34-week 23-day-old female with a prominent vertex and parasagittal burst of theta/alpha activity (arrows). Note the rare delta brushes and absent temporal theta at a postconceptional age of 37 weeks.
117
REM have been described during different states of sleep in the neonate, and the number and types of REM movements evolve with brain maturation (Ersyukova, 1980; Lynch and Aserinsky, 1986). A study of multiple physiologic behaviors during sleep in the preterm infant correlated the occurrence of REM with more continuous EEG tracings, while it correlated negatively with discontinuous EEG segments (Scher et al., 1994d) in preterm infants as early as 30 weeks’ PMA (Figures 8.8 and 8.9). Motility patterns are also an integral part of neonatal state definition but differ between preterm and fullterm infants. Different motility patterns emerge at increasing PMA, for both the fetus as well as the extrauterine-reared neonate (Robertson, 1982, 1987). Myoclonic and whole-body movements predominate for the preterm infant (Prechtl et al., 1979; Fukumoto et al., 1981) while smaller, slower segmental body movements are seen in the full-term neonate. Statespecific decreases in the number of small and large body movements have been correlated with increasing EEG discontinuity in preterm infants (Scher et al., 1994d), while increased head and facial movements are associated with only active sleep, between 30 and 36 weeks’ PMA.
40wk / 2D/O
FP3- T3 T3 - O1 FP4 - T4 T4 - O2 FP3 - C3 C3 - O1 FP4 - C4 C4 - O2 T3 - C3 C3 - CZ CZ - C4 C4 - T4 FZ - CZ CZ - PZ T3 - CZ T4 - CZ EMGCHIN LOC - A1 ROC - A2
E/C head right
RESP. EKG
50µv
2sec
Fig. 8.7. An electroencephalogram (EEG) segment of a 40-week 2-day-old female, depicting mixed-frequency active sleep, characterized by continuous EEG, body movements, rapid eye movements (arrowhead), and irregular respirations and heart rate. Note the onset of a spontaneous arousal coincident with a temporary flattening of the EEG background.
118
M.S. SCHER 41wk ? 1D/O
FP3 - T3 T3 - O1 FP4 - T4 T4 - O2 FP3 - C3 C3 - O1 FP4 - C4 C4 - O2 T3 - C3 C3 - CZ CZ - C4 C4 - T4 FZ - CZ Cz - PZ T3 - CZ T4 - CZ EMGCHIN LOC - A1 ROC - A2
E/C Head right
RESP. EKG
50µv 2sec
Fig. 8.8. An electroencephalogram segment of a 40-week 1-day-old female documenting high-voltage slow quiet sleep. Regular respirations and the absence of rapid eye movements are noted. 40wk / 2D/O
Fp3 - T3 T3 - O1 Fp4 - T4 T4 - O2 Fp3 - C3 C3 - O1 Fp4 - C4 C4 - O2 T3 - C3 C3 - CZ CZ - C4 C4 - T4 FZ - CZ CZ - PZ
et al., 1986; Glotzbach et al., 1989). Using spectral analyses, decreased variability of cardiorespiratory behavior during quiet sleep is seen at increasing PMA (Scher et al., 1995). However, EEG measures appear to be an alternative for state prediction to noncerebral measures, such as cardiorespiratory behavior. In a study of multiple sleep behaviors in the preterm infant less than 36 weeks’ PMA, REMs rather than cardiorespiratory, motility, and temperature changes predictably varied with EEG changes, suggesting that specific brain regions physiologically coalesce with EEG activities before other neuronal systems (Scher et al., 1997).
T3 - CZ T4 - CZ
ASSESSMENT OF STATE ORGANIZATION IN THE FULL-TERM INFANT
EMGCHIN LOC - A1 ROC - A2
E/C Head Right
RESP. EKG
50 µv 2 sec
Fig. 8.9. An electroencephalogram segment of a 40-week 15-day-old female, documenting a discontinuous trace´ alternant, quiet sleep segment.
Maturational changes in cardiorespiratory behavior have also been studied in the preterm infant. Periodic breathing and respiratory pauses are physiological events that commonly occur in preterm infants (Martin
Extensive information has been published over the last half-century with respect to the functional significance of the relatively short ultradian sleep rhythm in the near-term and term neonate (Hildebrandt, 1986). For older infants, the human sleep cycle is an ultradian period with an interval of 75–90 minutes. The full-term neonate expresses an ultradian cycle that is approximating 30–70 minutes in duration (Scher et al., 1992). Sleep segments that comprise the neonatal sleep cycle also differ from older individuals, comparing EEG and polysomnographic behaviors. Two active and two
ONTOGENY OF EEG SLEEP FROM NEONATAL THROUGH INFANCY PERIODS quiet sleep segments as well as transitional or indeterminate sleep segments have been described. Arousal periods, defined as reactivity, occur both within and between the sleep segments. Indeterminate or transitional sleep as well as the arousal phenomena are important expressions of sleep continuity in the immature brain. State definitions in the term infant traditionally require the temporal coalescence of specific physiologic behaviors. Based on visual analyses, comparisons between EEG and non-EEG behaviors are temporally observed to determine state for either adults or children (Rechtschaffen and Kales, 1968). Visual interpretations of EEG sleep states are also easily identified for the full-term neonate (Pope et al., 1992). Active, or REM, sleep for the full-term neonate is traditionally associated with the coalescence of REMs, increased variability of cardiorespiratory rates, low muscle tone in the context of low-voltage or mixed-frequency continuous EEG patterns, and the abundance of body movements. Conversely, quiet or non-REM sleep is associated with the absence of REMs, fewer body movements, higher muscle tone, and decreased variability in respiratory rates in the context of continuous high-voltage slow or discontinuous EEG patterns. The above-described patterns are not expressed until after 36 weeks’ PMA and no longer seen beyond 46–48 weeks’ PMA. Typically the ultradian sleep cycle begins as an active sleep after sleep onset in over 50% of newborns. This initial active sleep segment is a mixed-frequency EEG segment which comprises 25– 30% of the total sleep cycle. This active sleep segment is then followed by a brief high-voltage slow quiet sleep segment which is approximately 3–5% of the sleep cycle. Subsequently, a discontinuous quiet sleep period (historically described as a tracé alternant pattern) now comprises approximately 25% of the sleep cycle of the neonate. Finally, a postquiet sleep active sleep segment known as low-voltage irregular comprises approximately 15% of the cycle. Transitional or indeterminate sleep comprises 10–15% of the sleep cycle. While the child does not yet express a strong diurnal or circadian rhythmicity of sleep, wakefulness is distributed over a 24-hour period. As many as 6–8 hours of waking sleep over a 24-hour period may occur in the neonate. A cross-sectional analysis of sleep and wakefulness over 24 hours in preterm and full-term newborns documented diurnal differences in the expression of EEG sleep patterns (Biagioni et al., 2005). For example, higher percentages of quiet sleep were expressed during daytime hours. Other environmental conditions such as sleep position can alter the expression of EEG frequencies during quiet sleep, consequently diminishing arousal when the infant is
119
placed in a prone position. These two reports offer additional insights into diverse environmental influences of time of day and position on sleep organization and arousal. Two biorhythmic processes define the temporal organization of sleep in the neonate: a weak circadian sleep wave rhythm is present, and a stronger ultradian REM and non-REM rhythm is also active (Glotzbach et al., 1995). Both biorhythms evolve with increasing age. Internal “biologic clocks” become better organized around environmental cues, such as light/dark cycle, temperature, noise, and social interaction (Anders et al., 1995). For the normal full-term neonate, sleep alternates with waking states in a 3–4-hour cycle, during both the night and day. This has historically been referred to as the basic rest/activity cycle. Within the first month or two of life after birth for the full-term infant, sleep/wake state reorganization begins, particularly with a more dominant diurnal effect to environmental cues. Circadian rhythmicity of body temperature and heart rate is noted in approximately 50% of preterm infants at 29–35 weeks’ PMA (Mirimiran and Kok, 1991). Yet, stronger ultradian rhythms over a 3–4-hour duration correspond to social intervention such as feeding (Rechtschaffen and Kales, 1968). Increases in body movement activities as well as heart rate and decreases in rectal and skin temperatures are noted during interventions, reflecting changes in the infant’s microenvironment and the infant/caretaker interaction. The length of the ultradian EEG sleep cycle increases with maturing postconceptional age, demonstrating a positive correlation between cycle length and increasing PMA (Scher et al., 1994d).
SLEEP ONTOGENESIS ^ STATE MATURATION FROM FETAL THROUGH INFANCY PERIODS Reasons for the continuity of fetal state expression from intrauterine through neonatal ages prior to 46 weeks’ PMA remain obscure. This physiologic continuity may reflect the need for homeostasis of the fetus during the transition from intrauterine to extrauterine environments, requiring approximately a postnatal month of brain development before infancy sleep patterns begin to emerge. State development involves multiple interconnected neuronal networks which are actively maturing during fetal life. Beginning as early as 10 weeks’ gestational age, the human fetus displays spontaneous movements as visualized on ultrasonography. These movements are now more clearly visualized with three-dimensional ultrasonography which can document more readily eye opening and closing and rhythmic body movements
120 M.S. SCHER while fetal heart rate is electronically recorded. All EEG analyses, increases in theta power by 9 months of these behaviors allow estimation of fetal state transiage (Sterman et al., 1977; Samson-Dollfus et al., 1983) tions (Nijhius et al., 1984). Rhythmic cycling of motoric herald the emergence of the S1 and S2 segments of activity has been described in fetuses as young as the non-REM sleep segment, codified for adult sub20–28 weeks’ gestation (Parmelee et al., 1967), with jects by Rechtschaffen and Kales’ (1968) sleep state the fetal rest–activity pattern for long quiescent pericriteria. A decline of theta power after 9 months was ods lasting minutes to hours, during which time no observed in nocturnal sleep studies of infants, interrespiratory movements are noted (Dawes et al., 1972). preted as a change in sleep regulatory processes Preterm infants as immature as 24 weeks’ PMA reflected as a dissipation of sleep propensity during express cyclicity of rudimentary state, when time interinfancy (Jenni et al., 2004). There is also a continual vals are measured between successive epochs of EEG decrease in total sleep time, REM sleep, and indetermidiscontinuity and REM periods (Scher et al., 2005a). nate sleep, as well as concomitant increases in waking Cycle times vary but usually range between 40 and time and non-REM sleep, particularly stages I–II 60 minutes (Sterman and Hoppenbrauwers, 1971). non-REM sleep. Behavioral estimations of quiet (i.e., non-REM) sleep Sleep organization for 15 normal infants was studapproximate 53% in the 30-week conceptional age ied in a natural home environment during six 24-hour study, increasing to 60% by near-term ages. sleeping periods over 12–24 months after birth (Louis State studies of fetal baboons documented similar et al., 1997). Sleep staging was scored according to coalescence among EEG and non-EEG behaviors while adult criteria (Rechtschaffen and Kales, 1968) with in the intrauterine environment, similar to humans modifications for children by Guilleminault and (Myers et al., 1993). These same temporal relationships Souquet (1979). While these authors reconfirmed are expressed by preterm neonates in an extrauterine earlier reported changes in percentages of total sleep environment. These physiologic interrelationships time, REM, non-REM, indeterminate sleep, and defining state persist to 4–6 weeks of postnatal life, wakefulness, the authors also reported age and day/ after which infant sleep patterns gradually emerge to night effects on sleep ontogenesis. Modifications with resemble adult sleep rhythms between the first and secage were more precocious and more pronounced in ond years of life, following the coalescence of EEG diurnal expression over a 24-hour cycle, especially and non-EEG components of state approximately regarding REM sleep. During the nocturnal part of 1 month before term ages. the 24-hour cycle, there was a significant increase Specific features regarding sleep organization occur in sleep efficiency during the REM period after after 46–48 weeks’ estimated gestational age (Kahn 12 months of age. The authors went on to demonet al., 1996; de Weerd and van den Bossche, 2003). strate that the total sleep duration and the number Lengthening of the overall sleep cycle, as well as reorof awakenings decreased. These authors point to the ganization of sleep architectural segments, are high stability in the percentage of slow-wave sleep expressed; gradual reductions in REM sleep percentduring the first 2 years of life. Until 12 months of age are noted while non-REM sleep becomes more age, stage II/REM sleep ratio equals 1, and sleep abundant. Rather than a sleep-onset active or REM changes occur earlier during the diurnal part of the sleep after wakefulness, non-REM sleep segments first 24-hour cycle. These examples of sleep ontogeny appear after waking to drowsiness. Non-REM sleep suggest how developmental neurophysiologic changes stages I–IV as defined (Rechtschaffen and Kales, occur within neuronal networks that are responsible 1968) do not fully develop until late infancy. Highfor sleep expression. These data also highlight the voltage delta slow non-REM sleep remains the preemergence of a well-developed circadian rhythm after dominant electrographic expression of this segment 3 months of age, prior to the maturation of nocturnal of the sleep cycle, similar in EEG frequency distribusleep organization. This coincides with the milestone tion to the high-voltage slow quiet sleep segment of of continuous nighttime sleeping commonly asked the neonate. Reductions in arousals, body, and REMs after by pediatricians and anticipated by parents. are noted as the child matures past 46–48 weeks’ PMA. Those brain structures responsible for circadian During the first 3 months of life, rapid maturation cycling predate other regions that are responsible for of electrical activities in the brain occurs, such as generation of S2 sleep and the decrease in REM sleep. the disappearance of tracé alternant, the emergence Nine months of age appears to represent an important of sleep spindle activity, and the emergence of developmental age for sleep maturation. During the “adult-like” delta wave activity (Curzi-Dascalova, night, significant reductions in REM sleep and 1977; Ellingson, 1979; Louis et al., 1992; Schechtman increases in S2 occur after this age. Rapid acceleraet al., 1994). Using quantitative assessments of spectral tion in brain myelination, dendritic arborization, and
ONTOGENY OF EEG SLEEP FROM NEONATAL THROUGH INFANCY PERIODS synaptogenesis occurs after 9 months, resulting in increased neuronal interactions between brainstem and thalamocortical structures (Van der Knaap and Valk, 1990). Better understanding of sleep ontogeny during infancy offers insights into the use of sleep analyses to predict behavioral patterns and later neurobehavioral phenotypes during childhood. A longitudinal intervention study documented nighttime sleep–wake patterns and self-soothing from birth to 1 year of age (Nikolopoulou and St. James-Roberts, 2003). Specific infant and parental factors interact to influence the development of self-soothing. Such a tract can be interpreted as the infant’s ability to regulate states of arousal. This transactional model was proposed to advance our understanding of daytime regulatory behavior for vigilance and attention during childhood based on earlier self-soothing abilities during sleep. These insights may foster research into interventional programs during infancy which promote improved sleep initiation and maintenance during nighttime, with positive benefits for children and caregivers over shortand long-term time periods (Burnham et al., 2002).
Ontogeny of autonomic behavior during sleep: heart rate variability As the neonate matures into infancy and early childhood, changes in cardiovascular functions during sleep reflect changes in autonomic nervous system dominance of neuronal networks subserving cardiac activity. In general, sympathetic nerve activity, blood pressure, and heart rate are lower during non-REM sleep than in wakefulness. During REM sleep, sympathetic nerve activity increases, reaching values greater than those measured during wakefulness (Somers et al., 1995), reflecting increased sympathetic control of cardiovascular function. Because short-term oscillations of heart rate (i.e., heart rate variability (HRV)) reflect autonomic nervous system activity, these values can be useful for assessing autonomic control under various physiologic and pathologic conditions. Spectral analysis of HRV can provide quantitative estimations of the balance between sympathetic and parasympathetic control (Baharav et al., 1995). Short-term HRV spectra distinguish three main power components. The higher-frequency component (range 0.15–0.40 Hz), corresponding to heart rate and blood pressure oscillations induced by respiratory activity, mediated by the vagal branch of autonomic nervous system, is considered a marker for parasympathetic activity. Lower-frequency components (0.04– 0.15 Hz) reflect baroreflex control of systemic blood pressure, providing a measure of sympathetic activity.
121
Using time domain and frequency domain analyses of HRV signals, researchers have reported parasympathetic predominance during non-REM, while increased sympathetic activity is expressed during REM sleep (Gaultier, 1995). Sleep stage and age both significantly influence short-term HRV during sleep in both healthy infants and children (Villa et al., 2000). Greater parasympathetic control during sleep is observed for children than for infants. This difference may reflect autonomic nervous system maturation that takes place over the first several years of life (Chatow et al., 1995). Greater insights into interactions among physiological systems subserving sleep can be achieved by time domain-specific nonlinear modeling techniques. For example, the use of coupled-oscillation models can be used to describe sleep organization and maturation, as reflected in cardiorespiratory behaviors over the neonatal and infant sleep cycle (Mrowka et al., 2003). While there exists a symmetrical interaction between respiration and heart rhythms at birth, the direction of interaction is mainly determined by respiratory frequency. This physiological interaction becomes practically unidirectional by 6 months of life. Speculations regarding altered expressions of these physiologic dynamics with stress and disease may uncover neuronal mechanisms predicting epilepsy, sleep problems, and cognitive-behavioral disorders (Stam, 2005). In summary, sleep ontogenesis during infancy gradually evolves into adult sleep organization over the first 2 years of life with temporal coalescence of specific neuronal networks. Circadian rhythms appear after 3 months of age, followed by expression of an adult ultradian sleep cycle after 9 months of age. There is a lengthening of the ultradian sleep cycle after 12 months of age. Reductions in arousals, motility, REMs, and sympathetic control reflect developmental changes within multiple brain regions which are responsible for sleep initiation and maintenance.
BRAIN ADAPTATION TO STRESS AS REFLECTED IN SLEEP REORGANIZATION Endogenous or exogenous factors can alter the ontogenesis of specific physiologic behaviors during sleep. This is exemplified by neurophysiologic studies that compare differences between preterm and full-term infants at matched postmaturational term ages concerning sleep architecture, continuity, phasic, spectral, cardiorespiratory, and temperature behaviors (Scher et al., 1992, 1994e–h). Unlike the full-term infant, sleep of the preterm infant adapts to an extrauterine environment by expressing a one-third longer sleep cycle, a greater
122
M.S. SCHER
percentage of quiet sleep, fewer movements, and shorter arousals. Preterm infants also exhibit higher rectal temperatures over the ultradian cycle, with less change from non-REM to REM segments. Greater cardiorespiratory irregularity is noted during quiet sleep, and lower spectral EEG energies are observed during specific sleep segments. These differences reflect conditions of prematurity on brain maturation relatively independent from medical illnesses after birth; adaptation of brain function for the preterm infant in an extrauterine environment represents physiologic dysmaturity to biological and/or environmental stresses (Scher, 1997a; Scher et al., 2003b). Such sleep differences reflect physiologic expressions of neural plasticity involving interconnected macronetworks subserving multiple neuronal pathways throughout the neuroaxis. Dysmature EEG sleep measures may also help predict neurodevelopmental performance for neonates with clinical risk factors other than prematurity, such as prenatal substance exposure (Scher et al., 1988), chronic lung disease (Hahn and Tharp, 1990), or general medical complications (Beckwith and Parmelee, 1986). Documentation of the persistence or resolution of dysmature sleep behaviors during infancy for clinical risk groups needs to be better addressed. Reprogramming of molecular pathways responsible for activities of neuronal networks after stresses can result in positive or negative consequences of experience-dependent development, inherent to the process of developmental neural plasticity. Changes in environmental conditions for sleep in preterm infants can alter sleep architecture and continuity measures as markers of brain behavior (Bertelle et al., 2005). Fp3 - T3 T3 - O1 Fp4 - T4 T4 - O2 Fp3 - C3 C3 - O1 Fp4 - C4 C4 - O2 T3 - C3 C3 - CZ CZ - C4 C4 - T4 FZ - CZ CZ - PZ T3 - CZ T4 - CZ EMGCHIN LOC-A1 ROC-A2 RESP. EKG
COMPUTER-ASSISTED ANALYSES OF EEG SLEEP ORGANIZATION IN NEONATES AND INFANTS Relationships among multiple physiologic processes are certainly less developed in the preterm infant. State transitions are more difficult to recognize, particularly over short recording intervals. Even with longer recording times, less well-developed associations among physiologic variables may not be obvious by visual analysis. Automated systems for EEG sleep analyses can complement visual inspection (Scher et al., 1990) (Figure 8.10). Computer analyses better characterize relationships among electrographic and polysomnographic components over extended recording intervals, and better detect rudimentary sleep behaviors. Studies which compare computer and visual analyses of neonatal EEG recordings through infancy have ascertained which physiologic relationships best represent state expression; spectral EEG energies and REM best define maturational trends when compared to other measures in the preterm infant (Hildebrandt, 1986; Scher et al., 1992, 1995, 1997) (Figure 8.11). Conversely, other noncerebral measures such as cardiorespiratory, motility, and temperature changes may predict unique maturational trends of sleep state organization regarding these interconnected neural networks. Computer algorithms may better detect diurnal or nocturnal rhythmicities more accurately than by visual inspection (Scher et al., 1990, 2005b). Comparatively less attention has been directed to automated analyses of neonatal EEG sleep studies compared with older persons (Agarwal and Gotman, 2002). 40wk / 2D/O
E/C Head Right
50 µv
2 sec
Fig. 8.10. An electroencephalogram segment of a 40-week 2-day-old female, documenting a low-voltage irregular active sleep segment. Note prominent sucking and rapid eye movements.
ONTOGENY OF EEG SLEEP FROM NEONATAL THROUGH INFANCY PERIODS
123
Temperature (°C)
37.8
36.8 0
20
40
60
80 100 time (mins)
120
140
160
180
0
20
40
60
80
120
140
160
180
EEG (ave) energy
30000
0 1.0
100
DELTA-band energy
time (mins)
0.0 0
20
40
60
80 100 time (mins)
120
140
160
180
20
40
60
80 100 time (mins)
120
140
160
180
state 10 state 21 state 31 state 41 state 32 state 22 0
Fig. 8.11. A 3-hour summary of physiological behaviors constituting neonatal sleep at full-term age. In the lower tracing: state 10 awake, state 21 mixed-frequency active sleep, state 31 high-voltage slow quiet sleep, state 41 indeterminate sleep, state 32 trace´ alternant quiet sleep, state 22 low-voltage irregular active sleep. Spectral delta and total electroencephalogram (EEG) energies in panels 2 and 3 illustrate changes in these values, depending on the segment of the neonatal sleep cycle. Note the minimum total EEG energy and maximum delta energy during trace´ alternant quiet sleep. The top panel illustrates a slower multiple-hour temperature rhythm which changes over multiple sleep cycles.
Since an earlier review of this topic (Scher et al., 1990), further advancements in the development of both computerized devices and mathematical programming have been achieved (Scher et al., 2005b). To succeed in the development of an automated state detector for neonates, technical innovations must recognize the unique neurophysiologic expressions of state transitions of the newborn that are not expressed for the older patient. A short list of these unique electrographic/ polysomnographic behaviors include a shorter sleep cycle, prominent EEG delta rhythms in different regional locations, intra- and interhemispheric electrographic asynchrony, discrete neonatal waveform
patterns (i.e., delta brush and theta burst patterns), a high percentage of periodic breathing, a greater number and heterogeneity of REMs, and unique motor patterns that reflect fetal postural reflexes which precede the expression of more sophisticated developmental movement patterns. Previous neonatal sleep studies initially applied automated techniques to assess functional brain maturation, using analyses that were based on assumptions of linearity, without consideration of time-dependent changes (Havlicek et al., 1975; Giaquinto et al, 1977; Sterman et al., 1977; Lombroso, 1979; Willekens et al., 1984; Connell et al., 1987; Bes et al., 1988; Eyre et al.,
124
M.S. SCHER
1988; Kuks et al., 1988). The preferred methodological approach has been fast Fourier transform analyses, studied initially with full-term neonates (Ktonas et al., 1995; Witte et al., 1997; Lehtonen et al., 1998; Eiselt et al., 2001; Field et al., 2002), followed by more recent reports in preterm infants (Sawaguchi et al., 1996; Eiselt et al., 1997; Myers et al., 1997; Holthausen et al., 2000; Schramm et al., 2000; Kuhle et al., 2001; Vanhatalo et al., 2002). Similar calculations, based primarily on assumptions of linearity, were also described for specific neonatal and infant risk groups for sudden infant death syndrome (Schechtman et al., 1995), apnea (Schramm et al., 2000), hyperbilirubinemia (Gurses et al., 2002), white-matter necrosis (Inder et al., 2003), and asphyxia (Hellstro¨m-Westas, 1992), applying power analyses to one particular physiologic behavior, with little attention to the multiple neuronal networks that contemporaneously express state transitions. Single-channel monitoring devices have demonstrated that important global maturational trends can be documented using standard spectral values (Burdjalov et al., 2003) without regional or hemispheric specificity. Few reports have combined EEG and non-EEG measures to study more comprehensively newborn sleep states (Pan and Ogawa, 1999; Regalado et al., 2001). One research group has applied automated analysis methods of neonatal sleep to both EEG and non-EEG measures, combining computations to detect and quantify linear and nonlinear sleep behaviors. Simultaneous assessments of multiple cerebral and noncerebral measures are emphasized to define neonatal state (Scher et al., 1992). Spectral analyses of EEG (Scher et al., 1994f, h, 1995, 2003a; Scher, 1996), cardiorespiratory behavior (Scher et al., 1994f, 2003b), arousal behavior (Scher et al., 1992, 1994h, 2003c), and REMs (Scher et al., 1992, 1996, 2003a), establish that there are important physiologic differences during sleep between healthy preterm and full-term cohorts. Nonlinear computations for feature extraction of EEG signals (Turnbull et al., 2001), arousals (Scher et al., 2003c), and state/outcome prediction (Turnbull et al., 2003) have also been suggested as a part of the overall strategy to develop an automated neonatal state detector. Differences in the functional brain organization between neonatal cohorts have been incorporated into a statistical model that offers a mathematical paradigm to define physiologic brain dysmaturity of preterm neonates at corrected full-term ages. This dysmaturity index is based on seven selected physiologic measures (Scher, 1997a, b; Scher et al., 1997, 2003a, c) that best represent differences in functional brain organization and maturation between healthy preterm and fullterm cohorts. This statistical model characterizes any
particular physiologic behavior of the preterm infant as either delayed or accelerated in relation to full-term controls. Automated methodologies which can capture these selected behaviors over time offer an opportunity to characterize the process of developmental neuroplasticity within the immature brain of a neonate who has been stressed by environmental or disease conditions (Scher et al., 2005b). Computer analyses of EEG sleep during infancy have also helped demonstrate the physiologic ontogenesis of the neuronal macronetworks (Woodruff, 1979; Harper et al., 1981; Harmony, 1984; Bell and Fox, 1992; Dawson et al., 1992; Marshall et al., 2002). EEG frequencies with maturation, based on power spectral analyses, document alterations in all frequency bandwidths, particularly at the higher frequency ranges for human EEG (i.e., the alpha and beta ranges). These changes are surrogate markers of cognitive and behavioral development, especially in the frontal lobe (Thatcher, 1991; Dawson et al., 1992). Also, deviations in the ontogenesis of spectral signals differentiate specific at-risk populations of children (Shibagaki and Kiyono, 1983; Shibagaki et al., 1985; Hauser et al., 1993). Relatively little attention has been devoted to very-high-frequency spectral bandwidths (> 40–1000 Hz) which have been studied primarily in adult populations. Spectral analyses have also been performed involving sleep studies for non-EEG physiologic parameters, particularly cardiorespiratory measures, as discussed under the section on ontogeny of autonomic behavior during sleep. Changes in the balance between sympathetic and parasympathetic influences during sleep can be assessed by the spectral analysis of HRV (Villa et al., 2000). Few studies extend these evaluations up through infancy. Most studies dealing with maturation of cardiorespiratory behavior do not include ages beyond 6 months of age.
Sleep ontogenesis and neural plasticity Advances in developmental neuroscience over the last 15 years have expanded our knowledge base regarding the sequential steps in brain maturation. Third-trimester and early postnatal developmental stages of brain maturation encompass extensive remodeling or resculpting. This process of experience or activity-dependent development signifies how signaling at the molecular level influences both individual cell types as well as neuronal networks of interconnecting cell groups which subserve more complex functions. Use or disuse of specific neuronal populations or networks will lead to pruning and remodeling of the brain’s neuronal circuitry. During the last trimester of pregnancy and
ONTOGENY OF EEG SLEEP FROM NEONATAL THROUGH INFANCY PERIODS into the first year of life, dendritic arborization, synaptogenesis, myelinization, and neurotransmitter development rapidly evolve in the immature brain (Goldman-Rakic, 1987). Apoptosis or programmed cell death also contributes to modifying brain structure or function during both prenatal and postnatal periods (Bredesen, 1995; Hughes et al., 1999). Adverse conditions of prematurity (i.e., during both prenatal and postnatal time periods) from medical illnesses and environmental stresses collectively alter this process of activity-dependent development and apoptosis, changing neuronal circuitry relative to the stage of maturation. Given that remodeling of neuronal connectivity is ultimately required for the expression of complex neurobehaviors of sleep, cognition, emotion, and social skills at older ages (Caviness, 1989), aberrant remodeling will alternatively contribute to neurocognitive and neurobehavioral deficits. Automated neurophysiologic methodologies can assess brain organization and maturation in the newborn, offering a surrogate marker for activity-dependent development of the fetal and neonatal brain. Computational algorithms applied to selected physiologic measures of neonatal sleep can provide insights into the process by which neuronal networks change and adapt over longer periods of time during extrauterine life under adverse medical and socioeconomic conditions, and in the context of genetic endowment. Applications and methods of nonlinear dynamics to experiments in neurobiology will help characterize better the biologic process of neuroplasticity (Arabanel and Rabinovich, 2001; Stam, 2005). Computational analyses of complex physiologic behaviors reflect changes in neuronal circuitry and can enhance our understanding of the encoding and transmission of information by neuronal networks that subserve human performance ranging from sleep to cognition. The application of these processing techniques in both neonatal intensive care and pediatric sleep laboratory settings will permit better assessment of EEG sleep state organization and maturation through computational neuroscience.
SUMMARY Serial neonatal and infant electroencephalographic/ polysomnographic studies document the ontogeny of cerebral and noncerebral physiologic behaviors, based on visual inspection or computer analyses. EEG patterns and other physiologic relationships serve as templates for normal brain maturation, and also help distinguish intrauterine from extrauterine development. Such strategies will ultimately improve our diagnostic skills for the care of the high-risk fetus, neonate, and infant.
125
EEG sleep studies remain the only bedside neurodiagnostic procedure which provides a continuous record of cerebral function over long periods of time. While other advanced methods of anatomical or functional inquiry, such as volumetric and functional magnetic resonance imaging, report brief snapshots of cerebral anatomy and function, neurophysiologic studies provide a time- and frequency-dependent functional perspective into brain ontogeny. Sleep ontogenesis in neonates and infants can document expected patterns of brain maturation, to anticipate better deviations from these biologically programmed processes under stressful and/or pathological conditions.
ACKNOWLEDGMENT This study was supported in part by grants NS01110, NS26793, NS34508, NR09814, NR04926, and HL07193.
REFERENCES Agarwal R, Gotman J (2002). Digital tools and polysomnography. J Clin Neurophysiol 19: 136–143. Ajmone-Marsan, C (Ed.), (1986). American Electroencephalographic Society guidelines in EEG and evoked potentials. J Clin Neurophysiol 3 (Suppl 1): 1–152. Anders T, Ende R, Parmelee A (1971). A Manual of Standardized Terminology, Technique, and Criteria for Scoring of States of Sleep and Wakefulness in Newborn Infants, UCLA Brain Information Service. NINDS, Neurological Information Network, Los Angeles. Anders TF, Sadeh A, Appareddy V (1995). Normal sleep in neonates and children. In: R Ferber, M Kryger (Eds.), Principles and Practice of Sleep Medicine in the Child. WB Saunders, Philadelphia. Arabanel ADI, Rabinovich MI (2001). Neurodynamics: nonlinear dynamics and neurobiology. Curr Opin Neurobiol 11: 423–430. Baharav A, Kotagal S, Gibbons V et al. (1995). Fluctuations in autonomic nervous activity during sleep displayed by power spectrum analysis of heart rate variability. Neurology 45: 1183–1187. Beckwith L, Parmelee AH Jr (1986). EEG patterns of preterm infants, home environment, and later IQ. Child Dev 57: 777–789. Bell MA, Fox NA (1992). The relations between frontal brain electrical activity and cognitive development during infancy. Child Dev 63: 1142–1163. Benda GI, Engel RCH, Zhang Y (1989). Prolonged inactive phases during the discontinuous pattern of prematurity in the electroencephalogram of very-low-birthweight infants. Electroencephalogr Clin Neurophysiol 72: 189–197. Bertelle V, Mabin D, Adrien J et al. (2005). Sleep of preterm neonates under developmental care or regular environmental conditions. Early Hum Dev 81: 595–600. Bes F, Baroncini P, Dugovic C et al. (1988). Time course of night sleep EEG in the first year of life: a description
126
M.S. SCHER
based on automatic analysis. Electroencephalogr Clin Neurophysiol 69: 501–507. Biagioni E, Boldrini A, Giganti F et al. (2005). Distribution of sleep and wakefulness EEG patterns in 24-h recordings of preterm and full-term newborns. Early Hum Dev 81: 333–339. Bredesen DE (1995). Neural apoptosis. Ann Neurol 38: 839–851. Burdjalov VF, Baumgart S, Spitzer AR (2003). Cerebral function monitoring: a new scoring system for the evaluation of brain maturation in neonates. Pediatrics 112: 855–861. Burnham MM, Goodlin-Jones BL, Gaylor EE et al. (2002). Nighttime sleep–wake patterns and self-soothing from birth to one year of age: a longitudinal intervention study. J Child Psychol Psychiatry 43 (6): 713–725. Caviness VS Jr (1989). Normal development of cerebral neocortex. In: P Evrard, A Minkowski (Eds.), Developmental Neurobiology. Raven Press, New York, pp. 1–10. Chatow U, Davidson S, Reichman BL et al. (1995). Development and maturation of the autonomic nervous system in premature and full-term infants using spectral analysis of heart rate fluctuation. Pediatr Res 37: 294–302. Connell JA, Oozeer R, Dubowitz V (1987). Continuous 4channel EEG monitoring: a guide to interpretation with normal values in preterm infants. Neuropediatrics 18: 138–145. Curzi-Dascalova L (1977). EEG de veille et de sommeil du nourisson normal avant 6 mois d’aˆge. Rev Electroencephalogr Neurophysiol Clin 7: 316–326. Curzi-Dascalova L, Mirmiran M (1996). Manual of Methods For Recording and Analyzing Sleep-Wakefulness States in Preterm and Full-Term Infant. Les Editions INSERM, Paris. Curzi-Dascalova L, Peirano P, Morel-Kahn Inserm F (1988). Development of sleep states in normal premature and full-term newborns. Dev Psychobiol 21: 431–444. Curzi-Dascalova L, Figueroa JM, Eiselt M et al. (1998). Sleep state organization in premature infants of less than 35 weeks’ gestational age. Pediatr Res 34: 624–628. Dawes GS, Fox HE, Leduc BM et al. (1972). Respiratory movements and rapid eye movement sleep in the foetal lamb. J Physiol 220: 119–193. Dawson G, Panagiotides H, Grofer-Klinger LG et al. (1992). The role of frontal lobe functioning in the development of infant self-regulatory behavior. Brain Cogn 20: 152–175. de Weerd AW, van den Bossche AS (2003). The development of sleep during the first months of life. Sleep Med Rev 7: 179–191. Dittrichova´ J, Paul K, Pavlikova’ E (1972). Rapid eye movements in paradoxical sleep in infants. Neuropaediatrie 3: 248–257. Dreyfus-Brisac C (1968). Sleep ontogenesis in early human prematurity from 24 to 27 weeks of conceptional age. Dev Psychobiol 1: 162–169. Dreyfus-Brisac C (1979). Neonatal electroencephalography. In: EM Scarpelli, EV Cosmie (Eds.), Reviews in Perinatal Medicine, vol. III. Raven Press, New York, pp. 397–430.
Eiselt M, Schendel M, Witte H et al. (1997). Quantitative analysis of discontinuous EEG in premature and full-term newborns during quiet sleep. Electroencephalogr Clin Neurophysiol 103: 528–534. Eiselt M, Schindler J, Arnold M et al. (2001). Functional interactions within the newborn brain investigated by adaptive coherence analysis of EEG. Neurophysiol Clin 31: 104–113. Ellingson RJ (1964). Studies of the electrical activity of the developing human brain. In: WA Himwich (Ed.), The Developing Brain: Progress in Brain Research. Elsevier, Amstersam, pp. 26–53. Ellingson RJ (1979). The eegs of prematures and full-term newborns. In: DW Klass, DD Daly (Eds.), Current Practice of Clinical Electroencephalography. Raven Press, New York, pp. 149–177. Ersyukova II (1980). Oculomotor activity and autonomic indices of newborn infants during paradoxical sleep. Hum Physiol 6: 57–64. Eyre JA, Nanei S, Wilkinson AR (1988). Quantification of changes in normal neonatal eegs with gestation from continuous five-day recordings. Dev Med Child Neurol 30: 599–607. Field T, Diego M, Hernandez-Reif M et al. (2002). Relative right versus left frontal EEG in neonates. Dev Psychobiol 41: 147–155. Fukumoto M, Mochizuki N, Takeishi M et al. (1981). Studies of body movements during night sleep in infancy. Brain Dev 3: 37–43. Gaultier C (1995). Cardiorespiratory adaptation during sleep in infants and children. Pediatr Pulmonol 19: 105–117. Giaquinto S, Marciano F, Monod N et al. (1977). Applications of statistical equivalence to newborn EEG recordings. Electroencephalogr Clin Neurophysiol 42: 406–413. Glotzbach SF, Tansey PA, Baldwin RB et al. (1989). Periodic breathing cycle duration in preterm infants. Pediatr Res 25: 258–261. Glotzbach SF, Edgar DM, Ariagno RL (1995). Biological rhythmicity in preterm infants prior to discharge from neonatal intensive care. Pediatrics 95: 231–237. Goldman-Rakic PS (1987). Development of cortical circuitry and cognitive function. Child Dev 58: 601–622. Guilleminault C, Souquet M (1979). Sleep states and related pathology. In: R Korobkin, C Guilleminault (Eds.), Advances in Perinatal Neurology. SP Medical and Scientific Books, New York, pp. 225–247. Gurses D, Kilic I, Sahiner T (2002). Effects of hyperbilirubinemia on cerebrocortical electrical activity in newborns. Pediatr Res 52: 125–130. Hahn JS, Tharp BR (1990). The dysmature EEG pattern in infants with bronchopulmonary dysplasia and its prognostic implications. Electroenceph Clin Neurophysiol 76: 106–113. Harmony T (1984). Functional Neuroscience: Neurometric Assessment of Brain Dysfunction in Neurological Patients. vol. 3. Lawrence Erlbaum, Hillsdale, NJ, pp. 338–375. Harper RM, Leake B, Miyahara L et al. (1981). Development of ultradian periodicity and coalescence at 1 cycle per hour in electroencephalographic activity. Exp Neurol 73: 127–143.
ONTOGENY OF EEG SLEEP FROM NEONATAL THROUGH INFANCY PERIODS Hauser E, Seidl R, Rohrbach D et al. (1993). Quantitative EEG before and after open-heart surgery in children. A significant decrease in the beta and alpha 2 bands postoperatively. Electroencephalogr Clin Neurophysiol 87: 284–290. Havlicek V, Chiliaeva R, Chernick V (1975). EEG frequency spectrum characteristics of sleep states in full-term and pre-term infants. Neuropaediatrie 6: 24–40. Hayakawa F, Watanabe K, Hakamada S et al. (1987). FZ theta/ alpha bursts: a transient EEG pattern in healthy newborns. Electroencephalogr Clin Neurophysiol 67: 27–31. Hellstro¨m-Westas L (1992). Comparison between tape recorded amplitude integrated EEG monitoring and sick newborn infants. Acta Pediatr 81: 812–819. Hildebrandt G (1986). Functional significance of ultradian rhythms and reactive periodicity. J Interdiscipl Cycle Res 17: 307–319. Holthausen K, Breidbach O, Scheidt B et al. (2000). Brain dysmaturity index for automatic detection of high-risk infants. Pediatr Neurol 22: 187–191. Hrachovy RA, Mizrahi EM, Kellaway P (1990). Electroencephalography of the newborn. In: DD Daly, TA Pedley (Eds.), Current Practice of Clinical Electroencephalography. 2nd edn. Raven Press, New York, pp. 201–242. Hughes JR, Fino J, Gagnon L (1983). Periods of activity and quiescence in the premature EEG. Neuropediatrics 14: 66–72. Hughes JR, Fino JJ, Hart LA (1987). Premature temporal theta. Electroencephalogr Clin Neurophysiol 67: 7–15. Hughes JR, Miller JK, Fino JJ et al. (1990). The sharp theta rhythm on the occipital areas of prematures (STOP): a newly described waveform. Clin Electroencephalography 21: 77–87. Hughes PE, Alexi T, Walton M et al. (1999). Activity and injury-dependent expression of inducible transcription factors, growth factors and apoptosis-related genes within the central nervous system. Prog Neurobiol 57: 421–450. Inder TE, Buckland L, Williams CE et al. (2003). Lowered electroencephalographic spectral edge frequency predicts the presence of cerebral white matter injury in premature infants. Pediatrics 111: 27–33. Jenni OG, Borbe´ly AA, Achermann P (2004). Development of the nocturnal sleep electroencephalogram in human infants. Am J Physiol Regul Integr Comp Physiol 286: R528–R538. Kahn A, Dan B, Groswasser J et al. (1996). Normal sleep architecture in infants and children. J Clin Neurophysiol 13: 184–197. Ktonas PY, Fagioli I, Salzarulo P (1995). Delta (0.5–1.5 Hz) and sigma (11.5–15.5 Hz) EEG power dynamics throughout quiet sleep in infants. Electroencephalogr Clin Neurophysiol 95: 90–96. Kuhle S, Klebermass K, Olischar M et al. (2001). Sleep– wake cycles in preterm infants below 30 weeks of gestational age. Preliminary results of a prospective amplitudeintegrated EEG study. Wien Klin Wochenschr 113: 219–223.
127
Kuks JBM, Vos JE, O’Brien MJ (1988). EEG coherence functions for normal newborns in relation to their sleep state. Electroencephalogr Clin Neurophysiol 69: 295–302. Lehtonen J, Kononen M, Purhonen M et al. (1998). The effect of nursing on the brain activity of the newborn. J Pediatr 132: 646–651. Lenard HC (1970). Sleep studies in infancy: facts, concepts, and significances. Acta Paedriatr Scand 59: 572–581. Lombroso CT (1979). Quantified electrographic scales on 10 pre-term healthy newborns followed up to 40–43 weeks of conceptional age by serial polygraphic recordings. Electroencephalogr Clin Neurophysiol 46: 460–474. Lombroso CT (1985). Neonatal polygraphy in full-term and preterm infants: a review of normal and abnormal findings. J Clin Neurophysiol 2: 105–155. Lombroso CT (1989). Neonatal electroencephalography. In: E Niedermeyer, F Lopez-Desilva (Eds.), Electroencephalography, Basic Principles, Clinical Applications in Related Fields. Urban and Schwarzenberg, Baltimore, pp. 599–637. Louis J, Zhang JX, Revol M et al. (1992). Ontogenesis of nocturnal organization of sleep spindles: a longitudinal study during the first 6 months of life. Electroencephalogr Clin Neurophysiol 83: 289–296. Louis J, Cannard C, Bastus H et al. (1997). Sleep ontogenesis revisited: a longitudinal 24-hour home polygraphic study on 15 normal infants during the first two years of life. Sleep 20: 323–333. Lynch JA, Aserinsky E (1986). Developmental changes of oculomotor characteristics in infants when awake and in the active state of sleep. Behav Brain Res 20: 175–183. Marshall PJ, Bar-Haim Y, Fox NA (2002). Development of the EEG from 5 months to 4 years of age. Clin Neurophysiol 113: 1199–1208. Martin RJ, Miller MJ, Carlo WA (1986). Pathogenesis of apnea in preterm infants. J Pediatr 109: 733–741. Mirimiran M, Kok JH (1991). Circadian rhythm in early human development. Early Hum Dev 262: 121–128. Mrowka R, Cimponeriu L, Patzak A et al. (2003). Directionality of coupling of physiological subsystems: age-related changes of cardiorespiratory interaction during different sleep stages in babies. Am J Physiol Regul Integr Comp Physiol 285: R1395–R1401. Myers MM, Stark RI, Fifer WP et al. (1993). A quantitative method for classification of EEG in the fetal baboon. Am J Physiol 265: R706–R714. Myers MM, Schulze KF, Fifer WP et al. (1995). Methods of quantifying state-specific patterns of EEG activity in fetal baboons and immature human infants. In: J LeCanuet, WP Fifer, NA Krasnesor et al. (Eds.), Fetal Development: A Psychological Perspective. Lawrence Erlbaum, Hillsdale, NJ, pp. 35–49. Myers MM, Fifer WP, Grose-Fifer J et al. (1997). A novel quantitative measure of trace´-alternant EEG activity and its association with sleep states of preterm infants. Dev Psychobiol 31: 167–174. Nijhius JG, Martin CB, Prechtl HFR (1984). Behavioral status of the human fetus. In: HFR Prechtl (Ed.), Clinics in
128
M.S. SCHER
Developmental Medicine. No. 98: Continuity of neural functions from prenatal to postnatal life. London Spastic International Medical Publications, London, pp. 65–78. Nikolopoulou M, St. James-Roberts I (2003). Preventing sleeping problems in infants who are at risk of developing them. Arch Dis Child 88: 108–111. Pan XL, Ogawa T (1999). Microstructure of longitudinal 24 hour electroencephalograms in healthy preterm infants. Pediatr Int 41: 18–27. Parmelee AH, Stern R (1972). Development of states in infants. In: DC Clemente, DP Purpurer, EE Mayer (Eds.), Sleep and the Maturing Nervous System. Academic Press, New York, pp. 199–228. Parmelee AH, Wenner WH, Akiyama Y et al. (1967). Sleep states in premature infants. Dev Med Child Neurol 9: 70–77. Pope JJ, Werner SJ, Bickford RG (1992). Atlas of Neonatal Electroencephalography. Raven Press, New York. Prechtl HFR (1974). The behavioral states of the newborn infant. Brain Res 76: 185–212. Prechtl HFR, Nijhuis JG (1983). Eye movements in the human fetus and newborn. Behav Brain Res 10: 119–124. Prechtl HFR, Fargel JW, Weinmann HM et al. (1979). Postures, motility and respiration of low risk preterm infants. Dev Med Child Neurol 21: 3–27. Rechtschaffen A, Kales A (Eds.) (1968). A Manual of Standardized Terminology, Techniques and Scoring System for Sleep Stages of Human Subjects. Brain Research Institute/ Brain Information Services, University of California, Los Angeles. Regalado MG, Schechtman VL, Khoo MC et al. (2001). Spectral analysis of heart rate variability and respiration during sleep in cocaine-exposed neonates. Clin Physiol 21: 428–436. Robertson SS (1982). Intrinsic temporal patterning in the spontaneous movement of awake neonates. Child Dev 53: 1016–1021. Robertson SS (1987). Human cyclic motility: fetal–newborn continuities and newborn state differences. Dev Psychobiol 20: 425–442. Samson-Dollfus D, Nogues B, Menard JF et al. (1983). Delta, theta, alpha and beta power spectrum of sleep electroencephalogram in infants aged two to eleven months. Sleep 6: 376–383. Sawaguchi H, Ogawa T, Takano T et al. (1996). Developmental changes in electroencephalogram for term and preterm infants using an autoregressive model. Acta Paediatr Jpn 38: 580–589. Schechtman VL, Harper RK, Harper RM (1994). Distribution of slow-wave EEG activity across the night in developing infants. Sleep 17: 316–322. Schechtman VL, Harper RK, Harper RM (1995). Aberrant temporal patterning of slow-wave sleep in siblings of SIDS victims. Electroencephalogr Clin Neurophysiol 94: 95–102. Scher MS (1996). Normal electrographic-polysomnographic patterns in preterm and fullterm infants. Semin Pediatr Neurol 3: 12.
Scher MS (1997a). Neurophysiological assessment of brain function and maturation II. A measure of brain dysmaturity in healthy preterm neonates. Pediatr Neurol 16: 287–295. Scher MS (1997b). Neurophysiological assessment of brain function and maturation. I. A measure of brain adaptation in high risk infants. Pediatr Neurol 16: 191–198. Scher MS, Barmada A (1987). Estimation of gestational age by electrographic, clinical and anatomical criteria. Pediatr Neurol 3: 256–262. Scher MS, Richardson GA, Coble PA et al. (1988). The effects of prenatal alcohol and marijuana exposure: disturbances in neonatal sleep cycling and arousal. Pediatr Res 24: 101–105. Scher MS, Sun M, Hatzilabrou GM et al. (1990). Computer analyses of EEG sleep in the neonate: methodological considerations. J Clin Neurophysiol 7: 417–441. Scher MS, Steppe DA, Dahl RE et al. (1992). Comparison of EEG-sleep measures in healthy full-term and preterm infants at matched conceptional ages. Sleep 15: 442–448. Scher MS, Martin J, Steppe DA et al. (1994a). Comparative estimates of neonatal gestational maturity by electrographic and fetal ultrasonographic criteria. Pediatr Neurol 11: 214–218. Scher MS, Sun M, Steppe DA et al. (1994b). Comparisons of EEG sleep state-specific spectral values between healthy full-term and preterm infants at comparable postconceptional ages. Sleep 17: 47–51. Scher MS, Bova JM, Dokianakis SG et al. (1994c). Positive temporal sharp waves on EEG recordings of healthy neonates: a benign pattern of dysmaturity in preterm infants at postconceptional term ages. Electroencephalogr Clin Neurophys 90: 173–178. Scher MS, Steppe DA, Dokianakis SG et al. (1994d). Maturation of phasic and continuity measures during sleep in preterm neonates. Pediatr Res 36: 732–737. Scher MS, Dokianakis SG, Sun M et al. (1994e). Rectal temperature changes during sleep state transitions in fullterm and preterm neonates at postconceptional term ages. Pediatr Neurol 10: 191–194. Scher MS, Steppe DA, Dokianakis SG et al. (1994f). Cardiorespiratory behavior during sleep in fullterm and preterm neonates at comparable postconceptional term ages. Pediatr Res 36: 738–744. Scher MS, Sun M, Steppe DA et al. (1994g). Comparisons of EEG spectral and correlation measures between healthy term and preterm infants. Pediatr Neurol 10: 104–108. Scher MS, Bova JM, Dokianakis SG et al. (1994h). Physiological significance of sharp wave transients on EEG recordings of healthy pre-term and full-term neonates. Electroencephalogr Clin Neurophys 90 (3): 179–185. Scher MS, Steppe DA, Banks DL et al. (1995). Maturational trends of EEG-sleep measures in the healthy preterm neonate. Pediatr Neurol 12: 314–322. Scher MS, Dokianakis SG, Sun M et al. (1996). Computer classification of sleep in preterm and fullterm neonates at similar postconceptional term ages. Sleep 19: 18–25.
ONTOGENY OF EEG SLEEP FROM NEONATAL THROUGH INFANCY PERIODS Scher MS, Dokianakis SG, Steppe DA et al. (1997). Computer classification of state in healthy preterm neonates. Sleep 20: 132–141. Scher MS, Jones BL, Steppe DA et al. (2003a). Functional brain maturation in neonates as measured by EEG-sleep analyses. Clin Neurophysiol 114: 875–882. Scher MS, Steppe DA, Salerno DG et al. (2003b). Temperature differences during sleep between fullterm and preterm neonates at matched conceptional ages. Clin Neurophysiol 114: 17–22. Scher MS, Kelso RS, Turnbull JP et al. (2003c). Automated arousal detection in neonates. Sleep 26 (Suppl): A143. Scher MS, Johnson MW, Holditch-Davis D (2005a). Cyclicity of neonatal sleep behaviors at 25 to 30 weeks corrected age. Pediatr Res 57 (6): 879–882. Scher MS, Loparo KA, Turnbull JP et al. (2005b). Automated state analyses: proposed applications to neonatal neurointensive care. J Clin Neurophysiol 22: 256–270. Schramm D, Scheidt B, Hubler A et al. (2000). Spectral analysis of electroencephalogram during sleep-related apneas in pre-term and term born infants in the first weeks of life. Clin Neurophysiol 111: 1788–1791. Shibagaki M, Kiyono S (1983). Cyclic variation of integrated delta components during nocturnal sleep in mentally retarded children. Electroencephlogr Cin Neurophysiol 56: 190–193. Shibagaki M, Kiyono S, Takeuchi T (1985). Nocturnal sleep in mentally retarded infants with cerebral palsy. Electroencephologr Clin Neurophysol 61: 465–471. Somers VK, Dyken ME, Mark AL et al. (1995). Sympathetic nerve activity during sleep in normal subjects. N Engl J Med 328: 303–307. Stam CJ (2005). Nonlinear dynamical analysis of EEG and MEG: review of an emerging field. Clin Neurophysiol 116: 2266–2301. Sterman MB, Hoppenbrauwers T (1971). The development of sleep-waking and rest-activity patterns from fetus to
129
adult in man. In: MB Sterman, DJ McGinty, AM Adinolfi (Eds.), Brain Development and Behavior. Academic Press, New York, pp. 203–225. Sterman MP, Harper RM, Havens B et al. (1977). Quantitative analysis of infant EEG development during quiet sleep. Electroencephalogr Clin Neurophysiol 43: 371–385. Thatcher RW (1991). Maturation of the human frontal lobes: physiological evidence for staging. Dev Neuropsychol 7: 397–419. Turnbull JP, Loparo KA, Johnson MW et al. (2001). Automated detection of trace´ alternant during sleep in healthy full term neonates using discrete wavelet transform. Clin Neurophysiol 112: 1893–1900. Turnbull JP, Johnson MW, Loparo KA et al. (2003). Nonlinear dynamical system analyses of neonatal sleep state. Sleep 26 (Suppl): A404. Van der Knaap MS, Valk J (1990). MR imaging of the various stages of normal myelination during the first year of life. Neuroradiology 31: 459–470. Vanhatalo S, Tallgren P, Andersson S et al. (2002). DC-EEG discloses prominent, very slow activity patterns during sleep in preterm infants. Clin Neurophysiol 113: 1822–1825. Villa MP, Calcagnini G, Pagani J et al. (2000). Effects of sleep stage and age on short-term heart rate variability during sleep in healthy infants and children. Chest 117: 460–466. Willekens H, Oumermuth G, Duc G et al. (1984). EEG spectral powers and coherence analysis in healthy full-term neonates. Neuropediatrics 15: 180–190. Witte H, Putsche P, Eiselt M et al. (1997). Analysis of the interrelations between a low-frequency and a highfrequency signal component in human neonatal EEG during quiet sleep. Neurosci Lett 236: 175–179. Woodruff DS (1979). Brain electrical activity and behavior relationships over the life span. Life-Span Development and Behavior 1: 111–179.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 9
Neurobiology of waking and sleeping BARBARA E. JONES * Department of Neurology and Neurosurgery, McGill University, Montreal Neurological Institute, Montreal, Quebec, Canada
HISTORICAL BACKGROUND Over the course of the 20th century, concepts evolved as evidence accumulated concerning the existence and delineation of intrinsic neural systems controlling waking and sleeping. Waking was once thought to be maintained by sensory inputs and sleep to result from the cessation of sensory inputs to the brain (Bremer, 1929; Kleitman, 1939). Yet, from variable alterations of waking and sleeping that occurred with cerebral lesions clinically in humans or experimentally in animals, both waking and sleeping were found to be generated actively by intrinsic neural systems. Based upon analyses of human brains following death from encephalitis lethargica, von Economo (1930) was among the first to propose that waking and sleeping systems were localized in different regions of the forebrain since hypersomnolence was associated with lesions of the posterior hypothalamus whereas insomnia was associated with lesions of the anterior hypothalamus and preoptic area (Figure 9.1). Moruzzi and Magoun (1949) went on to show that the brainstem reticular formation together with the posterior hypothalamus were both necessary and sufficient for the maintenance of a waking state (Figure 9.1).
Cortical activation and deactivation In the early studies, it was established that lesions in the rostral pontine and mesencephalic reticular formation, extending into the posterior hypothalamus, resulted in a loss of fast electroencephalographic (EEG) activity typical of cortical activation of the wake state (Lindsley et al., 1950). In contrast, lesions of the ascending sensory pathways or even complete sensory deafferentation did not diminish the amount of cortical activation (Vital-Durand and Michel, 1969). The absence of waking signs in the experimental animals was similar to that in humans diagnosed as comatose *
and found to have lesions of the rostral brainstem and posterior diencephalon (Plum and Posner, 1980). Electrical stimulation of the brainstem reticular formation in an anesthetized animal evoked cortical activation which was conducted along two major pathways into the forebrain to reach the cortex (Starzl et al., 1951) (Figure 9.1). The first route was into the thalamus from where impulses were in turn conveyed in a relatively widespread manner to the cerebral cortex, particularly the frontal regions. The second route was ventral to the thalamus extending through the hypothalamus up to the basal forebrain from where impulses were also conveyed in a widespread manner to the cortex. This ventral extrathalamic route was found to be sufficient, since cortical activation could still be attained following total ablation of the thalamus. Neuroanatomical studies revealed that the neurons within the netlike, or reticular, core of the brainstem were characterized by long radiating dendrites which received collateral inputs from multiple sensory modalities and by long branching axons which ascended from the rostral brainstem into the thalamus and/or into the hypothalamus and up to the basal forebrain (Nauta and Kuypers, 1958; Scheibel and Scheibel, 1958). The ascending reticular activating system thus had the capacity to respond to multiple sensory inputs and to transmit in turn impulses to widely distributed areas of the cortex, through neurons in the diffuse thalamocortical projection system and a basalocortical projection system. Electrical stimulation of the thalamus could elicit widespread cortical activation. However, the effect of the stimulation depended upon its frequency. Whereas high-frequency stimulation elicited fast cortical activity, low-frequency stimulation recruited spindle-like or slow wave-like activity on the cerebral cortex, which
Correspondence to: Dr. Barbara E. Jones, Montreal Neurological Institute, 3801 University Street, Montreal, Quebec, H3A 2B4, Canada. Tel: þ1 514-398-1913, Fax: þ1 514-398-5871, E-mail:
[email protected]
132
B.E. JONES
Cx
Th BF PH POA
TM
Mes DR VTA
RF LDT LC
CB
Pons
Cortical activation (W/REM):
Glu Ach
Cortical de-activation (SWS):
GABA
Behavioral arousal (W):
Glu NA/DA Ser HA Orx
Behavioral quiescence (SWS/REM):
GABA
RF Medulla
Fig. 9.1. Sleep–wake state substrates. Sagittal schematic view of the human brain depicting neurons with their chemical neurotransmitters and pathways by which they influence cortical activity or behavior across the sleep–wake cycle. Neurons which are active during waking (red symbols) include cells with ascending projections toward the cortex, which stimulate cortical activation, and cells with descending projections toward the spinal cord, which stimulate behavioral arousal with postural muscle tone. Those with predominantly ascending projections discharge in association with fast, gamma electroencephalogram (EEG) activity and cease firing with slow, delta activity to be active during both wakefulness and rapid eye movement sleep (W/REM, filled red symbols); they include neurons which release glutamate (Glu, diamonds) or acetylcholine (ACh, circles) (see Figures 9.2 and 9.3). Those with more diffuse or descending projections discharge in association with behavioral arousal and electromyogram (EMG) activity and cease firing with muscle atonia to be active during W and silent during REM (W, empty red symbols); they include neurons which release glutamate (Glu, diamonds), noradrenaline (norepinephrine) (NA, square), serotonin (Ser, star), histamine (HA, cross) or orexin (Orx, asterisk) (see Figure 9.4). Neurons which are active during sleep (blue or aqua symbols) include cells with ascending projections toward the cortex, which dampen fast cortical activity, and those with descending projections toward the hypothalamus, brainstem, or spinal cord, which diminish behavioral arousal and muscle tone. Those with projections to the cortex or local area discharge in association with slow EEG activity during slow-wave sleep (SWS, blue triangle; see Figure 9.3); those with descending projections discharge in association with decreasing muscle tone and EMG (SWS/REM, aqua triangles; see Figure 9.3). They include particular GABAergic neurons in the basal forebrain and preoptic area that bear a2-adrenergic receptors and are thereby inhibited by NA. Also shown are GABAergic neurons in the pontomesencephalic tegmentum, which can inhibit local reticular or monoaminergic neurons, and GABAergic neurons (together with glycinergic neurons, not shown) in the ventral medullary reticular formation that project directly to the spinal cord where they can inhibit neck and other motor neurons during sleep. BF, basal forebrain; CB, cerebellum; Cx, cortex; DR, dorsal raphe; GABA, gamma-aminobutyric acid; LC, locus coeruleus nucleus; LDT, laterodorsal tegmental nucleus; Mes, mesencephalon; PH, posterior hypothalamus; POA, preoptic area; RF, reticular formation; SC, spinal cord; Th, thalamus; TM, tuberomammillary nucleus; VTA, ventral tegmental area. (Adapted from Jones (2005).)
NEUROBIOLOGY OF WAKING AND SLEEPING 133 resembled the EEG activity of sleep (Akert et al., 1952). There are also a small number of GABAergic neuSimilarly, stimulation in the preoptic area and basal rons distributed through the reticular formation which forebrain could activate the cortex, yet depending upon would have the capacity to inhibit other neurons in the precise location and frequency, could also elicit the region (Figure 9.1). These could correspond to a slow-wave activity and a state of sleep (Hess, 1957; small number of neurons which actually increase their Sterman and Clemente, 1962a, b). It thus appeared rate of firing during sleep (Steriade et al., 1982). In that, within the same regions of the forebrain, differstudies using c-Fos expression as a reflection of neural ent patterns of discharge by the same or different neuactivity, a number of GABAergic neurons in the reticrons could stimulate either cortical activation and ular formation did appear to be active during sleep waking or cortical slow-wave activity and sleeping. (Maloney et al., 1999, 2000).
Behavioral arousal and quiescence Neurons of the reticular formation were also seen to send descending projections into the spinal cord (Scheibel and Scheibel, 1958) (Figure 9.1). As evident from electrical stimulation, reticulospinal neurons could stimulate movement and enhance postural muscle tone, recorded on the electromyogram (EMG), as typical of behavioral arousal (Sprague and Chambers, 1954). Yet, depending upon the condition of the animal, such stimulation in the medulla could also inhibit muscle tone, reflexes, and movement (Magoun and Rhines, 1946). Thus presumably different neurons in the brainstem evoked behavioral arousal with postural muscle tone or behavioral quiescence with muscle atonia.
THE RETICULAR ACTIVATING SYSTEM Forebrain projecting reticular neurons The neurons of the reticular formation with ascending projections are concentrated in the oral pontine and mesencephalic reticular formation, although they are present in smaller numbers in the caudal pontine and medullary reticular formation (Jones and Yang, 1985). They project rostrally to the midline and intralaminar thalamic nuclei which form the nonspecific thalamocortical projection system that project in turn in a widespread manner to the cerebral cortex (Figure 9.1). The reticular neurons also project through the hypothalamus up to the level of the basal forebrain. In the mesencephalon, they discharge at their highest rate in association with fast cortical activity that occurs during both wakefulness and rapid eye movement (REM) sleep (Steriade et al., 1982). Considerable evidence indicates that neurons of the ascending reticular activating system utilize the neurotransmitter glutamate (Glu) and thus excite through multiple Glu receptors (a-amino-3-hydroxyl5-methyl-4-isoxazole-propionate (AMPA), kainate, N-methyl-D-aspartic acid (NMDA) or metabotropic) their target neurons in the thalamus, hypothalamus, and/or basal forebrain (Kaneko et al., 1989, 2002; McCormick, 1992; Jones, 1995).
Spinal projecting reticular neurons Neurons through the reticular formation project to the spinal cord, though in greatest numbers from the caudal pontine and medullary fields, and terminate variably in the dorsal horn, intermediate zone or ventral horn (Jones and Yang, 1985). The vast majority of pontine and medullary reticular neurons discharge at their highest rate during waking in association with movements (Siegel et al., 1977, 1979). They decrease or cease firing with slow-wave sleep (SWS). Many fire in association with phasic activity during REM sleep. Considerable evidence indicates that the large, thus presumably reticulospinal neurons of the pontine and medullary reticular formation utilize the neurotransmitter Glu (Kaneko et al., 1989, 2002; Jones, 1995) (Figure 9.1). A large number of smaller neurons through the reticular formation and a small number of spinally projecting medium-sized neurons in the medullary reticular formation synthesize gamma-aminobutyric acid (GABA) (Jones et al., 1991). In addition, these or other medium-sized reticulospinal neurons utilize the inhibitory neurotransmitter glycine (Fort et al., 1993). Such GABAergic or glycinergic reticular or reticulospinal neurons could exert an inhibitory influence upon other excitatory reticulospinal neurons or brainstem and spinal motor neurons (Holstege and Bongers, 1991). They could represent the small percentage of reticular neurons that increase their discharge rate with quiet waking and sleep, relative to active waking and discharge maximally with muscle atonia during REM sleep (Sakai et al., 1981). They could also correspond to the small number of medullary reticular neurons that discharge in association with loss of muscle tone which occurs in narcolepsy with cataplexy (Siegel et al., 1991). Indeed, many medullary reticular neurons which are GABAergic express c-Fos with REM sleep, as evident during rebound following deprivation (Maloney et al., 1999, 2000). In any event, both excitatory and inhibitory reticulospinal neurons can influence movement and muscle tone such as to stimulate behavioral arousal or reciprocally promote behavioral quiescence and different states (Figure 9.1).
134
B.E. JONES
The cholinergic pontomesencephalic neurons Neurons which utilize acetylcholine (ACh) as a neurotransmitter were proposed to form a major contingent of the reticular formation based upon histochemical staining for its catabolic enzyme, acetylcholinesterase (AChE), by Shute and Lewis (1967) (Figure 9.1). The cholinergic contingent of the activating system was considered by Shute & Lewis to be preeminent, thus leading them to designate the entire system as the “cholinergic reticular activating system.” With application of immunohistochemical staining for the synthetic enzyme choline acetyltransferase (ChAT), the cholinergic neurons were later found to be more limited in their distribution and localized to two major cell groups in the brainstem, the laterodorsal tegmental nucleus and pedunculopontine tegmental nucleus (Mesulam et al., 1983b). Like other neurons of the reticular formation, nonetheless, these cholinergic neurons project forward into the forebrain. They project prominently to the thalamus, including most densely to the medial and lateral geniculate nuclei and the midline and intralaminar nuclei. They can thus excite both specific and nonspecific thalamocortical projection systems. Acting through both nicotinic and muscarinic receptors, indeed, ACh depolarizes and excites the thalamic projection neurons and evokes tonic firing by them to stimulate thalamocortical activation and prevent slow-wave activity (McCormick, 1992). The pontomesencephalic cholinergic neurons also project through the extrathalamic ventral ascending pathway into the posterior hypothalamus where they influence wake-promoting neurons (see below) and to a lesser degree up to the basal forebrain (Jones and Cuello, 1989; Ford et al., 1995). Although cholinergic neurons have not yet been unequivocally identified in the pontomesencephalic tegmentum in recording studies, neurons considered to be “possibly” cholinergic were recorded in the region of those cells in the cat and shown to discharge in association with cortical activation during both wake (W) and REM sleep (W/REM) (El Mansari et al., 1989) (Figure 9.1). In addition, however, some “possibly” cholinergic neurons were found to discharge only during REM sleep and in association with the muscle atonia of that state (El Mansari et al., 1989; Kayama et al., 1992). It is thus possible that particular cholinergic neurons, which project to the pontomedullary reticular formation (Mitani et al., 1988; Jones, 1990; Semba et al., 1990), might generate REM sleep with muscle atonia. Injection of the cholinergic agonist, carbachol, into the pontomesencephalic tegmentum induces cortical activation with muscle atonia and other signs of REM sleep (George et al., 1964; Baghdoyan et al., 1984). Such action might be possible through different
effects of ACh upon different neurons mediated by muscarinic type 1 (M1) and 2 (M2) receptors. ACh could inhibit (through M2 receptors) glutamatergic reticular neurons involved in facilitating activity and muscle tonus and excite (through M1 receptors) particular GABAergic neurons involved in inhibiting activity and muscle tone (Figure 9.1).
FOREBRAIN RELAYS OF THE ACTIVATING SYSTEM The nonspecific thalamocortical projection system The midline and intralaminar nuclei of the thalamus, unlike the sensory and motor relay nuclei, project to multiple regions of the cerebral cortex in a thus nonspecific manner, often in highest density to frontal regions, though for some nuclei in a truly diffuse manner in high density to all regions (Herkenham, 1986) (Figure 9.1). They discharge at their highest rate in association with cortical activation during waking and REM sleep. Their discharge is generally tonic and relatively fast during these states (Glenn and Steriade, 1982). Indeed, they can attain frequencies in the gamma range (40 Hz) in association with similar gamma EEG activity, which they may accordingly stimulate (Steriade et al., 1993a). They utilize Glu as a neurotransmitter, as proven recently by their content of vesicular Glu transporter 2 (VGluT2) (Fremeau et al., 2001; Kaneko et al., 2002; Hur and Zaborszky, 2005). Like other thalamocortical projection neurons, those of the midline and intralaminar nuclei change both their rate and mode of discharge during SWS (Steriade et al., 1993a). Due to intrinsic properties, all thalamic projection neurons have two modes of firing, tonic and bursting, the latter mediated by a calcium lowthreshold spike (LTS), which is activated when the neurons are hyperpolarized (Steriade and Llinas, 1988). This hyperpolarization occurs when the thalamic neurons are released from excitatory influences from the brainstem-activating systems. Moreover, the reticular thalamic neurons which surround and innervate the thalamic relay neurons begin first to discharge in bursts when removed from this depolarizing influence. The reticular thalamic neurons utilize GABA as a neurotransmitter and thereby further hyperpolarize the thalamocortical projection neurons in an active and punctual manner. They accordingly entrain the projection neurons in rhythmic bursting, which occurs first at a spindle frequency (12–14 Hz) and then at a delta frequency (1–4 Hz), as well as a slower oscillation (0.1–1 Hz). These patterns of SWS are thus transmitted through thalamo-cortico-thalamic loops as a product of
NEUROBIOLOGY OF WAKING AND SLEEPING the intrinsic properties of the neurons within those circuits (Steriade et al., 1993b). During these slow patterns, thalamocortical transmission of sensory inputs is virtually blocked and consciousness is lost.
The basalocortical projection system First identified by immunohistochemical staining for AChE, the innervation of the cerebral cortex by cholinergic fibers from the basal forebrain was originally proposed by Shute and Lewis (1967) to represent the important relay of the brain reticular activating system to the cerebral cortex within the “cholinergic reticular activating system” (Figure 9.1). Moreover, a potent excitatory effect of ACh upon cortical neurons was demonstrated by Krnjevic and Phillis (1963) and proposed to underlie the fast cortical activity that characterized activation. Indeed, pharmacological enhancement of ACh with physostigmine, the AChE inhibitor, or administration of muscarinic or nicotinic agonists stimulated cortical activation with waking (Domino et al., 1968). Blocking muscarinic receptors with atropine led to deactivation of the cortex with predominant slowwave activity, despite continued behavioral arousal, and thus disassociation between cortical activity and behavior (Longo, 1966). It was also found by Jasper and Tessier (1971) that ACh release from the cerebral cortex was maximal in association with cortical activation during both waking and REM sleep (Celesia and Jasper, 1966). These early studies thus indicated that ACh and cholinergic neurons played an important, if not critical, role in cortical activation which occurs during waking and REM sleep and thus in cortical activation, irrespective of behavioral arousal. As identified and delineated by ChAT immunohistochemistry, the cholinergic neurons are distributed across the basal forebrain from rostral to caudal in the medial septum (MS), nuclei of the diagonal band of Broca (DBB), magnocellular preoptic nucleus (MCPO), substantia innominata (SI) and globus pallidus (GP), as described in the rat brain (Mesulam et al., 1983b) and corresponding largely to what was originally called the nucleus basalis magnocellularis of Meynert in primates (Mesulam et al., 1983a). Collectively these cell groups provide a rich cholinergic innervation to the hippocampus and paleocortex (predominantly from MS-DBB) and to the entire neocortex (predominantly from MCPO-SI-GP). In the cortex, cholinergic fibers innervate both interneurons and pyramidal cells across all layers (Beaulieu and Somogyi, 1991). ACh exerts excitatory influences upon both cell types, predominantly through muscarinic (M1) receptors and also inhibitory influences upon some interneurons (through M2 receptors) (McCormick, 1993). The influence of the basal
135
forebrain cholinergic neurons upon cortical neurons prevents slow-wave cortical activity and promotes fast cortical activity, particularly in a gamma range (30–60 Hz) (Metherate et al., 1992; Cape and Jones, 2000). As recently determined by juxtacellular labeling and immunohistochemical identification of recorded neurons in rats, the cholinergic basal forebrain neurons discharge maximally in association with cortical activation during waking and REM sleep or, as it is more appropriately called in rats, paradoxical sleep (PS) (Lee et al., 2005b) (Figure 9.2). Moreover, they fire in high-frequency spike bursts with gamma and theta activity during active, attentive waking and during PS (Figure 9.2, expanded traces). As typical of W/PSactive (or W/REM, as represented in the human brain in Figure 9.1), their discharge is positively correlated with high-frequency gamma EEG activity and negatively correlated with slow delta EEG activity, and it is not correlated with EMG amplitude (Figure 9.3). In contrast to thalamocortical neurons of the nonspecific thalamocortical projection system, the cholinergic cells cease firing prior to and during SWS. Since ACh stimulates cortical activation, the cessation of discharge by the cholinergic cells is likely a determinant in the natural onset of SWS, including spindle, delta, and slow oscillations in the cortex. In addition to cholinergic neurons, other neurons, including glutamatergic and GABAergic neurons, are distributed through the basal forebrain and give rise to cortical, local, or descending projections (Jones, 2004, 2005; Henny and Jones, 2008). These noncholinergic cells are heterogeneous in their response to different neurotransmitters, in their activity profile across sleep–wake states, and in their role in modulating cortical activity and sleep–wake states, as will be elaborated below. Some presumed glutamatergic neurons, likely having cortical projections, discharge like the cholinergic basalocortical projection neurons, maximally in association with cortical activation during waking and REM sleep (Figure 9.3). Other presumed glutamatergic neurons, likely having descending projections, discharge maximally with behavioral arousal during waking. Some GABAergic neurons discharge also in parallel with the cholinergic cells; yet another important contingent discharges in an inverse manner to the cholinergic and presumed glutamatergic neurons and could thus promote sleep (see below) (Figure 9.3).
DIFFUSELY PROJECTING AROUSAL SYSTEMS The reticular formation and cholinergic pontomesencephalic tegmental neurons have the capacity to influence widespread areas of the forebrain and cortex
136
B.E. JONES
Cholinergic basal forebrain unit aW
B
SWS
C
tPS
D
PS
Unit EEG : RS EEG : PF EMG
A
Fig. 9.2. Discharge of a cholinergic basal forebrain neuron across sleep–wake states. Record of a neuron labeled by juxtacellular technique with Neurobiotin (Nb) and identified by immunohistochemistry for choline acetyltransferase (ChAT) as cholinergic in the magnocellular preoptic nucleus (MCPO) of the rat. As evident in 10-second traces (above), the unit fired during aW, virtually ceased firing during SWS, resumed firing during tPS, and discharged maximally during PS. As evident in expanded 0.5-second traces (below), the unit discharged in rhythmic bursts of spikes with theta EEG activity that was present intermittently during periods of aW, toward the end of tPS, and continuously during PS. aW, active wake; EMG, electromyogram; EEG, electroencephalogram; PF, prefrontal cortex; RS, retrosplenial cortex; SWS, slow-wave sleep; tPS, transition to paradoxical sleep; PS, paradoxical sleep. Bar for horizontal scale: 1 second. Bar for vertical scales: 1 mV for EEG/EMG and 1.5 mV for unit. (Reprinted with permission from Lee et al. (2005b).)
through their projections to the major subcortical relay stations. Some also give rise to branching axons with descending as well as ascending projections of some distance, thus allowing simultaneous influence upon forebrain and spinal cord systems (Jones and Yang, 1985). It is thus likely that some neurons of the reticular formation can simultaneously stimulate cortical activation and behavioral arousal with enhanced muscle tone and/or motor activity. In the case of the cholinergic neurons, some may actually stimulate cortical activation while dampening behavioral arousal and diminishing muscle tone in the generation of REM sleep. Such widespread influence can thus determine the state of the brain and organism. Following the development of histofluorescent techniques in the 1960s, other cell groups were revealed within the brainstem which contained monoamines and which gave rise to highly diffuse projections through the entire central nervous system (Dahlstrom and Fuxe, 1964; Ungerstedt, 1971b). Moreover, they acted as neuromodulators able to influence
the activity of other neurons or actions of other neurotransmitters on those neurons in a relatively subtle, slow, and prolonged manner. As proposed by Jouvet (1969), the monoamines and their neural systems appeared ideally suited to influence – if not determine – sleep–wake states. Most notable of these, the locus coeruleus nucleus neurons were found to contain noradrenaline (NA) (norepinephrine) and to give rise to varicose axons which branched and sent collaterals through the entire nervous system, such as potentially to permit from one neuron the simultaneous release of NA throughout the brain and spinal cord (Jones and Moore, 1977; Jones and Yang, 1985). Indeed, this small cluster of neurons in the brain resembles a central sympathetic ganglion, sending fibers to broad regions and releasing NA from the varicosities along its axons to influence its multiple target cells in a nonsynaptic manner (Descarries et al., 1977). The locus coeruleus noradrenergic neurons thus appeared to represent an ideal substrate stimulating arousal.
NEUROBIOLOGY OF WAKING AND SLEEPING Slow EEG: Delta
EMG
1.0
1.0
0.8
0.8
0.8
0.6
0.4
0.2
0.0
0.6
0.4
0.2
0.0 aW
qW tSWS SWS tPS
PS
A
Normalized EMG Amplitude
1.0
Normalized Delta Power
Normalized Gamma Power
Fast EEG : Gamma
0.6
0.4
0.2
0.0 aW
qW tSWS SWS tPS
PS
B
aW
0.9
0.9
0.8 0.7 0.6 ACh Glu
Glu
0.4 0.3 0.2
Normalized Average Spike Rate
Normalized Average Spike Rate
1.0
0.1
0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1
0.0
0.0 aW
qW tSWS SWS tPS
aW
PS
D
qW tSWS SWS tPS
PS
E Gamma–/Delta+: SWS Active Units
EMG–: SWS/PS Active Units
1.0
1.0
0.9
0.9
0.8 0.7 0.6
GABA
0.5 0.4 0.3 0.2
GABA
Normalized Average Spike Rate
Normalized Average Spike Rate
PS
EMG+:W Active Units
1.0
0.5
qW tSWS SWS tPS
C
Gamma+/Delta–: W/PS Active Units
0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1
0.1
0.0
0.0 aW
F
137
qW tSWS SWS tPS
PS
aW
qW tSWS SWS tPS
PS
G
Fig. 9.3. Sleep–wake-related electroencephalogram (EEG)/electromyogram (EMG) and unit activity of basal forebrain neurons in the rat. Normalized average gamma power (A), delta power (B), and EMG amplitude (C) across all sleep–wake stages in the rat. (D–G) Normalized average unit spike rate for basal forebrain cell groups. In D, waking (W)/paradoxical sleep (PS)-active cells, whose discharge is positively correlated with gamma EEG activity and negatively correlated with delta EEG activity (including putative cholinergic cells represented in Figure 9.1 in the human brain as W/REM cells, circles). E shows W-active cells whose discharge is positively correlated with EMG amplitude and which fire maximally during W (including putative glutamatergic cells represented in Figure 9.1, diamonds). F shows SWS-active cells whose discharge is negatively correlated with gamma and positively correlated with delta EEG activity and which fire maximally during SWS (including putative GABAergic neurons represented in Figure 9.1, triangles). G shows SWS/PS-active cells whose discharge is negatively correlated with EMG amplitude and which fire at progressively higher rates during SWS through PS (including putative GABAergic neurons represented in Figure 9.1 as SWS/REM cells, triangles). aW, active wake; qW, quiet wake; tSWS, transition to slow-wave sleep; SWS, slow-wave sleep; tPS, transition to paradoxical sleep; PS, paradoxical sleep. (Reprinted with permission from Jones, (2005).)
138
B.E. JONES
Early pharmacological studies had indicated a potent influence of the catecholamines, NA and dopamine (DA), in stimulating waking with behavioral arousal (Jouvet, 1972). Amphetamine, which releases NA and DA, evoked a prolonged waking state characterized by fast cortical activity and pronounced behavioral arousal. Depletion of NA and DA by inhibition of catecholamine synthesis (with a-methyl-para-tyrosine, AMPT) resulted in decreases in waking and increases in sleep.
Noradrenergic locus coeruleus neurons The locus coeruleus neurons project along the same ascending pathways as the neurons of the reticular formation; however, while innervating the relay stations in the thalamus, hypothalamus and basal forebrain, they send axons further along to innervate the entire cerebral cortex directly (Jones and Yang, 1985) (Figure 9.1). Other neurons send axons through the brainstem to innervate neurons therein, yet extend their fibers into the entire spinal cord, and a certain number innervate through bifurcating axons both the forebrain and the spinal cord. Through these regions, NA exerts different effects upon different neurons through different receptors. In the thalamus, NA serves mainly to depolarize and excite both specific and nonspecific thalamocortical projection neurons by acting primarily upon a1-adrenergic receptors and thus stimulating fast tonic discharge and preventing slow bursting discharge of the thalamic neurons to promote cortical activation (McCormick, 1992). In the posterior hypothalamus, NA also excites wake-promoting neurons (Bayer et al., 2005) (see below). In the basal forebrain, the cholinergic neurons are similarly excited by NA through a1-adrenergic receptors (Fort et al., 1995). NA also excites motor systems and exerts a direct excitatory influence upon motor neurons in the spinal cord (Sqalli-Houssaini and Cazalets, 2000). Indeed, the excitatory influence of NA upon motor neurons and their activity is also evident in brainstem motor neurons as an important tonic influence that determines their activity and tonus during waking (Fenik et al., 2005). It is notable that NA inhibits certain neurons through a2-adrenergic receptors; indeed, sleep-promoting neurons in the forebrain appear to be inhibited by NA (see below). According to their projections and the effects of NA released by their diffusely projecting fibers, the locus coeruleus noradrenergic neurons thus have the capacity simultaneously to stimulate cortical activation and behavioral arousal of waking and to prevent sleep. As established many years ago without the need to identify recorded neurons as NA-containing in the
locus coeruleus, given the very compact and homogeneous aggregation of these cells in the rat brain, locus coeruleus noradrenergic neurons discharge selectively during waking, diminish firing during SWS, and cease firing altogether during PS (Aston-Jones and Bloom, 1981) as W-active cells (W, Figure. 9.1). Their discharge during waking is maximal in response to sensory stimuli and situations that are associated with high behavioral arousal, stress, and activation of the peripheral sympathetic nervous system (Jacobs et al., 1991). Their discharge would thus be associated with behavioral arousal and incompatible with SWS and PS. Indeed, as was formally proposed by McCarley and Hobson (1975) many years ago, locus coeruleus noradrenergic neurons could prevent the occurrence of PS through an inhibitory influence upon cholinergic PS promoting neurons in the pontomesencephalic tegmentum. They can also prevent the muscle atonia of PS by their excitatory influence upon motor neurons (Fenik et al., 2005).
Dopaminergic mesencephalic neurons The DA-containing neurons are located in the mesencephalic tegmentum concentrated within the substantia nigra and ventral tegmental area. Although the dopaminergic neurons do not project in the diffuse manner of the noradrenergic neurons, they nonetheless reach broad areas of the forebrain, particularly the dorsal striatum from the substantia nigra and the ventral striatum and cortex from the ventral tegmental area (Moore and Bloom, 1979). They also project to the thalamus (Sanchez-Gonzalez et al., 2005) and on to cholinergic basal forebrain neurons (Jones and Cuello, 1989; Gaykema and Zaborszky, 1996), similar to noradrenergic neurons. They influence target neurons in differing manners through D1 or D2 receptors. From early lesion studies, DA neurons appeared to influence behavioral arousal more than cortical activity, since their destruction in animals resulted in akinesia with little change in cortical activation, as in Parkinson patients (Ungerstedt, 1971a; Jones et al., 1973). Yet, evidence subsequently indicated that these neurons can also facilitate cortical activation by enhancing gamma EEG activity along with attentive behavior (Montaron et al., 1982). Recordings from identified DA-containing neurons have not yet been realized in naturally sleeping–waking animals. Early studies described the activity of possibly dopaminergic neurons, which particularly in the ventral tegmental area are intermingled with a vast majority of nondopaminergic neurons, across the sleep–waking cycle, and concluded that they did not change their average firing rate across this cycle (Miller et al.,
NEUROBIOLOGY OF WAKING AND SLEEPING 1983), a very surprising finding. On the other hand, studies employing c-Fos as an indicator of activity presented evidence that dopaminergic neurons of the ventral tegmental area are more active during waking and REM sleep (W/REM) than SWS (Maloney et al., 2002). A study employing electrophysiological properties as a marker for dopaminergic neurons found that possibly DA-containing neurons of the ventral tegmental area discharged in bursts of spikes during aroused waking and during PS (Dahan et al., 2007). It is thus possible that dopaminergic neurons are more similar to cholinergic neurons, from which they receive input and to which they project, and thereby discharge maximally during both W and PS. Considering the important role of DA in the limbic system, such activity could mediate the emotive aspects of particular waking and dream states. Given, however, that the drugs employed in the prevention of hypersomnolence including narcolepsy with cataplexy act prominently upon both NA and DA release (Wisor et al., 2001), it is currently not clear whether dopaminergic neurons in the ventral mesencephalon (or perhaps diencephalon) function to promote behavioral arousal and prevent sleep-like noradrenergic neurons (Figure 9.1) or might be active during REM sleep to stimulate cortical activation without stimulating behavioral arousal. In any event, it is likely that the enhanced release of both NA and DA is important for the antinarcoleptic action of amphetamines and modafinil (Lin et al., 1992).
Serotonergic raphe neurons The influence of serotonin (Ser, also 5-hydroxytryptamine, 5-HT) upon EEG activity and sleep–wake states is different from that of the catecholamines. Indeed, it is so different that the early pharmacological and lesion studies indicated to Jouvet (1972) that the serotonergic raphe neurons generated SWS. Inhibition of Ser synthesis (with para-chlorophenylalanine, PCPA) and lesions of serotonergic raphe neurons both produced insomnia. Yet, upon recording from possibly serotonergic raphe neurons, it was surprisingly discovered that the presumed serotonergic cells discharged during waking, diminished firing during SWS, and ceased firing during REM sleep (McGinty and Harper, 1976). They are, thus, like noradrenergic neurons, W-active cells (W, Figure 9.1). In contrast to noradrenergic locus coeruleus neurons, however, the presumed serotonergic raphe neurons do not discharge during response and orientation to sensory stimuli and do not fire under conditions of physiological stress when the sympathetic nervous system is activated (Jacobs and Fornal, 1999). They do fire during motor activity and
139
particularly during rhythmic motor patterns, such as grooming or locomotion. Ser is known to facilitate locomotor activity and directly excite motor neurons, particularly through 5-HT2 receptors (Barbeau and Rossignol, 1990; Kjaerulff and Kiehn, 2001). In that serotonergic raphe neurons can also attenuate sensory inputs (Fields and Basbaum, 1978), it is possible that their activity prevents sensory inputs from disrupting rhythmic motor activity during locomotion or grooming (Jacobs and Fornal, 1999). The major serotonergic projections into the spinal cord dorsal and ventral horns derive from medullary raphe nuclei (magnus, pallidus, and obscurus). Serotonergic neurons also project into the forebrain (particularly from the dorsal and central superior raphe nuclei) along the major ascending brainstem pathways, and like the noradrenergic neurons, also beyond to reach directly the cerebral cortex. Ser can inhibit many thalamic neurons, including the intralaminar nuclei, through 5-HT1 receptors, though exciting others through 5-HT2 receptors (Monckton and McCormick, 2002). Ser inhibits cholinergic basal forebrain neurons through 5-HT1 receptors and thereby diminishes gamma EEG activity (Khateb et al., 1993; Cape and Jones, 1998). Serotonergic raphe neurons would thus promote waking and behavioral arousal along with rhythmic motor activity but not cortical activation with sensory responsiveness, which would be attenuated. Promotion of such rhythmic pattern generation that would underlie behaviors such as grooming might favor a more relaxed waking state from which sleep would follow more easily than from a highly attentive state. Ser does nonetheless facilitate muscle tone and antagonize the hyperpolarization of motor neurons that occurs with the muscle atonia of REM sleep (Kubin et al., 1992; Fenik et al., 2005). It can also prevent REM sleep initiation by inhibiting cholinergic pontomesencephalic neurons (Luebke et al., 1992).
Histaminergic tuberomammilary neurons Histamine (HA) was long thought to have a wakepromoting influence since antihistaminergic drugs, used for the treatment of allergies, were associated with somnolence (Lin et al., 1988; Schwartz et al., 1991). It was subsequently discovered that, like the noradrenergic locus coeruleus neurons, the histaminergic neurons give rise to a highly diffuse innervation of the brain and spinal cord. The histaminergic neurons are also relatively tightly clustered in the posterior hypothalamus concentrated in the tuberomammillary nucleus (Figure 9.1). They excite target neurons in the brain, including thalamocortical projection neurons, cholinergic basal forebrain neurons, and cortical neurons
140 B.E. JONES predominantly through H1 receptors, by which HA also partially redundant; although, as discussed above, each appears to stimulate fast cortical activity (McCormick, plays a slightly different role and is invoked by a 1992; Reiner and Kamondi, 1994; Khateb et al., 1995). slightly different condition. On the other hand, it was Recently identified histaminergic neurons have quite surprising to learn in recent years that one particbeen recorded in the tuberomammillary nucleus of the ular peptide, its receptors and the neurons that release mouse across natural sleep–waking states (Takahashi it, appeared to be critical for the maintenance of et al., 2006). Like other monoaminergic neurons, these waking and behavioral arousal, since in its absence narcells discharge during waking and cease firing during colepsy with cataplexy occurs (Chemelli et al., 1999; sleep as W-active, or even wake-specific, cells suppoLin et al., 1999; Peyron et al., 2000; Thannickal et al., sedly not discharging at all during SWS or PS (W, Fig2000). This peptide is orexin (Orx, also called ure 9.1). Their discharge was particularly elevated hypocretin). during attentive waking, more so than during waking with movement. They would appear to differ in this Orexinergic posterior hypothalamic neurons way from both the noradrenergic and serotonergic In the 1990s, two groups simultaneously discovered a neurons and have been postulated to play a particularly new set of peptides in the hypothalamus, Sakurai and important role in attention. Such a role was supported his colleagues (1998) called them orexins (Orx A and by a diminished arousal response to novel stimuli seen B), meaning peptides that would stimulate appetite in mice with knockout of the gene for histidine decarand eating; de Lecea and his colleagues (1998) called boxylase, the synthetic enzyme for HA (Parmentier them hypocretins (Hcrt 1 and 2), meaning peptides that et al., 2002). It is also noteworthy that in narcoleptic are contained in hypothalamic neurons and have simidogs, presumed histaminergic neurons continued to larities with the gut hormone, secretin. Just 1 year later, fire, in contrast to noradrenergic locus coeruleus neuit was discovered by Yanagisawa and his collaborators rons, during episodes of cataplexy (John et al., 2004). that knockout of the gene for Orx in mice resulted in Such discharge seemingly did not affect the immobility narcolepsy and cataplexy (Chemelli et al., 1999) and or muscle atonia of the abnormal state and could be by Mignot and his collaborators (2002) that it was the partly responsible for the state of alertness and congene for the Hrct 2 (Orx 2) receptor that was lacking scious awareness that can persist during cataplectic in dogs with narcolepsy-cataplexy (Lin et al., 1999). episodes in dogs and humans. Histaminergic neurons Indeed, humans having suffered from narcolepsy with are nonetheless normally active during attentive and cataplexy were subsequently found to have mutations aroused waking when, as W-active cells, they would in Orx (Hcrt) genes, low levels of Orx (Hcrt) in cerepromote cortical activation and attention. brospinal fluid and/or loss of Orx-containing neurons Early lesion studies, employing particularly large in the hypothalamus (Peyron et al., 2000; Thannickal electrolytic or thermolytic lesions, of each of the actiet al., 2000). Clearly, orexinergic hypothalamic neurons vating or arousal systems, including the reticular forplay a critical role in maintaining waking. mation with the posterior hypothalamus (Lindsley The Orx neurons are located in the posterior portion et al., 1950) and the catecholaminergic neurons (Jones of the hypothalamus, where they are distributed across et al., 1973), revealed major deficits or elimination of the lateral hypothalamus, perifornical area, and dorcortical activation, behavioral arousal and the waking somedial nucleus (Peyron et al., 1998) (Figure 9.1). Like state in experimental animals, corroborating observathe noradrenergic locus coeruleus neurons, they give tions in human cases of coma following large brainrise to highly diffuse projections extending through stem lesions (Plum and Posner, 1980; Parvizi and the forebrain to reach the subcortical relays of the actiDamasio, 2003). Yet, when using more refined technivating systems in the thalamus and basal forebrain and ques for performing lesions and particularly using neuto continue up to the cerebral cortex. They also project rotoxins selective for cell bodies and neurons through the hypothalamus, the brainstem, and into the containing particular neurotransmitters or bearing parspinal cord. According to orexin’s effects following ticular receptors, no long-lasting deficits in waking or intracerebroventricular administration and to the cortical activation were apparent (Jones et al., 1977; effects of elimination of Orx or Orx neurons in knockWebster and Jones, 1988; Denoyer et al., 1991; Holmes out mice, the orexinergic system facilitates cortical and Jones, 1994; Blanco-Centurion et al., 2004, 2006, activation and arousal, stimulates the hypothalamo2007). These results, emerging over many years now, pituitary-adrenal and hypothalamo-pituitary-thyroid have indicated that no one neural system or neuroaxis and excites both sympathetic and motor systems transmitter is critical for generating a waking state, (Lubkin and Stricker-Krongrad, 1998; Shirasaka et al., although any one might be sufficient. The activating 1999; Hara et al., 2001; Espana et al., 2002; Yamanaka and arousal systems are thus multiple, parallel, and
NEUROBIOLOGY OF WAKING AND SLEEPING et al., 2003). Orx neurons thus stimulate arousal while activating neuroendocrine, sympathetic, and motor systems to support and sustain activity through the physiological changes associated with increased energy metabolism. This influence occurs through the excitatory action of Orx on Orx-1 or Orx-2 receptors upon multiple neurons, including cortical neurons, midline thalamocortical projection neurons, cholinergic basal forebrain neurons, histaminergic neurons, cholinergic pontomesencephalic neurons, noradrenergic locus coeruleus neurons, and motor neurons (Horvath et al., 1999; Bayer et al., 2001, 2004; Eggermann et al., 2001; Burlet et al., 2002; Yamuy et al., 2004). Interestingly, no inhibitory actions of Orx have been found, even upon the sleep-promoting neurons which are inhibited by NA (see below) (Bayer et al., 2002). The Orx neurons can thus play a central role in stimulating arousal by exciting all other arousal systems while activating neuroendocrine, sympathetic, and motor systems that support arousal and activity. Studies utilizing c-Fos expression or release of Orx indicated that Orx neurons are active and release their peptide in association with waking and arousal during the active period of the day (Kiyashchenko et al., 2002; Zeitzer et al., 2003). Yet, it remained uncertain whether they became silent during sleep and particularly REM sleep until recording from identified Orx neurons was achieved by juxtacellular labeling in the rat (Lee et al., 2005a; Mileykovskiy et al., 2005). Orx neurons were thus found to discharge during waking and virtually cease firing during SWS and PS (Figure 9.4). Their discharge occurred during active waking and was correlated with postural muscle tone recorded on the nuccal EMG (Figure 9.4, expanded traces). The Orx neurons were thus like other neurons whose discharge was positively correlated with EMG (Figure 9.3) and whose profile could be typified as W-on and PS-off (W, Figure 9.1). In their case, however, in contrast to other known cell groups, including the noradrenergic locus coeruleus neurons, their discharge is necessary to maintain active waking, since it is in their absence that narcolepsy with cataplexy occurs. Since cataplexy is often elicited by an emotional stimulus or also in animals by food, it appears to be triggered by activation of systems which act in an opposite manner to the Orx neurons during those conditions. The cholinergic neurons, which are active during both waking and REM sleep, and ACh or its agonists, which can evoke cortical activation with muscle atonia or a REM sleep-like state, could exert this opposing influence. Indeed, this influence could be exerted from both the basal forebrain and brainstem to result in cortical activation associated with a loss of muscle tonus (Reid et al., 1994a, b; Nishino et al., 1995;
141
Cape et al., 2000) during conditions when orexin release is absent, such as during natural REM sleep or narcoleptic attacks occurring in the absence of orexinergic transmission, which would otherwise override the cholinergic influence to excite motor and sympathetic systems.
SLEEP-PROMOTING SYSTEMS Although it is clear that thalamic neurons play an important role in shaping the activity of the cortex across waking and sleeping, their influence depends upon their pattern of discharge, which is tonic and fast during waking and becomes bursting and slow during sleep. In contrast, there are neurons in the forebrain and brainstem which are selectively active during sleep and thus appear to play a specific role in promoting sleep.
Preoptic region and basal forebrain From early studies involving lesions or stimulation, the preoptic region and basal forebrain were known to have the capacity to exert a sleep-promoting influence. Early lesions produced insomnia (McGinty and Sterman, 1968). Stimulation produced a predominance of parasympathetic responses, including decreased heart rate, blood pressure, respiration, and temperature along with decreased activity (Hess, 1957) and sleep (Sterman and Clemente, 1962a, b). Single-unit recording studies revealed neurons in the preoptic area and basal forebrain that discharged maximally during sleep (Szymusiak and McGinty, 1986; Alam et al., 1996; Szymusiak et al., 1998). In both these regions, however, such cells are intermingled with cells which discharge maximally during waking and PS in association with cortical activation (above) or less commonly during waking alone (above) (Koyama and Hayaishi, 1994; Lee et al., 2005b). Sleepactive neurons are of two types, one which discharges in association with cortical slow-wave, delta activity during SWS and another which discharges in association with progressively decreasing muscle tonus during SWS and PS (Figure 9.3). The SWS cell group could influence cortical deactivation or slow-wave activity by ascending projections to the cortex or local projections on to basalocortical cholinergic neurons. The SWS/PS cell group could influence muscle tone and behavioral quiescence by descending projections to the posterior hypothalamus and brainstem (Figure 9.1).
GABAergic neurons Sleep-active neurons have also been revealed by c-Fos expression during sleep recovery following deprivation (Sherin et al., 1996). By this technique, the majority of
142
B.E. JONES
Orexinergic lateral hypothalamic unit
B
W
SWS
C
tPS
D
PS
Unit EEG : RS EEG : PF EMG
A
aW
Fig. 9.4. Discharge of an Orx neuron across sleep–wake states. Record of a neuron labeled by juxtacellular technique with Neurobiotin (Nb) and identified by immunohistochemistry for Orx in the rat. As evident in 10-second traces (above), the unit fired during wakefulness (A) and was virtually silent during slow-wave sleep (B), transition to paradoxical sleep (C), and paradoxical sleep (D). As evident in an expanded trace (of approximately 4 seconds, below), the unit discharged during active wake (aW) and increased firing phasically in association with increases in muscle tone seen on the EMG. aW, active wake; EEG, electroencephalogram; EMG. electromyogram; PF, prefrontal cortex; PS, paradoxical sleep; RS, retrosplenial cortex; SWS, slow-wave sleep; tPS, transition to paradoxical sleep; W, wake. Horizontal scale bars: 1 second. Vertical scale bar: 1 mV for EEG, 0.5 mV for EMG, and 2 mV for unit. (Reprinted with permission from Lee et al. (2005a).)
sleep-active cells in the preoptic area and basal forebrain have been found to contain the synthetic enzyme for GABA (glutamic acid decarboxylase, GAD) (Gong et al., 2004; Modirrousta et al., 2004). Yet, many GABAergic neurons are active during waking and cortical activation, as evident from both c-Fos and juxtacellular recording studies (Manns et al., 2000; Modirrousta et al., 2004). The sleep-active GABAergic cells must then be different in other ways from the Wactive or W/PS-active GABAergic cells. From in vitro pharmacological studies performed first in the basal forebrain and then in the ventrolateral preoptic area (VLPO), it was discovered that, whereas cholinergic neurons were depolarized and excited by NA through a1-adrenergic receptors, a small contingent
of cells, which were identified as GABAergic in the VLPO, were hyperpolarized and inhibited by NA through a2-adrenergic receptors (Fort et al., 1995, 1998; Gallopin et al., 2000). Moreover, following juxtacellular recording and labeling of neurons that discharge maximally with slow-wave activity, it was found that a large proportion of these were GABAergic and that these particular GABAergic cells bear a2-adrenergic receptors (Manns et al., 2003). An important contingent of sleep-promoting neurons would thus be composed of GABAergic neurons in the basal forebrain and preoptic area which are inhibited by NA and would thus be disinhibited when NA release declines as locus coeruleus neurons cease discharge with decreasing arousal (Jones, 2005). Reciprocally, by
NEUROBIOLOGY OF WAKING AND SLEEPING releasing GABA, the sleep-promoting neurons can inhibit cortical or subcortical systems promoting cortical activation or behavioral arousal, including noradrenergic, histaminergic, and orexinergic neurons (Sherin et al., 1998; Steininger et al., 2001; Henny and Jones, 2006). It should also be mentioned that there are GABAergic neurons through the hypothalamus and brainstem, which can also function to inhibit arousal-promoting neurons. Notably, GABAergic neurons in the pontomesencephalic tegmentum and medulla appear to be active with sleep and PS recovery during which they may inhibit local monoaminergic cells, other reticular neurons, or motor neurons (Maloney et al., 1999, 2000; Fenik et al., 2005) (see above) (Figure 9.1). Glycinergic neurons also participate in this process (Chase et al., 1989; Boissard et al., 2002), and both GABA and glycine are released in high concentrations in the region of brainstem and spinal cord motor neurons during muscle atonia (Kodama et al., 2003). In addition, the neurons of the thalamic reticular nucleus which shape spindling activity utilize GABA through which they hyperpolarize and pace the relay neurons to induce bursting in thalamo-cortico-thalamic circuits (Steriade et al., 1994) (see above).
GABA and hypnotic drugs Given the important role of GABA in inhibiting neurons of the arousal systems and thus in promoting sleep, it is not surprising that many hypnotic drugs as well as anesthetics act as GABA agonists (Lancel, 1999; Gottesmann, 2002; Mignot et al., 2002; Rudolph and Antkowiak, 2004; Mendelson, 2005). Such drugs act upon the benzodiazepine site of the GABAA receptor (linked to chloride channels) to enhance and prolong GABA’s action or directly upon the GABAA receptor to mimic its action and promote respectively spindling activity or slow-wave activity along with sleep. Some drugs act upon GABAB receptors (linked to potassium channels) and promote slow-wave activity along with minimal muscle tone with sleep.
SUMMARY Waking and sleeping are actively generated by neuronal systems distributed through the brainstem and forebrain with different projections, discharge patterns, neurotransmitters, and receptors. Specific ascending systems stimulate cortical activation, characterized by fast, particularly gamma, activity which occurs during waking and REM sleep. In addition to glutamatergic neurons of the reticular formation and thalamus, cholinergic pontomesencephalic and basal forebrain neurons are
143
integral components of the ascending activating system. Discharging during W and REM sleep, cholinergic neurons stimulate cortical activation in the presence or absence of postural muscle tone and behavioral arousal. Comprised by glutamatergic reticulospinal and other neurons, specific descending systems stimulate behavioral arousal, characterized by postural muscle tone along with motor activity during waking. Diffusely projecting systems give rise to both ascending and descending projections and thus simultaneously facilitate both cortical activation and behavioral arousal. These include the neurons containing the modulatory neurotransmitters NA, DA, Ser, HA, and Orx. Commonly discharging during waking and ceasing to discharge during SWS and REM sleep, these systems excite through particular receptors other neurons of the activating and arousal systems to promote waking and prevent sleep. Largely parallel in their projections and actions, they are partially redundant and thus not individually necessary for the generation of waking and arousal. On the other hand, Orx is necessary for the maintenance of waking since in its absence narcolepsy with cataplexy occurs in humans and animals. These neurons excite all other activating and arousal systems along with neuroendocrine, sympathetic, and motor systems to support activity, arousal, and muscle tone. Sleeping is initiated by inhibition of the activating and arousal systems. This inhibition is effected at multiple levels through particular GABAergic neurons which become active during sleep. Neurons in the preoptic area and basal forebrain play a particularly important role in this process. Some become active during SWS, promoting deactivation and slow-wave activity in the cerebral cortex. Others discharge at progressively increasing rates during SWS and REM sleep, promoting behavioral quiescence and diminishing muscle tone. Through their projections and inhibitory neurotransmitter, they have the capacity to inhibit the monoaminergic neurons and Orx neurons in the brainstem and hypothalamus. They are in turn inhibited by NA through a2-adrenergic receptors. During REM sleep, cholinergic systems become active and stimulate cortical activation, while the monoaminergic and orexinergic systems are inhibited, leaving motor and other neurons devoid of their excitatory influence. The selective inhibition of these systems and additional direct inhibition of motor neurons by GABA (and glycine) produces a loss of behavioral responsiveness and postural muscle tone, despite maintained activation of the cerebral cortex, which characterizes this “paradoxical” state of sleep as well as its pathological manifestation in narcolepsy with cataplexy.
144
B.E. JONES
ACKNOWLEDGMENTS Most of the recent research of the author presented in this article was funded by grants from the Canadian Institutes of Health Research and US National Institutes of Health and performed at the Montreal Neurological Institute by Maan Gee Lee, Ian Manns, Oum Hassani, Mandana Modirrousta, Pablo Henny, Frederic Brischoux, and Lynda Mainville, to whom I am most grateful. I am also thankful to my collaborators Michel Muhlethaler and colleagues at the Centre Me´dicale Universitaire in Geneva, whose work is also mentioned. I also thank Napoleon Soberanis for his assistance with the schematic figures.
REFERENCES Akert K, Koella WP, Hess RJ (1952). Sleep produced by electrical stimulation of the thalamus. Am J Physiol 168: 260–267. Alam MN, McGinty D, Szymusiak R (1996). Preoptic/anterior hypothalamic neurons: thermosensitivity in wakefulness and non rapid eye movement sleep. Brain Res 718 (1–2): 76–82. Aston-Jones G, Bloom FE (1981). Activity of norepinephrine-containing locus coeruleus neurons in behaving rats anticipates fluctuations in the sleep-waking cycle. J Neurosci 1: 876–886. Baghdoyan HA, Rodrigo-Angulo ML, McCarley RW et al. (1984). Site-specific enhancement and suppression of desynchronized sleep signs following cholinergic stimulation of three brainstem regions. Brain Res 306: 39–52. Barbeau H, Rossignol S (1990). The effects of serotonergic drugs on the locomotor pattern and on cutaneous reflexes of the adult chronic spinal cat. Brain Res 514 (1): 55–67. Bayer L, Eggermann E, Serafin M et al. (2001). Orexins (hypocretins) directly excite tuberomammillary neurones. Eur J Neurosci 14: 1571–1575. Bayer L, Eggermann E, Saint-Mleux B et al. (2002). Selective action of orexin (hypocretin) on nonspecific thalamocortical projection neurons. J Neurosci 22 (18): 7835–7839. Bayer L, Serafin M, Eggermann E et al. (2004). Exclusive postsynaptic action of hypocretin-orexin on sublayer 6b cortical neurons. J Neurosci 24 (30): 6760–6764. Bayer L, Eggermann E, Serafin M et al. (2005). Opposite effects of noradrenaline and acetylcholine upon hypocretin/orexin versus melanin concentrating hormone neurons in rat hypothalamic slices. Neuroscience 130 (4): 807–811. Beaulieu C, Somogyi P (1991). Enrichment of cholinergic synaptic terminals on GABAergic neurons and coexistence of immunoreactive GABA and choline acetyltransferase in the same synaptic terminals in the striate cortex of the cat. J Comp Neurol 304: 666–680. Blanco-Centurion C, Gerashchenko D, Salin-Pascual RJ et al. (2004). Effects of hypocretin2-saporin and antidopaminebeta-hydroxylase-saporin neurotoxic lesions of the dorsolateral pons on sleep and muscle tone. Eur J Neurosci 19 (10): 2741–2752.
Blanco-Centurion C, Xu M, Murillo-Rodriguez E et al. (2006). Adenosine and sleep homeostasis in the basal forebrain. J Neurosci 26 (31): 8092–8100. Blanco-Centurion C, Gerashchenko D, Shiromani PJ (2007). Effects of saporin-induced lesions of three arousal populations on daily levels of sleep and wake. J Neurosci 27 (51): 14041–14048. Boissard R, Gervasoni D, Schmidt MH et al. (2002). The rat ponto-medullary network responsible for paradoxical sleep onset and maintenance: a combined microinjection and functional neuroanatomical study. Eur J Neurosci 16 (10): 1959–1973. Bremer F (1929). Cerveau ‘isole´’ et physiologie du sommeil. C R Soc Biol (Paris) 102: 1235–1241. Burlet S, Tyler CJ, Leonard CS (2002). Direct and indirect excitation of laterodorsal tegmental neurons by hypocretin/orexin peptides: implications for wakefulness and narcolepsy. J Neurosci 22 (7): 2862–2872. Cape EG, Jones BE (1998). Differential modulation of high frequency gamma electroencephalogram activity and sleep–wake state by noradrenaline and serotonin microinjections into the region of cholinergic basalis neurons. J Neurosci 18: 2653–2666. Cape EG, Jones BE (2000). Effects of glutamate agonist versus procaine microinjections into the basal forebrain cholinergic cell area upon gamma and theta EEG activity and sleep–wake state. Eur J Neurosci 12: 2166–2184. Cape EG, Manns ID, Alonso A et al. (2000). Neurotensininduced bursting of cholinergic basal forebrain neurons promotes gamma and theta cortical activity together with waking and paradoxical sleep. J Neurosci 20: 8452–8461. Celesia GG, Jasper HH (1966). Acetylcholine released from cerebral cortex in relation to state of activation. Neurology 16: 1053–1064. Chase MH, Soja PJ, Morales FR (1989). Evidence that glycine mediates the postsynaptic potentials that inhibit lumbar motoneurons during the atonia of active sleep. J Neurosci 9: 743–751. Chemelli RM, Willie JT, Sinton CM et al. (1999). Narcolepsy in orexin knockout mice: molecular genetics of sleep regulation. Cell 98 (4): 437–451. Dahan L, Astier B, Vautrelle N et al. (2007). Prominent burst firing of dopaminergic neurons in the ventral tegmental area during paradoxical sleep. Neuropsychopharmacology 32 (6): 1232–1241. Dahlstrom A, Fuxe K (1964). Evidence for the existence of monoamine-containing neurons in the central nervous system. I. Demonstration of monoamines in the cell bodies of brain stem neurons. Acta Physiol Scand 62 (Suppl. 232): 1–55. de Lecea L, Kilduff TS, Peyron C et al. (1998). The hypocretins: hypothalamus-specific peptides with neuroexcitatory activity. Proc Natl Acad Sci U S A 95 (1): 322–327. Denoyer M, Sallanon M, Buda C et al. (1991). Neurotoxic lesion of the mesencephalic reticular formation and/or the posterior hypothalamus does not alter waking in the cat. Brain Res 539: 287–303.
NEUROBIOLOGY OF WAKING AND SLEEPING Descarries L, Watkins KC, Lapierre Y (1977). Noradrenergic axon terminals in the cerebral cortex of rat. III. Topometric ultrastructural analysis. Brain Res 133: 197–222. Domino EF, Yamamoto K, Dren AT (1968). Role of cholinergic mechanisms in states of wakefulness and sleep. Progr Brain Res 28: 113–133. Eggermann E, Serafin M, Bayer L et al. (2001). Orexins/ hypocretins excite basal forebrain cholinergic neurones. Neuroscience 108: 177–181. El Mansari M, Sakai M, Jouvet M (1989). Unitary characteristics of presumptive cholinergic tegmental neurons during the sleep–waking cycle in freely moving cats. Exp Brain Res 76: 519–529. Espana RA, Plahn S, Berridge CW (2002). Circadian-dependent and circadian-independent behavioral actions of hypocretin/orexin. Brain Res 943 (2): 224–236. Fenik VB, Davies RO, Kubin L (2005). Noradrenergic, serotonergic and GABAergic antagonists injected together into the XII nucleus abolish the REM sleep-like depression of hypoglossal motoneuronal activity. J Sleep Res 14 (4): 419–429. Fields HL, Basbaum AI (1978). Brain stem control of spinal pain transmission neurons. Ann Rev Physiol 40: 193–221. Ford B, Holmes C, Mainville L et al. (1995). GABAergic neurons in the rat pontomesencephalic tegmentum: codistribution with cholinergic and other tegmental neurons projecting to the posterior lateral hypothalamus. J Comp Neurol 363: 177–196. Fort P, Luppi PH, Jouvet M (1993). Glycine-immunoreactive neurones in the cat brain stem reticular formation. Neuroreport 4 (9): 1123–1126. Fort P, Khateb A, Pegna A et al. (1995). Noradrenergic modulation of cholinergic nucleus basalis neurons demonstrated by in vitro pharmacological and immunohistochemical evidence in the guinea pig brain. Eur J Neurosci 7: 1502–1511. Fort P, Khateb A, Serafin M et al. (1998). Pharmacological characterization and differentiation of non-cholinergic nucleus basalis neurons in vitro. Neuroreport 9: 1–5. Fremeau RTJr., Troyer MD, Pahner I et al. (2001). The expression of vesicular glutamate transporters defines two classes of excitatory synapse. Neuron 31 (2): 247–260. Gallopin T, Fort P, Eggermann E et al. (2000). Identification of sleep-promoting neurons in vitro. Nature 404: 992–995. Gaykema RP, Zaborszky L (1996). Direct catecholaminergiccholinergic interactions in the basal forebrain. II. Substantia nigra-ventral tegmental area projections to cholinergic neurons. J Comp Neurol 374 (4): 555–577. George R, Haslett W, Jenden D (1964). A cholinergic mechanism in the brainstem reticular formation: induction of paradoxical sleep. Int J Neuropharmacol 3: 541–552. Glenn LL, Steriade M (1982). Discharge rate and excitability of cortically projecting intralaminar thalamic neurons during waking and sleep states. J Neurosci 2: 1387–1404. Gong H, McGinty D, Guzman-Marin R et al. (2004). Activation of c-fos in GABAergic neurones in the preoptic area during sleep and in response to sleep deprivation. J Physiol 556 (Pt 3): 935–946.
145
Gottesmann C (2002). GABA mechanisms and sleep. Neuroscience 111 (2): 231–239. Hara J, Beuckmann CT, Nambu T et al. (2001). Genetic ablation of orexin neurons in mice results in narcolepsy, hypophagia, and obesity. Neuron 30 (2): 345–354. Henny P, Jones BE (2006). Innervation of orexin/hypocretin neurons by GABAergic, glutamatergic or cholinergic basal forebrain terminals evidenced by immunostaining for presynaptic vesicular transporter and postsynaptic scaffolding proteins. J Comp Neurol 499: 645–661. Henny P, Jones BE (2008). Projections from basal forebrain to prefrontal cortex comprise cholinergic, GABAergic and glutamatergic inputs to pyramidal cells or interneurons. Eur J Neurosci 27 (3): 654–670. Herkenham M (1986). New perspectives on the organization and evolution of nonspecific thalamocortical projections. In: EG Jones, A Peters (Eds.), Cerebral Cortex, Vol. 5. Plenum, New York, pp. 403–445. Hess WR (1957). The Functional Organization of the Diencephalon. Grune & Stratton, New York. Holmes CJ, Jones BE (1994). Importance of cholinergic, GABAergic, serotonergic and other neurons in the medullary reticular formation for sleep–wake states studied by cytotoxic lesions in the cat. Neuroscience 62: 1179–1200. Holstege JC, Bongers CMH (1991). A glycinergic projection from the ventromedial lower brainstem to spinal motoneurons. An ultrastructural double labeling study in rat. Brain Res 566: 308–315. Horvath TL, Peyron C, Diano S et al. (1999). Hypocretin (orexin) activation and synaptic innervation of the locus coeruleus noradrenergic system. J Comp Neurol 415 (2): 145–159. Hur EE, Zaborszky L (2005). Vglut2 afferents to the medial prefrontal and primary somatosensory cortices: a combined retrograde tracing in situ hybridization. J Comp Neurol 483 (3): 351–373. Jacobs BL, Fornal CA (1999). Activity of serotonergic neurons in behaving animals. Neuropsychopharmacology 21 (2 Suppl): 9S–15S. Jacobs BL, Abercrombie ED, Fornal CA et al. (1991). Singleunit and physiological analyses of brain norepinephrine function in behaving animals. Progr Brain Res 88: 159–165. Jasper HH, Tessier J (1971). Acetylcholine liberation from cerebral cortex during paradoxical (REM) sleep. Science 172: 601–602. John J, Wu MF, Boehmer LN et al. (2004). Cataplexy-active neurons in the hypothalamus: implications for the role of histamine in sleep and waking behavior. Neuron 42 (4): 619–634. Jones BE (1990). Immunohistochemical study of choline acetyl transferase-immunoreactive processes and cells innervating the pontomedullary reticular formation. J Comp Neurol 295: 485–514. Jones BE (1995). Reticular formation. Cytoarchitecture, transmitters and projections. In: G Paxinos. (Ed.), The Rat Nervous System. Academic Press, Sydney, Australia, pp. 155–171.
146
B.E. JONES
Jones BE (2004). Activity, modulation and role of basal forebrain cholinergic neurons innervating the cerebral cortex. Progr Brain Res 145: 157–169. Jones BE (2005). From waking to sleeping: neuronal and chemical substrates. Trends Pharmacol Sci 26: 578–586. Jones BE, Cuello AC (1989). Afferents to the basal forebrain cholinergic cell area from pontomesencephalic – catecholamine, serotonin, and acetylcholine – neurons. Neuroscience 31: 37–61. Jones BE, Moore RY (1977). Ascending projections of the locus coeruleus in the rat. II. Autoradiographic study. Brain Res 127: 23–53. Jones BE, Yang T-Z (1985). The efferent projections from the reticular formation and the locus coeruleus studied by anterograde and retrograde axonal transport in the rat. J Comp Neurol 242: 56–92. Jones BE, Bobillier P, Pin C et al. (1973). The effect of lesions of catecholamine-containing neurons upon monoamine content of the brain and EEG and behavioral waking in the cat. Brain Res 58: 157–177. Jones BE, Harper ST, Halaris AE (1977). Effects of locus coeruleus lesions upon cerebral monoamine content, sleep–wakefulness states and the response to amphetamine. Brain Res 124: 473–496. Jones BE, Holmes CJ, Rodriguez-Veiga E et al. (1991). GABA-synthesizing neurons in the medulla: their relationship to serotonin-containing and spinally projecting neurons in the rat. J Comp Neurol 312: 1–19. Jouvet M (1969). Biogenic amines and the states of sleep. Science 163: 32–41. Jouvet M (1972). The role of monoamines and acetylcholinecontaining neurons in the regulation of the sleep–waking cycle. Ergeb Physiol 64: 165–307. Kaneko T, Itoh K, Shigemoto R et al. (1989). Glutaminaselike immunoreactivity in the lower brainstem and cerebellum of the adult rat. Neuroscience 32: 79–98. Kaneko T, Fujiyama F, Hioki H (2002). Immunohistochemical localization of candidates for vesicular glutamate transporters in the rat brain. J Comp Neurol 444 (1): 39–62. Kayama Y, Ohta M, Jodo E (1992). Firing of “possibly” cholinergic neurons in the rat laterodorsal tegmental nucleus during sleep and wakefulness. Brain Res 569: 210–220. Khateb A, Fort P, Alonso A et al. (1993). Pharmacological and immunohistochemical evidence for a serotonergic input to cholinergic nucleus basalis neurons. Eur J Neurosci 5: 541–547. Khateb A, Fort P, Pegna A et al. (1995). Cholinergic nucleus basalis neurons are excited by histamine in vitro. Neuroscience 69: 495–506. Kiyashchenko LI, Mileykovskiy BY, Maidment N et al. (2002). Release of hypocretin (orexin) during waking and sleep states. J Neurosci 22 (13): 5282–5286. Kjaerulff O, Kiehn O (2001). 5-HT modulation of multiple inward rectifiers in motoneurons in intact preparations of the neonatal rat spinal cord. J Neurophysiol 85 (2): 580–593.
Kleitman N (1939). Sleep and Wakefulness. University of Chicago Press, Chicago. Kodama T, Lai YY, Siegel JM (2003). Changes in inhibitory amino acid release linked to pontine-induced atonia: an in vivo microdialysis study. J Neurosci 23 (4): 1548–1554. Koyama Y, Hayaishi O (1994). Firing of neurons in the preoptic/anterior hypothalamic areas in rat: its possible involvement in slow wave sleep and paradoxical sleep. Neurosci Res 19: 31–38. Krnjevic K, Phillis JW (1963). Pharmacological properties of acetylcholine-sensitive cells in the cerebral cortex. J Physiol (Lond) 166: 328–350. Kubin L, Tojima H, Davies RO et al. (1992). Serotonergic excitatory drive to hypoglossal motoneurons in the decerebrate cat. Neurosci Lett 139: 243–248. Lancel M (1999). Role of GABAA receptors in the regulation of sleep: initial sleep responses to peripherally administered modulators and agonists. Sleep 22 (1): 33–42. Lee MG, Hassani O, Jones BE (2005a). Discharge of identified orexin/hypocretin neurons across the sleep-waking cycle. J Neurosci 25 (28): 6716–6720. Lee MG, Hassani OK, Alonso A et al. (2005b). Cholinergic basal forebrain neurons burst with theta during waking and paradoxical sleep. J Neurosci 25 (17): 4365–4369. Lin JS, Sakai K, Jouvet M (1988). Evidence for histaminergic arousal mechanisms in the hypothalamus of cats. Neuropharmacol 27: 111–122. Lin JS, Roussel B, Akaoka H et al. (1992). Role of catecholamines in the modafinil and amphetamine induced wakefulness, a comparative pharmacological study in the cat. Brain Res 591: 319–326. Lin L, Faraco J, Li R et al. (1999). The sleep disorder canine narcolepsy is caused by a mutation in the hypocretin (orexin) receptor 2 gene. Cell 98 (3): 365–376. Lindsley DB, Schreiner LH, Knowles WB et al. (1950). Behavioral and EEG changes following chronic brain stem lesions. Electroencephalogr Clin Neurophysiol 2: 483–498. Longo VG (1966). Behavioral and electroencephalographic effects of atropine and related compounds. Pharmacol Rev 18: 965–996. Lubkin M, Stricker-Krongrad A (1998). Independent feeding and metabolic actions of orexins in mice. Biochem Biophys Res Commun 253 (2): 241–245. Luebke JI, Greene RW, Semba K et al. (1992). Serotonin hyperpolarizes cholinergic low-threshold burst neurons in the rat laterodorsal tegmental nucleus in vitro. Proc Natl Acad Sci 89: 743–747. McCarley RW, Hobson JA (1975). Neuronal excitability modulation over the sleep cycle: a structural and mathematical model. Science 189: 58–60. McCormick DA (1992). Neurotransmitter actions in the thalamus and cerebral cortex and their role in neuromodulation of thalamocortical activity. Prog Neurobiol 39: 337–388. McCormick DA (1993). Actions of acetylcholine in the cerebral cortex and thalamus and implications for function. Prog Brain Res 98: 303–308.
NEUROBIOLOGY OF WAKING AND SLEEPING McGinty DJ, Sterman MB (1968). Sleep suppression after basal forebrain lesions in the cat. Science 160: 1253–1255. McGinty D, Harper RM (1976). Dorsal raphe neurons: depression of firing during sleep in cats. Brain Res 101: 569–575. Magoun HW, Rhines R (1946). An inhibitory mechanism in the bulbar reticular formation. J Neurophysiol 9: 165–171. Maloney KJ, Mainville L, Jones BE (1999). Differential c-Fos expression in cholinergic, monoaminergic and GABAergic cell groups of the pontomesencephalic tegmentum after paradoxical sleep deprivation and recovery. J Neurosci 19: 3057–3072. Maloney KJ, Mainville L, Jones BE (2000). C-Fos expression in GABAergic, serotonergic and other neurons of the pontomedullary reticular formation and raphe after paradoxical sleep deprivation and recovery. J Neurosci 20: 4669–4679. Maloney K, Mainville L, Jones BE (2002). C-Fos expression in dopaminergic and GABAergic neurons of the ventral mesencephalic tegmentum after paradoxical sleep deprivation and recovery. Eur J Neurosci 15: 1–6. Manns ID, Alonso A, Jones BE (2000). Discharge profiles of juxtacellularly labeled and immunohistochemically identified GABAergic basal forebrain neurons recorded in association with the electroencephalogram in anesthetized rats. J Neurosci 20: 9252–9263. Manns ID, Lee MG, Modirrousta M et al. (2003). Alpha 2 adrenergic receptors on GABAergic, putative sleeppromoting basal forebrain neurons. Eur J Neurosci 18 (3): 723–727. Mendelson WB (2005). Hypnotic medications: mechanisms of action and pharmacologic effects. In: MH Kryger, T Roth, W Dement (Eds.), Principles and Practice of Sleep Medicine. Elsevier Saunders, Philadelphia, pp. 444–451. Mesulam M-M, Mufson EJ, Levey AI et al. (1983a). Cholinergic innervation of cortex by the basal forebrain: cytochemistry and cortical connections of the septal area, diagonal band nuclei, nucleus basalis (substantia innominata), and hypothalamus in the rhesus monkey. J Comp Neurol 214: 170–197. Mesulam M-M, Mufson EJ, Wainer BH et al. (1983b). Central cholinergic pathways in the rat: an overview based on an alternative nomenclature (Ch1–Ch6). Neuroscience 10: 1185–1201. Metherate R, Cox CL, Ashe JH (1992). Cellular bases of neocortical activation: modulation of neural oscillations by the nucleus basalis and endogenous acetylcholine. J Neurosci 12: 4701–4711. Mignot E, Taheri S, Nishino S (2002). Sleeping with the hypothalamus: emerging therapeutic targets for sleep disorders. Nat Neurosci 5 (Suppl): 1071–1075. Mileykovskiy BY, Kiyashchenko LI, Siegel JM (2005). Behavioral correlates of activity in identified hypocretin/orexin neurons. Neuron 46 (5): 787–798. Miller JD, Farber J, Gatz P et al. (1983). Activity of mesencephalic dopamine and non-dopamine neurons across
147
stages of sleep and waking in the rat. Brain Res 273 (1): 133–141. Mitani A, Ito K, Hallanger AE et al. (1988). Cholinergic projections from the laterodorsal and pedunculopontine tegmental nuclei to the pontine gigantocellular tegmental field in the cat. Brain Res 451: 397–402. Modirrousta M, Mainville L, Jones BE (2004). GABAergic neurons with alpha2-adrenergic receptors in basal forebrain and preoptic area express c-Fos during sleep. Neuroscience 129 (3): 803–810. Monckton JE, McCormick DA (2002). Neuromodulatory role of serotonin in the ferret thalamus. J Neurophysiol 87 (4): 2124–2136. Montaron M-F, Bouyer J-J, Rougeul A et al. (1982). Ventral mesencephalic tegmentum (VMT) controls electrocortical beta rhythms and associated attentive behaviour in the cat. Behav Brain Res 6: 129–145. Moore RY, Bloom FE (1979). Central catecholamine neuron systems: anatomy and physiology of the norepinephrine and epinephrine systems. Ann Rev Neurosci 2: 113–168. Moruzzi G, Magoun HW (1949). Brain stem reticular formation and activation of the EEG. Electroencephalogr Clin Neurophysiol 1: 455–473. Nauta WJH, Kuypers HGJM (1958). Some ascending pathways in the brain stem reticular formation. In: HH Jasper, LD Proctor, RS Knighton et al. (Eds.), Reticular Formation of the Brain. Little, Brown, Boston, pp. 3–30. Nishino S, Tafti M, Reid MS et al. (1995). Muscle atonia is triggered by cholinergic stimulation of the basal forebrain: implication for the pathophysiology of canine narcolepsy. J Neurosci 15: 4806–4814. Parmentier R, Ohtsu H, Djebbara-Hannas Z et al. (2002). Anatomical, physiological, and pharmacological characteristics of histidine decarboxylase knock-out mice: evidence for the role of brain histamine in behavioral and sleep–wake control. J Neurosci 22 (17): 7695–7711. Parvizi J, Damasio AR (2003). Neuroanatomical correlates of brainstem coma. Brain 126 (Pt 7): 1524–1536. Peyron C, Tighe DK, van den Pol AN et al. (1998). Neurons containing hypocretin (orexin) project to multiple neuronal systems. J Neurosci 18 (23): 9996–10015. Peyron C, Faraco J, Rogers W et al. (2000). A mutation in a case of early onset narcolepsy and a generalized absence of hypocretin peptides in human narcoleptic brains. Nat Med 6 (9): 991–997. Plum F, Posner JB (1980). The Diagnosis of Stupor and Coma. Davis, Philadelphia. Reid MS, Siegel JM, Dement WC et al. (1994a). Cholinergic mechanisms in canine narcolepsy II. Acetylcholine release in the pontine reticular formation is enhanced during cataplexy. Neuroscience 59 (3): 523–530. Reid MS, Tafti M, Nishino S et al. (1994b). Cholinergic regulation of cataplexy in canine narcolepsy in the pontine reticular formation is mediated by M2 muscarinic receptors. Sleep 17: 424–435. Reiner PB, Kamondi A (1994). Mechanisms of antihistamineinduced sedation in the human brain: H1 receptor
148
B.E. JONES
activation reduces a background leakage potassium current. Neuroscience 59: 579–588. Rudolph U, Antkowiak B (2004). Molecular and neuronal substrates for general anaesthetics. Nat Rev Neurosci 5 (9): 709–720. Sakai K, Sastre J-P, Kanamori N et al. (1981). State-specific neurons in the ponto-medullary reticular formation with special reference to the postural atonia during paradoxical sleep in the cat. In: O Pompeiano, C Ajmone-Marsan (Eds.), Brain Mechanisms and Perceptual Awareness. Raven Press, New York, pp. 405–429. Sakurai T, Amemiya A, Ishii M et al. (1998). Orexins and orexin receptors: a family of hypothalamic neuropeptides and G protein-coupled receptors that regulate feeding behavior. Cell 92 (4): 573–585. Sanchez-Gonzalez MA, Garcia-Cabezas MA, Rico B et al. (2005). The primate thalamus is a key target for brain dopamine. J Neurosci 25 (26): 6076–6083. Scheibel ME, Scheibel AB (1958). Structural substrates for integrative patterns in the brain stem reticular core. In: HH Jasper, LD Proctor, RS Knighton et al. (Eds.), Reticular Formation of the Brain. Little, Brown, Boston, pp. 31–55. Schwartz JC, Arrang JM, Garbarg M et al. (1991). Histaminergic transmission in the mammalian brain. Physiol Rev 71 (1): 1–51. Semba K, Reiner PB, Fibiger HC (1990). Single cholinergic mesopontine tegmental neurons project to both the pontine reticular formation and the thalamus in the rat. Neuroscience 38 (3): 643–654. Sherin JE, Shiromani PJ, McCarley RW et al. (1996). Activation of ventrolateral preoptic neurons during sleep. Science 271: 216–219. Sherin JE, Elmquist JK, Torrealba F et al. (1998). Innervation of histaminergic tuberomammillary neurons by GABAergic and galaninergic neurons in the ventrolateral preoptic nucleus of the rat. J Neurosci 18 (12): 4705–4721. Shirasaka T, Nakazato M, Matsukura S et al. (1999). Sympathetic and cardiovascular actions of orexins in conscious rats. Am J Physiol 277 (6 Pt 2): R1780–R1785. Shute CCD, Lewis PR (1967). The ascending cholinergic reticular system: neocortical, olfactory and subcortical projections. Brain 90: 497–520. Siegel JM, McGinty DJ, Breedlove SM (1977). Sleep and waking activity of pontine gigantocellular field neurons. Exp Neurol 56: 553–573. Siegel JM, Wheeler RL, McGinty DJ (1979). Activity of medullary reticular formation neurons in the unrestrained cat during waking and sleep. Brain Res 179: 49–60. Siegel JM, Nienhuis R, Fahringer HM et al. (1991). Neuronal activity in narcolepsy: identification of cataplexy-related cells in the medial medulla. Science 252: 1315–1318. Sprague JM, Chambers WW (1954). Control of posture by reticular formation and cerebellum in the intact, anesthetized and unanesthetized and in the decerebrated cat. Am J Physiol 176: 52–64. Sqalli-Houssaini Y, Cazalets JR (2000). Noradrenergic control of locomotor networks in the in vitro spinal cord of the neonatal rat. Brain Res 852 (1): 100–109.
Starzl TE, Taylor CW, Magoun HW (1951). Ascending conduction in reticular activating system, with special reference to the diencephalon. J Neurophysiol 14: 461–477. Steininger TL, Gong H, McGinty D et al. (2001). Subregional organization of preoptic area/anterior hypothalamic projections to arousal-related monoaminergic cell groups. J Comp Neurol 429 (4): 638–653. Steriade M, Llinas RR (1988). The functional states of the thalamus and the associated neuronal interplay. Physiol Rev 68: 649–742. Steriade M, Oakson G, Ropert N (1982). Firing rates and patterns of midbrain reticular neurons during steady and transitional states of the sleep–waking cycle. Exp Brain Res 46: 37–51. Steriade M, Curro Dossi R, Contreras D (1993a). Electrophysiological properties of intralaminar thalamocortical cells discharging rhythmic (approximately 40 Hz) spike-bursts at approximately 1000 Hz during waking and rapid eye movement sleep. Neuroscience 56 (1): 1–9. Steriade M, McCormick DA, Sejnowski TJ (1993b). Thalamocortical oscillations in the sleeping and aroused brain. Science 262 (5134): 679–685. Steriade M, Contreras D, Amzica F (1994). Synchronized sleep oscillations and their paroxysmal developments. Trends Neurosci 17: 199–208. Sterman MB, Clemente CD (1962a). Forebrain inhibitory mechanisms: cortical synchronization induced by basal forebrain stimulation. Exp Neurol 6: 91–102. Sterman MB, Clemente CD (1962b). Forebrain inhibitory mechanisms: sleep patterns induced by basal forebrain stimulation in the behaving cat. Exp Neurol 6: 103–117. Szymusiak R, McGinty D (1986). Sleep-related neuronal discharge in the basal forebrain of cats. Brain Res 370: 82–92. Szymusiak R, Alam N, Steininger TL et al. (1998). Sleep– waking discharge patterns of ventrolateral preoptic/anterior hypothalamic neurons in rats. Brain Res 803: 178–188. Takahashi K, Lin JS, Sakai K (2006). Neuronal activity of histaminergic tuberomammillary neurons during wake-sleep states in the mouse. J Neurosci 26 (40): 10292–10298. Thannickal TC, Moore RY, Nienhuis R et al. (2000). Reduced number of hypocretin neurons in human narcolepsy. Neuron 27 (3): 469–474. Ungerstedt U (1971a). Adipsia and aphagia after 6-hydroxydopamine induced degeneration of the nigro-striatal dopamine system. Acta Physiol Scand Suppl 367: 95–122. Ungerstedt U (1971b). Stereotaxic mapping of the monoamine pathways in the rat brain. Acta Physiol Scand Suppl 367: 1–48. Vital-Durand F, Michel F (1969). [Effects of sensory deafferentation on the wakefulness-sleep cycle]. J Physiol (Paris) 61 (Suppl 1): 186. von Economo C (1930). Sleep as a problem of localization. Journal of Nervous and Mental Disease 71 (3): 249–259. Webster HH, Jones BE (1988). Neurotoxic lesions of the dorsolateral pontomesencephalic tegmentum-cholinergic
NEUROBIOLOGY OF WAKING AND SLEEPING cell area in the cat. II. Effects upon sleep–waking states. Brain Res 458: 285–302. Wisor JP, Nishino S, Sora I et al. (2001). Dopaminergic role in stimulant-induced wakefulness. J Neurosci 21 (5): 1787–1794. Yamanaka A, Beuckmann CT, Willie JT et al. (2003). Hypothalamic orexin neurons regulate arousal according to energy balance in mice. Neuron 38 (5): 701–713.
149
Yamuy J, Fung SJ, Xi M et al. (2004). Hypocretinergic control of spinal cord motoneurons. J Neurosci 24 (23): 5336–5345. Zeitzer JM, Buckmaster CL, Parker KJ et al. (2003). Circadian and homeostatic regulation of hypocretin in a primate model: implications for the consolidation of wakefulness. J Neurosci 23 (8): 3555–3560.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 10
Neurobiology of REM sleep ROBERT W. MCCARLEY * Neuroscience Laboratory and Harvard Department of Psychiatry, VA Boston Healthcare System, Brockton, MA, USA
INTRODUCTION This chapter presents an overview of the current “state of the art” of knowledge of the neurophysiology and cellular pharmacology of sleep mechanisms. It is written from the perspective that recent years have seen a remarkable development of knowledge about sleep mechanisms, due to the capability of current cellular neurophysiological, pharmacological, and molecular techniques to provide focused, detailed, and replicable studies that have enriched and informed the knowledge of sleep phenomenology and pathology derived from electroencephalogram (EEG) analysis. This chapter has a cellular and neurophysiological/neuropharmacological focus, with most of the emphasis on mechanisms relevant to rapid eye movement (REM) sleep. With respect to a detailed historical introduction to the topics of this chapter, this is available in Steriade and McCarley (2005). For the reader interested in an update on the terminology and techniques of cellular physiology, one of the standard neurobiology texts could be consulted (Kandel et al., 2000). Overviews of REM sleep physiology are also available (McCarley, 2004; Steriade and McCarley, 2005), and the present chapter draws on these accounts for the text. We begin this chapter with brief and elementary overviews of sleep architecture and phylogeny/ontogeny so as to provide a basis for the later mechanistic discussions. We then move to a discussion of REM sleep and the relevant anatomy and physiology, then comment very briefly on the role of hypocretin/orexin in REM sleep control. Sleep may be divided into two phases. REM sleep is most often associated with vivid dreaming and a high level of brain activity. The other phase of sleep, called non-REM sleep or slow-wave sleep (SWS), is usually associated with reduced neuronal activity; thought
*
content during this state in humans is, unlike dreams, usually nonvisual and consisting of ruminative thoughts. As one goes to sleep the low-voltage fast EEG of waking gradually gives way to a slowing of frequency and, as sleep moves toward the deepest stages, there is an abundance of delta waves, EEG waves with a frequency of 0.5 to < 4 Hz and of high amplitude. The first REM period usually occurs about 70 minutes after the onset of sleep. REM sleep in humans is defined by the presence of low-voltage fast EEG activity, suppression of muscle tone (usually measured in the chin muscles) and the presence, of course, of REMs. The first REM sleep episode in humans is short. After the first REM sleep episode, the sleep cycle repeats itself with the appearance of non-REM sleep and then about 90 minutes after the start of the first REM period, another REM sleep episode occurs. This rhythmic cycling persists throughout the night. The REM sleep cycle length is 90 minutes in humans and the duration of each REM sleep episode after the first is approximately 30 minutes. While EEG staging of REM sleep in humans usually shows a fairly abrupt transition from non-REM to REM sleep, recording of neuronal activity in animals presents a quite a different picture. Neuronal activity begins to change long before the EEG signs of REM sleep are present. To introduce this concept, Figure 10.1 shows a schematic of the time course of neuronal activity relative to EEG definitions of REM sleep. Later portions of this chapter will elaborate on the activity depicted in this figure. Over the course of the night delta wave activity tends to diminish and non-REM sleep has waves of higher frequencies and lower amplitude. REM sleep is present in all mammals, and recent data suggest this includes the egg-laying mammals
Correspondence to: Robert W. McCarley, M.D., Director, Neuroscience Laboratory, Professor and Head, Harvard Department of Psychiatry, VA Boston Healthcare System, 940 Belmont Street, Brockton, Massachusetts 02301, USA. Tel: (508) 583-4500 x63723, E-mail:
[email protected]
152
R.W. MCCARLEY Time course of REM sleep and sleep neurotransmitter rhythms: REM-on neurons, , acetylcholine REM-off neurons, , norepinephrine, serotonin 4
Relative level
3 2 1 0 0
1
2
3
4
5
Time in hours since sleep onset
6
7
8
= REM sleep.
Fig. 10.1. Schematic of a night’s course of rapid eye movement (REM) sleep in humans showing the occurrence and intensity of REM sleep as dependent upon the activity of populations of “REM-on” ( ¼ REM-promoting neurons), indicated by the solid line. As the REM-promoting neuronal activity reaches a certain threshold, the full set of REM signs occurs (dark areas under curve indicate REM sleep). Note, however that, unlike the step-like electroencephalographic diagnosis of stage, the underlying neuronal activity is a continuous function. The neurotransmitter acetylcholine is thought to be important in REM sleep production, acting to excite populations of brainstem reticular formation neurons to produce the set of REM signs. Other neuronal populations utilizing the monoamine neurotransmitters serotonin and norepinephrine are likely REM-suppressive; the time course of their activity is sketched by the dotted line. The terms REM-on and REM-off generally apply to other neuronal populations important in REM sleep, including those utilizing the neurotransmitter gamma-aminobutyric acid. (These curves mimic actual time courses of neuronal activity, as recorded in animals, and were generated by a mathematical model of REM sleep in humans, the limit cycle reciprocal interaction model of McCarley and Massaquoi (1986a)).
(monotremes), such as the echidna (spiny anteater) and the duckbill platypus. Birds have very brief bouts of REM sleep. REM sleep cycles vary in duration according to the size of the animal, with elephants having the longest cycle and smaller animals having shorter cycles. For example, the cat has a sleep cycle of approximately 22 minutes, while the rat cycle is about 12 minutes. In utero, mammals spend a large percentage of time in REM sleep, ranging from 50% to 80% of a 24-hour day. At birth, animals born with immature nervous systems have a much higher percentage of REM sleep than do the adults of the same species. For example, sleep in the human newborn occupies two-thirds of the time, with REM sleep occupying one-half of the total sleep time, or about one-third of the entire 24-hour period. The percentage of REM sleep declines rapidly in early childhood so that by approximately age 10 the adult percentage of REM sleep is reached, 20% of total sleep time. The predominance of REM sleep in the young suggests an important function in promoting nervous system growth and development. Delta sleep is minimally present in the newborn but increases over the first years of life, reaching a maximum at about age 10 and declining thereafter. Feinberg and coworkers (1990) have noted the first three decades of this delta activity time course can be fit by a
gamma probability distribution and that approximately the same time course obtains for synaptic density and positron emission tomography measurements of metabolic rate in human frontal cortex. They speculate that the reduction in these three variables may reflect a pruning of redundant cortical synapses that is a key factor in cognitive maturation, allowing greater specialization and sustained problem-solving.
REM SLEEP PHYSIOLOGY AND RELEVANT BRAIN ANATOMY REM-promoting systems TRANSECTION
STUDIES
Lesion studies performed by Jouvet and co-workers in France demonstrated that the brainstem contains the neural machinery of the REM sleep rhythm (reviewed in Steriade and McCarley, 2005). As illustrated in Figure 10.2, a transection made just above the junction of the pons and midbrain produced a state in which periodic occurrence of REM sleep was found in recordings made in the isolated brainstem while, in contrast, recordings in the isolated forebrain showed no signs of REM sleep. Thus, while forebrain mechanisms (including those related to circadian rhythms) modulate REM sleep, the fundamental rhythmic
NEUROBIOLOGY OF REM SLEEP Cortex
Plane of pontine transection
Cerebellum LDT/PPT
Forebrain
Thalamus DRN MRF
LC
PRF BRF Brainstem
Fig. 10.2. Schematic of a sagittal section of a mammalian brain (cat) showing the location of nuclei especially important for rapid eye movement (REM) sleep. BRF, PRF, and MRF, bulbar, pontine, and mesencephalic reticular formation; LDT/PPT, laterodorsal and pedunculopontine tegmental nuclei, the principal site of cholinergic (acetylcholinecontaining) neurons important for REM sleep and electroencephalogram desynchronization. LC, locus coeruleus, where most norepinephrine-containing neurons are located; DRN, dorsal raphe nucleus, the site of many serotonin-containing neurons. The oblique line is the plane of transection that Jouvet (1962) found preserves REM sleep signs caudal to the transection but abolishes them rostral to the transection.
generating machinery is in the brainstem, and it is here that anatomical and physiological studies have focused. The anatomical sketch provided by Figure 10.2 also shows the cell groups important in REM sleep; the attention of the reader is called to the cholinergic neurons, which act as promoters of REM phenomena, and to the monoaminergic neurons, which may act to suppress most components of REM sleep. Note that Figure 10.2 shows that the Jouvet transection spared these essential brainstem zones.
EFFECTOR NEURONS FOR DIFFERENT COMPONENTS OF REM SLEEP: BRAINSTEM RETICULAR FORMATION IS PRINCIPAL LOCATION
By effector neurons we mean those neurons directly in the neural pathways leading to the production of different REM components, such as the REMs. A series of physiological investigations over the past 30 years have shown that the “behavioral state” of REM sleep in nonhuman mammals is dissociable into different components under control of different mechanisms and different anatomical loci. The reader familiar with pathology associated with human REM sleep will find this concept easy to understand, since much pathology consists of inappropriate expression or suppression of individual components of REM sleep. As in humans, the cardinal signs of REM sleep in nonhuman mammals
153
are muscle atonia, EEG activation (low-voltage fast pattern, sometimes termed an activated or desynchronized pattern), and REMs. PGO waves are another important component of REM sleep found in recordings from deep brain structures in many animals (they are visible in the cat recording of Figure 10.3). PGO waves are spiky EEG waves that arise in the pons and are transmitted to the thalamic lateral geniculate nucleus (a visual system nucleus) and to the visual occipital cortex, hence the name PGO waves. There is suggestive evidence that PGO waves are present in humans but the depth recordings necessary to establish their existence have not been done. PGO waves are EEG signs of neural activation; they index an important mode of brainstem activation of the forebrain during REM sleep. It is worth noting that they are also present in nonvisual thalamic nuclei, although their timing is linked to eye movements, with the first wave of the usual burst of 3–5 waves occurring just before an eye movement. Most of the physiological events of REM sleep have effector neurons located in the brainstem reticular formation, with important neurons especially concentrated in the pontine reticular formation (PRF). Thus PRF neuronal recordings are of special interest for information on mechanisms of production of these events. Intracellular recordings of PRF neurons (Figure 10.3) show that these effector neurons have relatively hyperpolarized membrane potentials and generate almost no action potentials during non-REM sleep. As illustrated in Figure 10.3, PRF neurons begin to depolarize even before the occurrence of the first EEG sign of the approach of REM sleep, the PGO waves that occur 30–60 seconds before the onset of the rest of the EEG signs of REM sleep. As PRF neuronal depolarization proceeds and the threshold for action potential production is reached, these neurons begin to discharge (generate action potentials). Their discharge rate increases as REM sleep is approached and the high level of discharge is maintained throughout REM sleep, due to the maintenance of this membrane depolarization. Throughout the entire REM sleep episode almost the entire population of PRF neurons remains depolarized. The resultant increased action potential activity leads to the production of those REM sleep components which have their physiological bases in activity of PRF neurons. PRF neurons are important for the REMs (the generator for saccades is in PRF), the PGO waves (a different group of neurons) and a group of dorsolateral PRF neurons controls the muscle atonia of REM sleep (these neurons become active just before the onset of muscle atonia). Neurons in midbrain reticular formation (MRF, see location in Figure 10.2) are
154
R.W. MCCARLEY EMG
EEG
LGN
100 µV
EOG
S T T
S
T REM REM
REM W W Wm
MP
A
–45 –65 mV
60 SEC
S
S
T
T
T
REM
–45 –55 –65 REM
REM
W
W
Wm
–45 –55 –65 mV
B
0.5 SEC
Fig. 10.3. Changes in the membrane potential (MP) of a medial pontine reticular formation neuron over a sleep–wake cycle. The five traces (from electromyogram (EMG) through MP) in (A) are a set of inkwriter recordings defining behavioral states in relationship to the MP level. Note that the inkwriter sensitivity is not high enough to trace individual action potentials (MP trace). (B) Oscilloscope photographs detail changes in the frequency of action potentials together with the MP level. The first trace of (A) is EMG from the deep nuchal muscles. The second trace is EEG from the frontal cortex. The third trace of lateral geniculate nucleus (LGN) activity shows PGO waves, which consist of high-amplitude pre-REM waves in T, irregular, highfrequency waves during REM sleep, and rather high-amplitude waves near the end of REM sleep. The fourth trace is an electro-oculogram (EOG) from the lateral rectus extraocular muscles. The fifth trace is the inkwriter MP record in which the many single spike-like deflections on the trace are prominent excitatory postsynaptic potentials (EPSPs) or compounds of EPSPs and actual action potentials. The MP records in (B) are eight photographs of the oscilloscope display of the tape-recorded MP. The labels indicate the corresponding segment on the inkwriter MP trace (double arrows). See also text description. (Adapted from Ito et al. (2002).)
especially important for EEG activation, for the lowvoltage fast EEG pattern. These neurons were originally described as making up the ascending reticular activating system (ARAS), the set of neurons responsible for EEG activation. Subsequent work has enlarged this original ARAS concept to include cholinergic neurons, with contributions in waking to EEG activation also coming from monoaminergic systems,
neurons utilizing serotonin and norepinephrine (NE) as neurotransmitters.
REM-on neurons and REM promotion Current data suggest that cholinergic influences act by increasing the excitability of brainstem reticular neurons important as effectors in REM sleep either
NEUROBIOLOGY OF REM SLEEP
155
directly or indirectly by disinhibition, inhibiting GABAergic neurons which are inhibitory to reticular formation neurons. The essential data supporting cholinergic mechanisms are summarized below.
PRODUCTION
OF A
REM-LIKE
IC
STATE BY DIRECT
Cnf
INJECTION OF ACETYLCHOLINE AGONISTS INTO
LDT
THE PONTINE RETICULAR FORMATION
It has been known since the mid-1960s that cholinergic agonist injection into the PRF produces a state that very closely mimics natural REM sleep (for review and detailed literature citations for this section, see Steriade and McCarley, 2005). The latency to onset and duration are dose-dependent; within PRF, most workers have found the shortest latencies to come from injections in dorsorostral pontine reticular sites. Muscarinic cholinergic receptors appear to be of major importance, with nicotinic receptors playing a lesser role. Of note, most of the in vivo cholinergic data has come from felines. In rats and mice a similar REM induction effect can be induced, although it often is less robust in these species, perhaps as a result of difficulty in localization of applications in the smaller brains and interaction with circadian control (reviewed in Steriade and McCarley, 2005), as well as perhaps a different localization of GABAergic neurons inhibited by carbachol (see below). However, as described below, the in vitro evidence for carbachol excitatory effects on reticular formation neurons in the rat is undisputed. The precise site where in vivo carbachol is most effective in inducing REM or muscle atonia in the rat is disputed but appears to be within the pontine oralis nucleus slightly rostral to the subcoeruleus or in an area neighboring the superior cerebral peduncle (ventral tegmental nucleus) (Gnadt and Pegram, 1986; Taguchi et al., 1992; Bourgin et al., 1995; Deurveilher et al., 1997; Marks and Birabil, 1998). Experiments using the acetylcholinesterase inhibitor neostigmine in the mouse suggest that the pontine oralis nucleus is also an effective REM-inducing site in the mouse (Coleman et al., 2004a, b), although these findings have been disputed (Pollack and Mistlberger, 2005). Of note also are the REM-reducing effects of muscarinic knockouts (Goutagny et al., 2005).
LDT/PPT CHOLINERGIC PROJECTIONS TO RETICULAR FORMATION NEURONS
Cholinergic projections in brainstem and to brainstem sites arise from two nuclei at the pons–midbrain junction that contain cholinergic neurons, the laterodorsal tegmental nucleus (LDT) and the pedunculopontine tegmental nucleus (PPT). A sagittal schematic of their location is shown in Figure 10.1, and Figure 10.4, a
SCP PPT PPT PFTG
Fig. 10.4. Coronal section of the brainstem at the pons– midbrain junction showing the location of the acetylcholine-containing neurons most important for rapid eye movement sleep in laterodorsal tegmental nucleus (LDT)/ pedunculopontine tegmental nucleus (PPT), and a schematic of projections of LDT to pontine reticular formation. (PFTG is an abbreviation of one component of PRF.) IC, inferior colliculus; Cnf, cuneiform nucleus; SCP, superior cerebellar peduncle. (Adapted from Mitani et al., 1988.)
coronal view, shows their projections to critical PRF zones, as first shown by Mitani et al. (1988) and repeatedly confirmed. A similar series of studies has documented the extensive rostral projections of cholinergic neurons to thalamus and basal forebrain, where their actions are important for EEG activation – a topic to be discussed below.
DIRECT
EXCITATION OF PONTINE RETICULAR
FORMATION NEURONS BY CHOLINERGIC AGONISTS
In vitro pontine brainstem slice preparations offer the ability to apply agonists/antagonists in physiological concentrations, which are usually in the low micromolar range, whereas effective in vivo injections use concentrations that are a thousandfold greater, in the millimolar range, and thus raise the possibility of mediation of effects by nonphysiological mechanisms. Application of micromolar amounts of cholinergic agonists in vitro produces an excitation of a majority (about two-thirds) of medial PRF neurons. Another advantage of the in vitro preparation is the ability to use a sodium-dependent action potential blocker, tetrodotoxin; these experiments show that the excitatory effects of cholinergic agonists on PRF neurons in the
R.W. MCCARLEY
156
rat in vitro are direct (Greene et al., 1989). Furthermore the depolarizing, excitatory effects of cholinergic agonist mimic the changes seen in PRF neurons during natural REM sleep (Figure 10.3).
discharges during both wakefulness and REM sleep, are important for the EEG activation of both REM sleep and waking (see extensive discussion in Steriade and McCarley, 2005).
LDT/PPT
OTHER
LESION AND STIMULATION EFFECTS
Extensive destruction of the cell bodies of LDT/PPT neurons by local injections of excitatory amino acids leads to a marked reduction of REM sleep (Webster and Jones, 1988). Low-level (10 mA) electrical stimulation of LDT increases REM sleep (Thakkar et al., 1996).
DISCHARGE ACROSS THE
ACTIVITY OF
REM
LDT/PPT
NEURONS
CYCLE
A subset of these neurons has been shown to discharge selectively during REM sleep, and with the onset of increased discharges occurring before the onset of REM sleep (El Mansari et al., 1990; Steriade et al., 1990; Kayama et al., 1992), as schematized in Figure 10.1. This LDT/PPT discharge pattern and the presence of excitatory projections to the PRF suggest that LDT/PPT cholinergic neurons may be important in producing the depolarization of reticular effector neurons, leading to production of the events characterizing REM sleep. The group of LDT/PPT and reticular formation neurons that become active in REM sleep are often referred to as REM-on neurons. Subgroups of PRF neurons may show discharges during waking motoric activity, either somatic or oculomotor, but a sustained depolarization throughout almost all of the population occurs only during REM sleep. Studies of the immediate early gene cFos expression have shown activation of choline acetyltransferase-positive neurons in REM rebound in the rat following deprivation (Merchant-Nancy et al., 1995; Maloney et al., 1999). Verret et al. (2005) have questioned these two Jones laboratory studies’ findings; Jones (personal communication, October 2005) notes that the 72-hour-long duration of deprivation in the Verret et al. (2005) study may have produced anomalous findings. It must be emphasized that cFos expression, although useful, does not offer a 1:1 isomorphism with action potential occurrence (Fields et al., 1997). Of particular note, rat single-unit in vivo studies strongly support cholinergic activation during REM sleep (Steriade and McCarley, 2005).
CHOLINERGIC
NEURONS
Cholinergic neurons are important in the production of the low-voltage fast or “desynchronized” EEG pattern of both REM sleep and waking. Rostral projections of a subgroup of LDT/PPT neurons, those with
NEUROTRANSMITTERS AND PONTINE
RETICULAR FORMATION NEURONS
Peptides colocalized with acetylcholine. There are many peptides that are colocalized with the neurotransmitter acetylcholine in LDT/PPT neurons; this colocalization likely also means they are synaptically coreleased with acetylcholine. The peptide substance P is found in about 40% of LDT/PPT neurons and, overall, more than 15 different colocalized peptides have been described. The role of these peptides in modulating acetylcholine activity relevant to wakefulness and sleep remains to be elucidated, but it should be emphasized that the colocalized vasoactive intestinal peptide has been reported by several different investigators to enhance REM sleep when it is injected intraventricularly. A later section of this chapter will discuss GABAergic influences, as well as the role of GABAergic reticular formation neurons.
REM
MUSCLE ATONIA
This is an important REM feature from a clinical point of view because disorders of this system are present in many patients who present to sleep disorder clinicians. This topic is covered in detail in another chapter in this volume, so we here very briefly summarize. Work by Chase and collaborators and by Segal and collaborators (reviewed in Steriade and McCarley, 2005) suggests three important zones for atonia, which we list according to their projections: PRF ! bulbar reticular formation ! motoneurons. We here discuss only the PRF portion of the atonia circuitry. Pontine reticular formation ventral to locus coeruleus. Jouvet and colleagues in Lyon, France, reported that bilateral lesions of the pontine reticular region just ventral to the locus coeruleus (LC), termed by this group the peri-LC alpha, and its descending pathway to the bulbar reticular formation abolished the muscle atonia of REM sleep (Jouvet, 1979; Sastre and Jouvet, 1979). It is to be emphasized that this zone is a reticular zone, not one containing noradrenergic neurons like the LC proper, and that the name refers only to proximity to LC. The Lyon group also reported that not only was the nuchal muscle atonia of REM suppressed, but that cats so lesioned exhibited “oneiric behavior,” including locomotion, attack behavior, and behavior with head raised and with horizontal and vertical movements “as if watching something.” Morrison and collaborators (Hendricks et al., 1982) confirmed the basic finding of REM without atonia with bilateral
NEUROBIOLOGY OF REM SLEEP
REM-SUPPRESSIVE SYSTEMS: REM-OFF NEURONS The neurons described in the previous section that increase discharge rate with the advent of REM have been termed “REM-on neurons.” In contrast, groups of other neurons radically decrease and may nearly arrest discharge activity with the approach and onset of REM; these are often termed “REM-off” neurons. The typical discharge activity profile is for discharge rates to be highest in waking, then decrease in synchronized sleep and with near-cessation of discharge in REM sleep. REM-off neurons are distinctive both because they are in the minority in the brain and also because they are recorded in zones with neurons that use biogenic amines as neurotransmitters. The loci include a midline zone of the brainstem raphe nuclei, and a more lateral band-like zone in the rostral pons/ midbrain junction that includes the nucleus LC, a reticular zone and the peribrachial zone. Figure 10.5 provides an illustration of the time course of REM-on and REM-off neurons over the sleep cycle, as recorded in animals; these data are the basis for the REM time course over the night presented in Figure 10.1.
Raphe nuclei Neurons with a REM-off discharge profile were first described by McGinty and Harper (1976) in the dorsal raphe nucleus (DRN), a finding confirmed by other workers (Trulson and Jacobs, 1979; Hobson et al., 1983a; Lydic et al., 1987a, b). Neurons with the same REM-off discharge pattern have been found in the other raphe nuclei, including nucleus linearis centralis (McCarley, 1978; Hobson et al., 1983a), centralis superior (Rasmussen et al., 1984), raphe magnus (Cespuglio et al., 1981; Fornal et al., 1985), and in raphe pallidus (Sakai et al., 1983). Identification of these extracellularly recorded neurons with serotonin-containing neurons was made on the basis of recording site location in the vicinity of histochemically identified serotonin neurons and the similarity of the extracellularly recorded slow, regular discharge pattern to that of histochemically identified serotonergic neurons in vitro. Nonserotonergic neurons in the raphe system have
157
15 Discharge rate (impulse/sec)
pontine tegmental lesions but reported that lesions extending beyond the LC alpha region and its efferent pathway to bulb were necessary for more than a minimal release of muscle tone and to produce the elaborate “oneiric behaviors.” The exact location and numbers of inhibitory pathways are still a matter of some controversy, with all investigators agreeing on the important, if not exclusive, role of the peri-LC alpha, or, as it is often termed, the subcoeruleus.
10
5
0 0
20 40 60 80 Percentage of cycle completed
100
Fig. 10.5. Time course of rapid eye movement (REM)-on neurons (solid lines) and REM-off neurons (dotted lines) over the sleep cycle. The cycle begins with the end of one REM period (0%) and ends with the end of the next REM period (100% complete). The data in bins are from averaging of the time course of a REM-on reticular neuron over many cycles and the solid smooth line is the reciprocal interaction mathematical model fit. The arrow marks the bin at which an electrographically defined REM sleep episode is most likely to begin. The REM-off data were similarly derived from locus coeruleus recordings (empirical data not shown here, and discharge rate is not to the same scale as REM-on neurons). (Adapted from McCarley and Hobson, 1975.)
been found to have different discharge pattern characteristics. While this extracellular identification methodology does not approach the “gold standard” of intracellular recording and labeling, the circumstantial evidence that the raphe REM-off neurons are serotonergic appears strong.
Locus coeruleus The second major locus of REM-off neurons is the LC, as described in cat (Hobson et al., 1973, 1975), rat (Aston-Jones and Bloom, 1981a, b), and monkey (Foote et al., 1980). The argument that these extracellularly recorded discharges are from NE-containing neurons parallels that for the putative serotonergic REM-off neurons. Extracellularly recorded neurons that are putatively noradrenergic have the same slow, regular discharge pattern as NE-containing neurons identified in vitro and have the proper anatomical localization of recording sites, including recording sites in the compact LC in the rat, where the NE-containing neurons are rather discretely localized. Thus, while the evidence that these REM-off neurons are NE-containing is indirect and circumstantial, it nonetheless appears quite strong.
158 R.W. MCCARLEY Finally, the remaining groups of REM-off neurons activity over the sleep–wake cycle was very clear: are principally localized to the anterior pontine tegmenwaking > non-REM > REM sleep. There was also a tum/midbrain junction either in the peribrachial zone, clear inverse relationship between PGO waves and dorsal or in a more medial extension of it, recording sites that raphe discharge, and a premonitory increase in dorsal correspond to the presence of aminergic neurons scatraphe activity prior to the end of the REM sleep episode, tered through this zone. The “stray” REM-off neurons a phenomenon also observed and commented upon by in other reticular locations also correspond to dispersed Trulson and Jacobs (1979). adrenergic neuronal groups, although adrenergic idenEvidence that dorsal raphe serotonergic activity tification in this case is much less secure. At this point inhibited REM sleep also came from in vivo pharmacowe note that putatively dopaminergic neurons in sublogical experiments (Ruch-Monachon et al., 1976) and stantia nigra and midbrain do not alter their discharge dorsal raphe cooling by Cespuglio et al. (1979). Hobson rate or pattern over the sleep–wake cycle (Steinfels and McCarley (Hobson et al., 1975; McCarley and et al., 1983), and thus are unlikely to play important Hobson, 1975) originally proposed that monoaminergic roles in sleep–wake cycle control. neurons might inhibit REM-on cholinergic REMpromoting neurons, now known to be in LDT/PPT. This Do REM-off neurons play a permissive, postulate of monoaminergic inhibition of cholinergic disinhibitory role in REM sleep genesis neurons was originally regarded as extremely controby interacting with cholinergic versial. However, interest was quickened in the 1990s REM-on neurons? by: (1) documentation of serotonergic projections from the dorsal raphe to the mesopontine cholinergic neuThe intriguing reciprocity of the discharge time course rons in the laterodorsal (LDT) and pedunculopontine of REM-off and REM-on neurons led to the initial (PPT) tegmental nuclei that are implicated in the prohypothesis of interaction of these two groups, as origiduction of REM sleep (Aston-Jones and Bloom, nally proposed for the REM-off adrenergic neurons 1981a; Semba and Fibiger, 1992; Honda and Semba, (Hobson et al., 1973, 1975; McCarley, 1973; McCarley 1995; Steininger et al., 1997); (2) in vitro demonstration and Hobson, 1975). The phenomenological, behavioral, of serotonergic inhibition of mesopontine cholinergic and cellular data have been sufficiently strong so that neurons (Luebke et al., 1992; Leonard and Llina´s, diverse groups of investigators have proposed that 1994); and (3) the report that microinjection of a serothe REM-off neurons, as a complete or partial set, tonergic 5-HT1A agonist into the PPT inhibits REM act in a permissive, disinhibitory way on some or all sleep (Sanford et al., 1994). It was also demonstrated of the components of REM sleep, and we will here that the level of serotonin release in the cat DRN parsummarize these postulates, as well as presenting the allels the time course of presumptively serotonergic phenomenology on which they are based. Many of neuronal activity: waking (W) > SWS > REM sleep these theories arose in the mid-1970s, as increased tech(Portas and McCarley, 1994), suggesting that this nical capability led to extracellular recordings of REMwould also be true at axonal release sites in the LDT/ off neurons. PPT, since serotonin levels at distant DRN projection sites had the same behavioral state ordering of levels as DORSAL RAPHE SEROTONERGIC NEURONS those in the DRN: W > SWS > REM sleep (Auerbach The possibility that the dorsal raphe serotonergic neuet al., 1989; Imeri et al., 1994) in rats and in cats (Wilkinrons act to suppress one of the major phenomena of son et al., 1991). REM sleep, PGO waves, was explicitly proposed by Since axon collaterals of DRN serotonergic neurons Simon et al. (1973), on the basis of lesion data, and inhibit this same DRN population via somatodendritic in vivo pharmacological experiments using reserpine 5-HT1A receptors (Sprouse and Aghajanian, 1987), it (Brooks et al., 1972), which depleted brainstem serotofollowed that the introduction of a selective 5-HT1A nin and simultaneously produced nearly continuous receptor agonist in the DRN via microdialysis perfuPGO-like waves. The study of McGinty and Harper sion should produce strong inhibition of serotonergic (1976) was the first of many to document the inverse neural activity, which would be indicated by a reduction relationship between the discharge activity of extracelof 5-HT release in the DRN. Moreover, if the hypothesis lularly recorded dorsal raphe neurons and REM sleep. of serotonergic inhibition of REM-promoting neurons With respect to REM sleep onset, the decrease in diswere correct, the inhibition of DRN serotonergic activity charge activity of presumptively serotonergic raphe neushould disinhibit REM-promoting neurons, producing rons is remarkably consistent. Using a cycle-averaging an increase in REM sleep concomitant with the changes technique, Lydic et al. (1983), found the time course in DRN extracellular serotonin. Portas et al. (1996) of presumptively serotonergic dorsal raphe neuronal tested the effects of microdialysis perfusion of
NEUROBIOLOGY OF REM SLEEP 8-hydroxy-2-(di-n-propylamino)tetralin (8-OH-DPAT), a selective 5-HT1A receptor agonist, in freely moving cats. In perfusions during W, DRN perfusion of 8-OH-DPAT decreased 5-HT levels by 50% compared with artificial cerebrospinal fluid (Figure 10.6), presumptively through 5-HT1A autoreceptor-mediated inhibition of serotonergic neural activity. Concomitantly the 8-OH-DPAT perfusion produced a short latency, approximately threefold increase in REM sleep, from a mean of 10.6% baseline to 30.6% (P < 0.05, n ¼ 5 animals), although waking was not significantly affected (Figure 10.6). In contrast, and suggesting DRN specificity, 8-OH-DPAT delivery through a probe in the aqueduct did not increase REM sleep but rather tended to increase waking and decrease SWS. These data in the cat were confirmed in the rat. Bjorvatn et al. (1997) used microdialysis to perfuse 8-OH-DPAT (10 mmol/l) into the DRN of rats and
159
found a fourfold increase in REM sleep compared to control perfusion with artificial cerebrospinal fluid, while the other vigilance states were not significantly altered. Sakai and Crochet (2001) failed to replicate the findings of Portas et al. (1996) in the cat and Bjorvatn et al. (1997) in the rat, perhaps due to technical differences (McCarley, 2004).
IN
VIVO AND IN VITRO EVIDENCE OF SEROTONERGIC
INHIBITION OF
LDT/PPT
NEURONS
The data of Portas et al. (1996), however, did not directly demonstrate serotonergic inhibition of neurons in the cholinergic LDT/PPT. Moreover the presence of some neurons with REM-on and other neurons with wake/REM-on activity in LDT/PPT was a puzzle in terms of the global changes in monoaminergic inhibition. McCarley et al. (1995) postulated that, while
Microdialysis delivery of 8-OH DPAT to dorsal raphe Effects on 5HT release & REM sleep
5HT release (fmoles/sample)
4
W SWS REM
3
2
1
0
Behavioral state
REM
SWS
W ACSF control 0
1
8-OH DPAT 2
3 Time in Hours
4
5
Fig. 10.6. Time course of 5-hydroxytryptamine (5-HT) levels (top portion of figure) and behavioral state (bottom portion of figure) during control dorsal raphe nucleus (DRN) artificial cerebrospinal fluid perfusion (interrupted horizontal line) and during DRN 8-hydroxy-2-(di-n-propylamino)tetralin (8-OH-DPAT) perfusion (solid horizontal line) in a typical experiment. Note that, prior to perfusion, waking DRN 5-HT levels (circles) are higher than those in slow-wave sleep (SWS: squares) and rapid eye movement (REM) sleep (stars). Each 5-HT value is expressed in fmol per 7.5 ml sample, and was obtained during an uninterrupted 5-minute sequence of the behavioral state. Upon the onset of 10 mM 8-OH-DPAT perfusion (arrow) the 5-HT level dropped quickly to levels as low as those normally present in SWS or REM. Behaviorally, 8-OH-DPAT administration markedly increased REM sleep (black bars in the hypnogram). (Adapted from Portas et al. (1996).)
160
R.W. MCCARLEY
monoamines might inhibit REM-on cholinergic neurons, wake/REM-on neurons might not be inhibited, thus explaining their continued activity in waking – since serotonergic activity is highest during wakefulness, the observed high discharge rate of wake/ REM-on neurons during wakefulness would not be consistent with a high level of serotonergic inhibition from a high level of DRN activity. In vitro data were also consistent with a subset, not the entire population, of LDT/PPT cholinergic neurons inhibited by serotonin acting at 5-HT1A receptors (Luebke et al., 1992; Leonard and Llina´s, 1994). Thakkar and collaborators (1998) developed a novel methodology allowing both extracellular single-cell recording and local perfusion of neuropharmacological agents via an adjacent microdialysis probe in freely behaving cats to test this hypothesis of differential serotonergic inhibition as an explanation of the different staterelated discharge activity. Discharge activity of REM-on neurons was almost completely suppressed by local microdialysis perfusion of the selective 5-HT1A agonist 8-OH-DPAT, while this agonist had minimal or no effect on the wake/REM-on neurons, as illustrated in Figure 10.7. Of note, the ordering of 5-HT concentrations in the cholinergic PPT is wake > non-REM > REM, consistent with the unit discharge data and, moreover, application of the
5-HT1A agonist 8-OH DPAT to the PPT suppressed REM sleep and increased wakefulness (Strecker et al., 1999, and unpublished data; Figure 10.8). The finding that only a subpopulation of the recorded LDT/PPT cells was inhibited by 8-OH-DPAT is consistent with rat pontine slice data, where, in combined intracellular recording and labeling to confirm the recorded cell’s cholinergic identity, some, but not all, of the cholinergic neurons in the LDT/PPT were inhibited by serotonin (Luebke et al., 1992). The different percentages of LDT/PPT neurons that are inhibited by serotonin or serotonin agonists in vitro (64%) compared with the in vivo findings (36.4%) of Thakkar et al. (1998) may be due to anatomical differences between species (rat versus cat) and/or different concentrations of agents at the receptors.
LOCUS
COERULEUS AND
SLEEP PHENOMENA
Lesion studies. Lesion studies furnish an unclear picture of the role of the LC in REM sleep. Bilateral electrolytic lesions of LC in cat by Jones et al. (1977) led these workers to conclude that the LC was not necessary for REM sleep. In the REM-like sleep state following the lesion there was a twofold reduction of PGO spikes while the number in deep synchronized sleep increased approximately threefold, so that the total number of spikes
REM-on neurons
8
REM
Wake/REM-on neurons 4
ACSF
ACSF
8-OH-DPAT
8-OH-DPAT
6
Spikes/sec
Spikes/sec
3 4
2 2
0
A
1 AW
QW
SWS
REM–
Behavioral state
REM+
B
AW
QW
SWS
REM– REM+
Behavioral state
Fig. 10.7. State-related activity of units in the cholinergic laterodorsal tegmental nucleus (LDT) and pedunculopontine tegmental nucleus (PPT) and the effects of a serotonin 1A agonist applied by microdialysis. (A) Rapid eye movement (REM)-on units (n ¼ 9): grand mean (SEM) of discharge rate in each behavioral state before (open circle, artificial cerebrospinal fluid) and after (closed circle) 10 mmol/l 8-hydroxy-2-(di-n-propylamino)tetralin (8-OH-DPAT) was added to the perfusate. Note suppression of activity (highly statistically significant). (B) Wake/REM-on units (n ¼ 25): grand mean ( SEM) of discharge rate before (open circle, artificial cerebrospinal fluid) and after (closed circle) 10 mmol/l 8-OH-DPAT was added to the perfusate. Note the minimal effect of 8-OH-DPAT, not statistically significant. AW, active wake; QW, quiet wake; SWS, slow-wave sleep. (Adapted from Thakkar et al. (1998).)
NEUROBIOLOGY OF REM SLEEP (Mean +/− SEM) 5-HT fmoles/sample
2.0
5HT concentrations in PPT vary with behavioral state
1.5 1.0 0.5 0.0
A
Wake 350
REM
Control 1 µM 8-OH-DPAT (n=5)
300 250 % Control
Non REM
5HT agonist in PPT increases wakefulness and decreases REM sleep
200 150 100 50
B
0 Wake
Non REM
REM
Fig. 10.8. (A) Microdialysis measurements of 5-hydroxytryptamine (5-HT) concentrations in the cholinergic pedunculopontine tegmental nucleus (PPT) parallel the behavioral state discharge rate ordering of dorsal raphe neurons. 8-OH-DPAT, 8-hydroxy2-(di-n-propylamino)tetralin. (Adapted from Strecker et al. (1999).) (B) Microdialysis-applied 5-HT1A agonist in the PPT suppresses rapid eye movement (REM) sleep and increases wakefulness. (From Strecker et al., unpublished paper.)
remained approximately the same – a picture much like that following acute raphe lesions. Over time the total number of PGO spikes declined and the percentage of a REM sleeplike state increased from about 5% to 10% versus a control value of 15%. We use the term “REM sleep-like” because muscle atonia was abolished and there was in fact motor activity like that described in the previous chapter for the “REM sleep without atonia” state following tegmental lesions; this syndrome likely resulted from spread of the lesion to the reticular area subserving atonia. Other lesion effects included loss of spontaneous micturition and defecation, a rise in mean temperature from 37.1 to 38.3 C, loss of grooming, and a loss of coordination and balance. The picture following unilateral LC lesions was quite strikingly different. Caballero and De Andres (1986) found a 50% increase in the percentage of REM sleep (P < 0.001) following unilateral electrolytic lesions of LC in cats; cats with lesions in neighboring tegmentum and sham-operated controls showed no change. The postoperative condition of animals with unilateral lesions was much better than after bilateral lesions; in only one unilaterally LC-lesioned animal was there urinary retention, and this was transient and no “alteration in any other vegetative function was observed.” Accordingly, Caballero and DeAndres (1986) attributed the differences between their study and that of Jones et al.
161
(1977) to nonspecific effects of the larger lesions that, as with almost any central nervous system insult, may have led to a REM sleep reduction. Locus coeruleus cooling induces REM sleep. Cespuglio et al. (1982) performed unilateral and bilateral cooling of the LC in felines, using the same methodology as for the dorsal raphe cooling. In repeated cooling trials REM sleep was repetitively induced, and the percentage of REM sleep increased by 120% over control periods. This raises the general point that nonspecific effects of destructive lesions always decrease REM, as do other central nervous system insults. Satinoff’s comment (1988) about nonspecific effects is that, “One might also say that rendering an animal unconscious by a blow to the head eliminates REM sleep. In a sense it does, but that sense is completely trivial.” It is consequently hard to draw definitive and interpretable conclusions about destructive lesions, especially those that do not enhance REM sleep. Jones and colleagues (1977), for example, concluded that her lesions showed the LC was not necessary for REM sleep, in the sense of being a region actively promoting REM, although later studies in the Jones laboratory were consistent with a disinhibition hypothesis (Maloney et al., 1999). In summary, many nonspecific factors decrease REM and few, if any, increase it; consequently lesions or manipulations that increase REM are always more directly interpretable.
SITE(S)
OF
REM-OFF
AND
REM-ON
INTERACTION
The model for REM sleep control proposed here discusses REM-off suppression of REM-on neurons. It must be emphasized that there are several, nonmutually exclusive possible sites of interaction. These include direct acetylcholine (Ach)-NE interactions in the LDT and PPT. For example, there is now evidence that choline acetyltransferase-labeled fibers are present in LC and it has long been known that the NE-containing LC neurons also stain intensely for the presence of acetylcholinesterase (see review of NE–ACh anatomical interrelationship in McCarley, 2004). NE varicosities are present throughout the reticular formation and the LDT and the peribrachial area that is the site of choline acetyltransferase-positive neurons. Thus adrenergic–cholinergic interactions may take place directly between these two species of neurons and/or may take place at reticular neurons.
GABAERGIC INFLUENCES AND REM SLEEP In addition to the monoamines and acetylcholine as modulators and controllers of the sleep cycle, there is accumulating evidence that GABAergic influences
R.W. MCCARLEY
162
may play an important role. Defining the role of gamma-aminobutyric acid (GABA) with certainty is difficult, however. Since GABA is a ubiquitous inhibitory neurotransmitter, purely pharmacological experiments using agents that increase or decrease GABA do not answer a key question, namely whether the results so obtained were representative of the increases or decreases in GABA that occur naturally in the course of the sleep cycle, or were simply and trivially the result of a pharmacological manipulation of GABA systems not naturally playing a role in sleep cycle control. Microdialysis is potentially a very useful way of sampling naturally occurring changes in GABA levels over the sleep cycle, but is often limited in sensitivity and hence in time resolution of when the changes occur in the sleep cycle. This section surveys GABA data from dorsal raphe, LC, and PRF that are relevant to sleep–wakefulness control. From the standpoint of sleep cycle control, one of the most puzzling aspects has been defining what causes the “REM-off” neurons in the LC and DRN to slow and cease discharge as REM sleep is approached and entered. The reciprocal interaction model (see below) hypothesized that a recurrent inhibition of LC/DRN might account for this. While recurrent inhibition is present, there is no clear evidence that it might be the causal agent in REM-off neurons turning off. Thus, the prospect that a GABAergic mechanism might be involved is of great intrinsic interest.
Dorsal raphe nucleus MICRODIALYSIS
IN DORSAL RAPHE NUCLEUS
Nitz and Siegel (1997b) obtained in vivo microdialysis samples from the DRN in naturally sleeping cats, noting that “cessation of firing of serotonergic dorsal raphe neurons is a key controlling event of rapid eye movement (REM) sleep.” This study is the single extant microdialysis study of GABA release in DRN, and reported a significant increase in GABA levels in REM sleep (0.072 pmol/ml or 72 fmol/ml) compared with wakefulness (0.042 pmol/ml), while SWS (0.049 pmol/l) did not significantly differ from wakefulness. Glutamate and glycine release did not change over the sleep cycle. Further supporting a GABA role in REM control via inhibition of serotonergic neurons was the 67% increase in REM sleep observed with microinjections of the GABA agonist muscimol into the DRN and the observation that reverse microdialysis of the GABA antagonist picrotoxin completely abolished REM sleep. For comparative purposes we note that the approximately threefold increase in REM sleep observed with microdialysis application of the 5-HT1A agonist 8-OHDPAT to DRN by Portas et al. (1996) was greater,
suggesting that factors other than GABA might influence serotonergic neurons. Although the data did not directly support GABAergic inhibition as a mechanism of the slowing of serotonergic unit discharge in the passage from wakefulness to SWS, Nitz & Siegel noted the possibility that a small increase in the release of GABA, possibly beyond the resolution of the microdialysis technique, might be sufficient to reduce DRN unit discharge in SWS, a suggestion indirectly supported by data from (Levine and Jacobs, 1992).
MICROIONTOPHORESIS
OF
DRN
NEURONS
Gervasoni et al. (2000) reported that, in the unanesthetized but head-restrained rat, the iontophoretic application of bicuculline on rodent DRN serotonergic neurons, identified by their discharge characteristics, induced a tonic discharge during SWS and REM and an increase of discharge rate during quiet waking. They postulated that an increase of a GABAergic inhibitory tone present during wakefulness was responsible for the decrease of activity of the DRN serotonergic cells during SWS and REM sleep. In addition, by combining retrograde tracing with cholera toxin B subunit and glutamic acid decarboxylase immunohistochemistry, they provided evidence that the GABAergic innervation of the DRN arose from multiple distant sources and not only from interneurons, as classically accepted. Among these afferents, they suggested GABAergic neurons located in the lateral preoptic area and the pontine ventral periaqueductal gray (PAG), including the DRN itself, could be responsible for the reduction of activity of the DRN serotonergic neurons during SWS and REM sleep, respectively. However a report from the same laboratory in the same year described results at variance with these, in that Sakai and Crochet (2000) were unable to block the cessation in vivo of extracellular discharge of presumed serotonergic DRN neurons during REM sleep by either bicuculline or picrotoxin application via a nearby microdialysis probe in felines. While it is entirely possible that GABA pharmacological actions could differ radically in the cat and rat, the most parsimonious interpretation is that the two series of experiments had technical differences. The argument for a different pharmacology in the cat and rat is weakened also by the results of Nitz and Siegel (1997b), which agree with the Gervasoni et al. (2000) rat data.
Locus coeruleus MICRODIALYSIS
IN LOCUS COERULEUS
The single published study on sleep–wake analysis of GABA release in the LC region placed microdialysis probes on the border of LC or in the peri-LC region in the cat (Nitz and Siegel, 1997a). GABA release was
NEUROBIOLOGY OF REM SLEEP found to increase during REM sleep (1.9 fmol/ml) as compared to both waking values (1.2 fmol/ml) and SWS (1.6 fmol/ml). GABA release during SWS showed a trend-level significance (P < 0.06) when compared with waking. The concentration of glutamate and glycine in microdialysis samples was unchanged across sleep and wake states. These data, because of the SWS differences, appear to offer more direct support for LC than for DRN neurons for the hypothesis of GABA-induced inhibition causing the reduction in LC/DRN discharge in SWS and virtual cessation of firing in REM sleep. Incidentally, the authors did not explicitly comment on the reason for their finding a 35-fold greater GABA concentration in the DRN than in the LC during waking; this may have been due to various methodological differences, thus calling to attention the difficulty in measuring GABA.
MICROIONTOPHORESIS
OF
LC
NEURONS
Gervasoni et al. (1998) applied their methodology of microiontophoresis and single-unit extracellular recordings in the LC of unanesthetized, head-restrained rats. Bicuculline, a GABA-A receptor antagonist, was able to restore tonic firing in the LC noradrenergic neurons during both REM sleep (in contrast to its effects in the DRN) and SWS. Application of bicuculline during wakefulness increased discharge rate. These data, combined with those of Nitz and Siegel (1997a), are thus consistent with GABAergic inhibition in the LC during REM and SWS.
Source of state-related GABAergic input to DRN and LC Overall, the DRN and LC studies just surveyed are consistent with, but do not prove, the hypothesis that increased GABAergic inhibition leads to REM-off cells turning off. The increased GABAergic tone could simply be a consequence of other state-related changes without causing these changes. Here, as with other neurotransmitters, it would be helpful to have unit recordings of GABAergic neurons with inputs to LC/DRN. One could see if these neurons had the requisite lead times and state-related discharge time course to cause the changes. Where might these neurons be located?
PERIAQUEDUCTAL
GRAY?
The Gervasoni et al. (2000) study on DRN pointed to the PAG as a possible source of the GABAergic input proposed to inhibit DRN neurons. In accord with this hypothesis, both ventrolateral (vl) PAG lesions (Petitjean et al., 1975) and muscimol injections (Sastre et al., 1996) produced a large increase in REM sleep.
163
Thakkar and colleagues (2002) thus decided to record vlPAG unit activity in freely behaving cats to determine if neurons selectively increased their tonic discharge activity before and during REM sleep, and hence might furnish GABAergic inhibition of monoaminergic neurons. Several types of state-specific neuronal populations were found in the PAG, but none of the 33 neurons showed a tonic discharge increase before and during REM, but rather were phasic in pattern and increased discharge rate too late in the cycle to be a cause of the DRN SWS suppression. These data thus suggest that, although vlPAG neurons may regulate phasic components of REM sleep, they do not have the requisite tonic pre-REM and REM activity to be a source of GABAergic tone to monoaminergic neurons responsible for their REM-off discharge pattern. The negative findings would suggest that, at a minimum, neurons with the requisite activity are not abundant in the vlPAG.
VENTROLATERAL
PREOPTIC AREA
(VLPO)?
This forebrain site was retrogradely labeled by Gervasoni et al. (2000) as projecting to the DRN. Forebrain influences on REM sleep are discussed in the next chapter, but the Jouvet transection experiments suggest, however, these are not essential for the basic REM cyclicity found in the pontine cat.
GABA and the pontine reticular formation: disinhibition and REM sleep PHARMACOLOGICAL
STUDIES IN CATS ON THE
BEHAVIORAL STATE EFFECTS OF
GABA
AGENTS
Xi et al. (1999, 2001) have provided pharmacological evidence of GABA suppression of REM using agents injected into the nucleus pontis oralis, in a region about 2 mm lateral to the midline and more than 1 mm ventral to LC, a region where carbachol induced a short-latency (<4 minutes) onset of REM sleep. Here GABA agonists (both A and B) induced wakefulness while antagonists (both A and B) increased REM in felines. The effects of baclofen and phaclofen were similar to the GABA-A agents, but less strong. These data suggested that pontine GABAergic processes acting on both GABA-A and GABA-B receptors might play a critical role in generating and maintaining wakefulness and in controlling the occurrence of the state of REM sleep.
PHARMACOLOGICAL
STUDIES IN RATS ON THE
BEHAVIORAL STATE EFFECTS OF
GABA
AGENTS
In the head-restrained rat, Boissard et al. (2002) used microiontophoresis of the GABA-A antagonists bicuculline and gabazine in the PRF just ventral to the
R.W. MCCARLEY
LC and LDT, termed the dorsal and alpha subcoeruleus nuclei by Paxinos and Watson (1997) and the sublaterodorsal nucleus (SLD) by Swanson (1992). These agents produced a REM-like state with prominent muscle atonia, but the EEG power spectrum was more similar to W, with little theta activity, and not REMs or penile erections. In contrast to the cat, carbachol applied to the SLD in these head-restrained rats produced wakefulness and not REM sleep. These data suggested a role of GABA disinhibition in producing some REM-like phenomena, especially muscle atonia. Sanford et al. (2003) assessed REM after bilateral microinjections into RPO of muscimol (suppressed REM) and bicuculline (enhanced REM) in rats during the light (inactive) period, but they did not observe the pronounced short-latency, long-duration increase in REM seen in cats (Xi et al., 2001). Repeating these experiments in the dark (active) phase would help determine whether the strongly circadian rat differs from the cat as a function of circadian phase. Microdialysis measurements of GABA in the feline pontine reticular formation. Thakkar et al. (2004a, b) have reported preliminary data on GABA release in PRF of freely moving cats (Figure 10.9), after validating GABA measurements by pharmacologically increasing/decreasing GABA release. In the four PRF sites tested, multiple episodes of REM sleep had consistently lower levels of GABA than wakefulness (Figure 10.9). Although wake was not statistically different from SWS, there was a trend toward lower GABA levels in SWS. These data provide very preliminary but direct evidence compatible with GABA disinhibition in the PRF during REM sleep.
A MODEL OF REM SLEEP GENERATION INCORPORATING GABAERGIC NEURONS We here briefly summarize a structural model of REM sleep cyclicity, based on the data discussed above, and note that Steriade and McCarley (2005) have a much more complete exposition. The history of the development of structural models encompasses the history of discovery of neurons and neurotransmitters important in REM sleep, and is one of evergrowing complexity. The first formal structural and mathematical model was presented in 1975 by McCarley & Hobson. This model, termed the reciprocal interaction model, was based on the interaction of populations of REM-on and REM-off neurons and mathematically described by the Lotka–Volterra equations, derived from population models of prey–predator
Chromatogram of microdialysis sample collected during W. Arrow indicates GABA peak
0 1 3 5 6 8 10 11 13 15 16 18 20 21 23 25 26 28 30
A
Time (min)
120
% Release
164
B
60
0 Wakefulness
Non REM
REM
GABA release in the PRF is lowest in REM sleep
Fig. 10.9. Gamma-aminobutyric acid (GABA) release in the pontine reticular formation. (A) GABA chromatogram peak is clearly resolved. (B) GABA release in felines (n ¼ 3) as a function of behavioral state (bars are percentage of waking release). REM, rapid eye movement. (From unpublished data of Thakkar et al.)
interaction. We suggest that the basic notion of interaction of REM-on and REM-off neuronal populations is a very useful one for modeling and conceptualization, even though the description of the populations of neurons characterized as REM-on and REM-off has been altered and made much more detailed. Figure 10.10 describes the “core” features of the structural and mathematical model, namely the interaction of REMon and REM-off neurons, and provides a description of the dynamics. Figure 10.11 identifies the neurotransmitter components of the REM-on and REM-off interaction described in Figure 10.10. Steriade and McCarley (2005) provide a detailed account of the evidence supporting the model. In this model cholinergic neurons promote REM through action on reticular effector neurons, which also provide a positive feedback on to the cholinergic neurons, LDT/PPT a`PRF a` LDT/PPT. (Mathematically, this is the basis of the postulate of self-excitation (positive feedback) and exponential growth of REM-on neurons, term a in Figure 10.10.)
NEUROBIOLOGY OF REM SLEEP Core reciprocal interaction schematic c b
REM-on neurons PRODUCE REM
REM-off neurons INHIBIT REM
d a Legend:
Excitation
Inhibition
Core reciprocal interaction equations (Lotka-Volterra equations) X’(t) = aX − bXY Y’(t) = −cy + dXY where X = Time course of activity of REM-on neurons, Y = Time course of activity of REM-off neurons
McCarley, 2003, unpublished
Fig. 10.10. Summary of the “core” features of the reciprocal interaction model. The rapid eye movement (REM)-on neuronal population has a positive feedback so that activity grows (see connection labeled a). This activity gradually excites the REM-off population (connection d). The REM-off population then inhibits the REM-on population (connection b), terminating the REM episode. The REM-off population is also self-inhibiting (connection c), and, as REM-off activity wanes, the REM-on population is released from inhibition and is free to augment its activity. This begins a new cycle of events. This interaction is formally described by the Lotka–Volterra equations, where X ¼ REM-on activity and Y ¼ REM-off activity:
REM-off neurons
REM-on neurons
Feedback Inhibition, direct and ? via local GABA interneurons
LDT/PPT REM-on cholinergic neurons PRODUCE REM
Reticular formation effector neurons
Legend:
Excitation
Dorsal raphe - serotonin locus coeruleus - NE INHIBIT REM
GABAergic RF interneurons: dis-inhibition
Inhibition
GABA Inhibition in REM. ?Local interneurons and/or distant source?
GABA mechanisms
Fig. 10.11. A structural model of rapid eye movement (REM) sleep control. LDT, laterodorsal tegmental nucleus; PPT, pedunculopontine tegmental nucleus; RF, reticular formation; GABA, gamma-aminobutyric acid; NE, norepinephrine. See text for description.
Reticular formation and GABAergic influences Not only may LDT/PPT cholinergic input excite PRF neurons but there is the intriguing possibility that inhibitory LDT/PPT projections from REM-on neurons impinge on to GABAergic PRF interneurons with
165
projections on to PRF neurons. This would have the effect of disinhibiting glutamatergic PRF neurons as REM sleep was approached and entered. Gerber et al. (1991) found that about one-fourth of PRF neurons in vitro were inhibited by muscarinic cholinergic agents. Whether these neurons that were inhibited were GABAergic or not, however, is still not known. Preliminary data in the cat support cholinergic inhibition of GABAergic neurons, since microdialysis application of carbachol to the PRF not only induced REM but decreased GABA concentrations in samples from the same microdialysis probe (Thakkar et al., 2004a, b). Moreover, as outlined above, there is considerable evidence that reduction of GABA inhibition in the PRF might play a role in production of REM sleep. First, there are preliminary microdialysis data in both the cat (Thakkar et al., 2004a, b) and the rat (Marks et al., 2003) that GABA levels in the PRF are decreased during REM sleep compared to wakefulness and the Thakkar et al. (2004a, b) data indicate that levels in non-REM sleep are intermediate between wakefulness and REM sleep. Second, pharmacological experiments support this concept since GABA antagonists applied to the rostral PRF produced REM sleep in both cat (Xi et al., 1999, 2001) and rat (Sanford et al., 2003). This postulated pathway of LDT/PPT muscarinic inhibition of GABA PRF neurons during REM sleep is illustrated in Figure 10.11. The dotted lines for this and other GABAergic pathways indicate the more tentative nature of identification of both the projections and their source. This figure graphically emphasizes that inhibition of PRF GABAergic neurons that inhibit PRF neurons would “disinhibit” the PRF neurons and so constitute an additional source of positive feedback. Of note, the GABA levels in wake and in REM in the PRF (Thakkar et al., 2004a, b) are almost the exact inverse of Nitz and Siegel’s (1997a) measurements of GABA in LC. This suggests a possible common GABAergic source of inhibition of the inhibition ( ¼ disinhibition) of PRF REM-on neurons and inhibition of LC REM-off neurons (PRF wake/REM ratio ¼ 1.7 and LC REM/wake ratio ¼ 1.7).
REM-off neurons and their excitation by REM-on neurons (Figure 10.10, term d) There is anatomical evidence for cholinergic projections to both LC and DRN (Jones, 1993). In vitro data indicate excitatory effects of ACh on LC neurons, but data do not support such direct effects on dorsal raphe (Li et al., 1998). The REM-on neuronal excitation of dorsal raphe neurons may be mediated through the reticular formation; there is in vitro evidence for
R.W. MCCARLEY
166
excitatory amino acids excitatory effects on both LC and DR neurons.
Inhibition of REM-on neurons by REM-off neurons (Figure 10.10, term b) For many years, this aspect of the model was most controversial, since the indirect evidence from in vivo data, although generally supportive, was subject to alternative explanations. Now in vitro data indicate a subpopulation of cholinergic neurons in the LDT are inhibited by serotonin (Luebke et al., 1992). Inhibition is especially consistent for the population of LDT neurons that fire in bursts; such burst firing has been shown by in vivo extracellular recordings to be tightly correlated with lateral geniculate nucleus PGO waves, which other data indicate are cholinergically mediated. The action potential burst itself is caused by a particular calcium current, the low-threshold spike, which causes calcium influx and depolarization to a level that produces a burst of sodium-dependent action potentials. Some nonburst cholinergic neurons are also hyperpolarized by serotonin. Other data indicate effects of NE on LDT/PPT cholinergic neurons are also inhibitory (Williams and Reiner, 1993). Moreover, noncholinergic, presumptively GABAergic interneurons, are excited by NE (Kohlmeier and Reiner, 1999); GABAergic interneurons acting to inhibit cholinergic neurons would furnish yet another possible mechanism of inhibition of cholinergic mesopontine neurons by NE, thus further strengthening the model’s postulates.
Inhibitory feedback of REM-off neurons (Figure 10.10, term c) There is strong in vitro physiological evidence for NE inhibition of LC neurons and of serotonergic inhibition of DR neurons, and anatomical studies indicate the presence of recurrent inhibitory collaterals. However, there is no clear evidence that these recurrent collaterals are responsible for REM-off neurons turning off as REM sleep is approached and entered. Indeed, from the standpoint of sleep cycle control, one of the most puzzling aspects has been defining what causes the “REM-off” neurons in the LC and DRN to slow and cease discharge as REM sleep is approached and entered. Thus, the prospect that a GABAergic mechanism might be involved is of great intrinsic interest. As reviewed above, supporting a GABAergic mechanism in the DRN is the in vivo microdialysis finding of Nitz and Siegel (1997b) in naturally sleeping cats that there is a significant increase in DRN GABA levels in REM sleep. Moreover, as discussed above, the balance of pharmacological studies supports a GABA-induced suppression of DRN activity. We think
it important to emphasize that the issue of GABAergic and serotonergic inhibition as important in suppression of DRN discharge is not an either/or but likely one of joint influences, since, as noted above, the approximately threefold increase in REM sleep observed with microdialysis application of the 5-HT1A agonist 8-OH-DPAT to DRN by Portas et al. (1996) was greater than that observed with the GABA agonist muscimol by Nitz and Siegel (1997b), suggesting that factors other than GABA might influence serotonergic neurons. Determination of whether the GABA time course of release parallels the decrease in activity of DRN serotonergic neurons during SWS as REM is approached awaits better technology for measurement of GABA with short duration collection periods. GABAergic influences in the LC during REM sleep have been described above in the microdialysis experiments of Nitz and Siegel (1997a) and the microiontophoresis studies of Gervasoni et al. (1998).
Source of GABAergic inputs to LC and DRN The major missing piece of evidence on GABAergic inhibition of LC/DRN and REM-off neurons is the recording of GABAergic neurons whose activity has the proper inverse time course to that of LC and DRN neurons (see Figure 10.5 and review in Steriade and McCarley, 2005). In our diagram in Figure 10.11 of the brainstem anatomy of REM sleep cycle control, we have suggested that GABAergic neurons in the PRF might provide the input to DRN/LC. Certainly neurons in the PRF have the requisite time course of activity, but there is, to date, no evidence that these are GABAergic neurons. Within the LC and DRN, Maloney et al. (1999) found the extent of c-Fos labeling of glutamic acid decarboxylase-positive neurons in DRN and LC to be inversely correlated with REM sleep percentage, and to decrease in recovery from REM sleep deprivation. This is of course compatible with a local source of GABA increase during REM. However unit recordings in DRN and LC have not found evidence for neurons with an inverse time course to that of the presumptively monoaminergic LC and DRN neurons, suggesting no local source of GABA input. Recent unpublished in vitro studies by Brown et al. in the mouse have found evidence of a subgroup of reticular GABAergic neurons with projections to LC. If confirmed, this might be the source of GABAergic input.
An alternative REM-on and REM-off model with GABAergic neurons Lu et al. (2006) have proposed a GABAergic organization of REM-off and REM-on neurons, based on cFos
NEUROBIOLOGY OF REM SLEEP expression data, lesions, and anatomical connectivity mapping, but with no cellular electrophysiological data (this study notes that their characterization of REM-on and REM-off neuronal activity with cFos must be confirmed by electrophysiological recordings, also needed to determine the time course of activity). They find REM-off (by cFos criteria) GABAergic neurons are present in an arc of brainstem extending from the vlPAG and continuing laterally and ventrally in a reticular area they term the lateral pontine tegmentum. They suggest these GABAergic REM-off neurons inhibit REM-on (cFos criteria) GABAergic neurons in what they term, following Luppi, the SLD (equivalent to the subcoeruleus area or peri-LC alpha in cats) and a dorsal extension of this region, termed the precoeruleus. In turn, the SLD GABAergic REM-on neurons may inhibit GABAergic REM-off neurons in the vlPAG–lateral pontine tegmentum, suggesting a flip-flop switch arrangement in which each side inhibits the other. Lu et al. (2006) also report evidence that other neurons in this circuit are important in muscle atonia and hippocampal theta. In particular they found that glutamatergic ventral SLD neurons have direct projections to spinal cord interneurons – apparently not requiring a relay in the medial medulla – that might inhibit spinal motoneurons. Lesions of the vSLD caused episodes of REM sleep without atonia, while animals with lesions of the ventromedial medulla with orexin B–saporin had normal REM atonia. In terms of EEG phenomena of REM sleep, a group of glutamatergic precoeruleus neurons was found to project to medial septum, and lesions of this region abolished REM hippocampal theta. This paper provides a wealth of new data, but Lu et al. do not address how REM sleep periodicity might come about in this flip-flop model. Indeed, from a formal mathematical point of view two mutually inhibitory populations will not cycle and some external input would be required for them to get out of a state in which one inhibitory population predominates (the ecological analogy would be two populations of predators, where one would eventually devour the other, rather than the cycling observed in the prey–predator equations of the Lotka–Volterra model).
OREXIN EFFECTS AND MODELING CIRCADIAN CONTROL OF REM SLEEP These can only be summarized briefly in this review. Mathematically a limit cycle model best describes the dynamics of the REM cycle, which retains its basic cyclicity no matter how it is set into motion (for discussion, see McCarley and Massaquoi, 1986a, b, 1992; Massaquoi and McCarley, 1992).
167
The other important feature not addressed in the simple model is circadian variation. Figure 10.1 sketches the modeling of the normal course of a night of REM activity in entrained humans. This smaller amplitude and shorter initial first cycle, as well as the absence of REM activity during the day, is modeled by having the REM oscillator shut off and modulated by excitatory input to the REM-off neurons. When this excitatory input to the REM-off neurons was not present, this allowed the REM oscillator to become active (McCarley and Massaquoi, 1986a, b, 1992; Massaquoi and McCarley, 1992). One of the exciting possibilities is that orexin could be this factor (or one of the factors) exciting the REM-off neurons, consistent with its effects on LC and DRN neurons. Experiments in which the orexin ligand is either knocked down or orexin neurons are destroyed will be useful in determining if these manipulations destroy the circadian modulation of REM sleep, as would be predicted by this hypothesis. The breakthrough of REM-like phenomena during the day in narcolepsy, a disorder characterized by a loss of orexinergic neurons, would be consistent with this hypothesis (see review of orexin and narcolepsy in Chen et al., 2009). Supporting this possibility are data from transgenic mice and rats in which orexin-containing neurons are destroyed postnatally by orexinergic-specific expression of a truncated Machado–Joseph disease gene product (ataxin-3) with an expanded polyglutamine stretch under control of the human prepro-orexin promoter; this has provided a valuable animal model of narcolepsy (Beuckmann et al., 2004). This transgenic rat, compared with wild types, showed a markedly different REM sleep profile. Perhaps the most striking change in REM percentage was the difference in diurnal distribution. REM sleep (including REM sleep onset) was approximately twofold increased over the wild type in the normally REM-poor dark period. Finally, data from Chen et al. (2005, 2006) indicate that small interfering RNA-induced knockdown of preproorexin led to an increase in REM sleep in the active (dark) period of the rat, but not in the light period.
ACKNOWLEDGMENT This work was supported by grants from the Department of Veterans Affairs, Medical Research Service, and NIMH (R37 MH39,683 and R01 MH40,799).
REFERENCES Aston-Jones G, Bloom FE (1981a). Activity of norepinephrinecontaining locus coeruleus neurons in behaving rats anticipates fluctuations in the sleep–waking cycle. J Neurosci 1: 876–886.
168
R.W. MCCARLEY
Aston-Jones G, Bloom FE (1981b). Norepinephrine-containing locus coeruleus neurons in behaving rat exhibit pronounced responses to non-noxious environmental stimuli. J Neurosci 1: 887–900. Auerbach SB, Minzenberg MJ, Wilkinson LO (1989). Extracellular serotonin and 5-hydroxyindoleacetic acid in hypothalamus of the unanesthetized rat measured by in vivo dialysis coupled to high-performance liquid chromatography with electrochemical detection: dialysate serotonin reflects neuronal release. Brain Res 499: 281–290. Beuckmann CT, Sinton CM, Williams SC et al. (2004). Expression of a poly-glutamine-ataxin-3 transgene in orexin neurons induces narcolepsy-cataplexy in the rat. J Neurosci 24: 4469–4477. Bjorvatn B, Fagerland S, Eid T et al. (1997). Sleep/waking effects of a selective 5-HT1A receptor agonist given systemically as well as perfused in the dorsal raphe nucleus in rats. Brain Res 770: 81–88. Boissard R, Gervasoni D, Schmidt MH et al. (2002). The rat ponto-medullary network responsible for paradoxical sleep onset and maintenance: a combined microinjection and functional neuroanatomical study. Eur J Neurosci 16: 1959–1973. Bourgin P, Escourrou P, Gaultier C et al. (1995). Induction of rapid eye movement sleep carbachol infusion into the pontine reticular formation in the rat. Neuroreport 6: 532–536. Brooks DC, Gershon MD, Simon RP (1972). Brainstem serotonin depletion and ponto-geniculo-occipital wave activity in the cat treated with reserpine. Neuropharmacol 11: 511–520. Caballero A, De Andres I (1986). Unilateral lesions in locus coeruleus area enhance paradoxical sleep. Electroencephalogr Clin Neurophysiol 64: 339–346. Cespuglio R, Gomez ME, Walker E et al. (1979). Effets du refroidissement et de la stimulation des noyaux du syste`me du raphe´ sur les e´tats de vigilance chez le chat. Electroencephalogr Clin Neurophysiol 47: 289–308. Cespuglio R, Faradji H, Gomez ME et al. (1981). Single unit recordings in the nuclei raphe dorsalis and magnus during the sleep–waking cycle of semi-chronic prepared cats. Neurosci Lett 24: 133–138. Cespuglio R, Gomez ME, Faradji H et al. (1982). Alterations in the sleep–waking cycle induced by cooling of the locus coeruleus area. Electroencephalogr Clin Neurophysiol 54: 570–578. Chen L, Thakkar M, Winston S et al. (2005). RNA interference induces orexin knockdown and sleep changes in rats. Sleep 28: A340. Chen L, Thakkar MM, Winston S et al. (2006). REM sleep changes in rats induced by siRNA-mediated orexin knockdown. Eur J Neurosci 24: 2039. Chen L, Brown RE, McKenna JT et al. (2009). Animal models of narcolepsy. CNS Neurol Disord Drug Targets 8: 296–308. Coleman CG, Lydid R, Baghdoyan HA (2004a). Acetylcholine release in the pontine reticular formation of C57BL/ 6J mouse is modulated by non-M1 musacarinic receptors. Neurosci 126: 831–838.
Coleman CG, Lydic R, Baghdoyan HA (2004b). M2 musacarinic receptors in pontine formation of C57BL/6J mouse contribute to rapid eye movement sleep generation. Neurosci 126: 821–830. Deurveilher S, Hars B, Hennevin E (1997). Pontine microinjection of carbachol does not reliably enhance paradoxical sleep in rats. Sleep 20: 593–607. El Mansari M, Sakai K, Jouvet M (1990). Responses of presumed cholinergic mesopontine tegmental neurons to carbachol microinjections in freely moving cats. Exp Brain Res 83: 115–123. Feinberg I, Thode HC, Chugani HT et al. (1990). Gamma function describes maturational curves for delta wave amplitude, cortical metabolic rate and synaptic density. J Theor Biol 142: 149–161. Fields RD, Feleke E, Stevens B et al. (1997). Action potential-dependent regulation of gene expression: temporal specificity in Ca21, cAMP-responsive element binding proteins, and mitogen-activated protein kinase signaling. J Neurosci 17 (19): 7252–7266. Foote SL, Aston-Jones G, Bloom FE (1980). Impulse activity of locus coeruleus neurons in awake rats and monkeys is a function of sensory stimulation and arousal. Proc Natl Acad Sci U S A 77: 3033–3037. Fornal C, Auerbach S, Jacobs BL (1985). Activity of serotonin containing neurons in nucleus raphe magnus in freely moving cats. Exp Neurol 88: 590–608. Gerber U, Stevens DS, McCarley RW et al. (1991). A muscarinic-gated conductance increase in medial pontine reticular neurons of the rat in vitro. J Neurosci 11: 3861–3867. Gervasoni D, Darracq L, Fort P et al. (1998). Electrophysiological evidence that noradrenergic neurons of the rat locus coeruleus are tonically inhibited by GABA during sleep. Eur J Neurosci 10: 964–970. Gervasoni D, Peyron C, Rampon C et al. (2000). Role and origin of the GABAergic innervation of dorsal raphe serotonergic neurons. J. Neurosci 20: 4217–4225. Gnadt JW, Pegram GV (1986). Cholinergic brainstem mechanisms of REM sleep in the rat. Brain Res 384: 29–41. Goutagny R, Comte JC, Salvert D et al. (2005). Paradoxical sleep in mice lacking M3 and M2/M4 muscarinic receptors. Neuropsychobiol 52: 140–146. Greene RW, Gerber U, McCarley RW (1989). Cholinergic activation of medial pontine reticular formation neurons in vitro. Brain Res 476: 154–159. Hendricks JC, Morrison AR, Mann GL (1982). Different behaviors during paradoxical sleep without atonia depend on pontine lesion site. Brain Res 239: 81–105. Hobson JA, McCarley RW, Wyzinski PA et al. (1973). Reciprocal firing by two neuronal groups during the sleep cycle. Soc Neurosci Abstr 3: 373. Hobson JA, McCarley RW, Wyzinski PW (1975). Sleep cycle oscillation: reciprocal discharge by two brainstem neuronal groups. Science 189: 55–58. Hobson JA, McCarley RW, Nelson JP (1983a). Location and spike-train characteristics of cells in anterodorsal pons
NEUROBIOLOGY OF REM SLEEP having selective decreases in firing rate during desynchronized sleep. J Neurophysiol 50: 770–783. Honda T, Semba K (1995). An ultrastructural study of cholinergic and non-cholinergic neurons in the laterodorsal and pedunculopontine tegmental nuclei in the rat. Neuroscience 68: 837–853. Imeri L, De Simoni MG, Giglio R et al. (1994). Changes in the serotonergic system during the sleep–wake cycle: simultaneous polygraphic and voltammetric recordings in hypothalamus using a telemetry system. Neuroscience 58: 353–358. Ito K, Yanagihara M, Imon L et al. (2002). Intracellular recordings of pontine medial gigantocellular tegmental field neurons in the naturally sleeping cat: behavioral state-related activity and soma size difference in order of recruitment. Neuroscience 114: 23. Jones BE (1993). The organization of central cholinergic systems and their functional importance in sleep–waking states. Progr Brain Res 98: 61–71. Jones BE, Harper ST, Halaris AE (1977). Effects of locus coeruleus lesions upon cerebral monoamine content, sleep–wakefulness states and the response to amphetamine in the cat. Brain Res 124: 473–496. Jouvet M (1962). Recherches sur les structures nerveuses et les me´canismes responsables des diffe´rentes phases du sommeil physiologique. Arch Ital Biol 100: 125. Jouvet M (1979). What does a cat dream about? Trends Neurosci 2: 15–16. Kandel E, Schwarz JH, Jessell TM (Eds.) (2000). Principles of Neural Science. McGraw-Hill, New York. Kayama Y, Ohta M, Jodo E (1992). Firing of “possibly” cholinergic neurons in the rat laterodorsal tegmental nucleus during sleep and wakefulness. Brain Res 569: 210–220. Kohlmeier KA, Reiner PB (1999). Noradrenaline excites non-cholinergic laterodorsal tegmental neurons via two distinct mechanisms. Neuroscience 93: 619–630. Leonard CS, Llina´s RR (1994). Serotonergic and cholinergic inhibition of mesopontine cholinergic neurons controlling REM sleep: an in vitro electrophysiological study. Neuroscience 59: 309–330. Levine ES, Jacobs BL (1992). Neurochemical afferents controlling the activity of serotonergic neurons in the dorsal raphe nucleus: microiontophoretic studies in the awake cat. J Neurosci 12: 4037–4044. Li X, Rainnie DG, McCarley RW et al. (1998). Presynaptic nicotinic receptors facilitate monoaminergic transmission. J Neurosci 18: 1904–1912. Lu J, Sherman D, Devor M et al. (2006). A putative flip-flop switch for control of REM sleep. Nature 441: 589. Luebke JI, Greene RW, Semba K et al. (1992). Serotonin hyperpolarizes cholinergic low-threshold burst neurons in the rat laterodorsal tegmental nucleus in vitro. Proc Natl Acad Sci U S A 89: 743–747. Lydic R, McCarley RW, Hobson JA (1983). The time-course of dorsal raphe discharge, PGO waves, and muscle tone averaged across multiple sleep cycles. Brain Res 274: 365–370. Lydic R, McCarley RW, Hobson JA (1987a). Serotonin neurons and sleep. I. Long term recordings of dorsal raphe discharge frequency and PGO waves. Arch Ital Biol 125: 317–343.
169
Lydic R, McCarley RW, Hobson JA (1987b). Serotonin neurons and sleep. II. Time course of dorsal raphe discharge, PGO waves, and behavioral states. Arch Ital Biol 126: 1–28. McCarley RW (1973). A model for the periodicity of brainstem neuronal discharges during the sleep cycle. Sleep Res 2: 30. McCarley RW (1978). Control of sleep–waking state alteration in Felix domesticus. In: JA Ferrendelli (Ed.), Neuroscience Symposia, vol III. Society for Neuroscience, Bethesda, MA, p. 90. McCarley RW (2004). Mechanisms and models of REM sleep control. Arch Ital Biol 142: 429–468. McCarley RW, Hobson JA (1975). Neuronal excitability modulation over the sleep cycle: a structural and mathematical model. Science 189: 58–60. McCarley RW, Massaquoi SG (1986a). A limit cycle mathematical model of the REM sleep oscillator system. Am J Physiol 251: R1011–R1029. McCarley RW, Massaquoi SG (1986b). Further discussion of a model of the REM sleep oscillator. Am J Physiol 251: R1033–R1036. McCarley RW, Massaquoi SG (1992). The limit cycle reciprocal interaction model of REM cycle control: new neurobiological structure. J Sleep Res 1: 132. McCarley RW, Greene RW, Rainnie D et al. (1995). Brainstem neuromodulation and REM sleep. Sem Neurosci 7: 341–354. McGinty DJ, Harper RM (1976). Dorsal raphe neurons: depression of firing during sleep in cats. Brain Res 101: 569–575. Maloney KJ, Mainville L, Jones BE (1999). Differential c-Fos expression in cholinergic, monoaminergic, and GABAergic cell groups of the pontomesencephalic tegmentum after paradoxical sleep deprivation and recovery. J Neurosci 19: 3057–3072. Marks GA, Birabil CG (1998). Enhancement of rapid eye movement sleep in the rat by cholinergic and adenosinergic agonists infused into the pontine reticular formation. Neurosci 86: 29–37. Marks GA, Kramer GL, Birabil CG (2003). GABAergic mechanisms in the REM sleep induction zone of the rat. Sleep 26 (Abstract Supplement): A8. Massaquoi SG, McCarley RW (1992). Extension of the limit cycle reciprocal interaction model of REM cycle control: an integrated sleep control model. J Sleep Res 1: 138–143. Merchant-Nancy H, Vazquaz J, Garcia F et al. (1995). Brain distribution of c-fos expression as a result of prolonged rapid eye movement (REM) sleep period duration. Brain Res 681: 15–22. Mitani A, Ito K, Hallanger AE et al. (1988). Cholinergic projections from the laterodorsal and pedunculopontine tegmental nuclei to the pontine gigantocellular tegmental field in the cat. Brain Res 451: 397–402. Nitz DA, Siegel JM (1997a). GABA release in the locus coeruleus as a function of sleep/wake state. Neuroscience 78: 795–801.
170
R.W. MCCARLEY
Nitz DA, Siegel JM (1997b). Inhibitory amino acid neurotransmission in the dorsal raphe nucleus during sleep/ wake states. Am J Physiol 273: R451–454. Paxinos GT, Watson C (1997). The rat brain. In: Stereotaxic Coordinates, Academic Press, San Diego. Petitjean F, Sakai K, Blondaux C et al. (1975). Hypersomnia by isthmic lesion in cat. II. Neurophysiological and pharmacological study. Brain Res 88: 439–453. Pollack MD, Mistlberger RE (2005). Microinjection of neostigmine into the pontine reticular formation of the mouse: further evaluation of a proposed REM sleep enhancement technique. Brain Res 1031: 253–267. Portas CM, McCarley RW (1994). Behavioral state-related changes of extracellular serotonin concentration in the dorsal raphe nucleus: a microdialysis study in the freely moving cat. Brain Res 648: 306–312. Portas CM, Thakkar M, Rainnie D et al. (1996). Microdialysis perfusion of 8-hydroxy-2-(di-n-propylamino)tetralin (8-OH-DPAT) in the dorsal raphe nucleus decreases serotonin release and increases rapid eye movement sleep in the freely moving cat. J Neurosci 16: 2820–2828. Rasmussen K, Heym J, Jacobs BL (1984). Activity of serotonin containing neurons in nucleus centralis superior of freely moving cats. Exp Neurol 83: 302–317. Ruch-Monachon MA, Jalfre M, Haefeley W (1976). Drugs and PGO waves in the lateral geniculate body of the curarized rat. Arch Int Pharmacodyn The´r 219: 251–346. Sakai K, Crochet S (2000). Serotonergic dorsal raphe neurons cease firing by disfacilitation during paradoxical sleep. Neuroreport 11: 3237–3241. Sakai K, Crochet S (2001). Role of dorsal raphe neurons in paradoxical sleep generation in the cat: no evidence for a serotonergic mechanism. Eur J Neurosci 13: 103–112. Sakai K, Vanni-Mercier G, Jouvet M (1983). Evidence for the presence of PS-Off neurons in the ventromedial oblongata of freely moving cats. Exp Brain Res 49: 311–314. Sanford LD, Ross RJ, Seggos AE et al. (1994). Central administration of two 5-HT receptor agonists: effect on REM sleep initiation and PGO waves. Pharmacol Biochem Behav 49: 93–100. Sanford LD, Tang X, Xiao J et al. (2003). GABAergic regulation of REM sleep in reticularis pontis oralis and caudalis in rats. J Neurophysiol 90: 938–945. Sastre JP, Jouvet M (1979). Le comportement onirique du chat. Physiol Behav 22: 979–989. Sastre JP, Buda C, Kitahama K et al. (1996). Importance of the ventrolateral region of the periaqueductal gray and adjacent tegmentum in the control of paradoxical sleep as studied by muscimol microinjections in the cat. Neuroscience 74: 415–426. Satinoff E (1988). Thermal influences on REM sleep. In: R Lydic, JF Biebuyck (Eds.), Clinical Physiology of Sleep. American Physiological Society, Bethesda, MA, pp. 135–144. Semba K, Fibiger HC (1992). Afferent connections of the laterodorsal and the pedunculopontine tegmental nuclei in the rat: a retro- and antero-grade transport and immunohistochemical study. J Comp Neurol 323: 387–410.
Simon RP, Gershon MP, Brooks DC (1973). The role of the raphe nuclei in the regulation of ponto-geniculo-occipital wave activity. Brain Res 58: 313–330. Sprouse JS, Aghajanian GK (1987). Electrophysiological responses of serotoninergic dorsal raphe neurons to 5-HT1A and 5-HT1B agonists. Synapse 1: 3–9. Steinfels GF, Heym J, Strecker RE et al. (1983). Behavioral correlates of dopaminergic unit activity in freely moving cats. Brain Res 258: 217–228. Steininger TL, Wainer BH, Blakely RD et al. (1997). Serotonergic dorsal raphe nucleus projections to the cholinergic and noncholinergic neurons of the pedunculopontine tegmental region: a light and electron microscopic anterograde tracing and immunohistochemical study. J Comp Neurosci 382: 302–322. Steriade M, McCarley RW (2005). Brain Control of Wakefulness and Sleep. Kluwer Academic/Plenum, New York, New York. Steriade M, Datta S, Pare´ D et al. (1990). Neuronal activities in brainstem cholinergic nuclei related to tonic activation processes in thalamocortical systems. J Neurosci 10: 2541–2559. Strecker RE, Thakkar MM, Porkka-Heiskanen T et al. (1999). Behavioral state-related changes of extracellular serotonin concentration in the pedunculopontine tegmental nucleus: a microdialysis study in freely moving animals. Sleep Res Online 2: 21–27. http://www.sro.org/ 1999/strecker/21/. Swanson LW (1992). Brain Maps: Structure of the Rat Brain. Elsevier, New York. Taguchi O, Kubin L, Pack AI (1992). Evocation of postural atonia and respiratory depression by pontine carbachol in the decerebrate rat. Brain Res 595: 107–115. Thakkar M, Portas CM, McCarley RW (1996). Chronic low amplitude electrical stimulation of the laterodorsal tegmental nucleus of freely moving cats increases REM sleep. Brain Res 723: 223–227. Thakkar MM, Strecker RE, McCarley RW (1998). Behavioral state control through differential serotonergic inhibition in the mesopontine cholinergic nuclei: a simultaneous unit recording and microdyalisis study. J Neurosci 18: 5490–5497. Thakkar M, Strecker R, McCarley RW (2002). Phasic but not tonic REM selective discharge of periaqueductal gray neurons in freely behaving animals: relevance to postulates of GABAergic inhibition of monoaminergic neurons. Brain Res 945: 276–280. Thakkar MM, Tao R, Ma Z et al. (2004a). GABA release in the mPRF: role in the regulation of sleep–wakefulness. Sleep 27 (Abstract Supplement). Thakkar MM, Tao R, Yunren B et al. (2004b). GABA release in the pontine reticular formation is lowest during REM sleep. Soc Neurosci Abstr. Program no. 895:5. Trulson MF, Jacobs BL (1979). Raphe unit activity in freely moving cats: correlation with level of behavioral arousal. Brain Res 163: 135–150. Verret L, Leger L, Fort P et al. (2005). Cholinergic and noncholinergic brainstem neurons expressing Fos after
NEUROBIOLOGY OF REM SLEEP paradoxical (REM) sleep deprivation and recovery. Eur J Neurosci 21: 2488–2504. Webster HH, Jones BE (1988). Neurotoxic lesions of the dorsolateral pontomesencephalic tegmentum-cholinergic area in the cat. II. Effects upon sleep–waking states. Brain Res 458: 285–302. Wilkinson LO, Auerbach SB, Jacobs BL (1991). Extracellular serotonin levels change with behavioral state but not with pyrogen-induced hyperthermia. J Neurosci 11: 2732–2741.
171
Williams JA, Reiner PB (1993). Noradrenaline hyperpolarizes identified rat mesopontine cholinergic neurons in vitro. J Neurosci 13: 3878–3883. Xi MC, Morales FR, Chase MH (1999). A GABAergic pontine reticular system is involved in the control of wakefulness and sleep. Sleep Res Online 2: 43–48. Xi MC, Morales FR, Chase MH (2001). Induction of wakefulness and inhibition of active (REM) sleep by GABAergic processes in the nucleus pontis oralis. Arch Ital Biol 139: 125–145.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 11
Neurochemistry of sleep: an overview of animal experimental work PIERRE-HERVE´ LUPPI * AND PATRICE FORT UMR5167 CNRS, Institut Fédératif des Neurosciences de Lyon (IFR 19), Université Claude Bernard Lyon I, Lyon, France
NEURONAL NETWORK RESPONSIBLE FOR SLEEP ONSET AND MAINTENANCE The forebrain sleep center Between World Wars I and II, von Economo reported that comatose patients, struck down with encephalitis lethargica, had prominent parenchyma injury at the level of the preoptic area (POA) near the optic tract. From these results, he proposed that the POA is involved in sleep (von Economo, 1926, 1929). These seminal clinical studies, indicating that an intact rostral hypothalamus is critical for the production of normal sleep, represented a founding step for the research aimed at discovering the neurobiological mechanisms regulating behavioral states, namely wakefulness (W), slow-wave sleep (SWS), and paradoxical sleep (PS). During the subsequent period until the 1990s, developments in basic research, using standard lesions, neuronal unit recording, neuropharmacological and neurochemical approaches in animals, led to the establishment of a few fundamental concepts. They could be summarized as follows: (1) in line with early predictions by von Economo, the POA, more especially its lateral part (LPOA), is the unique brain structure that fulfilled necessary and sufficient criteria for a hypnogenic center containing neurons that directly promote sleep (Shiromani et al., 1999; Schmidt et al., 2000; Saper et al., 2001; Szymusiak et al., 2001; McGinty and Szymusiak, 2003); (2) this simplicity contrasts highly with the redundant network responsible for arousal, involving numerous brain areas and neurotransmitter systems such as acetylcholine-, norepinephrine-, serotonin-, histamine-, and more recently discovered orexin-containing neurons, with widespread projections from rhombencephalon to cerebral mantle. Collectively, these components, with an activity specific *
to wakefulness, form the so-called ascending reticular activating system (ARAS) that regulates cortical activation during waking (Moruzzi, 1949, 1972; Jones, 1993b, 1994); (3) as soon as drowsiness begins, the hypnogenic center would put out of function the ARAS system through sustained inhibition; and (4) the sleep pressure as well as drowsiness would be owed to the conjunction of homeostatic and circadian processes that are able to modulate the sleep center directly (Borbely, 1982, 2001). Despite these crude consensual concepts and some real progress of our knowledge since von Economo’s proposal, the basic neurobiological mechanisms involved in sleep promotion and the harmonious succession of behavioral states remain largely underestimated. Indeed, LPOA is a vast forebrain region that contains multiple contingents of intermingled and loosely arranged neurons, governing vital functions. This cytoarchitectonic configuration and the lack of a precise plotting of the sleep-promoting neurons have hindered the decoding of cellular, synaptic, or molecular mechanisms used by the sleep center to play its functional role. However, a decisive stage was set in 1996 by establishing the critical role of the ventrolateral preoptic nucleus (VLPO), a small neuronal core (radius 300 mm) located in the most ventral part of the LPOA. This was made possible by means of a functional neuroimaging paradigm at the cellular level, using the expression of the early gene c-Fos as a marker of neuronal activity in rats having slept for a long period before sacrifice (Sherin et al., 1996). This hypersomnia, also coined sleep rebound, is the typical behavioral response following sleep deprivation in rats. While neurons specifically activated during sleep and immunostained for c-Fos (c-Fosþ) were diffusely distributed in LPOA, they were more densely packed within the
Correspondence to: Dr. Pierre-Herve´ Luppi, UMR5167 CNRS, Faculte´ de Me´decine Laennec, 7, rue Guillaume Paradin, 69372 Lyon cedex 08, France. Tel: (þ33) 4 78 77 10 40, Fax: (þ33) 4 78 77 10 22, E-mail:
[email protected]
174
P.-H. LUPPI AND P. FORT
VLPO. Furthermore, the density of c-Fosþ neurons correlated closely with the sleep quantities during the last 2 hours preceding sacrifice. This labeling pattern of sleep-active neurons would be related to the production of sleep itself rather than to a homeostatic regulation induced by its deprivation. Indeed, while drowsiness markedly increased in deprived rats, little staining was observed in rats sacrificed before the sleep rebound (Sherin et al., 1996, 1998). By the same functional approach, it has been demonstrated that VLPO and suprachiasmatic nucleus (SCN) have synchronized activity (Novak and Nunez, 1998). Further, they are interconnected and receive inputs from retinal ganglionic cells. Similarly, the dorsomedian hypothalamic nucleus, an SCN relay, projects strongly to the VLPO. Considered together, these anatomical data suggest that circadian- and photic-linked information may be conveyed to modulate the VLPO activity across the nyctemeral period (Watts et al., 1987; Thompson et al., 1996; Lu et al., 1999; Novak and Nunez, 2000; Sun et al., 2001; Chou et al., 2002, 2003; Deurveilher et al., 2002). Besides, electrophysiological experiments in freely moving rats have shown that neurons that doubled their firing rate at sleep onset are more frequently recorded in VLPO than in other LPOA parts (Szymusiak et al., 1998). Furthermore, their recruitment and firing activation are positively correlated with both sleep depth and duration. Of particular functional interest, this sleep-specific activity of VLPO neurons (i.e., sleep-on neuron) is inverse to that of wake-active neurons (Aston-Jones and Bloom, 1981; Jacobs, 1985; Sakai, 1986; Barnes and Sharp, 1999). Functionally, the bilateral neurotoxic destruction of VLPO neurons (more than 70%) is followed by a profound and long-lasting insomnia with a reduction of 56% of sleep quantities in rats (Lu et al., 2000). In line with these data, we further demonstrated that iontophoretic application of carbachol, a cholinergic agonist, targeted to the VLPO suppressed sleep in anestheticfree head-restrained rats (Schmidt et al., 2001, 2002). These physiological data support the necessity of VLPO for producing normal sleep. Besides, retrograde and anterograde tract-tracing studies indicate that VLPO neurons are reciprocally connected with cerebral areas containing wake-active neurons such as the histaminergic tuberomammillary nucleus (TMN), serotonergic midbrain raphe nuclei, noradrenergic locus coeruleus (LC), cholinergic pontine laterodorsal tegmental nucleus (LDT)/pedunculopontine tegmental nucleus (PPT) and magnocellular preoptic nuclei, as well as orexinergic perifornical area of the lateral hypothalamus (Luppi et al., 1995; Sherin et al., 1996, 1998; Fort et al., 1998; Gervasoni et al., 2000; Steininger
et al., 2001; Lu et al., 2002; Schmidt et al., 2003). Finally, more than 90% of c-Fosþ sleep-active neurons in VLPO express galanin mRNA while 80% of neurons projecting to the TMN contain both galanin and glutamic acid decarboxylase (GAD), the GABA-synthesizing enzyme, suggesting that projections to the waking systems are inhibitory in nature (Sherin et al., 1996, 1998; Lu et al., 2002). Taken together, these data indicate that the VLPO plays a key role in coordinating the inhibition of arousal systems to promote sleep and thus occupies a privileged place within the complex neuronal network involved in behavioral states. Obviously, its critical role has opened new fields for investigation of the underlying regulatory mechanisms of sleep. For us, the fact that VLPO neurons are: (1) specifically active during sleep; (2) endowed with reciprocal inhibitory connections with the wake-promoting areas; and (3) densely packed in a small-sized nucleus offers a unique opportunity and evident methodological advantage to study at cellular, synaptic, and molecular levels the neurons responsible for sleep. A special effort to characterize neurotransmitters and pathways that control VLPO sleep-active neurons would thus contribute to understanding the mechanisms that manage their excitability across the sleep–waking cycle and should provide key insight into the regulation of behavioral states.
Neurotransmitters regulating the activity of VLPO sleep-promoting neurons In recent years, we have undertaken electrophysiological recordings of VLPO neurons in rat brain slices. This in vitro experimental approach proved suitable for exploring electrophysiological, pharmacological, and chemomorphological properties of neurons and thus for drawing up the so-called “functional ID card” of the sleep-active neurons. One of our primary objectives was to determine whether neurons inhibited by neurotransmitters released from wake-promoting areas could be frequently recorded in VLPO. We thus successfully identified a homogeneous neuronal group with a specific set of intrinsic membrane properties and a clearcut chemomorphology that are inhibited by the major neurotransmitters of waking. Their high proportion (80% of the recorded neurons), matching that of cells active during sleep in VLPO, and their pharmacological profile represent convincing arguments about their presumed status as sleep-promoting neurons (PSP). In fact, we showed that PSP neurons are GABAergic, multipolar and triangular-shaped and endowed with a potent low-threshold calcium potential. These neurons are inhibited by norepinephrine (Gallopin et al., 2000).
NEUROCHEMISTRY OF SLEEP: AN OVERVIEW OF ANIMAL EXPERIMENTAL WORK It was shown that this inhibitory effect is mediated by postsynaptic alpha-2 adrenoceptors (Matsuo et al., 2003; Gallopin et al., 2004). Interestingly, we further found that norepinephrine-inhibited neurons are also inhibited by acetylcholine. In contrast, histamine and orexin did not modulate PSP neurons, although an inhibitory influence was expected (Gallopin et al., 2000; Eggermann et al., 2001). However, it should be noted that TMN neurons contain both histamine and GABA (Airaksinen et al., 1992) and are thus in position, as noradrenergic and cholinergic drives, to inhibit PSP neurons during waking. Considering their unique profile of neuromodulation (since the remaining recorded cells are excited by norepinephrine, acetylcholine, histamine, and orexin), the overall inhibition of the PSP neurons by neurotransmitters of waking is in agreement with their inactivity during waking (Szymusiak et al., 1998). We previously suggested that the reciprocal inhibitory interaction of PSP neurons with the multiple waking systems to which they project is a key factor for promoting sleep by coordinating their inhibition at sleep onset (Gallopin et al., 2000). More recently, a consensual model has been proposed suggesting that this reciprocity of projections is analogous to a “flip-flop” switch electrical circuit (Saper et al., 2001). Simply stated, when VLPO neurons start to fire at sleep onset and fire rapidly during sleep, they would inhibit the waking-promoting neurons allowing for their own disinhibition and reinforced firing. Conversely, during arousal, waking-promoting neurons fire at a high rate, thus inhibiting VLPO neurons and resulting in the disinhibition of their own firing. Either sleep or waking is self-reinforcing when its component neurons are sufficiently active. The reciprocal inhibitory interaction of these systems provides a mechanism for the maintenance of one of the two stable configurations. Accordingly, disruption of wake- and sleep-promoting pathways would result in behavioral instability due to a destabilization of the reciprocal inhibitory interactions. This is likely the case in murine models of narcolepsy, a human sleep pathology, with functional failure of the orexin system concomitant to pronounced vigilance disturbances and sudden transitions in behavioral states (Lin et al., 1999; Nishino et al., 2000). An increasing number of data agree that orexin-containing neurons would play a major role in the maintenance of arousal. The widespread excitatory projection to waking-promoting neurons provides to this neuronal system an ideal position to orchestrate their respective activity (Peyron et al., 1998). Turned on during waking, orexin-containing neurons would strengthen the activity of the wake-promoting neurons, which in turn, via their inhibitory projections to PSP neurons, would prevent sleep onset and thus stabilize waking (de Lecea
175
et al., 1998; Peyron et al., 1998; Kilduff and Peyron, 2000; Saper et al., 2001). Certainly, functional properties of the “flip-flop” model may easily support the production of stable states of wakefulness and sleep by a simple neuronal network and an important resistance to switching by limiting inappropriate changes when inputs to VLPO or wake-promoting areas fluctuate. In great contrast, this model does not take account of the necessary instability or unbalanced relationship between wakeand sleep-promoting neurons that should occur for rapid transitions between sleep and waking (drowsiness or awaking), switching events that are frequently encountered across the sleep–waking cycle (75% of all transition states in rats). In this context, mechanisms responsible for the increased firing of sleep-on neurons just before or at sleep onset remain unknown. They would be the result of (1) a disinhibition linked to a decreased activity of wake-promoting neurons, thus releasing PSP neurons from potent inhibitions during waking; and/or (2) an increase of a sleepdependent excitatory drive, thus inducing the inhibition of the wake-promoting neurons and reinforcing sleep. It is tempting to hypothesize that such excitatory drive would be related to thermoregulation (McGinty et al., 2001) or homeostatic process, involving hypnogenic factors that directly excite PSP neurons. Numerous substances contributing to sleep homeostasis have been described (Krueger, 1999; Krueger and Majde, 2003; Obal and Krueger, 2003). Among them, adenosine, which is a central link between energy and neuronal activity, has been found to be an important endogenous sleep-promoting substance (Benington et al., 1995; Porkka-Heiskanen et al., 1997). It mediates the somnogenic effects of prior wakefulness, and also seems to have an important role in the regulation of the duration and depth of sleep after wakefulness. Early pharmacological experiments focused the contribution of the A1 receptors (A1R) to sleep regulation through the inhibition of the wake-promoting neurons, in particular the cholinergic forebrain and pontine neurons (Rainnie et al., 1994; Portas et al., 1997; Basheer et al., 1999; PorkkaHeiskanen et al., 2000). However, more recent data using transgenic mice demonstrated that the lack of A1R does not prevent the homeostatic regulation of sleep (Stenberg et al., 2003) while the lack of A2AR does (Urade et al., 2003), suggesting that the activation of A2AR, not that of A1R, is crucial in sleep induction and regulation. In that context, a number of recent results suggest that adenosine might activate VLPO neurons at the onset of sleep via an action on their A2A receptors. Indeed, the infusion of A2AR agonist in the subarachnoid space rostral to the VLPO
176
P.-H. LUPPI AND P. FORT
increases sleep and induces c-Fos expression in VLPO neurons (Satoh et al., 1996; Scammell et al., 2001). Further, the application on slices of an A2AR agonist induces an excitation of half of the VLPO neurons (Gallopin et al., 2005) and the waking effect of caffeine is blocked in A2AR knockout mice (Huang et al., 2005). Besides, we showed that modafinil, an increasingly popular wake-promoting drug for narcolepsy treatment, specifically increased the inhibition of VLPO neurons induced by norephinephrine but had no effect when applied alone or in combination with other substances (Gallopin et al., 2004). From these results, we suggested that modafinil blocks the reuptake of norepinephrine by the noradrenergic terminals on sleep-promoting neurons from the VLPO and we proposed that such a mechanism could be at least partially responsible for the wake-promoting effect of modafinil.
A new model of the network responsible for sleep onset and maintenance Altogether, it is today accepted that the VLPO contains the neurons responsible for sleep onset and maintenance. These neurons would be inhibited during waking by the classical multiple waking systems. VLPO neurons would start firing at the onset of sleep due to growing excitatory drives arising from the SCN and adenosine via the A2A receptors. The removal of these excitatory influences will lead to a progressive decrease in the activity of these neurons and therefore of their inhibition of the wake systems resulting in awakening (Figure 11.1).
Structures responsible for W and SWS
DRN LC
BF Adenosine A2A
VLPO SCN TMN
Sensory inputs
Excitatory pathways Adenosine, glutamate Inhibitory pathways GABA, monoamines
Fig. 11.1. Model of the network responsible for sleep onset and maintenance. W, waking; SWS, slow-wave sleep; BF, basal forebrain; DRN, dorsal raphe nucleus; LC, locus coeruleus; SCN, suprachiasmatic nucleus; TMN, tuberomammillary nucleus; VLPO, ventrolateral preoptic nucleus; GABA, gamma-aminobutyric acid.
NEURONAL NETWORK RESPONSIBLE FOR PARADOXICAL (REM) SLEEP ONSET AND MAINTENANCE The discovery of paradoxical sleep In 1959, Michel Jouvet & Franc¸ois Michel discovered in cats a sleep phase characterized by a complete disappearance of the muscle tone, paradoxically associated with a cortical activation and rapid eye movements (REMs). In view of its singularity, they proposed to call this state paradoxical sleep (PS). It corresponds to the stage of sleep named REM sleep in 1953 by Aserinsky & Kleitman and shown to correlate in humans with dream activity (Aserinsky and Kleitman, 1953; Dement and Kleitman, 1957). The discovery that complete muscle atonia occurs during this stage of sleep led Jouvet to propose that PS was a third state of vigilance independent of SWS and W.
The search for the “center” of paradoxical sleep During the 40 years after the discovery of PS, Jouvet, with the researchers from his laboratory, pursued his study of PS. Supporting his theory of a duality of the sleep stages, he showed that PS is present in mammals and birds but absent in amphibians and reptiles, in contrast to SWS. He also demonstrated that PS is initiated and maintained by structures different from those regulating SWS and W. He first showed that PS persists following decortication, cerebellar ablation, or brainstem transections rostral to the pons. In contrast, transection at the posterior limit of the pons suppressed PS (Jouvet, 1962). He also demonstrated that a state resembling PS is still visible in the “pontine cat,” a preparation in which all the structures rostral to the pons have been removed (Jouvet, 1962). These results indicated that brainstem structures are necessary and sufficient to trigger and maintain the state of PS, a concept still valid today. Jouvet and others then showed that electrolytic and chemical lesions of the dorsal part of the pontis oralis (PnO) and caudalis (PnC) nuclei specifically suppress PS (Jouvet, 1962; Carli and Zanchetti, 1965; Sastre et al., 1981; Webster and Jones, 1988), indicating that these nuclei contain the neurons responsible for PS onset and maintenance.
The reciprocal role of the monoaminergic PS-off and cholinergic PS-on neurons In the 1960s and 1970s, following the introduction of histochemical methods to localize the cholinergic and monoaminergic neurons, that of drugs specifically increasing or decreasing the action of their neurotransmitters and
NEUROCHEMISTRY OF SLEEP: AN OVERVIEW OF ANIMAL EXPERIMENTAL WORK the development of electrophysiological methods allowing the recordings of the single unit activity of neurons, Jouvet and his colleagues, in parallel with several other teams in the world, reached the conclusion that the onset of PS is due to a reciprocal interaction between monoaminergic and cholinergic neurons (Jouvet, 1969, 1975). Jouvet (1962) was the first to demonstrate that cholinergic mechanisms play a major role in PS generation since peripheral atropine administration suppressed PS, whereas anticholinesterase compounds increase PS. Then, George et al. (1964) discovered that bilateral injections of carbachol, a cholinergic agonist, into the PnO and PnC promote PS. It was later shown that PS is induced with the shortest latency when carbachol is injected in a small area of the dorsal PnO and PnC (Vanni-Mercier et al., 1989; Lai and Siegel, 1990; Yamamoto et al., 1990; Baghdoyan, 1997; Garzon et al., 1998), named peri-locus coeruleus a (peri-LCa) by Sakai et al. (1979, 1981). Sakai and coworkers from Jouvet’s laboratory (Sakai et al., 1981, 2001; Sakai, 1985; Sakai and Koyama, 1996) found that the great majority of the pontine neurons with a tonic activity specific during PS (PS-on neurons) were localized in the peri-LCa. They divided these neurons into two populations (Sakai and Koyama, 1996): the first population of neurons are: (1) located in the dorsal and rostral peri-LCa; (2) inhibited by carbachol, a cholinergic agonist; and (3) project rostrally to the intralaminar thalamic nuclei of the thalamus, the posterior hypothalamus, and the basal forebrain. The second population of PS-on neurons are: (1) excited by carbachol; (2) distributed in all parts of the peri-LCa; and (3) project caudally to the nucleus reticularis magnocellularis (Mc) localized in the ventromedial bulbar reticular formation (Sakai et al., 1979, 1981). Based on these and other results, it has been proposed that the first type of neurons are cholinergic and responsible for cortical activation during PS, whereas the second type of neurons are glutamatergic and generate the muscle atonia observed during this sleep state via descending excitatory projection to glycinergic pre-motoneurons within the Mc (Luppi et al., 1988; Chase et al., 1989; Fort et al., 1990, 1993; Jones, 1991b; Sakai and Koyama, 1996; Sakai et al., 2001). Supporting this hypothesis, the great majority of the neurons in the peri-LCa projecting to the Mc are not cholinergic (Luppi et al., 1988), glutamate release in the Mc increases specifically during PS (Kodama et al., 1998), and injection of non-N-methyl-Daspartic acid (NMDA) glutamate agonists in the Mc suppresses muscle tone (Lai and Siegel, 1991). In addition, spinal-projecting PS-on neurons have been recorded in the Mc (Siegel et al., 1979) and cytotoxic lesion of this structure induced a decrease in PS quantities and an increase in muscle tone during PS (Holmes and Jones, 1994). Further, intracellular recordings of motoneurons combined with strychnine applications demonstrated that
177
glycine is responsible for the tonic hyperpolarization of the spinal, hypoglossal, and trigeminal motoneurons (Chase et al., 1989; Soja et al., 1991; Kohlmeier et al., 1996; Yamuy et al., 1999) and we have shown that the Mc contains a large contingent of glycinergic neurons (Fort et al., 1990, 1993; Rampon et al., 1996a). These glycinergic neurons directly project to spinal motoneurons (Holstege and Bongers, 1991) while those of the parvocellular and parvocellular alpha nuclei directly project to the trigeminal motor nucleus (Li et al., 1996; Rampon et al., 1996b). The release of glycine and GABA is increased in the spinal cord and the hypoglossal motor nucleus during atonia induced by cholinergic stimulation of the peri-LCa (Kodama et al., 2003). In addition, we have shown that glycinergic neurons from these nuclei express Fos after the induction of PS (Boissard et al., 2002). Moreover, following induction of PS by carbachol injections in the peri-LCa, c-Fosþ cells in the Mc have been shown to project to the trigeminal motor nucleus (Morales et al., 1999). On the other hand, a number of results indicated that the onset of PS was due to a reciprocal inhibitory interaction between the PS-on neurons and monoaminergic PS-off neurons. McCarley and Hobson (1975) were the first to draw in detail this hypothesis in the mid-1970s. They were followed by Sakai et al. (1981), who proposed a slightly revised model. This wellaccepted hypothesis was formulated following the findings that serotonergic neurons from the raphe nuclei and noradrenergic neurons from the LC cease firing specifically during PS, i.e., have a mirror activity to PS-on neurons (Hobson et al., 1975; McGinty and Harper, 1976; Aston-Jones and Bloom, 1981; Aghajanian and VanderMaelen, 1982). Supporting this theory, drugs enhancing serotonin and noradrenergic transmission – in particular, monoamine oxidase inhibitors and serotonin and norepinephrine reuptake blockers – specifically suppress PS (Jouvet, 1969; Jones, 1991b; Gervasoni et al., 2002). However, the sites where the monoamines, and, in particular serotonin, exert their PS-suppressing effect remain to be unambiguously identified. Indeed, applications of norepinephrine, epinephrine, or benoxathian (an a2-agonist) into the peri-LCa inhibit PS but that of serotonin has no effect (Tononi et al., 1991; Crochet and Sakai, 1999a, b). In addition, norepinephrine via a2-adrenoceptor inhibits the noncholinergic PS-on neurons but has no effect on the cholinergic PS-on neurons from the peri-LCa while serotonin has no effect on both types of neurons (Sakai and Koyama, 1996). Monoamines could also act on PS-on neurons localized in other structures than the peri-LCa, like the Mc (Luppi et al., 1988) or the PPT and LDT (Horner and Kubin, 1999). The PPT and LDT have indeed been reported to contain PS-on neurons,
178
P.-H. LUPPI AND P. FORT
although the great majority of the neurons from these nuclei are tonically active both during W and PS (Kayama et al., 1992; Datta and Hobson, 1994; Datta et al., 2001; Datta and Siwek, 2002). In conclusion, a large number of data supports the hypothesis that the onset and maintenance of PS are due to reciprocal inhibitory interactions between PSon neurons and PS-off monoaminergic neurons. However, we have obtained results in rats indicating that GABAergic and glutamatergic neurons might be more important players than cholinergic and monoaminergic neurons. These results were obtained with a new model combining single-unit recordings, precise and limited local pharmacology by microiontophoresis in unanesthetized head-restrained rats, and anterograde and retrograde tracing combined with c-Fos labeling and neurochemical identification of labeled cells (Darracq et al., 1996; Gervasoni et al., 1998, 2000; Boissard et al., 2002, 2003). In the following, we detail these results and propose a new theory on the neuronal network responsible for PS.
The discovery that a population of GABAergic neurons gate PS onset We found that a long-lasting PS-like hypersomnia can be pharmacologically induced with a short latency in the head-restrained rats by iontophoretic applications of bicuculline or gabazine, two GABAA receptor antagonists specifically into a very small area of the dorsolateral pontine tegmentum (Boissard et al., 2002). We also recorded neurons in this region specifically active during PS and excited by bicuculline or gabazine iontophoresis (Boissard et al., 2000). This region has been denominated the sublaterodorsal nucleus (SLD) by Swanson (1998). It approximately corresponds to the dorsal subcoeruleus nucleus in Paxinos and Watson’s (1997) atlas and seems to be the equivalent in rats of the cat peri-LCa. Our results have been more recently reproduced in freely moving rats (Pollock and Mistlberger, 2003; Sanford et al., 2003) and are in agreement with a study in cats showing that pressure injection of bicuculline and to a lesser extent phaclofen (a GABAB receptor antagonist) in the dorsal portion of the nucleus PnO (which roughly corresponds to the peri-LCa) induces a strong increase in PS quantities with short latencies, whereas the application of muscimol (a GABAA agonist) or baclofen (a GABAB agonist) induced W (Xi et al., 1999, 2001). It has been further shown that the microinjection of scopolamine (a muscarinic receptor antagonist) did not block the induction of PS by bicuculline (Xi et al., 2004), indicating that the effect is not mediated by acetylcholine. These and our data imply that the onset of PS-on neurons of the SLD is mainly due to the removal of a tonic
GABAergic input present during W and SWS. Combining retrograde tracing with cholera toxin B subunit (CTb) and GAD immunostaining, we tried to identify the GABAergic neurons at the origin of this input (Boissard et al., 2003). Our results suggest that the GABAergic innervation of SLD neurons arises both from interneurons and distant neurons located in the pontine and deep mesencephalic reticular nuclei and to a minor extent hypothalamic and medullary structures (Boissard et al., 2003). These results are in agreement with previous studies indicating that the GABAergic neurons responsible for the tonic inhibition present during W and SWS of the PS-on neurons from the SLD could be within the SLD itself and/or in the pontine and deep mesencephalic reticular nuclei. A study by Xi et al. (1999) indeed suggested that GABAergic interneurons might be the best candidates for the inhibition of PS-on SLD neurons. They found in cats that administration of antisense oligonucleotides against GAD mRNA in the peri-LCa, produces a significant decrease in W and an increase in PS. On the other hand, Maloney et al. (2000) found in rats that the number of c-Fosþ GABAergic neurons in the rostral pontine reticular nucleus decreased following PS rebound, suggesting that they are active during W and SWS and inactive during PS. Finally, it has been shown in cats (Sastre et al., 1996, 2000) and rats (Boissard et al., 2000) that muscimol injections in the most ventrolateral part of the periaqueductal gray and in the region of the deep mesencephalic reticular nucleus just ventral to it induce a strong increase in PS quantities. More recently, Sakai et al. (2001) reported that muscimol applications limited to the region of the deep mesencephalic reticular nucleus just ventral to the periaqueductal gray induced an increase in PS quantities while those in the ventrolateral periaqueductal gray had no effect. We reported a strong non-GABAergic projection to the SLD from the ventrolateral periaqueductal gray and a mixed GABAergic and non-GABAergic projection from the deep mesencephalic reticular nucleus just ventral to the periaqueductal gray (Boissard et al., 2003). Altogether, we propose that GABAergic neurons located in the most dorsal part of the deep mesencephalic reticular nucleus, the pontine reticular nucleus, and/or in the SLD itself project to and directly inhibit the PS-on neurons from the SLD specifically during W and SWS.
Glutamatergic neurons tonically excite PS-on neurons of the SLD during all vigilance states We have shown that kainic acid (a glutamate agonist) iontophoretic application into the SLD induces an activation of PS-on neurons and is consistently associated
NEUROCHEMISTRY OF SLEEP: AN OVERVIEW OF ANIMAL EXPERIMENTAL WORK with the induction of a PS-like state (Boissard et al., 2002). Further, the PS-like state induced by bicuculline iontophoresis in the SLD was reversed by the application of kynurenate (Boissard et al., 2002). In agreement with our results, it has been shown in cats that the administration of kainic acid in the peri-LCa using microdialysis induces a PS-like state (Onoe and Sakai, 1995). Altogether these results suggest that PS-on neurons in the SLD receive a tonic glutamatergic input during all sleep–waking states. They further suggest that, following the removal of the tonic GABAergic input at the onset of PS, the unmasked glutamatergic input would be responsible for the tonic activity of the SLD PS-on neurons. The glutamatergic neurons providing a constant excitatory input to SLD PS-on neurons should be located in the brainstem, although forebrain glutamatergic neurons could also participate. Indeed, a PS-like state persists in the “pontine cat,” indicating that the structures responsible for the onset and maintenance of PS are restricted to the brainstem (Jouvet, 1962). Such glutamatergic inputs can arise from the numerous non-GABAergic neurons projecting to the SLD localized in the ventrolateral periaqueductal gray, the mesencephalic, pontine, and parvocellular reticular nuclei. Additional studies are necessary to determine which one of these structures provides a glutamatergic input to the SLD PS-on neurons. The afferents to the SLD from the primary motor area of the frontal cortex, the bed nucleus of the stria terminalis, and central nucleus of the amygdala could also participate in the activation of the SLD PS-on neurons. Indeed, descending pyramidal cortical cells are known to be glutamatergic. In addition, Maquet et al. (1996) found that regional cerebral blood flow is positively correlated with PS in the amygdaloid complex. Furthermore, electrical stimulation of the central nucleus of the amygdala increases the frequency of pontine waves recorded in or just dorsal to the SLD during PS (Deboer et al., 1998). From these and our results, it might be hypothesized that the frontal cortex and the central nucleus of the amygdala and the functionally related bed nucleus of the stria terminalis provide excitatory glutamatergic projections to PS-on neurons from the SLD.
179
indicate important species differences between rats and cats in the pharmacological sensitivity of the pontine PS-on neurons. In agreement with our results, following carbachol administration into the rat pontine reticular formation, the enhancement of PS was of small magnitude (Gnadt and Pegram, 1986; Shiromani and Fishbein, 1986; Velazquez-Moctezuma et al., 1989; Bourgin et al., 1995) or not reliably obtained (Deurveilher et al., 1997). In cats, however, PS is induced almost immediately after the carbachol injection and the episodes last longer than in control PS. The effective sites in rats were widely distributed in the pontine reticular formation. In contrast, the most effective site in cats is the peri-LCa that corresponds to the rat SLD (Vanni-Mercier et al., 1989). The absence of effect of carbachol ejection in the SLD does not rule out a role of cholinergic processes in PS onset and maintenance in the rat. It is indeed possible that PS-on neurons in the SLD have muscarinic and/or nicotinic receptors, but that the activation of these receptors by carbachol is unable to modify their activity due to the strong GABAergic tonic inhibition revealed in our study. Supporting this hypothesis, it has been shown that carbachol applications in the region of the SLD are able to induce with a short latency a long period of atonia in anesthetized or decerebrate rat models (Taguchi et al., 1992; Fenik et al., 1999) in which the GABAergic inhibitory tone on SLD neurons could be decreased or even absent. Another possibility is that the cholinergic system plays an important role in PS in rats via an action on populations of neurons controlling PS localized in pontine regions other than the SLD. Supporting this idea, a strong enhancement in PS quantities was found following carbachol pressure ejection in the most ventral part of the oral pontine reticular formation (De Andres et al., 1985; Garzon et al., 1998). Besides, an increase in the number of PPT and LDT cholinergic neurons containing Fos has been observed following PS recovery (Maloney et al., 1999), although in our study reproducing these experiments, we observed only occasional c-Fosþ cholinergic neurons in the PPT and LDT (Verret et al., 2005). In addition, knockout mice for M2 and M4 muscarinic receptors displayed no change in PS while M3 knockout mice showed only a small decrease in PS quantities (Goutagny et al., 2005a).
Evidence that acetylcholine does not play a crucial role in the activation of the PS executive neurons localized in the SLD
Evidence that GABAergic neurons are responsible for the inactivation of monoaminergic neurons during PS
We found that carbachol iontophoresis into the rat SLD induced a W state with increased muscle activity and that SLD PS-on neurons do not respond to carbachol iontophoresis (Boissard et al., 2002). These results
According to the classical “reciprocal interaction” model (McCarley and Hobson, 1975; Sakai et al., 1981), the cessation of firing of the noradrenergic and serotonergic neurons at the onset of PS is the result
180
P.-H. LUPPI AND P. FORT
of active PS-specific inhibitory processes originating from PS-on cells. These neurons were first hypothesized to be cholinergic and localized in the peri-LCa LDT and PPT. However, acetylcholine excites LC noradrenergic neurons and is only weakly inhibitory on serotonergic dorsal raphe nucleus (DRN) neurons (Guyenet and Aghajanian, 1979; Koyama and Kayama, 1993). It has therefore been suggested that GABA or glycine, rather than acetylcholine, might be used as an inhibitory neurotransmitter (Jones, 1991a; Luppi et al., 1991). To test this hypothesis we determined the effect of iontophoretic applications of bicuculline and gabazine (two GABAA antagonists) and strychnine (a glycine antagonist) during W, SWS, and PS on the activity of LC noradrenergic and DRN serotonergic cells in the head-restrained unanesthetized rat (Darracq et al., 1996; Gervasoni et al., 1998, 2000). Iontophoretic application of bicuculline, gabazine, or strychnine during SWS or PS induced a tonic firing in LC noradrenergic and DRN serotonergic neurons (Darracq et al., 1996; Gervasoni et al., 1998, 2000). In addition, application of these antagonists during W induced a sustained increase in discharge rate. These results indicate the existence of tonic GABA and glycinergic inputs to the LC and DRN that are active during all vigilance states. Importantly, we found that when the strychnine effect occurred during transitions between PS and W, the discharge rate of the LC or DRN neurons further increased at the onset of W. In contrast, in the same situation but after bicuculline administration, the discharge rate of a given neuron was unchanged at the transition between PS and W. These results strongly suggest that the release of GABA but not that of glycine is responsible for the inactivation of LC noradrenergic and DRN serotonergic neurons during PS. At variance with our results, Levine and Jacobs (1992) found in cats that the iontophoretic application of bicuculline reversed the typical suppression of neuronal activity of DRN serotonergic neurons during SWS but not during PS. In addition, Sakai and Crochet (2000) did not find in cats an effect of bicuculline microdialysis infusion on DRN serotonergic neurons during PS and hypothesized that our results were due to a nonspecific excitatory action of bicuculline. This is unlikely since we reproduced the effect of bicuculline with gabazine, another specific GABAA antagonist (unpublished results). Further, our results are supported by those of Nitz and Siegel (1997a, b), who found in cats with the microdialysis technique a significant increase in GABA release in the DRN and LC during PS as compared to W and SWS and, in contrast, no detectable changes in glycine concentrations. Based on these and our results, we therefore suggest that, during W, the LC and DRN
cells are under a tonic GABAergic inhibition which increases during SWS and even further during PS, and that the increase in GABAergic inhibition is responsible for the inactivation of these neurons during the sleep states. In contrast, glycinergic tonic inhibition would be constant across the sleep–waking cycle and, thus, control the general excitability of LC and DRN neurons. Our results obtained with double-staining experiments indicate that the LC and DRN receive GABAergic inputs from neurons located in a large number of distant regions from the forebrain to the medulla (Luppi et al., 1999; Gervasoni et al., 2000). Indeed, we observed a substantial number of GAD-immunoreactive neurons in the POA, the lateral hypothalamic area, the mesencephalic and pontine periaqueductal gray, and the dorsal paragigantocellular reticular nucleus that project to the LC and DRN (Luppi et al., 1999; Gervasoni et al., 2000). Based on physiological and electrophysiological data (see above), we expect that one or several of these GABAergic afferents are “turned on” specifically at the onset of and during PS episodes and are responsible for the inhibition of brainstem monoaminergic neurons during PS. Although it has been proposed that GABAergic neurons located in the extended VLPO might also be involved (Lu et al., 2002), previous results highly suggest that brainstem GABAergic neurons are mostly responsible. Indeed, it is well known that PS-like episodes occur in pontine or decerebrate cats (Jouvet, 1972). Moreover, it has been shown in decerebrate animals that PS episodes induced by carbachol injections in the pons are still associated with a cessation of activity of serotonergic neurons of the raphe obscurus and pallidus nuclei (Woch et al., 1996). Among the brainstem GABAergic afferents revealed in our study, several are common to the DRN and the LC and are therefore good candidates for this role. We observed substantial GABAergic projections to the LC and DRN from the ventrolateral periaqueductal gray and the dorsal paragigantocellular nucleus (Luppi et al., 1999; Gervasoni et al., 2000). In agreement with these results, local application of bicuculline blocked the dorsal paragigantocellular-evoked inhibition of LC neurons (Ennis and Aston-Jones, 1989) and focal iontophoretic application of NMDA in the ventral periaqueductal gray induced bicuculline-sensitive inhibitory postsynaptic potentials in DRN serotonergic neurons (Liu et al., 2000). The hypothesis that the GABAergic inhibition is coming from neurons located in the periaqueductal gray is further supported by two studies. Yamuy et al. (1995) showed that, after a long period of PS induced by pontine injection of carbachol, a large number of Fos-positive cells are visible
NEUROCHEMISTRY OF SLEEP: AN OVERVIEW OF ANIMAL EXPERIMENTAL WORK 181 in the DRN and a region lateral to it. Moreover, immunoreactive to choline acetyltransferase (Verret Maloney et al. (1999) observed after a PS rebound et al., 2005). These findings demonstrate that many induced by deprivation, an increase in c-Fosþ GADbrainstem structures not previously identified contain immunoreactive neurons in the periaqueductal gray. neurons active during PS and may therefore play a To determine directly among the GABAergic afferkey role during this state. Among them, the posterior ents to the LC those active during PS, we combined hypothalamus particularly retained our attention since iontophoretic application of CTb in the LC with c-Fos a number of studies indicate that it plays an important staining in rats deprived of PS, rats with enhanced role in sleep–wake control. PS during rebound after PS deprivation, and control rats. Using this method, we observed a large number Role of the posterior hypothalamus of CTb and c-Fos double-immunostained neurons in in PS control the dorsal paragigantocellular reticular nucleus and a A large body of data indicates that the posterior hyposubstantial number in the ventrolateral periaqueductal thalamus plays a crucial role in vigilance state regulagray and the lateral paragigantocellular reticular tion. First, von Economo (1926) reported that posterior nucleus specifically after PS rebound (Verret et al., hypothalamic and midbrain junction lesions resulted in 2003; Verret et al., 2006). From these results, we prosleepiness. From these data, he predicted that the postepose that the GABAergic neurons responsible for the rior hypothalamus contains neurons that promote wakeinhibition of the LC noradrenergic neurons during fulness. In subsequent years, studies in monkeys PS are mainly, but not exclusively, localized in the (Ranson, 1939), rats (Nauta, 1946), and cats (Swett and dorsal paragigantocellular reticular nucleus. To test Hobson, 1968) reproduced his results with electrolytic this hypothesis further, we recorded the spontaneous lesions of the posterior hypothalamus. Then, sleepiness activity of neurons from the dorsal paragigantocelluwas obtained after ibotenic acid lesion (Swett and Hoblar reticular nucleus across the sleep–waking cycle in son, 1968; Sallanon et al., 1988) or inactivation by local head-restrained rats. Neurons with an activity specific application of muscimol, a GABAA agonist, of the to PS (PS-on neurons) were found within this nucleus posterior hypothalamus neurons (Lin et al., 1989; Salla(Goutagny et al., 2008), further supporting that it non et al., 1989). Further, it was shown that the waking contains the GABAergic neurons responsible for the effect of modafinil and amphetamine is suppressed cessation of activity of the noradrenergic neurons of by the injection of muscimol in the cat posterior the LC during PS. This hypothesis is also supported hypothalamus (Lin et al., 1992, 1996). In agreement with by a study showing that electrical stimulation of the the above observations, Vanni-Mercier et al. (1984) area of the dorsal paragigantocellular reticular recorded neurons active only or mainly during waking nucleus induces an increase in PS quantities (Kaur in the posterior hypothalamus of the cat by extracellular et al., 2001). recordings. Looking carefully at the literature, additional obserEvidence that additional structures play vations indicated that the posterior hypothalamus also a role in PS control plays a role in PS regulation. Indeed, Jouvet and his colTo localize the structures involved in the onset and leagues demonstrated that in “pontine cats” (animals maintenance of PS, we compared the distribution of that lacked all brain structures rostral to the brainstem, c-Fosþ neurons in the brainstem of control rats, rats including the posterior hypothalamus), a PS-like state selectively deprived of PS for approximately 72 hours, still occurred, indicating that the brainstem is sufficient and rats allowed to recover from such deprivation to induce PS; however, the PS recovery following PS (Verret et al., 2003, 2005, 2006). A large number of sleep deprivation was abolished in these animals (Jouvet, c-Fosþ cells positively correlated with the percentage 1988). These results suggested that the brainstem conof time spent in PS was observed in the structures tains the structures responsible for PS but not those described above as containing neurons implicated in responsible for its homeostatic regulation. In support the genesis of PS such as the laterodorsal tegmental of these observations, several studies mentioned that nuclei, sublaterodorsal, alpha and ventral gigantocellu9–15% of neurons recorded in the posterior hypothalalar reticular nuclei. In addition, a large number of mus were specifically active during PS (Steininger c-Fosþ cells were seen after PS rebound in the posteet al., 1999; Alam et al., 2002; Koyama et al., 2003). rior hypothalamus, lateral, ventrolateral and dorsal Recent data presented below revealed that two populaperiaqueductal gray, dorsal and lateral paragigantoceltions of intermingled peptidergic neurons located in lular reticular nuclei, and the nucleus raphe obscurus. the lateral hypothalamic area and the perifornical Interestingly, half of the cells in the latter nucleus were nucleus play an antagonistic role in PS control.
182
P.-H. LUPPI AND P. FORT
The hypocretin (orexin) neuronal population It has been shown that narcolepsy, a sleep disorder characterized by excessive daytime sleepiness and cataplexy, is due to the lack of hypocretin mRNA and peptides in humans (Peyron et al., 2000) or a disruption of the hypocretin receptor 2 or its ligand in dogs and mice (Chemelli et al., 1999; Lin et al., 1999). Hypocretin neurons are localized exclusively in the dorsomedial, lateral, and perifornical hypothalamic areas (Peyron et al., 1998).The hypocretins are two peptides, Hcrt-1 (orexin-A) and Hcrt-2 (orexin-B), generated from a single preprohypocretin and synthesized by a small number of neurons restricted to the perifornical area of the posterior hypothalamus (de Lecea et al., 1998; Peyron et al., 1998; Sakurai et al., 1998). Axons from these neurons are found in the hypothalamus, (LC), raphe nuclei, TMN, midline thalamus, all levels of spinal cord, sympathetic and parasympathetic centers, and many other brain regions (Peyron et al., 1998; van den Pol, 1999). The two G protein-coupled receptors of the hypocretins (HcrtR-1 and HcrtR-2) (Sakurai et al., 1998) also show a widespread and heterogeneous pattern of expression throughout the central nervous system (Trivedi et al., 1998; Hervieu et al., 2001; Marcus et al., 2001). Interestingly, HcrtR-1 and HcrtR-2 are densely packed in monoaminergic and cholinergic nuclei involved in the regulation of sleep and wakefulness (Jones, 1993a). Thus, hypocretins may control vigilance by modulating the activity of monoaminergic and cholinergic neurons. Pharmacological studies indicate potent wake-promoting (þ160%) and PS (–68%) reduction effects following intracerebroventricular administration and local injections in the LC of Hcrt (Hagan et al., 1999; Bourgin et al., 2000). Furthermore, the arousing effect of Hcrt-1 when injected in the lateral ventricle is blocked by systemic injections of antagonist of the H1 histaminergic receptors (Yamanaka et al., 2002) and absent in H1 knockout mice (Huang et al., 2001). These data, together with the observation that in vitro Hcrt applications on rat brain slices strongly stimulate firing rate of the noradrenergic LC (Hagan et al., 1999; Horvath et al., 1999), dopaminergic ventral tegmental area (Nakamura et al., 2000), serotonergic dorsal raphe (Brown et al., 2001; Liu et al., 2002), and histaminergic tuberomammillary cells (Bayer et al., 2001; Eriksson et al., 2001), are consistent with a global stimulatory effect of Hcrt on monoaminergic tone to maintain wakefulness. It is also interesting to note that histaminergic neurons project to hypocretin neurons and hypocretin neurons have an excitatory
projection to all monoaminergic cell groups known to be implicated in the regulation of wake. It is therefore likely that monoaminergic and hypocretinergic systems work in concert during wakefulness, with partial specialization. It has also been shown that Hcrt cells are c-Fosþ after a period of natural or pharmacologically induced waking by treatment with stimulants such as amphetamine or modafinil. In contrast, they are not c-Fosþ after PS rebound, indicating that Hcrt neurons are inactive during PS (Torterolo et al., 2003; Verret et al., 2003). Consistent with these observations, it has been shown by continuous microdialysis or cerebrospinal fluid puncture through 24 hours that the level of Hcrt released in situ or in the cerebrospinal fluid is higher during the active period than the quiet period in the rat (Yoshida et al., 2001) and in monkeys (Zeitzer et al., 2003). Further, it has been shown that Hcrt cells are silent during SWS and tonic periods of PS, with occasional burst discharge in phasic PS. Hcrt cells discharge in active waking and have moderate and approximately equal levels of activity during grooming and eating and maximal activity during exploratory behavior (Lee et al., 2005; Mileykovskiy et al., 2005). The cessation of activity of Hcrt cells during sleep is likely due, like the monoaminergic neurons (see above), to a tonic GABAergic inhibition. Indeed, local application of bicuculline in the perifornical region induces waking and c-Fos labeling of the hypocretin but not of the intermingled melaninconcentrating hormone-containing (MCH) neurons (Alam et al., 2005; Goutagny et al., 2005b).
The MCH peptidergic neuronal population In our study (Verret et al., 2003), we showed that the MCH neurons located in the lateral hypothalamic area and the perifornical nucleus of the posterior hypothalamus are implicated in PS regulation. First, we found the presence of a very large number of c-Fosþ neurons in the entire posterior hypothalamus after a 3-hour PS rebound (PSR) consecutive to a 72-hour specific PS deprivation. The largest number of c-Fosþ neurons in PSR condition was localized in the lateral hypothalamic area. In the PSR condition, the MCHþ/c-Fosþ neurons made up for 76% of the c-Fosþ neurons localized in the perifornical area, 60% of the c-Fosþ neurons in the lateral hypothalamic area, and 34% of the c-Fosþ neurons in the rostral zona incerta. In all, 58% of the MCH neurons counted were immunoreactive to c-Fos. Our results suggest that MCH neurons, and also other unidentified neuronal populations of neurons intermingled with them or localized in adjacent
NEUROCHEMISTRY OF SLEEP: AN OVERVIEW OF ANIMAL EXPERIMENTAL WORK structures, like the dorsal hypothalamic area, are specifically and strongly active during PS. They are in agreement with electrophysiological studies showing the presence of neurons strongly active during PS in the posterior hypothalamus (Steininger et al., 1999; Alam et al., 2002; Koyama et al., 2003, Goutagny et al., 2005b). Altogether, our results indicate that MCH neurons are specifically active during PS. To determine the role of MCH in PS regulation and that MCH neurons play a role in the homeostasis of PS, we studied the effect of intracerebroventricular administrations of MCH. We found that injections of 0.2, 1, and 5 g induce a dose-dependent increase in PS and, to a minor extent, SWS quantities. This increase in PS quantities was due to an increase in the number of bouts of PS but not of their duration. To a minor extent, a higher quantity of SWS was also observed after MCH administration. Since MCH neurons are active during PS and MCH is rather an inhibitory peptide coexpressed with GABA (Gao and van den Pol, 2001), we can propose that MCH neurons promote PS indirectly by inhibiting neurons, themselves inhibiting the PS executive neurons during W and SWS. The monoaminergic neurons in the brainstem, the histaminergic neurons in the caudal hypothalamus, and the hypocretin neurons all belong to this category. They are active during W, decrease or nearly cease their activity during SWS, and are silent during PS (Gervasoni et al., 1998, 2000; Steininger et al., 1999; Lee et al., 2005; Mileykovskiy et al., 2005). Further, based on electron and photonic microscopy observations, it has been shown that MCH and hypocretin neurons are interconnected (Bayer et al., 2002; Guan et al., 2002). We therefore propose that MCH neurons primarily modulate SWS and PS quantities via an inhibitory action on the intermingled hypocretin neurons. In previous studies, we showed that GABA tonically inhibits the pontine PS executive neurons localized in the SLD (Boissard et al., 2002). Further, we localized in the pontomesencephalic reticular formation the GABAergic neurons potentially responsible for this inhibition (Boissard et al., 2003). We can then also propose that the increase of PS induced by MCH could therefore also be due to a direct inhibition of these GABAergic neurons of the pontomesencephalic reticular formation and that hypocretin neurons, that also project to this area, would be excitatory on these GABAergic neurons and, by this means, would prevent PS.
183
CONCLUSION: A NEW NETWORK MODEL FOR PS ONSET AND MAINTENANCE (FIGURE 11.2) In conclusion, based on our results, we propose that the onset and maintenance of PS are due to the activation of PS-on glutamatergic neurons from the SLD. During W and SWS, they would be hyperpolarized by tonic GABAergic inputs arising from GABAergic PSoff neurons localized in the SLD itself and the deep mesencephalic and pontine reticular nuclei. Noradrenergic and serotonergic PS-off neurons would also participate in the hyperpolarization of SLD neurons, particularly during W. The cessation of activity of the monoaminergic neurons at the onset of and during PS would be due to an active inhibition by PS-on GABAergic neurons localized in the dorsal paragigantocellular reticular nucleus and the ventrolateral periaqueductal gray. Although the exact mechanism of the cessation of activity of the GABAergic PS-off neurons remains to be identified, we propose that the GABAergic PS-on neurons inhibiting the monoaminergic neurons could, at the same time, inhibit the GABAergic PS-off neurons. The activation of the SLD PS-on neurons at the onset of PS would be due to the strong glutamatergic excitatory input present during all vigilance states blocked during W and SWS by the inhibitory inputs from the GABAergic and monoaminergic PS-off neurons. It would arise from one or several of the nonGABAergic brainstem afferents to the SLD (e.g., the periaqueductal gray, the deep mesencephalic and pontine reticular nuclei, and the parvocellular reticular nucleus). Ascending SLD PS-on glutamatergic neurons would induce cortical activation via their projections to intralaminar thalamic relay neurons in collaboration with W/PS-on cholinergic and glutamatergic neurons from the LDT and PPT, mesencephalic and pontine reticular nuclei, and the basal forebrain. Descending PS-on glutamatergic SLD neurons would induce muscle atonia via their excitatory projections to glycinergic pre-motoneurons localized in the medulary reticular nuclei.
ACKNOWLEDGMENTS This work was supported by CNRS UMR 5167 and Universite´ Claude Bernard Lyon 1.
184
P.-H. LUPPI AND P. FORT
vIPAG DRN DpMe LC
Hcrt
DPGi
MCH
SLD Giv
VLPO
Glycinergic pathways GABAergic or monoaminergic pathways Glutamatergic, cholinergic or Hcrt (hypocretin) pathways
Spinal motoneurons
Fig. 11.2. Model of the network responsible for paradoxical sleep onset and maintenance. DPGi, dorsal paragigantocellular reticular nucleus; DpMe, deep mesencephalic reticular nucleus; DRN, dorsal raphe nucleus; GiV, ventral gigantocellular reticular nucleus; Hcrt, hypocretin (orexin) neurons; LC, locus coeruleus; MCH, MCH-containing neurons; vlPAG, ventrolateral periaqueductal gray; VLPO, ventrolateral preoptic nucleus; SLD, sublaterodorsal nucleus.
REFERENCES Aghajanian GK, VanderMaelen CP (1982). Intracellular identification of central noradrenergic and serotonergic neurons by a new double labeling procedure. J Neurosci 2: 1786–1792. Airaksinen MS, Alanen S, Szabat E et al. (1992). Multiple neurotransmitters in the tuberomammillary nucleus: comparison of rat, mouse, and guinea pig. J Comp Neurol 323: 103–116. Alam MN, Gong H, Alam T et al. (2002). Sleep–waking discharge patterns of neurons recorded in the rat perifornical lateral hypothalamic area. J Physiol 538: 619–631. Alam MN, Kumar S, Bashir T et al. (2005). GABA-mediated control of hypocretin- but not melanin-concentrating hormone-immunoreactive neurones during sleep in rats. J Physiol 563: 569–582. Aserinsky E, Kleitman N (1953). Regularly occurring periods of eye motility and concomitant phenomena during sleep. Science 118: 273–274. Aston-Jones G, Bloom FE (1981). Activity of norepinephrinecontaining locus coeruleus neurons in behaving rats anticipates fluctuations in the sleep–waking cycle. J Neurosci 1: 876–886. Baghdoyan HA (1997). Cholinergic mechanisms regulating REM sleep. In: WJ Schwartz (Ed.), Sleep Science: Integrating Basic Research and Clinical Practice. S. Karger, Basel, pp. 88–116. Barnes NM, Sharp T (1999). A review of central 5-HT receptors and their function. Neuropharmacology JID 0236217 38: 1083–1152. Basheer R, Porkka-Heiskanen T, Stenberg D et al. (1999). Adenosine and behavioral state control: adenosine increases c-Fos protein and AP1 binding in basal forebrain of rats. Brain Res Mol Brain Res JID - 8908640 73: 1–10.
Bayer L, Eggermann E, Serafin M et al. (2001). Orexins (hypocretins) directly excite tuberomammillary neurons. Eur J Neurosci 14: 1571–1575. Bayer L, Mairet-Coello G, Risold PY et al. (2002). Orexin/ hypocretin neurons: chemical phenotype and possible interactions with melanin-concentrating hormone neurons. Regul Pept 104: 33–39. Benington JH, Kodali SK, Heller HC (1995). Stimulation of A1 adenosine receptors mimics the electroencephalographic effects of sleep deprivation. Brain Res JID - 0045503 692: 79–85. Boissard R, Gervasoni D, Fort P et al. (2000). Neuronal networks responsible for paradoxical sleep onset and maintenance in rats: a new hypothesis. Sleep 23 (Suppl): 107. Boissard R, Gervasoni D, Schmidt MH et al. (2002). The rat ponto-medullary network responsible for paradoxical sleep onset and maintenance: a combined microinjection and functional neuroanatomical study. Eur J Neurosci 16: 1959–1973. Boissard R, Fort P, Gervasoni D et al. (2003). Localization of the GABAergic and non-GABAergic neurons projecting to the sublaterodorsal nucleus and potentially gating paradoxical sleep onset. Eur J Neurosci 18: 1627–1639. Borbely AA (1982). A two process model of sleep regulation. Hum Neurobiol 1: 195–204. Borbely AA (2001). From slow waves to sleep homeostasis: new perspectives. Arch Ital Biol 139: 53–61. Bourgin P, Escourrou P, Gaultier C et al. (1995). Induction of rapid eye movement sleep by carbachol infusion into the pontine reticular formation in the rat. Neuroreport 6: 532–536. Bourgin P, Huitron-Resendiz S, Spier AD et al. (2000). Hypocretin-1 modulates rapid eye movement sleep
NEUROCHEMISTRY OF SLEEP: AN OVERVIEW OF ANIMAL EXPERIMENTAL WORK through activation of locus coeruleus neurons. J Neurosci 20: 7760–7765. Brown RE, Sergeeva O, Eriksson KS et al. (2001). Orexin A excites serotonergic neurons in the dorsal raphe nucleus of the rat. Neuropharmacology 40: 457–459. Carli G, Zanchetti A (1965). A study of pontine lesions suppressing deep sleep in the cat. Arch Ital Biol 103: 751–788. Chase MH, Soja PJ, Morales FR (1989). Evidence that glycine mediates the postsynaptic potentials that inhibit lumbar motoneurons during the atonia of active sleep. J Neurosci 9: 743–751. Chemelli RM, Willie JT, Sinton CM et al. (1999). Narcolepsy in orexin knockout mice: molecular genetics of sleep regulation. Cell 98: 437–451. Chou TC, Bjorkum AA, Gaus SE et al. (2002). Afferents to the ventrolateral preoptic nucleus. J Neurosci 22: 977–990. Chou TC, Scammell TE, Gooley JJ et al. (2003). Critical role of dorsomedial hypothalamic nucleus in a wide range of behavioral circadian rhythms. J Neurosci 23: 10691–10702. Crochet S, Sakai K (1999a). Alpha-2 adrenoceptor mediated paradoxical (REM) sleep inhibition in the cat. Neuroreport 10: 2199–2204. Crochet S, Sakai K (1999b). Effects of microdialysis application of monoamines on the EEG and behavioural states in the cat mesopontine tegmentum. Eur J Neurosci 11: 3738–3752. Darracq L, Gervasoni D, Souliere F et al. (1996). Effect of strychnine on rat locus coeruleus neurones during sleep and wakefulness. Neuroreport 8: 351–355. Datta S, Hobson JA (1994). Neuronal activity in the caudolateral peribrachial pons: relationship to PGO waves and rapid eye movement. J Neurophysiol 71: 95–109. Datta S, Siwek DF (2002). Single cell activity patterns of pedunculopontine tegmentum neurons across the sleep– wake cycle in the freely moving rats. J Neurosci Res 70: 611–621. Datta S, Spoley EE, Patterson EH (2001). Microinjection of glutamate into the pedunculopontine tegmentum induces REM sleep and wakefulness in the rat. Am J Physiol Regul Integr Comp Physiol 280: 752–759. De Andres I, Gomez-Montoya J, Gutierrez-Rivas E et al. (1985). Differential action upon sleep states of ventrolateral and central areas of pontine tegmental field. Arch Ital Biol 123: 1–11. Deboer T, Sanford LD, Ross RJ et al. (1998). Effects of electrical stimulation in the amygdala on ponto-geniculooccipital waves in rats. Brain Res 793: 305–310. de Lecea L, Kilduff TS, Peyron C et al. (1998). The hypocretins: hypothalamus-specific peptides with neuroexcitatory activity. Proc Natl Acad Sci U S A 95: 322–327. Dement W, Kleitman N (1957). The relation of eye movements during sleep to dream activity: an objective method for the study of dreaming. J Exp Psychol Learn Mem Cogn 53: 339–346. Deurveilher S, Hars B, Hennevin E (1997). Pontine microinjection of carbachol does not reliably enhance paradoxical sleep in rats. Sleep 20: 593–607. Deurveilher S, Burns J, Semba K (2002). Indirect projections from the suprachiasmatic nucleus to the ventrolateral
185
preoptic nucleus: a dual tract-tracing study in rat. Eur J Neurosci 16: 1195–1213. Eggermann E, Serafin M, Bayer L et al. (2001). Orexins/ hypocretins excite basal forebrain cholinergic neurones. Neuroscience 108: 177–181. Ennis M, Aston-Jones G (1989). GABA-mediated inhibition of locus coeruleus from the dorsomedial rostral medulla. J Neurosci 9: 2973–2981. Eriksson KS, Sergeeva O, Brown RE et al. (2001). Orexin/ hypocretin excites the histaminergic neurons of the tuberomammillary nucleus. J Neurosci 21: 9273–9279. Fenik V, Ogawa H, Davies RO et al. (1999). Pontine carbachol produces a spectrum of REM sleep-like and arousallike electrocortical responses in urethane-anesthetized rats. Sleep Res Online 2 (Suppl): 30. Fort P, Luppi PH, Wenthold R et al. (1990). [Glycine immunoreactive neurons in the medulla oblongata in cats.] C R Acad Sci III 311: 205–212. Fort P, Luppi PH, Jouvet M (1993). Glycine-immunoreactive neurones in the cat brain stem reticular formation. Neuroreport 4: 1123–1126. Fort P, Gervasoni D, Peyron C et al. (1998). GABAergic projections to the magnocellular preoptic area and substantia innominata in the rat. Neurosci Abstr, 423. Gallopin T, Fort P, Eggermann E et al. (2000). Identification of sleep-promoting neurons in vitro. Nature 404: 992–995. Gallopin T, Luppi PH, Rambert FA et al. (2004). Effect of the wake-promoting agent modafinil on sleep-promoting neurons from the ventrolateral preoptic nucleus: an in vitro pharmacologic study. Sleep 27: 19–25. Gallopin T, Luppi PH, Cauli B et al. (2005). The endogenous somnogen adenosine excites a subset of sleep-promoting neurons via A2A receptors in the ventrolateral preoptic nucleus. Neuroscience 134: 1377–1390. Gao XB, van den Pol AN (2001). Melanin concentrating hormone depresses synaptic activity of glutamate and GABA neurons from rat lateral hypothalamus. J Physiol 533: 237–252. Garzon M, De Andres I, Reinoso-Suarez F (1998). Sleep patterns after carbachol delivery in the ventral oral pontine tegmentum of the cat. Neuroscience 83: 1137–1144. George R, Haslett WL, Jenden DJ (1964). A cholinergic mechanism in the brainstem reticular formation: induction of paradoxical sleep. Int J Neuropharmacol 3: 541–552. Gervasoni D, Darracq L, Fort P et al. (1998). Electrophysiological evidence that noradrenergic neurons of the rat locus coeruleus are tonically inhibited by GABA during sleep. Eur J Neurosci 10: 964–970. Gervasoni D, Peyron C, Rampon C et al. (2000). Role and origin of the GABAergic innervation of dorsal raphe serotonergic neurons. J Neurosci 20: 4217–4225. Gervasoni D, Panconi E, Henninot V et al. (2002). Effect of chronic treatment with milnacipran on sleep architecture in rats compared with paroxetine and imipramine. Pharmacol Biochem Behav 73: 557–563. Gnadt JW, Pegram GV (1986). Cholinergic brainstem mechanisms of REM sleep in the rat. Brain Res 384: 29–41.
186
P.-H. LUPPI AND P. FORT
Goutagny R, Comte JC, Salvert D et al. (2005a). Paradoxical sleep in mice lacking M(3) and M(2)/M(4) muscarinic receptors. Neuropsychobiology 52: 140–146. Goutagny R, Luppi PH, Salvert D et al. (2005b). GABAergic control of hypothalamic melanin-concentrating hormonecontaining neurons across the sleep–waking cycle. Neuroreport 16: 1069–1073. Goutagny R, Luppi PH, Salvert D et al. (2008). Role of the dorsal paragigantocellular reticular nucleus in paradoxical (rapid eye movment) sleep generation: a combined electrophysiological and anatomical study in the rat. Neuroscience 152: 849–857. Guan JL, Uehara K, Lu S et al. (2002). Reciprocal synaptic relationships between orexin- and melanin-concentrating hormone-containing neurons in the rat lateral hypothalamus: a novel circuit implicated in feeding regulation. Int J Obes Relat Metab Disord 26: 1523–1532. Guyenet PG, Aghajanian GK (1979). Ach, substance P and met-enkephalin in the locus coeruleus: pharmacological evidence for independent sites of action. Eur J Pharmacol 53: 319–328. Hagan JJ, Leslie RA, Patel S et al. (1999). Orexin A activates locus coeruleus cell firing and increases arousal in the rat. Proc Natl Acad Sci U S A 96: 10911–10916. Hervieu GJ, Cluderay JE, Harrison DC et al. (2001). Gene expression and protein distribution of the orexin-1 receptor in the rat brain and spinal cord. Neuroscience 103: 777–797. Hobson JA, Mccarley RW, Wyzinski PW (1975). Sleep cycle oscillation: reciprocal discharge by two brainstem neuronal groups. Science 189: 55–58. Holmes CJ, Jones BE (1994). Importance of cholinergic, GABAergic, serotonergic and other neurons in the medial medullary reticular formation for sleep–wake states studied by cytotoxic lesions in the cat. Neuroscience 62: 1179–1200. Holstege JC, Bongers CM (1991). A glycinergic projection from the ventromedial lower brainstem to spinal motoneurons. An ultrastructural double labeling study in rat. Brain Res 566: 308–315. Horner RL, Kubin L (1999). Pontine carbachol elicits multiple rapid eye movement sleep-like neural events in urethane-anaesthetized rats. Neuroscience 93: 215–226. Horvath TL, Peyron C, Diano S et al. (1999). Hypocretin (orexin) activation and synaptic innervation of the locus coeruleus noradrenergic system. J Comp Neurol 415: 145–159. Huang ZL, Qu WM, Li WD et al. (2001). Arousal effect of orexin A depends on activation of the histaminergic system. Proc Natl Acad Sci U S A 98: 9965–9970. Huang ZL, Qu WM, Eguchi N et al. (2005). Adenosine A2A, but not A1, receptors mediate the arousal effect of caffeine. Nat Neurosci 8: 858–859. Jacobs BL (1985). Overview of the activity of brain monoaminergic neurons across the sleep–wake cycle. In: A Wauquier, JM Gaillard, JM Monti et al. (Eds.), Sleep: Neurotransmitters and Neuromodulators. Raven Press, New York, pp. 1–14.
Jones BE (1991a). Noradrenergic locus coeruleus neurons: their distant connections and their relationship to neighboring (including cholinergic and GABAergic) neurons of the central gray and reticular formation. Prog Brain Res 88: 15–30. Jones BE (1991b). Paradoxical sleep and its chemical/structural substrates in the brain. Neuroscience 40: 637–656. Jones B (1993a). The organization of central cholinergic systells and their functional importance in sleep–waking states. In: A Cuello (Ed.), Cholinergic Function and Dysfunction. Progress in Brain Research. Elsevier, Amsterdam. Jones BE (1993b). The organization of central cholinergic systems and their functional importance in sleep–waking states. Prog Brain Res 98: 61–71. Jones BE (1994). Basic mechanisms of sleep–wake states. In: MH Kryger, T Roth, WC Dement (Eds.), Principles and Practice of Sleep Medicine. WB Saunders, Philadelphia, pp. 61–71. Jouvet M (1962). Recherches sur les structures nerveuses et les me´canismes responsables des diffe´rentes phases du sommeil physiologique. Arch Ital Biol 100: 125–206. Jouvet M (1969). Biogenic amines and the states of sleep. Science 163: 32–41. Jouvet M (1972). The role of monoamines and acetylcholinecontaining neurons in the regulation of the sleep–waking cycle. Ergeb Physiol 64: 166–307. Jouvet M (1975). Cholinergic mechanisms and sleep. In: PG Waser (Ed.), Cholinergic Mechanisms. Raven Press, New York, pp. 455–476. Jouvet M (1988). The regulation of paradoxical sleep by the hypothalamo-hypophysis. Arch Ital Biol 126: 259–274. Jouvet M, Michel F (1959). Electromyographic correlations of sleep in the chronic decorticate and mesencephalic cat. CR Se´ances Soc Biol (Paris) 153: 422–425. Kaur S, Saxena RN, Mallick BN (2001). GABAergic neurons in prepositus hypoglossi regulate REM sleep by its action on locus coeruleus in freely moving rats. Synapse 42: 141–150. Kayama Y, Ohta M, Jodo E (1992). Firing of ‘possibly’ cholinergic neurons in the rat laterodorsal tegmental nucleus during sleep and wakefulness. Brain Res 569: 210–220. Kilduff TS, Peyron C (2000). The hypocretin/orexin ligandreceptor system: implications for sleep and sleep disorders. Trends Neurosci 23: 359–365. Kodama T, Lai YY, Siegel JM (1998). Enhanced glutamate release during REM sleep in the rostromedial medulla as measured by in vivo microdialysis. Brain Res 780: 178–181. Kodama T, Lai YY, Siegel JM (2003). Changes in inhibitory amino acid release linked to pontine-induced atonia: an in vivo microdialysis study. J Neurosci 23: 1548–1554. Kohlmeier KA, Lopez-Rodriguez F, Liu RH et al. (1996). State-dependent phenomena in cat masseter motoneurons. Brain Res 722: 30–38. Koyama Y, Kayama Y (1993). Mutual interactions among cholinergic, noradrenergic and serotonergic neurons studied by ionophoresis of these transmitters in rat brainstem nuclei. Neuroscience 55: 1117–1126.
NEUROCHEMISTRY OF SLEEP: AN OVERVIEW OF ANIMAL EXPERIMENTAL WORK Koyama Y, Takahashi K, Kodama T et al. (2003). Statedependent activity of neurons in the perifornical hypothalamic area during sleep and waking. Neuroscience 119: 1209–1219. Krueger JM (1999). Cytokines and sleep regulation. In: R Lydic, HA Baghdoyan (Eds.), Handbook of Behavioral State Control. Cellular and Molecular Mechanisms. CRC Press, New-York, pp. 609–622. Krueger JM, Majde JA (2003). Humoral links between sleep and the immune system: research issues. Ann N Y Acad Sci 992: 9–20. Lai YY, Siegel JM (1990). Cardiovascular and muscle tone changes produced by microinjection of cholinergic and glutamatergic agonists in dorsolateral pons and medial medulla. Brain Res 514: 27–36. Lai YY, Siegel JM (1991). Pontomedullary glutamate receptors mediating locomotion and muscle tone suppression. J Neurosci 11: 2931–2937. Lee MG, Hassani OK, Jones BE (2005). Discharge of identified orexin/hypocretin neurons across the sleep–waking cycle. J Neurosci 25: 6716–6720. Levine ES, Jacobs BL (1992). Neurochemical afferents controlling the activity of serotonergic neurons in the dorsal raphe nucleus: microiontophoretic studies in the awake cat. J Neurosci 12: 4037–4044. Li YQ, Takada M, Kaneko T et al. (1996). GABAergic and glycinergic neurons projecting to the trigeminal motor nucleus: a double labeling study in the rat. J Comp Neurol 373: 498–510. Lin JS, Sakai K, Vanni-Mercier G et al. (1989). A critical role of the posterior hypothalamus in the mechanisms of wakefulness determined by microinjection of muscimol in freely moving cats. Brain Res 479: 225–240. Lin JS, Roussel B, Akaoka H et al. (1992). Role of catecholamines in the modafinil and amphetamine induced wakefulness, a comparative pharmacological study in the cat. Brain Res 591: 319–326. Lin JS, Hou Y, Sakai K et al. (1996). Histaminergic descending inputs to the mesopontine tegmentum and their role in the control of cortical activation and wakefulness in the cat. J Neurosci 16: 1523–1537. Lin L, Faraco J, Li R et al. (1999). The sleep disorder canine narcolepsy is caused by a mutation in the hypocretin (orexin) receptor 2 gene. Cell 98: 365–376. Liu R, Jolas T, Aghajanian G (2000). Serotonin 5-HT(2) receptors activate local GABA inhibitory inputs to serotonergic neurons of the dorsal raphe nucleus. Brain Res 873: 34–45. Liu RJ, Van Den Pol AN, Aghajanian GK (2002). Hypocretins (orexins) regulate serotonin neurons in the dorsal raphe nucleus by excitatory direct and inhibitory indirect actions. J Neurosci 22: 9453–9464. Lu J, Shiromani P, Saper CB (1999). Retinal input to the sleep-active ventrolateral preoptic nucleus in the rat. Neuroscience JID - 7605074, 93: 209–214. Lu J, Greco MA, Shiromani P et al. (2000). Effect of lesions of the ventrolateral preoptic nucleus on NREM and REM sleep. J Neurosci JID - 8102140, 20: 3830–3842.
187
Lu J, Bjorkum AA, Xu M et al. (2002). Selective activation of the extended ventrolateral preoptic nucleus during rapid eye movement sleep. J Neurosci JID - 8102140, 22: 4568–4576. Luppi PH, Sakai K, Fort P et al. (1988). The nuclei of origin of monoaminergic, peptidergic, and cholinergic afferents to the cat nucleus reticularis magnocellularis: a doublelabeling study with cholera toxin as a retrograde tracer. J Comp Neurol 277: 1–20. Luppi PH, Charlety PJ, Fort P et al. (1991). Anatomical and electrophysiological evidence for a glycinergic inhibitory innervation of the rat locus coeruleus. Neurosci Lett 128: 33–36. Luppi PH, Aston-Jones G, Akaoka H et al. (1995). Afferent projections to the rat locus coeruleus demonstrated by retrograde and anterograde tracing with cholera-toxin B subunit and Phaseolus vulgaris leucoagglutinin. Neuroscience 65: 119–160. Luppi PH, Gervasoni D, Peyron C et al. (1999). Norepinephrine and REM Sleep. In: BN Mallick, S Inoue (Eds.), Rapid Eye Movement Sleep. Norosa Publishing House, New Delhi, pp. 107–122. McCarley RW, Hobson JA (1975). Neuronal excitability modulation over the sleep cycle: a structural and mathematical model. Science 189: 58–60. McGinty DJ, Harper RM (1976). Dorsal raphe neurons: depression of firing during sleep in cats. Brain Res 101: 569–575. McGinty D, Szymusiak R (2003). Hypothalamic regulation of sleep and arousal. Front Biosci 8: s1074–s1083. McGinty D, Alam MN, Szymusiak R et al. (2001). Hypothalamic sleep-promoting mechanisms: coupling to thermoregulation. Arch Ital Biol JID - 0372441, 139: 63–75. Maloney KJ, Mainville L, Jones BE (1999). Differential cFos expression in cholinergic, monoaminergic, and GABAergic cell groups of the pontomesencephalic tegmentum after paradoxical sleep deprivation and recovery. J Neurosci 19: 3057–3072. Maloney KJ, Mainville L, Jones BE (2000). c-Fos expression in GABAergic, serotonergic, and other neurons of the pontomedullary reticular formation and raphe after paradoxical sleep deprivation and recovery. J Neurosci 20: 4669–4679. Maquet P, Peters J, Aerts J et al. (1996). Functional neuroanatomy of human rapid-eye-movement sleep and dreaming. Nature 383: 163–166. Marcus JN, Aschkenasi CJ, Lee CE et al. (2001). Differential expression of orexin receptors 1 and 2 in the rat brain. J Comp Neurol 435: 6–25. Matsuo S, Jang IS, Nabekura J et al. (2003). Alpha 2-adrenoceptor-mediated presynaptic modulation of GABAergic transmission in mechanically dissociated rat ventrolateral preoptic neurons. J Neurophysiol 89: 1640–1648. Mileykovskiy BY, Kiyashchenko LI, Siegel JM (2005). Behavioral correlates of activity in identified hypocretin/orexin neurons. Neuron 46: 787–798. Morales FR, Sampogna S, Yamuy J et al. (1999). c-Fos expression in brainstem premotor interneurons during
188
P.-H. LUPPI AND P. FORT
cholinergically induced active sleep in the cat. J Neurosci 19: 9508–9518. Moruzzi GMH (1949). Brain stem reticular formation and activation of the EEG. J Clin Neurosci 7: 251–267. Moruzzi G (1972). The sleep–waking cycle. Ergeb Physiol 64: 1–165. Nakamura T, Uramura K, Nambu T et al. (2000). Orexininduced hyperlocomotion and stereotypy are mediated by the dopaminergic system. Brain Res 873: 181–187. Nauta WJ (1946). Hypothalamic regulation of sleep in rats. Experimental study. J Neurophysiol 9: 285–316. Nishino S, Ripley B, Overeem S et al. (2000). Hypocretin (orexin) deficiency in human narcolepsy. Lancet JID 2985213R, 355: 39–40. Nitz D, Siegel J (1997a). GABA release in the dorsal raphe nucleus: role in the control of REM sleep. Am J Physiol 273: R451–R455. Nitz D, Siegel JM (1997b). GABA release in the locus coeruleus as a function of sleep/wake state. Neuroscience 78: 795–801. Novak CM, Nunez AA (1998). Daily rhythms in Fos activity in the rat ventrolateral preoptic area and midline thalamic nuclei. Am J Physiol JID - 0370511, 275: R1620–R1626. Novak CM, Nunez AA (2000). A sparse projection from the suprachiasmatic nucleus to the sleep active ventrolateral preoptic area in the rat. Neuroreport JID - 9100935, 11: 93–96. Obal FJR, Krueger JM (2003). Biochemical regulation of nonrapid-eye-movement sleep. Front Biosci 8: d520–d550. Onoe H, Sakai K (1995). Kainate receptors: a novel mechanism in paradoxical (REM) sleep generation. Neuroreport 6: 353–356. Paxinos G, Watson C (1997). The Rat Brain in Stereotaxic Coordinates. Academic Press, Sydney. Peyron C, Tighe DK, Van Den Pol AN et al. (1998). Neurons containing hypocretin (orexin) project to multiple neuronal systems. J Neurosci 18: 9996–10015. Peyron C, Faraco J, Rogers W et al. (2000). A mutation in a case of early onset narcolepsy and a generalized absence of hypocretin peptides in human narcoleptic brains. Nat Med 6: 991–997. Pollock MS, Mistlberger RE (2003). Rapid eye movement sleep induction by microinjection of the GABA-A antagonist bicuculline into the dorsal subcoeruleus area of the rat. Brain Res 962: 68–77. Porkka-Heiskanen T, Strecker RE, Thakkar M et al. (1997). Adenosine: a mediator of the sleep-inducing effects of prolonged wakefulness. Science 276: 1265–1268. Porkka-Heiskanen T, Strecker RE, Mccarley RW (2000). Brain site-specificity of extracellular adenosine concentration changes during sleep deprivation and spontaneous sleep: an in vivo microdialysis study. Neuroscience JID - 7605074, 99: 507–517. Portas CM, Thakkar M, Rainnie DG et al. (1997). Role of adenosine in behavioral state modulation: a microdialysis study in the freely moving cat. Neuroscience 79: 225–235. Rainnie DG, Grunze HC, McCarley RW et al. (1994). Adenosine inhibition of mesopontine cholinergic neurons: implications for EEG arousal. Science 263: 689–692.
Rampon C, Luppi PH, Fort P et al. (1996a). Distribution of glycine-immunoreactive cell bodies and fibers in the rat brain. Neuroscience 75: 737–755. Rampon C, Peyron C, Petit JM et al. (1996b). Origin of the glycinergic innervation of the rat trigeminal motor nucleus. Neuroreport 7: 3081–3085. Ranson SW (1939). Somnolence caused by hypothalamic lesions in the monkey. Arch Neurol Psychiatr 41: 1–23. Sakai K (1985). Neurons responsible for paradoxical sleep. In: A Wauquier, Janssen Research Foundation (Eds.), Sleep: Neurotransmitters and Neuromodulators. Raven Press, New York, pp. 29–42. Sakai K (1986). Central mechanisms of paradoxical sleep. Brain Dev 8: 402–407. Sakai K, Crochet S (2000). Serotonergic dorsal raphe neurons cease firing by disfacilitation during paradoxical sleep. Neuroreport 11: 3237–3241. Sakai K, Koyama Y (1996). Are there cholinergic and noncholinergic paradoxical sleep-on neurones in the pons? Neuroreport 7: 2449–2453. Sakai K, Sastre JP, Salvert D et al. (1979). Tegmentoreticular projections with special reference to the muscular atonia during paradoxical sleep in the cat: an HRP study. Brain Res 176: 233–254. Sakai K, Sastre JP, Kanamori N et al. (1981). State-specific neurones in the ponto-medullary reticular formation with special reference to the postural atonia during paradoxical sleep in the cat. In: O Pompeiano, C Aimone Marsan (Eds.), Brain Mechanisms of Perceptual Awareness and Purposeful Behavior. Raven Press, New York. Sakai K, Crochet S, Onoe H (2001). Pontine structures and mechanisms involved in the generation of paradoxical (REM) sleep. Arch Ital Biol 139: 93–107. Sakurai T, Amemiya A, Ishii M et al. (1998). Orexins and orexin receptors: a family of hypothalamic neuropeptides and G protein-coupled receptors that regulate feeding behavior. Cell 92: 573–585. Sallanon M, Sakai K, Buda C et al. (1988). Increase of paradoxical sleep induced by microinjections of ibotenic acid into the ventrolateral part of the posterior hypothalamus in the cat. Arch Ital Biol 126: 87–97. Sallanon M, Denoyer M, Kitahama K et al. (1989). Longlasting insomnia induced by preoptic neuron lesions and its transient reversal by muscimol injection into the posterior hypothalamus in the cat. Neuroscience 32: 669–683. Sanford LD, Tang X, Xiao J et al. (2003). GABAergic regulation of REM sleep in reticularis pontis oralis and caudalis in rats. J Neurophysiol 90: 938–945. Saper CB, Chou TC, Scammell TE (2001). The sleep switch: hypothalamic control of sleep and wakefulness. Trends Neurosci 24: 726–731. Sastre JP, Sakai K, Jouvet M (1981). Are the gigantocellular tegmental field neurons responsible for paradoxical sleep? Brain Res 229: 147–161. Sastre JP, Buda C, Kitahama K et al. (1996). Importance of the ventrolateral region of the periaqueductal gray and adjacent tegmentum in the control of paradoxical sleep
NEUROCHEMISTRY OF SLEEP: AN OVERVIEW OF ANIMAL EXPERIMENTAL WORK as studied by muscimol microinjections in the cat. Neuroscience 74: 415–426. Sastre JP, Buda C, Lin JS et al. (2000). Differential c-Fos expression in the rhinencephalon and striatum after enhanced sleep–wake states in the cat. Eur J Neurosci 12: 1397–1410. Satoh S, Matsumura H, Suzuki F et al. (1996). Promotion of sleep mediated by the A2a-adenosine receptor and possible involvement of this receptor in the sleep induced by prostaglandin D2 in rats. Proc Natl Acad Sci U S A JID 7505876, 93: 5980–5984. Scammell TE, Gerashchenko DY, Mochizuki T et al. (2001). An adenosine A2a agonist increases sleep and induces Fos in ventrolateral preoptic neurons. Neuroscience JID - 7605074, 107: 653–663. Schmidt MH, Valatx JL, Sakai K et al. (2000). Role of the lateral preoptic area in sleep-related erectile mechanisms and sleep generation in the rat. J Neurosci 20: 6640–6647. Schmidt MH, Gervasoni D, Luppi PH et al. (2001). Carbachol administration into the lateral preoptic area induces penile erections and wakefulness. Neurosci Abstr, 522. Schmidt MH, Gervasoni D, Luppi PH et al. (2002). The ventrolateral preoptic area: role and origin of cholinergic input in the control of wakefulness and penile erections. Sleep 25 (Suppl). Schmidt MH, Gervasoni D, Luppi PH et al. (2003). Quantitative analysis of cholinergic afferents to the ventrolateral preoptic area: role in waking mechanisms. Sleep 26 (Suppl): 0089. Sherin JE, Shiromani PJ, McCarley RW et al. (1996). Activation of ventrolateral preoptic neurons during sleep. Science 271: 216–219. Sherin JE, Elmquist JK, Torrealba F et al. (1998). Innervation of histaminergic tuberomammillary neurons by GABAergic and galaninergic neurons in the ventrolateral preoptic nucleus of the rat. J Neurosci 18: 4705–4721. Shiromani PJ, Fishbein W (1986). Continuous pontine cholinergic microinfusion via mini-pump induces sustained alterations in rapid eye movement (REM) sleep. Pharmacol Biochem Behav 25: 1253–1261. Shiromani P, Scammell T, Sherin JE et al. (1999). Hypothalamic regulation of sleep. In: R Lydic, HA Baghdoyan (Eds.), Handbook of Behavioral State Control. Cellular and Molecular Machanisms. CRC Press, New York, pp. 311–325. Siegel JM, Wheeler RL, McGinty DJ (1979). Activity of medullary reticular formation neurons in the unrestrained cat during waking and sleep. Brain Res 179: 49–60. Soja PJ, Lopez-Rodriguez F, Morales FR et al. (1991). The postsynaptic inhibitory control of lumbar motoneurons during the atonia of active sleep: effect of strychnine on motoneuron properties. J Neurosci 11: 2804–2811. Steininger TL, Alam MN, Gong H et al. (1999). Sleep– waking discharge of neurons in the posterior lateral hypothalamus of the albino rat. Brain Res 840: 138–147. Steininger TL, Gong H, Mcginty D et al. (2001). Subregional organization of preoptic area/anterior hypothalamic projections to arousal-related monoaminergic cell groups. J Comp Neurol 429: 638–653.
189
Stenberg D, Litonius E, Halldner L et al. (2003). Sleep and its homeostatic regulation in mice lacking the adenosine A1 receptor. J Sleep Res 12: 283–290. Sun X, Whitefield S, Rusak B et al. (2001). Electrophysiological analysis of suprachiasmatic nucleus projections to the ventrolateral preoptic area in the rat. Eur J Neurosci JID 8918110 14: 1257–1274. Swanson LW (1998). Brain Maps: Structure of the Rat Brain: A Laboratory Guide with Printed and Electronic Templates for Data, Models, and Schematics. Elsevier, New York. Swett CP, Hobson JA (1968). The effects of posterior hypothalamic lesions on behavioral and electrographic manifestations of sleep and waking in cats. Arch Ital Biol 106: 283–293. Szymusiak R, Alam N, Steininger TL et al. (1998). Sleep– waking discharge patterns of ventrolateral preoptic/anterior hypothalamic neurons in rats. Brain Res 803: 178–188. Szymusiak R, Steininger T, Alam N et al. (2001). Preoptic area sleep-regulating mechanisms. Arch Ital Biol 139: 77–92. Taguchi O, Kubin L, Pack AI (1992). Evocation of postural atonia and respiratory depression by pontine carbachol in the decerebrate rat. Brain Res 595: 107–115. Thompson RH, Canteras NS, Swanson LW (1996). Organization of projections from the dorsomedial nucleus of the hypothalamus: a PHA-L study in the rat. J Comp Neurol JID - 0406041, 376: 143–173. Tononi G, Pompeiano M, Cirelli C (1991). Suppression of desynchronized sleep through microinjection of the alpha 2-adrenergic agonist clonidine in the dorsal pontine tegmentum of the cat. Pflugers Arch 418: 512–518. Torterolo P, Yamuy J, Sampogna S et al. (2003). Hypocretinergic neurons are primarily involved in activation of the somatomotor system. Sleep 26: 25–28. Trivedi P, Yu H, Macneil DJ et al. (1998). Distribution of orexin receptor mrna in the rat brain. FEBS Lett 438: 71–75. Urade Y, Eguchi N, Qu WM et al. (2003). Minireview: sleep regulation in adenosine A(2A) receptor-deficient mice. Neurology 61: S94–S96. van den Pol AN (1999). Hypothalamic hypocretin (orexin): robust innervation of the spinal cord. J Neurosci 19: 3171–3182. Vanni-Mercier G, Sakai K, Jouvet M (1984). [Specific neurons for wakefulness in the posterior hypothalamus in the cat]. C R Acad Sci III 298: 195–200. Vanni-Mercier G, Sakai K, Lin JS et al. (1989). Mapping of cholinoceptive brainstem structures responsible for the generation of paradoxical sleep in the cat. Arch Ital Biol 127: 133–164. Velazquez-Moctezuma J, Gillin JC, Shiromani PJ (1989). Effect of specific M1, M2 muscarinic receptor agonists on REM sleep generation. Brain Res 503: 128–131. Verret L, Goutagny R, Fort P et al. (2003). A role of melanin-concentrating hormone producing neurons in the central regulation of paradoxical sleep. BMC Neurosci 4: 19. Verret L, Leger L, Fort P et al. (2005). Cholinergic and noncholinergic brainstem neurons expressing Fos after paradoxical (REM) sleep deprivation and recovery. Eur J Neurosci 21: 2488–2504.
190
P.-H. LUPPI AND P. FORT
Verret L, Fort P, Gervasoni D et al. (2006). Localization of the neurons active during paradoxical (REM) sleep and projecting to the locus coeruleus noradrenergic neurons in the rat. J Comp Neurol 495: 573–586. von Economo C (1926). Die Pathologie des Schlafes. In: A Von Bethe, GV Bergman, G Embden et al. (Eds.), Handbuch des Normalen und Pathologischen Physiologie. Springer, Berlin. von Economo C (1929). Schlaftheorie. Ergeb Physiol 55: 121–135. Watts AG, Swanson LW, Sanchez-Watts G (1987). Efferent projections of the suprachiasmatic nucleus: I. Studies using anterograde transport of Phaseolus vulgaris leucoagglutinin in the rat. J Comp Neurol JID - 0406041, 258: 204–229. Webster HH, Jones BE (1988). Neurotoxic lesions of the dorsolateral pontomesencephalic tegmentum-cholinergic cell area in the cat. II. Effects upon sleep–waking states. Brain Res 458: 285–302. Woch G, Davies RO, Pack AI et al. (1996). Behaviour of raphe cells projecting to the dorsomedial medulla during carbachol-induced atonia in the cat. J Physiol 490 (Pt 3): 745–758. Xi MC, Morales FR, Chase MH (1999). Evidence that wakefulness and REM sleep are controlled by a GABAergic pontine mechanism. J Neurophysiol 82: 2015–2019. Xi MC, Morales FR, Chase MH (2001). The motor inhibitory system operating during active sleep is tonically suppressed by GABAergic mechanisms during other states. J Neurophysiol 86: 1908–1915.
Xi MC, Morales FR, Chase MH (2004). Interactions between GABAergic and cholinergic processes in the nucleus pontis oralis: neuronal mechanisms controlling active (rapid eye movement) sleep and wakefulness. J Neurosci 24: 10670–10678. Yamamoto K, Mamelak AN, Quattrochi JJ et al. (1990). A cholinoceptive desynchronized sleep induction zone in the anterodorsal pontine tegmentum: locus of the sensitive region. Neuroscience 39: 279–293. Yamanaka A, Tsujino N, Funahashi H et al. (2002). Orexins activate histaminergic neurons via the orexin 2 receptor. Biochem Biophys Res Commun 290: 1237–1245. Yamuy J, Sampogna S, Lopez-Rodriguez F et al. (1995). Fos and serotonin immunoreactivity in the raphe nuclei of the cat during carbachol-induced active sleep: a doublelabeling study. Neuroscience 67: 211–223. Yamuy J, Fung SJ, Xi M et al. (1999). Hypoglossal motoneurons are postsynaptically inhibited during carbacholinduced rapid eye movement sleep. Neuroscience 94: 11–15. Yoshida Y, Fujiki N, Nakajima T et al. (2001). Fluctuation of extracellular hypocretin-1 (orexin A) levels in the rat in relation to the light-dark cycle and sleep–wake activities. Eur J Neurosci 14: 1075–1081. Zeitzer JM, Buckmaster CL, Parker KJ et al. (2003). Circadian and homeostatic regulation of hypocretin in a primate model: implications for the consolidation of wakefulness. J Neurosci 23: 3555–3560.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 12
Molecular neurobiology of sleep CHIARA CIRELLI * AND GIULIO TONONI Department of Psychiatry, University of Wisconsin, Madison, WI, USA
A CELLULAR FUNCTION FOR SLEEP It is widely thought that the functions of sleep may ultimately relate to cellular and molecular aspects of neural function. Giuseppe Moruzzi argued that “sleep concerns primarily not the whole cerebrum, nor even the entire neocortex, but only those neurons or synapses, and possibly glial cells, which during wakefulness are responsible for the brain functions concerned with conscious behavior” (Moruzzi, 1966). Moruzzi suggested that neural cells or synapses supporting waking conscious activity undergo plastic changes that make sleep necessary, although he did not speculate about the mechanisms. Others have suggested that sleep may help to restore brain energy metabolism (Benington and Heller, 1995), or may be needed to maintain the synaptic efficacy of the neural circuits not frequently used during wakefulness (Krueger et al., 1995; Kavanau, 1997). Steriade and Timofeev (2003) have suggested that the rich spontaneous activity of neocortical neurons during slow-wave sleep may consolidate memory traces acquired during wakefulness. Several of these hypotheses are not mutually exclusive, and sleep may favor different cellular processes. One way to understand the benefits that sleep may bring at the cellular level is to perform an extensive analysis of its molecular correlates. The identification of the genes whose expression changes in the brain between sleep and wakefulness may suggest why brain cells need to sleep and why their functions are impaired if they are prevented from doing so during sleep deprivation. This correlational approach has taken advantage, over the past 6–8 years, of the DNA microarray technology, which allows wholegenome expression profiling of different tissues in different species, from flies to humans. Another, causal
*
approach to determine why sleep is necessary is to identify single genes whose activity can significantly affect sleep need. In mutagenesis screenings, for example, (ideally) all the genes of a given genome are mutagenized one at a time and the consequences of the mutations on the sleep phenotype are studied. In this review we will briefly discuss both molecular and genetic approaches.
GENE EXPRESSION PROFILING OF SLEEP AND WAKEFULNESS The systematic analysis of changes in gene expression between sleep and wakefulness started in the 1990s. At that time, while most scientists agreed that sleep and wakefulness differ in terms of metabolism, electrophysiological activity, and behavior, very few thought that they could also significantly and extensively differ at the level of gene expression. In fact, in the 1970s and 1980s, long before whole-genome profiling using DNA microarrays became possible, several studies had suggested that global changes in brain gene expression occur across behavioral states. These experiments did not focus on specific genes, but examined overall changes in RNA content or synthesis, as well as global changes in protein synthesis in relation to sleep and wakefulness or sleep deprivation (VitaleNeugebauer et al., 1970; Bobillier et al., 1971; Giuditta et al., 1980; Panov, 1982). The general conclusions of these studies were that significant changes in RNA and protein levels do occur between sleep, wakefulness, and sleep deprivation. More recently, Ramm and Smith (1990) found that the rate at which labeled leucine was incorporated into the rat brain was positively correlated with the occurrence of non-rapid eye movement (non-REM) sleep but not with that of either wakefulness or REM sleep. In a later study, Nakanishi
Correspondence to: Chiara Cirelli, M.D., Ph.D., University of Wisconsin/Madison, Department of Psychiatry, 6001 Research Park Blvd, Madison WI 53719, USA. Tel: (608) 263 9236, E-mail:
[email protected]
192
C. CIRELLI AND G. TONONI
and colleagues (1997) also found that in most brain regions protein synthesis rate was positively correlated with slow-wave sleep. The early 1990s saw the appearance of several studies aimed at identifying specific molecular correlates of sleep and wakefulness in flies, mice, and rats (Table 12.1). Immediate early genes (IEGs) such as c-fos, NGFI-A, c-jun, and junB were among the first specific genes whose expression was studied across the sleep/waking cycle. IEGs are so called because their transcription is induced via preexisting cell proteins without requiring de novo protein synthesis. Many IEGs, such as c-fos and other members of the fos and jun families, encode transcription factors like Fos, which, by binding to DNA regulatory regions, can control the expression of many other target genes (Sheng and Greenberg, 1990; Herrera and Robertson, 1996). Several laboratories (see references in Cirelli and Tononi, 2000a) examined IEG mRNA and/or protein levels and found that in most brain regions IEG expression is high during wakefulness and low during sleep (Pompeiano et al., 1992, 1994, 1997; Cirelli et al., 1993, 1995). Interestingly, even in areas with high level of IEG expression, c-fos and other genes are not
uniformly expressed in all neurons. Moreover, their induction is not strictly proportional to the amount of prior wakefulness. In the cerebral cortex, for instance, the overall levels of c-fos are higher after 3 hours than after 24 hours of continuous wakefulness and very low after several days of sleep deprivation. This suggests that c-fos expression during wakefulness does not directly depend on the duration of wakefulness per se. Finally, at least 30–60 minutes are required for the induction of IEGs. Interestingly, as will be discussed later, most IEGs are involved in synaptic activity and plasticity; their expression is increased by neuronal depolarization, and is dependent on the level of activity of the noradrenergic system of the locus coeruleus (LC). Thus, the time required for the induction of IEGs after awakening (at least as described in animals) may match the time required in humans to overcome the transitional state of lowered arousal occurring immediately after awakening and described as “sleep inertia.” The finding that IEG expression changes significantly between sleep and wakefulness prompted systematic gene expression profiling studies using microarrays (Rhyner et al., 1990; Cirelli and Tononi,
Table 12.1 Several, but not all, studies that identified molecular correlates of sleep (S), wakefulness (W), and sleep deprivation (SD) Year
Study type
Major findings
Refs
1990
First extensive gene expression study after SD in rats
Rhyner et al. (1990)
1992
First c-fos studies
1993
Other IEG studies
1995–1996
Expression of other candidate genes
1998–2000
Transcriptomic studies in rats after 3–8 hours of S, W, SD
2000
First gene expression studies in invertebrates Whole-genome transcriptomic analysis in rats and flies during S, W, SD
Expression of several unknown forebrain transcript changes after SD c-fos can be induced after SD and after rapid eye movement enhancement c-fos is also induced after spontaneous W; other IEGs are also induced after SD Dendrin, galanin, GHRH, IL-1b, neurogranin, P-CREB, somatostatin, and other mRNAs are affected by SD IEGs, mitochondrial genes, and heat shock proteins are upregulated during W and short-term SD Gene expression changes between S, W, and SD also in flies S and W-SD genes belong to different functional categories
2004–2005
Merchant-Nancy et al. (1992), Pompeiano et al. (1992), Shiromani et al. (1992) Cirelli et al. (1993), Landis et al. (1993), O’Hara et al. (1993) Neuner-Jehle al. (1995, 1996), Toppila et al. (1995, 1996), Cirelli et al. (1996), Mackiewicz et al. (1996) Cirelli and Tononi (1998, 2000b)
Shaw et al. (2000) Cirelli et al. (2004, 2005a)
IEGs, immediate early genes (see main text); GHRH, growth hormone-releasing hormone; IL-1b, interleukin 1b; P-CREB, phosphorylated CREB (cAMP response element-binding).
MOLECULAR NEUROBIOLOGY OF SLEEP 1998, 2000b; Cirelli et al., 2004, 2005a). The goal was to identify (ideally) all the genes whose transcripts changed as a function of behavioral state. In most of these studies the experimental paradigm included three experimental groups to distinguish between changes in gene expression related to sleep and wakefulness per se as opposed to circadian time or to the sleep deprivation procedure. Spontaneously asleep (S) rats were killed after 3 or 8 hours of sleep; sleep-deprived (SD) rats were killed at the same time of day as the S animals but after having been kept awake for 3 or 8 hours; spontaneously awake (W) rats were killed during the dark period after 3 or 8 hours of spontaneous wakefulness. Since S and SD rats were sacrificed at the same time of day but in opposite behavioral state, and since SD and W rats were sacrificed 12 hours apart but in the same behavioral state, day/night and sleep/ wakefulness effects could be dissociated. The studies focused on the cerebral cortex, because it is one of the most informative brain regions to examine the cellular consequences of sleep and wakefulness. The cerebral cortex responds to prolonged wakefulness with clear signs of increasing sleep pressure, such as an increase in slow-wave activity during non-REM sleep (Borbe´ly and Achermann, 1999). The cerebral cortex is also responsible for the cognitive defects observed after sleep deprivation, which increase progressively as a function of prior time awake (Van Dongen et al., 2003). Several general conclusions can be derived from these studies. First, changes in gene expression across behavioral states are extensive. For instance, up to 5% of the transcripts tested in the cerebral cortex (752, 4.9% of 15 459) are up- or downregulated in rats that had slept for 8 hours relative to rats that had been spontaneously awake or sleep-deprived for a similar period of time (Cirelli et al., 2004). Interestingly, a similar number of transcripts changed their expression in the cerebral cortex of S, SD, and W rats because of time of day, rather than because of behavioral state, suggesting that day/night time and sleep/wakefulness influence cortical gene expression to a similar extent. Second, although sleep is a state of behavioral inactivity, it is associated with the increased expression of many genes in the brain (at least 100). Importantly, the increased expression in the brain during sleep is specific, since transcripts that are sleep-related in the brain are not sleep-related in other tissues such as liver and skeletal muscle (Cirelli et al., 2004). Third, many (40%) of the genes that were wakefulness-related in the cerebral cortex were also wakefulness-related in the cerebellum. Similarly, many (50%) of the cortical sleep-related genes were also sleep-related in the cerebellum. This finding is intriguing because the
193
cerebellum is not involved in the generation of the classical electroencephalogram (EEG) markers of sleep such as spindles and slow waves. This suggests that functions associated with sleep may take place whether or not electrographic signs of sleep can be recorded. Moreover, it also suggests that at least some of the changes in gene expression observed between sleeping and awake animals may depend on changes in the activity of neuromodulatory systems with diffuse projections such as the LC system. Fourth, several of the molecular correlates of sleep and wakefulness identified in rats were also found in other species, from fruit flies to Djungarian hamsters and white crown sparrows. Finally, one of the most important results of our analysis was that sleep-related and wakefulnessrelated transcripts belong to different functional categories, suggesting that sleep and wakefulness may favor different cellular processes.
Wakefulness-related transcripts: energy metabolism, response to cellular stress, and synaptic potentiation As shown in Figure 12.1, many wakefulness-related transcripts are involved in energy metabolism, response to cellular stress, and synaptic potentiation. For instance, the mRNAs of two mitochondrial genes, subunit 1 of cytochrome c oxidase and subunit 2 of NADH dehydrogenase, increase after 3 hours of wakefulness. A recent study also found that the increased brain expression of mitochondrial genes is associated with an increase in cytochrome c oxidase enzymatic activity (Nikonova et al., 2005). Transcript levels of the glial glucose transporter Glut1 were also found to increase by 30–40% after a few hours of spontaneous or forced wakefulness. Brain energy expenditure is tightly controlled by brain activity (Lowry, 1975), mainly because of the high metabolic cost of ion pumping by Naþ/Kþ ATPase to counteract membrane depolarization (Erecin˜ska and Silver, 1989; Attwell and Laughlin, 2001). Cerebral glucose metabolism is 20–30% higher in wakefulness than in non-REM sleep in several species, including the rat (Ramm and Frost, 1983; Maquet, 1995), probably because during wakefulness cortical and thalamic cells are more depolarized and synaptic transmission is facilitated (Steriade and Timofeev, 2003). The brain uses glucose as the main energy substrate, metabolized almost exclusively through mitochondrial oxidative phosphorylation. Thus, the induction of mitochondrial genes and Glut1 may represent a mechanism by which the brain responds to the increased energy requirements of wakefulness. Interestingly, according to the traditional view, glucose transport capacity in the brain always
194
C. CIRELLI AND G. TONONI Increase in energy demand
Cellular stress response NE F,H,S
F,H
Cellular stress response
Synaptic potentiation
Glial disfunction?
Autoimmune response?
NE H,S
Sleep
Wakefulness
Increase in protein synthesis NE H
Synaptic depression
Prolonged sleep loss
Glial function? Membrane maintenance?
Fig. 12.1. Schematic representation of the major functional categories of genes whose expression increases in the rat brain during wakefulness (including 3–8 hours of sleep deprivation), sleep, and prolonged sleep loss (7 days of total sleep deprivation). F, similar changes also present in fruit flies; H, similar changes also present in Djungarian hamsters; S, similar changes also present in white crown sparrows. NE indicates those gene categories whose expression is also modulated by the noradrenergic system of the locus coeruleus (see main text for details).
exceeds demand. However, work has shown that hippocampal extracellular glucose concentration decreases significantly during a difficult spatial task and that such a decrease can be prevented by systemic administration of glucose (McNay et al., 2000). Thus, intense cognitive activity during wakefulness may deplete brain extracellular glucose and trigger compensatory mechanisms. Wakefulness-related transcripts include heat shock proteins (HSP) and molecular chaperones, such as those coding for HSP27, HSP60, HSP70, and binding protein (BiP: aka GRP78). Their induction in the brain and other tissues is usually observed in conditions of cellular stress due to glucose deprivation, depletion of intracellular calcium levels, increase in oxidant production, or increase in extracellular glutamate levels. The strong induction of these stress response genes after a few hours of spontaneous or forced wakefulness has been confirmed in other brain regions and in several species, from flies (Shaw et al., 2000) to mice (Terao et al., 2003), hamsters, sparrows, and humans (Cirelli et al., unpublished results), suggesting that the absence of sleep may indeed represent a cellular stress for brain cells. Supporting evidence for this hypothesis has been provided by Naidoo et al. (2005), who found that in the mouse cerebral cortex a few hours of sleep deprivation induce the “unfolded protein response,” a global stress response that includes the induction of BiP, which promotes the degradation of misfolded proteins, as well as a decrease in protein synthesis. Many wakefulness-related transcripts play a role in synaptic plasticity, and more specifically in the acquisition of new memories and synaptic potentiation. Among them are the genes coding for Arc, brainderived neurotropic factor (BDNF), phosphorylated
cAMP response element-binding (P-CREB), Narp, NGFI-A, glutamate a-amino-3-hydroxyl-5-methyl-4isoxazole-propionate (AMPA) receptor GluR2, Homer and others (Cirelli et al., 1996; Cirelli and Tononi, 2000b, c; Cirelli et al., 2004). Arc, for instance, is specifically induced during the acquisition of a novel behavior (Kelly and Deadwyler, 2002), and the inhibition of Arc expression impairs the maintenance of long-term potentiation (LTP) and the consolidation of long-term memory (Guzowski et al., 2000). BDNF is able to alter dendritic morphology and mice lacking BDNF show a deficit in the induction of LTP, which can be rescued with recombinant BDNF or re-expression of BDNF (Korte et al., 1996; Patterson et al., 1996). Conversely, dendrites from BDNF-overexpressing neurons undergo massive sprouting (Wilson Horch et al., 1999). Narp regulates the activity and clustering of glutamate AMPA receptors, whose insertion into synapses is essential for the induction and maintenance of LTP (Lamprecht and Ledoux, 2004). Narp transgenic expression increases the number of AMPA receptor clusters, while dominant-negative Narp reduces such number (see references in Xu et al., 2003). P-CREB and the activation of CREB-dependent transcription play a crucial role in the acquisition of different forms of long-term memory. For example, mice lacking CREB show deficit in the late phase of LTP and in the acquisition of long-term memory, while antisense oligonucleotides directed against CREB mRNA can block the conversion of short-term into long-term memory (see references in Silva et al., 1998). The increased expression of all these plasticity-related genes during wakefulness is one of the several findings (reviewed in Tononi and Cirelli, 2006) suggesting that synaptic potentiation occurs during wakefulness.
MOLECULAR NEUROBIOLOGY OF SLEEP
Sleep-related transcripts: protein synthesis, membrane trafficking and maintenance, and synaptic depression Figure 12.1 also shows that sleep-related transcripts include key components of the translational machinery, such as those coding for the translation elongation factor 2 and the initiation factor 4AII. Transcript levels of the elongation factor EF2 are also increased during sleep in the brain of Djungarian hamsters (Cirelli et al., unpublished results). These findings are in agreement with previous studies that identified a positive correlation between sleep and protein synthesis (Reich et al., 1967, 1973; Voronka, 1971; Drucker-Colı´n et al., 1975; Ramm and Smith, 1990; Nakanishi et al., 1997). Whether sleep favors protein synthesis globally, or whether it enhances the synthesis of specific classes of proteins, is still unclear. Another group of transcripts whose mRNA levels are higher in sleep than in wakefulness include calmodulindependent protein kinase IV, a gene that has been specifically involved in the consolidation of long-term memory as well as in synaptic depression (Kang et al., 2001), and other genes that have been associated with synaptic depression and depotentiation, such as calcineurin, FK506 binding protein 12, inositol 1,4,5trisphosphate receptor, and amphiphysin II. Thus, while wakefulness is the appropriate time for memory acquisition and synaptic potentiation, sleep may favor complementary aspects of plasticity, such as synaptic consolidation and/or downscaling. An involvement of sleep in such processes is suggested by behavioral and physiological experiments showing that sleep improves the performance of different learning tasks acquired during the previous waking period (Stickgold et al., 2001; Walker et al., 2002; Huber et al., 2004). At this stage, however, the mechanism by which sleep enhances performance is still debated. Some researchers think that, by allowing the rehearsal of previously acquired information (Lee and Wilson, 2002) sleep may further strengthen those specific synapses that have been potentiated during wakefulness (Sejnowski and Destexhe, 2000; Steriade and Timofeev, 2003). Others, instead, favor the view that wakefulness is associated with a diffuse potentiation of synaptic circuits, which results in a net increase in synaptic weight, and that sleep produces a generalized depression or downscaling of synapses. This downscaling would benefit the brain because it decreases the energetic cost of synaptic activity, eliminates weak and ineffective synapses, and increases the signal-to-noise ratio (Tononi and Cirelli, 2006). Finally, a large group of sleep-related transcripts is involved in membrane trafficking and maintenance. Some of these transcripts are involved in exocytosis
195
and neurotransmitter release, others in synaptic vesicle recycling, tethering/docking of vesicles to their target organelles, and cycling between trans-Golgi network and plasma membrane. Others are important for the synthesis/maintenance of membranes in general and of myelin in particular, including oligodendrocytic gene coding for myelin structural proteins, myelinrelated receptors, and enzymes. Finally, transcripts with higher expression in sleep code for enzymes involved in the synthesis and transport of cholesterol, a major constituent of myelin and other membranes and an important factor in regulating synaptic efficacy (Mauch et al., 2001; Christopherson et al., 2005). Depletion of cholesterol/sphingolipid leads to instability of surface AMPA receptors and gradual loss of synapses and dendritic spines (Hering et al., 2003). Thus, it may not be by chance that sleep seems to be linked to membrane trafficking and cholesterol synthesis on the one hand, and to protein synthesis and synaptic homeostasis on the other hand.
Noradrenergic control of gene expression in sleep and wakefulness What are the mechanisms by which gene expression changes according to behavioral state? One of the mechanisms that underlie the widespread changes in cortical gene expression between sleep and wakefulness is the activity of the noradrenergic system of the LC, whose neurons project diffusely over the entire brain. LC cells are tonically active during wakefulness, reduce their firing rate during non-REM sleep, and cease firing during REM sleep (Aston-Jones and Bloom, 1981a). Moreover, LC activity increases phasically in response to salient events (Aston-Jones and Bloom, 1981b; Rasmussen et al., 1986) and in relation to the decision to act (Rajkowski et al., 2004). In experiments rats were subjected to unilateral or bilateral LC lesions to deplete one or both sides of the brain of norepinephrine (Cirelli et al., 1996; Cirelli and Tononi, 2000c, 2004). In these animals the raw EEG and its power density spectrum were not significantly affected by the lesion. However, all cortical areas depleted of norepinephrine showed a marked decrease, during wakefulness, of the expression of plasticityrelated genes such as Arc, BDNF, NGFI-A, and P-CREB, as well as of stress response genes such as HSPs and BiP. By contrast, the transcript for the translation elongation factor 2 was the only known sleeprelated transcript whose expression increased after LC lesion (Figure 12.1). In a complementary experiment in mice (Salbaum et al., 2004) the activity of the LC of one side was increased using a conditional transgenic approach. This manipulation resulted in an increased
196
C. CIRELLI AND G. TONONI
ipsilateral expression of NGFI-A in cortical and subcortical target areas. Thus, LC activity during wakefulness modulates neuronal transcription to favor synaptic potentiation and memory acquisition and to counteract cellular stress, while LC inactivity during sleep may play a permissive role to enhance brain protein synthesis. The significant effect of the noradrenergic system appears to be specific, because diffuse lesions of cortical serotoninergic fibers do not affect the expression of these genes during wakefulness (Tononi et al., 2000).
Gene expression changes after long-term sleep deprivation Gene expression profiling has also been performed in the cerebral cortex of long-term sleep-deprived rats (Cirelli et al., 2005b). Animals were kept awake for 7 days using the disk-over-water method (DOW; Rechtschaffen et al., 1983). This method uses minimal stimulation to enforce chronic sleep deprivation in the sleep-deprived rat, while it simultaneously applies to the control rat the same stimulation, but without severely limiting its sleep. The sleep-deprived and the control rat are housed each on one side of a divided horizontal disk suspended over a shallow tray of 2–3 cm deep water. EEG and electromyogram are continuously recorded to detect sleep states. When the experimental rat falls asleep, the disk is automatically rotated at low speed, awakening the rat and forcing it to walk opposite to disk rotation to avoid being carried into the water. The yoked control rat receives the same physical stimulation because it is on the same disk. However, while sleep is severely reduced (by 80–90%) in the sleep deprivation rat, the control rat can sleep whenever the sleep-deprived rat is spontaneously awake and eating, drinking, or grooming and thus its sleep is only reduced by 25–40%. By screening more than 15 000 transcripts expressed in the cerebral cortex it was found that several genes induced in long-term sleep-deprived rats code for stress response genes such as the small HSPs HSP27 and alpha-crystallin, which are induced in glial cells after different kinds of brain insults. Another large group of genes upregulated after prolonged sleep loss codes for immunoglobulins, including two autoantibodies. Aryl-sulfotransferase, an enzyme involved in the catabolism of catecholamine, is also upregulated after chronic sleep deprivation. By contrast, among the genes whose expression was downregulated in longterm sleep-deprived animals were myelin constituents, including the most abundant structural protein component of myelin, the proteolipid protein. Glial cells are often the first to respond to brain insults of different nature. The upregulation of small
HSPs suggests that prolonged sleep loss represents a significant cellular stress, as already suggested by the findings in spontaneously awake or short-term sleepdeprived rats. It is currently unclear whether this response is protective, and/or whether the decrease in several myelin markers is an indication of significant glial impairment. It is worth mentioning again that one of the most unexpected categories of sleep-related genes is indeed glial genes, including genes coding for myelin components (Figure 12.1). The presence of several antibodies, including autoantibodies, in long-term sleep-deprived rats is puzzling. Both animal and human studies show that prolonged sleep deprivation results in an activation of the immune response. In humans, 3 days of sleep deprivation produce increases in natural killer cell activity and in granulocyte and monocyte counts (Dinges et al., 1994). Rats sleep-deprived for up to 20 days with the DOW show leukocytosis with increased counts of neutrophils and monocytes, induction of proinflammatory cytokines and chemokines, and increased production of serum immunoglobulin (Ig) M, IgG, and IgA, consistent with polyclonal activation of B lymphocytes (Everson, 2005). Importantly, polyclonal B responses such those associated with chronic antigenic stimulation have the potential to induce autoimmune response. The two autoantibodies identified in long-term sleepdeprived rats are directed against nerve growth factor (NGF) and against the acetylcholine receptor (AChR), and their effects on brain tissues could contribute to some of the most common symptoms of sustained sleep loss, i.e., cognitive impairment and fatigue. Anti-NGF antibodies, when injected in the rat cerebral cortex, can produce degeneration of cortical cholinergic boutons (Debeir et al., 1999) and disrupt learning (Gutierrez et al., 1997). Moreover, transgenic mice overexpressing anti-NGF antibodies develop an agedependent neurodegenerative pathology with dementialike symptoms (Capsoni et al., 2000). The anti-AchR antibodies, on the other hand, when infused in the rat cerebral cortex, produce fatigue and ataxia (Gomez et al., 1984). Additional experiments are needed to determine whether the autoimmune response is a specific effect of the DOW method or represents a more general consequence of sustained sleep deprivation.
GENETIC STUDIES OF SLEEPAND WAKEFULNESS It has long been known, first as a result of twin studies, that many aspects of sleep are to some extent under genetic control (Table 12.2). It is now clear that these aspects include sleep duration, sleep EEG parameters, the homeostatic regulation of sleep (i.e., the response
MOLECULAR NEUROBIOLOGY OF SLEEP
197
Table 12.2 Several, but not all, studies that identified aspects of the sleep behavior that are under genetic control (see main text) Year
Study type
Major findings
Refs
1937–1951
Sleep habits in MZ and DZ twins
Geyer (1937), Gedda (1951)
1945–2005 1972
EEG spectrum and coherence in humans and animals Genetic studies of sleep in mice
1986
Genetic study of sleep in rats
1992
Single gene linked to a sleep disorder (FFI) First sleep studies in transgenic and knockout (–/–) mice
Several sleep parameters show hereditability Electrical activity as measured by the EEG shows up to 90% heritability Sleep duration and EEG differ in inbred strains REM amount differs in two inbred rat strains FFI patients carry a point mutation in the prion protein gene Prion (–/–), transgenic mice with GHRH deficiency show decreased sleep/continuity Candidates genomic regions affecting REM sleep The genes hypocretin/orexin and hypocretin receptor 2 are linked to narcolepsy Some FASPS individuals carry a mutation in hPer2, others in CKIdelta CREB activity and wakefulness are reciprocally linked in flies and rodents Fruit flies carrying mutations in the voltage-dependent Kþ channel Shaker are short sleepers A genetic variation in an enzyme involved in adenosine metabolism affects duration and intensity of human non-REM sleep
1996
1997 1999
QTL mapping study of sleep duration in mice Narcolepsy studies
2001–2005
Single gene linked to the circadian regulation of sleep
1996–2003
cAMP and CREB pathways involved in sleep regulation
2005
Single gene controls sleep need in Drosophila
2005
Genetic variation in adenosine deaminase linked to non-REM sleep and SWA in humans
Lennox et al. (1945), Vogel (1958), Maret et al. (2005) Valatx et al. (1972) Rosenberg et al. (1987) Medori et al. (1992) Tobler et al. (1996), Zhang et al. (1996) Tafti et al. (1997) Chemelli et al. (1999), Lin et al. (1999) Toh et al. (2001), Xu et al. (2005)
Cirelli et al. (1996), Cirelli and Tononi (2000c), Hendricks et al. (2001), Graves et al. (2003) Cirelli et al. (2005c)
Retey et al. (2005)
MZ, monozygotic; DZ, dizygotic; EEG, electroencephalogram; FFI, fatal familial insomnia; GHRH, growth hormone-releasing hormone; QTL, quantitative trait loci; REM, rapid eye movement; non-REM, nonrapid eye movement; FASPS, familial advanced sleep-phase syndrome; cAMP, cyclic AMP (or 30 -50 -cyclic adenosine monophosphate); CREB, cAMP response element-binding; SWA, slow-wave activity.
to sleep deprivation), and the circadian regulation of sleep (i.e., how the occurrence of sleep is timed relative to the 24-hour cycle). Only recently, however, genetic studies have started identifying the specific genes controlling sleep phenotypes. In humans, a definitive link between a gene and a sleep disorder has been established in two cases. In animals (fruit flies), at least one gene has been shown to play a major role in controlling sleep duration.
Human studies and the genetics of some sleep disorders As shown in Table 12.2, sleep studies on twins started as early as in the 1930s. They have been based either on questionnaire investigations or on polygraphic
analysis and found higher concordance in monozygotic than in dizygotic twins for several sleep parameters, from the density of REMs to total sleep duration or the duration of stages 2, 3, and 4. Twin studies have also confirmed that the rhythmic brain electrical activity as measured by the EEG is one of the most heritable characteristics in humans during sleep as well as during wakefulness. For instance, in the wake EEG, the power spectrum in the delta, theta, alpha, and beta frequency bands shows 70–90% heritability. Similarly, there are strong genetic influences on EEG coherence (reviewed in Linkowski, 1999). A study also found that humans carrying a genetic variant of adenosine deaminase, which results in reduced metabolism of adenosine to inosine, show an increase
198 C. CIRELLI AND G. TONONI in slow-wave sleep duration and in slow-wave activity Animal studies and the physiological (Retey et al., 2005). sleep phenotype There are two human sleep disorders with a clearcut genetic basis: fatal familial insomnia (FFI) and familial Animal studies have also provided evidence that sevadvanced sleep phase syndrome (FASPS). FFI is a rare eral sleep phenotypes are to some extent under genetic autosomal-dominant disease due to a point mutation at control. In reverse genetics (from genotype to phenocodon 178 of the prion gene, which causes an amino type), a single candidate gene (e.g., transcription acid substitution in the prion protein (Lugaresi et al., factors like Clock and c-fos, genes related to dopami1986; Medori et al., 1992; Montagna et al., 2003). nergic, serotonergic, histaminergic, GABAergic neuroFASPS is also transmitted in a highly penetrant transmission, the prion gene, hypocretin/orexin) is autosomal-dominant manner (Toh et al., 2001). FASPS manipulated and the effects of such manipulation on subjects have a normal duration of sleep but their cirsleep are studied in mice or flies. In almost all these cadian clock is such that the sleep cycle occurs 4 hours studies, at least one sleep parameter was found to be earlier than in normal people. Some FASPS individuals affected, although most effects were subtle (reviewed carry a serine to glycine mutation in hPer2 (human in Franken and Tafti, 2003; Shaw and Franken, 2003; Period 2), one of the canonical circadian genes. The Wisor and Kilduff, 2005). Forward genetics (from phemutation affects the ability of casein kinase I epsilon notype to genotype) is an unbiased approach to disto phosphorylate the hPER2 protein. It was recently cover new genes involved in sleep regulation. Two found that other FASPS individuals carry a mutation forward genetic methods are used, quantitative trait in the gene coding for casein kinase I delta, and that loci (QTL) analysis and mutagenesis, which can comthe mutated kinase has decreased enzymatic activity plement each other. QTL analysis starts with the crossin vitro (Xu et al., 2005). Animal studies had previing between two inbred mouse strains that usually ously demonstrated that the extent to which period prodiffer as much as possible in the trait of interest. teins are phosphorylated greatly affects their nuclear QTL analysis maps a chromosomal region that may accumulation and, thus, influences the endogenous circontain either a single gene with a major effect on cadian period. sleep or several genes with small effects. Several proviCanine narcolepsy is an autosomal-recessive, fully sional QTLs for the amount of REM sleep have been penetrant disorder due to a mutation in the hypocretin identified in mice, although the statistical power was receptor 2 gene (Lin et al., 1999). In mice, a null mutalimited by the small number of strains available tion of the prepro-hypocretin (orexin) gene produces (Table 12.2). A linkage has been found in mice between behavioral arrest and EEG patterns resembling human a QTL on chromosome 13 and the delta power rebound narcolepsy (Chemelli et al., 1999). First-degree relatives after sleep deprivation, suggesting that the homeostatic of narcoleptic patients are 20–40 times more likely to regulation of sleep need is under genetic control (Franken develop the disease. However, the low concordance et al., 2001). A recent QTL study in mice has also linked of human narcolepsy in monozygotic twins (30%) the theta frequency during REM sleep to Acads, a gene strongly suggests that nongenetic factors play a major involved in fatty acid beta oxidation (Tafti et al., 2003). role. No association has been found between human Finally, another study in mice found that a mutation in narcolepsy and polymorphisms in the genes of the the gene encoding the retinoid acid receptor beta affects hypocretinergic system, and so far only one case of the ratio between delta and theta activity during slownarcolepsy with an unusually early onset has been wave sleep (Maret et al., 2005). found to be associated with a mutation in preproIn mutagenesis screenings, the whole genome is ranhypocretin (Peyron et al., 2000). Yet, most patients domly mutated using ethane methyl sulfonate (in flies) with narcolepsy-cataplexy have low or undetectable or N-ethyl-N-nitrosourea (in mice), chemical mutagens levels of hypocretins in the cerebrospinal fluid. Morethat induce single-point mutations in spermatogonia over, narcolepsy is strongly associated with human leuwith high efficiency. The goal is to find single genes kocyte antigen (HLA) alleles, in particular with HLA that are able alone to affect the sleep phenotype signifDQB1*0602. This suggests that the deficit in hypoicantly. Mutagenesis screenings in flies use continuous cretinergic neurotransmission in human narcolepsy periods of immobility to estimate sleep time, and are could be due to an autoimmune attack. An association currently searching for single-gene mutations that can between the severity of human narcolepsy and the cataffect daily sleep amount, the response to sleep depriechol-O-methyltransferase genotype has also been vation, and the response to wake-promoting drugs. In described (reviewed in Chabas et al., 2003; Taheri, mice, the current mutagenesis screenings use either 2004). the length of continuous inactivity (in adults) or
MOLECULAR NEUROBIOLOGY OF SLEEP electromyographic recordings (in pups) to estimate the sleep/waking cycle. In flies, by screening more than 9000 mutant lines (Cirelli, 2003), it was found that mutations of Shaker decrease daily sleep amount from 10–14 hours to 3–4 hours per night (Cirelli et al., 2005c). This is the first report of a single-gene mutation that can produce such an extreme short-sleeping phenotype. Shaker encodes the alpha subunit of a tetrameric voltage-dependent potassium channel that controls membrane repolarization after action potentials, and thus may be close to the core cellular mechanisms of sleep. Importantly, Shaker-like channels are also present in mammals, and their role in the regulation of mammalian sleep is currently under study. A few studies in mice, summarized in Table 12.3, show that the Kv3 family of voltagedependent potassium channels plays a role in the generation of sleep rhythms. However, it is not known whether members of other Kv families (e.g., the Kv1 family) are also important in sleep regulation. Similarly, it is not known whether human extreme short sleepers have mutations in voltage-dependent
199
potassium channels. Intriguingly, however, in one case of Morvan’s syndrome, a rare autoimmune disorder with central symptoms, marked sleeplessness has been associated with autoantibodies against voltage-dependent potassium channels that may have crossed the blood– brain barrier (Liguori et al., 2001).
CONCLUSIONS Old and new evidence indicates that extensive and divergent changes in gene expression occur in the brain between sleep and wakefulness. Transcripts differentially expressed in sleeping and awake rats belong to diverse and often complementary functional categories, suggesting that sleep and wakefulness favor different cellular processes. Wakefulness-related transcripts may help the brain to face high energy demand, the need for synaptic potentiation in the acquisition of new information, as well as the cellular stress associated with these processes. Sleep-related transcripts suggest that sleep is far from being a quiescent state of global inactivity, and may play a positive role in
Table 12.3 Studies that analyzed the role in sleep regulation of different subunits of the Kv family of potassium channels Year
Study type
Major findings
References
1999
Kv 3.1, mouse
Joho et al. (1999)
2002
Kv 3.2, mouse
2004
Kv 3.1, 3.3, mouse
Sleep EEG analysis in mice lacking the potassium channel subunit Kv 3.1. Kv 3.1 potassium channels are expressed in fast-spiking, parvalbumincontaining interneurons in cortex, hippocampus, striatum, and the thalamic reticular nucleus. Kv 3.1 channels contribute to short-duration action potentials, fast afterhyperpolarizations, and brief refractory periods enhancing the capability in these neurons for high-frequency firing. Homozygous Kv 3.1(–/–) mice show: (1) three- to fourfold increase in absolute and relative spectral power in the gamma frequency range (20–60 Hz; effect mainly in W); (2) 20–50% reduction of EEG power in the slow delta range (2–3 Hz; in all behavioral states) Sleep EEG analysis in mice lacking the potassium channel subunit Kv 3.2. Kv 3.2 subunits are expressed in specific neuronal populations such as thalamocortical neurons and fast-spiking GABAergic interneurons of the neocortex and hippocampus. Kv 3.2 (–/–) mice show lower EEG power density in the frequency range 3.25–6 Hz in non-REM sleep and 3.25–5 z in REM sleep. No change of EEG power in W. Normal response to 6 hours SD Kv 3.1/Kv 3.3-deficient mice show motor dysfunction (ataxia, myoclonus, tremor) and hyperactivity (spontaneous and when exposed to a novel environment); the “restlessness” that is particularly prominent during the light period, with a doubling of ambulatory and stereotypic activity, accompanied by a 40% sleep reduction; Kv 3.1-channel subunits are primarily responsible for the increased motor drive and the reduction in sleep time
EEG, electroencephalogram; W, wakefulness; non-REM, nonrapid eye movement; SD, sleep deprivation.
Vyazovskiy et al. (2002)
Espinosa et al. (2004)
200
C. CIRELLI AND G. TONONI
brain protein synthesis and in complementary aspects of neural plasticity such as synaptic consolidation and downscaling. Sleep-related transcripts also suggest that sleep may be involved in membrane trafficking and maintenance. Genetic studies in humans have for a long time suggested that several sleep phenotypes are under genetic control. Recent studies in flies and mice demonstrate that indeed single-gene mutations can powerfully affect sleep need and the response to sleep deprivation. Fly studies suggest that voltage-dependent potassium channels may play a crucial role in determining daily sleep amount, and their role in mammalian sleep is currently being investigated.
ACKNOWLEDGMENT This work was supported by the National Institutes of Mental Health and the National Institute of General Medical Sciences.
REFERENCES Aston-Jones G, Bloom FE (1981a). Activity of norepinephrinecontaining locus coeruleus neurons in behaving rats anticipates fluctuations in the sleep–waking cycle. J Neurosci 1: 876–886. Aston-Jones G, Bloom FE (1981b). Norepinephrine-containing locus coeruleus neurons in behaving rats exhibit pronounced responses to non-noxious environmental stimuli. J Neurosci 1: 887–900. Attwell D, Laughlin SB (2001). An energy budget for signaling in the grey matter of the brain. J Cereb Blood Flow Metab 21: 1133–1145. Benington JH, Heller HC (1995). Restoration of brain energy metabolism as the function of sleep. Prog Neurobiol 45: 347–360. Bobillier P, Sakai F, Seguin S et al. (1971). Deprivation of paradoxical sleep and in vitro cerebral protein synthesis in the rat. Life Sci 10: 1349–1357. Borbe´ly AA, Achermann P (1999). Sleep homeostasis and models of sleep regulation. J Biol Rhythms 14: 557–568. Capsoni S, Ugolini G, Comparini A et al. (2000). Alzheimerlike neurodegeneration in aged antinerve growth factor transgenic mice. Proc Natl Acad Sci U S A 97: 6826–6831. Chabas D, Taheri S, Renier C et al. (2003). The genetics of narcolepsy. Annu Rev Genomics Hum Genet 4: 459–483. Chemelli RM, Willie JT, Sinton CM et al. (1999). Narcolepsy in orexin knockout mice: molecular genetics of sleep regulation. Cell 98: 437–451. Christopherson KS, Ullian EM, Stokes CC et al. (2005). Thrombospondins are astrocyte-secreted proteins that promote CNS synaptogenesis. Cell 120: 421–433. Cirelli C (2003). Searching for sleep mutants of Drosophila melanogaster. Bioessays 25: 940–949.
Cirelli C, Tononi G (1998). Differences in gene expression between sleep and waking as revealed by mRNA differential display. Mol Brain Res 56: 293–305. Cirelli C, Tononi G (2000a). On the functional significance of c-fos induction during the sleep/waking cycle. Sleep 23: 453–469. Cirelli C, Tononi G (2000b). Gene expression in the brain across the sleep–waking cycle. Brain Res 885: 303–321. Cirelli C, Tononi G (2000c). Differential expression of plasticity-related genes in waking and sleep and their regulation by the noradrenergic system. J Neurosci 20: 9187–9194. Cirelli C, Tononi G (2004). Locus ceruleus control of statedependent gene expression. J Neurosci 24: 5410–5419. Cirelli C, Pompeiano M, Tononi G (1993). Fos-like immunoreactivity in the rat brain in spontaneous wakefulness and sleep. Arch Ital Biol 131: 327–330. Cirelli C, Pompeiano M, Tononi G (1995). Sleep deprivation and c-fos expression in the rat brain. J Sleep Res 4: 92–106. Cirelli C, Pompeiano M, Tononi G (1996). Neuronal gene expression in the waking state: a role for the locus coeruleus. Science 274: 1211–1215. Cirelli C, Gutierrez CM, Tononi G (2004). Extensive and divergent effects of sleep and wakefulness on brain gene expression. Neuron 41: 35–43. Cirelli C, LaVaute TM, Tononi G (2005a). Sleep and wakefulness modulate gene expression in Drosophila. J Neurochem 94: 1411–1419. Cirelli C, Faraguna U, Tononi G (2005b). Molecular correlates of long-term sleep deprivation in rats: a genomewide analysis. Sleep 28 (Suppl): A339. Cirelli C, Bushey D, Hill S et al. (2005c). Reduced sleep in Drosophila Shaker mutants. Nature 434: 1087–1092. Debeir T, Saragovi HU, Cuello AC (1999). A nerve growth factor mimetic TrkA antagonist causes withdrawal of cortical cholinergic boutons in the adult rat. Proc Natl Acad Sci U S A 96: 4067–4072. Dinges DF, Douglas SD, Zaugg L et al. (1994). Leukocytosis and natural killer cell function parallel neurobehavioral fatigue induced by 64 hours of sleep deprivation. J Clin Invest 93: 1930–1939. Drucker-Colı´n RR, Spanis CW, Cotman CW et al. (1975). Changes in protein levels in perfusates of freely moving cats: relation to behavioral states. Science 187: 963–965. Erecin˜ska M, Silver IA (1989). ATP and brain function. J Cereb Blood Flow Metab 9: 2–19. Espinosa F, Marks G, Heintz N et al. (2004). Increased motor drive and sleep loss in mice lacking Kv3-type potassium channels. Genes Brain Behav 3: 90–100. Everson CA (2005). Clinical assessment of blood leukocytes, serum cytokines, and serum immunoglobulins as responses to sleep deprivation in laboratory rats. Am J Physiol Regul Integr Comp Physiol 289: R1054–R1063. Franken P, Tafti M (2003). Genetics of sleep and sleep disorders. Front Biosci 8: e381–e397. Franken P, Chollet D, Tafti M (2001). The homeostatic regulation of sleep need is under genetic control. J Neurosci 21: 2610–2621.
MOLECULAR NEUROBIOLOGY OF SLEEP Gedda L (1951). Studio Dei Gemelli, Rome: Orizzonte Medico, p. 538. Geyer H (1937). Ueber den Schlaf von Zwillingen. Z Indukt Abstamm Vererbungsl 78: 524–527. Giuditta A, Rutigliano B, Vitale-Neugebauer A (1980). Influence of synchronized sleep on the biosynthesis of RNA in two nuclear classes isolated from rabbit cerebral cortex. J Neurochem 35: 1259–1266. Gomez CM, Wollmann RL, Richman DP (1984). Induction of the morphologic changes of both acute and chronic experimental myasthenia by monoclonal antibody directed against acetylcholine receptor. Acta Neuropathol (Berl) 63: 131–143. Graves LA, Hellman K, Veasey S et al. (2003). Genetic evidence for a role of CREB in sustained cortical arousal. J Neurophysiol 90: 1152–1159. Gutierrez H, Miranda MI, Bermudez-Rattoni F (1997). Learning impairment and cholinergic deafferentation after cortical nerve growth factor deprivation. J Neurosci 17: 3796–3803. Guzowski JF, Lyford GL, Stevenson GD et al. (2000). Inhibition of activity-dependent Arc protein expression in the rat hippocampus impairs the maintenance of long-term potentiation and the consolidation of long-term memory. J Neurosci 20: 3993–4001. Hendricks JC, Williams JA, Panckeri K et al. (2001). A noncircadian role for camp signaling and CREB activity in Drosophila rest homeostasis. Nat Neurosci 4: 1108–1115. Hering H, Lin CC, Sheng M (2003). Lipid rafts in the maintenance of synapses, dendritic spines, and surface AMPA receptor stability. J Neurosci 23: 3262–3271. Herrera DG, Robertson HA (1996). Activation of c-fos in the brain. Prog Neurobiol 50: 83–107. Huber R, Ghilardi MF, Massimini M et al. (2004). Local sleep and learning. Nature 430: 78–81. Joho RH, Ho CS, Marks GA (1999). Increased gamma- and decreased delta-oscillations in a mouse deficient for a potassium channel expressed in fast-spiking interneurons. J Neurophysiol 82: 1855–1864. Kang H, Sun LD, Atkins CM et al. (2001). An important role of neural activity-dependent CaMKIV signaling in the consolidation of long-term memory. Cell 106: 771–783. Kavanau JL (1997). Memory, sleep and the evolution of mechanisms of synaptic efficacy maintenance. Neuroscience 79: 7–44. Kelly MP, Deadwyler SA (2002). Acquisition of a novel behavior induces higher levels of Arc mRNA than does overtrained performance. Neuroscience 110: 617–626. Korte M, Griesbeck O, Gravel C et al. (1996). Virusmediated gene transfer into hippocampal CA1 region restores long-term potentiation in brain-derived neurotrophic factor mutant mice. Proc Natl Acad Sci U S A 93: 12547–12552. Krueger JM, Obal F Jr, Kapas L et al. (1995). Brain organization and sleep function. Behav Brain Res 69: 177–186. Lamprecht R, LeDoux J (2004). Structural plasticity and memory. Nat Rev Neurosci 5: 45–54.
201
Landis CA, Collins BJ, Cribbs LL et al. (1993). Expression of Egr-1 in the brain of sleep deprived rats. Mol Brain Res 17: 300–306. Lee AK, Wilson MA (2002). Memory of sequential experience in the hippocampus during slow wave sleep. Neuron 36: 1183–1194. Lennox W, Gibbs E, Gibbs F (1945). The brain-wave pattern an hereditary trait: evidence from 74 “normal” pairs of twins. J Hered 36: 233–243. Liguori R, Vincent A, Clover L et al. (2001). Morvan’s syndrome: peripheral and central nervous system and cardiac involvement with antibodies to voltage-gated potassium channels. Brain 124: 2417–2426. Lin L, Faraco J, Li R et al. (1999). The sleep disorder canine narcolepsy is caused by a mutation in the hypocretin (orexin) receptor 2 gene. Cell 98: 365–376. Linkowski P (1999). EEG sleep patterns in twins. J Sleep Res 8 (Suppl 1): 11–13. Lowry OH (1975). Energy metabolism in brain and its control. In: DH Ingvar, LA Lassen (Eds.), Brain Work: The Coupling of Function, Metabolism, and Blood Flow in the Brain. Academic Press, New York, pp. 48–64. Lugaresi E, Medori R, Montagna P et al. (1986). Fatal familial insomnia and dysautonomia with selective degeneration of thalamic nuclei. N Engl J Med 315: 997–1003. Mackiewicz M, Sollars PJ, Ogilvie MD et al. (1996). Modulation of IL-1 beta gene expression in the rat CNS during sleep deprivation. Neuroreport 7: 529–533. McNay EC, Fries TM, Gold PE (2000). Decreases in rat extracellular hippocampal glucose concentration associated with cognitive demand during a spatial task. Proc Natl Acad Sci U S A 97: 2881–2885. Maquet P (1995). Sleep function(s) and cerebral metabolism. Behav Brain Res 69: 75–83. Maret S, Franken P, Dauvilliers Y et al. (2005). Retinoic acid signaling affects cortical synchrony during sleep. Science 310: 111–113. Mauch DH, Nagler K, Schumacher S et al. (2001). CNS synaptogenesis promoted by glia-derived cholesterol. Science 294: 1354–1357. Medori R, Tritschler HJ, LeBlanc A et al. (1992). Fatal familial insomnia, a prion disease with a mutation at codon 178 of the prion protein gene. N Engl J Med 326: 444–449. Merchant-Nancy H, Vazquez J, Aguilar-Roblero R et al. (1992). C-fos proto-oncogene changes in relation to REM sleep duration. Brain Res 579: 342–346. Montagna P, Gambetti P, Cortelli P et al. (2003). Familial and sporadic fatal insomnia. Lancet Neurol 2: 167–176. Moruzzi G (1966). The functional significance of sleep with particular regard to the brain’s mechanisms underlying consciousness. In: JC Eccles (Ed.), Brain and Conscious Experience. Springer, New York, pp. 345–388. Naidoo N, Giang W, Galante RJ et al. (2005). Sleep deprivation induces the unfolded protein response in mouse cerebral cortex. J Neurochem 92: 1150–1157. Nakanishi H, Sun Y, Nakamura RK et al. (1997). Positive correlations between cerebral protein synthesis rates and deep sleep in Macaca mulatta. Eur J Neurosci 9: 271–279.
202
C. CIRELLI AND G. TONONI
Neuner-Jehle M, Rhyner TA, Borbely AA (1995). Sleep deprivation differentially alters the mRNA and protein levels of neurogranin in rat brain. Brain Res 685: 143–153. Neuner-Jehle M, Denizot JP, Mallet J (1996). Neurogranin is locally concentrated in rat cortical and hippocampal neurons. Brain Res 733: 149–154. Nikonova EV, Vijayasarathy C, Zhang L et al. (2005). Differences in activity of cytochrome C oxidase in brain between sleep and wakefulness. Sleep 28: 21–27. O’Hara BF, Young KA, Watson FL et al. (1993). Immediate early gene expression in brain during sleep deprivation: preliminary observations. Sleep 16: 1–7. Panov A (1982). RNA and protein content of brain stem cells after sleep deprivation. Riv Biol 75: 95–99. Patterson SL, Abel T, Deuel TA et al. (1996). Recombinant BDNF rescues deficits in basal synaptic transmission and hippocampal LTP in BDNF knockout mice. Neuron 16: 1137–1145. Peyron C, Faraco J, Rogers W et al. (2000). A mutation in a case of early onset narcolepsy and a generalized absence of hypocretin peptides in human narcoleptic brains. Nat Med 6: 991–997. Pompeiano M, Cirelli C, Tononi G (1992). Effects of sleep deprivation on fos-like immunoreactivity in the rat brain. Arch Ital Biol 130: 325–335. Pompeiano M, Cirelli C, Tononi G (1994). Immediate-early genes in spontaneous wakefulness and sleep: expression of c-fos and NGFI-A mRNA and protein. J Sleep Res 3: 80–96. Pompeiano M, Cirelli C, Ronca-Testoni S et al. (1997). NGFI-A expression in the rat brain after sleep deprivation. Mol Brain Res 46: 143–153. Rajkowski J, Majczynski H, Clayton E et al. (2004). Activation of monkey locus coeruleus neurons varies with difficulty and performance in a target detection task. J Neurophysiol 92: 361–371. Ramm P, Frost BJ (1983). Regional metabolic activity in the rat brain during sleep–wake activity. Sleep 6: 196–216. Ramm P, Smith CT (1990). Rates of cerebral protein synthesis are linked to slow wave sleep in the rat. Physiol Behav 48: 749–753. Rasmussen K, Morilak DA, Jacobs BL (1986). Single unit activity of locus coeruleus neurons in the freely moving cat. I. During naturalistic behavior and in response to simple and complex stimuli. Brain Res 371: 324–334. Rechtschaffen A, Gilliland MA, Bergmann BM et al. (1983). Physiological correlates of prolonged sleep deprivation in rats. Science 221: 182–184. Reich P, Driver JK, Karnovsky ML (1967). Sleep: effects on incorporation of inorganic phosphate into brain fractions. Science 157: 336–338. Reich P, Geyer SJ, Steinbaum L et al. (1973). Incorporation of phosphate into rat brain during sleep and wakefulness. J Neurochem 20: 1195–1205. Retey JV, Adam M, Honegger E et al. (2005). A functional genetic variation of adenosine deaminase affects the duration and intensity of deep sleep in humans. Proc Natl Acad Sci U S A 102: 15676–15681.
Rhyner TA, Borbely AA, Mallet J (1990). Molecular cloning of forebrain mRNAs which are modulated by sleep deprivation. Eur J Neurosci 2: 1063–1073. Rosenberg RS, Bergmann BM, Son HJ et al. (1987). Strain differences in the sleep of rats. Sleep 10: 537–541. Salbaum JM, Cirelli C, Walcott E et al. (2004). Chlorotoxinmediated disinhibition of noradrenergic locus coeruleus neurons using a conditional transgenic approach. Brain Res 1016: 20–32. Sejnowski TJ, Destexhe A (2000). Why do we sleep? Brain Res 886: 208–223. Shaw PJ, Franken P (2003). Perchance to dream: solving the mystery of sleep through genetic analysis. J Neurobiol 54: 179–202. Shaw PJ, Cirelli C, Greenspan RJ et al. (2000). Correlates of sleep and waking in Drosophila melanogaster. Science 287: 1834–1837. Sheng M, Greenberg ME (1990). The regulation and function of c-fos and other immediate early genes in the nervous system. Neuron 4: 477–485. Shiromani PJ, Kilduff TS, Bloom FE et al. (1992). Cholinergically induced REM sleep triggers Fos-like immunoreactivity in dorsolateral pontine regions associated with REM sleep. Brain Res 580: 351–357. Silva AJ, Kogan JH, Frankland PW et al. (1998). CREB and memory. Annu Rev Neurosci 21: 127–148. Steriade M, Timofeev I (2003). Neuronal plasticity in thalamocortical networks during sleep and waking oscillations. Neuron 37: 563–576. Stickgold R, Hobson JA, Fosse R et al. (2001). Sleep, learning, and dreams: off-line memory reprocessing. Science 294: 1052–1057. Tafti M, Franken P, Kitahama K et al. (1997). Localization of candidate genomic regions influencing paradoxical sleep in mice. Neuroreport 8: 3755–3758. Tafti M, Petit B, Chollet D et al. (2003). Deficiency in shortchain fatty acid beta-oxidation affects theta oscillations during sleep. Nat Genet 34: 320–325. Taheri S (2004). The genetics of sleep disorders. Minerva Med 95: 203–212. Terao A, Steininger TL, Hyder K et al. (2003). Differential increase in the expression of heat shock protein family members during sleep deprivation and during sleep. Neuroscience 116: 187–200. Tobler I, Gaus SE, Deboer T et al. (1996). Altered circadian activity rhythms and sleep in mice devoid of prion protein. Nature 380: 639–642. Toh KL, Jones CR, He Y et al. (2001). An hper2 phosphorylation site mutation in familial advanced sleep phase syndrome. Science 291: 1040–1043. Tononi G, Cirelli C (2006). Sleep function and synaptic homeostasis. Sleep Med Rev 10: 49–62. Tononi G, Cirelli C, Shaw PJ (2000). The molecular correlates of sleep, waking, and sleep deprivation. In: A Borbe´ly, O Hayaishi, TJ Sejnowski et al. (Eds.), Human Frontier Workshop VIII, The Regulation of Sleep. Human Frontier Scientific Press, Strasbourg, pp. 155–167.
MOLECULAR NEUROBIOLOGY OF SLEEP Toppila J, Stenberg D, Alanko L et al. (1995). REM sleep deprivation induces galanin gene expression in the rat brain. Neurosci Lett 183: 171–174. Toppila J, Asikainen M, Alanko L et al. (1996). The effect of REM sleep deprivation on somatostatin and growth hormone-releasing hormone gene expression in the rat hypothalamus. J Sleep Res 5: 115–122. Valatx JL, Bugat R, Jouvet M (1972). Genetic studies of sleep in mice. Nature 238: 226–227. Van Dongen HPA, Maislin G, Mullington JM et al. (2003). The cumulative cost of additional wakefulness: dose–response effects on neurobehavioral functions and sleep physiology from chronic sleep restriction and total sleep deprivation. Sleep 26: 117–126. Vitale-Neugebauer A, Giuditta A, Vitale B et al. (1970). Pattern of RNA synthesis in rabbit cortex during sleep. J Neurochem 17: 1263–1273. Vogel F (1958). Uber die Erblichkeit des normalen Electroencephalogramms. Thieme, Stuttgart, Germany. Voronka GSH (1971). Effect of prolonged phenamineinduced insomnia and subsequent sleep on the protein content of neurons and their glial cell-satellites of the brain supraoptic and red nuclei. Fiziol Zh SSSR Im I M Sechenova 57: 962–968.
203
Vyazovskiy VV, Deboer T, Rudy B et al. (2002). Sleep EEG in mice that are deficient in the potassium channel subunit K.v.3.2. Brain Res 947: 204–211. Walker MP, Brakefield T, Morgan A et al. (2002). Practice with sleep makes perfect: sleep-dependent motor skill learning. Neuron 35: 205–211. Wilson Horch H, Kru¨ttgen A, Portbury SD et al. (1999). Destabilization of cortical dendrites and spines by BDNF. Neuron 23: 353–364. Wisor JP, Kilduff TS (2005). Molecular and genetic advances in sleep research and their relevance to sleep medicine. Sleep 28: 357–367. Xu D, Hopf C, Reddy R, Cho RW et al. (2003). Narp and NP1 form heterocomplexes that function in developmental and activity-dependent synaptic plasticity. Neuron 39: 513–528. Xu Y, Padiath QS, Shapiro RE et al. (2005). Functional consequences of a ckidelta mutation causing familial advanced sleep phase syndrome. Nature 434: 640–644. Zhang J, Obal F Jr, Fang J et al. (1996). Non-rapid eye movement sleep is suppressed in transgenic mice with a deficiency in the somatotropic system. Neurosci Lett 220: 97–100.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 13
Manifestations and functional implications of sleep homeostasis ALEXANDER A. BORBE´LY * AND IRENE TOBLER Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland
DEFINITION Cannon (1932) defined homeostasis in physiology as “the coordinated physiologic processes which maintain most of the steady states in the organism.” The term “sleep homeostasis” posits that sleep strives to maintain a constant level by variation of its duration and intensity. This concept is based on the observation that a sleep deficit results in an increase of the intensity and duration of subsequent sleep, whereas excess sleep has the opposite effect. Due to sleep homeostasis sleep propensity is maintained within a certain range. Deviation in either direction leads to a compensatory response. The term was coined in 1980 on the basis of animal studies (Borbe´ly, 1980). A search in the Web of Science (www.isiknowledge.com) reveals that its use has continuously increased over the years. In 2005 it appeared in more than 100 papers.
PHYSIOLOGICAL CORRELATES OF SLEEP HOMEOSTASIS History Blake and Gerard (1937) reported that, across the sleep episode, the predominance of slow waves paralleled the arousal threshold. When slow waves were at their maximum a short time after sleep onset, subjects were most difficult to arouse. In the course of the night, slow waves exhibited a monotonic decline. The low-frequency electroencephalogram (EEG) seems to represent therefore a measure of sleep depth. This interpretation was confirmed in a number of studies.
*
Slow-wave activity in non-REM sleep as a marker of sleep homeostasis With the advent of the technical possibilities to perform all-night spectral analysis of the sleep EEG, slow waves could be quantified and their time course delineated (Borbe´ly et al., 1981). Slow-wave activity (SWA) was defined as the power density in the 0.75–4.5 Hz range. By plotting its mean value per nonrapid eye movement (non-REM) sleep episode, a monotonic decline over the first three cycles was shown (Figure 13.1). It has been known for a long time that sleep deprivation gives rise to increased slow-wave sleep (SWS; non-REM sleep stage 3 and 4) in the recovery night (see Borbe´ly, 1982, for a review of the older literature). The extent of SWS increase is a function of the duration of prior waking (Webb and Agnew, 1971). The assessment of slow waves by spectral analysis made it possible to quantify the response to sleep deprivation. Various studies using total or partial sleep deprivation protocols were performed (Borbe´ly and Achermann, 2005). They were complemented by nap studies. Daytime naps scheduled at 2-hour intervals throughout the day provided evidence for a monotonic rise of SWA (Beersma et al., 1987; Dijk et al., 1987a). Moreover, daytime naps led to a reduction of SWA during the subsequent nighttime sleep (see references in Werth et al., 1996). Taken together these studies confirmed that SWA is a function of prior waking (Dijk et al., 1990; Dijk, 1995). The regulation of slow waves can be analyzed also within a sleep episode (Achermann and Borbe´ly, 1987). At the beginning of the first non-REM sleep episode there is a gradual buildup of SWA as sleep
Correspondence to: Alexander A. Borbe´ly, M.D., University of Zurich, Institute of Pharmacology and Toxicology, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland. Tel. þ41 1 635 5960, Fax: þ41 1 635 5707, E-mail: borbely@pharma. unizh.ch
A.A. BORBE´LY AND I. TOBLER
206
HUMAN
(µV2/Hz)
RAT
W N R
400
400
300
300
200
200
100
100 0
0 0
300 250 200 150
2
4
6
8
0
10 12
350
350
300
300
250
250
200
200
150
150
100
100
50
50
2
4
6
8
10
12
100 50
0 0
2
4
6
8
10
12 0
2
4
6
8
10
12
Hours
0 1
2
3
4
5
6
7
1
2
3
4
5
6
7
Episode
Fig. 13.1. Time course of slow-wave activity (SWA) in sleep electroencephalogram (EEG) of rat and human under baseline conditions (left) and after sleep deprivation (right). SWA is defined as EEG power density in the frequency range of 0.75–4.0 Hz for rat and 0.75–4.5 Hz for human. Top left: SWA (bar represents 1000 mV2/Hz) and the three vigilance states (waking, W; nonrapid eye movement (non-REM) sleep, N; and REM sleep, R) during the 12-hour light period, the rat’s main sleep period. Left panel, baseline; right panel, recovery from 24-hour sleep deprivation. Bottom left: SWA in non-REM sleep (mean values with SEM of 9 rats plotted for 2-hour intervals; mean baseline value 100%). Top right: SWA during a baseline night and during recovery from 36-hour wakefulness (mean of 9 subjects). Bottom right: mean SWA per non-REM sleep episode (mean baseline value 100%). Note the progressive decline of SWA in the course of the sleep period in both species, and the significant increase of SWA compared to baseline during recovery from prolonged wakefulness. (Adapted from Franken et al. (1991a) and Dijk et al. (1990).)
intensifies. The rate of buildup is a function of prior waking and sleep. In the recovery night following sleep deprivation, the buildup rate is steeper than during baseline. Also in the course of the night, the buildup rate declines over consecutive non-REM sleep episodes (Achermann et al., 1993). It is possible to demonstrate the intrasleep regulation of SWA by selective deprivation protocols. Thus suppression of slow waves by acoustic stimuli during the first 3 hours of sleep resulted in a prominent rise of SWA after discontinuation of the stimuli (Dijk et al., 1987b). Sleep homeostasis is not restricted to humans (Figure 13.1). A considerable number of animal studies showed that EEG SWA in non-REM sleep is a function of prior waking and sleep (Tobler, 2005). Sleep deprivation has been a common experimental tool. This manipulation leads to a minor increase in sleep duration. The most salient feature of recovery sleep is the increase of slow waves in the non-REM sleep EEG; this was first demonstrated in the rabbit (Pappenheimer et al., 1975), then extensively documented in the rat (Borbe´ly and Neuhaus, 1979; Friedman et al., 1979) and, more recently, in several mouse strains (Franken et al., 1998, 2001; Huber et al., 2000a).
In animals, SWA is highest at the beginning of the daily sleep period. In nocturnal rodents (e.g., the rat, hamster, and inbred mouse strains) SWA is high at light onset. Conversely, in the diurnal chipmunk (Dijk and Daan, 1989) the highest SWA values occur at the beginning of the dark period. Irrespective of the nocturnal or diurnal preference for sleep, SWA shows a progressive decline interrupted by waking bouts that are typical for most mammals. In animals exhibiting little or no diurnal or nocturnal sleep preference (e.g., rabbit, guinea pig, cat, and blind mole rat (Tobler and Scherschlicht, 1990; Tobler et al., 1990, 1993, 1998), the decline of SWA is minor or absent. Changing the duration of the photoperiod in the rat and Djungarian hamster resulted in a redistribution of sleep and SWA while the total amount of sleep was maintained (Franken et al., 1995; Deboer et al., 2000).
Sleep homeostasis is independent of the circadian system Circadian rhythms can be abolished by lesioning the suprachiasmatic nuclei (SCN). To explore the relationship between sleep homeostasis and circadian rhythmicity,
207
50
150
100
100
SWA (%)
Number of brief awakenings
MANIFESTATIONS AND FUNCTIONAL IMPLICATIONS OF SLEEP HOMEOSTASIS rats were subjected to SCN lesions. This intervention led to a disruption of their circadian rest–activity rhythm. The arrhythmic animals were implanted with electrodes to record their sleep EEG during baseline and after a 24-hour sleep deprivation period (Mistlberger et al., 1983; Tobler et al., 1983; Trachsel et al., 1992). Both SWA in non-REM sleep and the amount of REM sleep were enhanced by extended waking. These results demonstrate that an intact circadian rhythm is not a prerequisite for sleep homeostasis. This does not mean that the homeostatic and circadian facets of sleep regulation do not interact. This interaction can be explored in “conflict experiments.” In the rat, recovery from a 24-hour sleep deprivation period can be scheduled to begin either at the onset or in the middle of the dark period, the circadian period in which waking predominates (Borbe´ly and Neuhaus, 1979; Trachsel et al., 1986). SWA showed a rebound in two stages: an immediate peak was followed by a waking episode, and then a second, delayed increase occurred at light onset. Recovery sleep after 12 hours sleep deprivation ending at the end of either the light period or dark period elicits different amounts of recovery sleep. However, slowwave energy, the amount of SWA within sleep, reaches the same level after both schedules despite the different circadian timing of the recovery phase (Vyazovskiy and Tobler, 2005). The relationship between circadian and homeostatic sleep regulation has been investigated in neurophysiological experiments. Simultaneous recordings of sleep stages and neuronal activity in the SCN of the rat demonstrated a feedback from sleep to the circadian pacemaker (Deboer et al., 2003). In addition to SWA sleep homeostasis also has behavioral correlates. Sleep continuity is a function of prior waking and sleep. In the rat, the frequency of short waking episodes was used as a measure. A 24-hour sleep deprivation period reduced the frequency of waking episodes shorter than 32 seconds during recovery sleep (Trachsel et al., 1991). Similar experiments in the rat and other rodents (guinea pigs and laboratory mice) showed that the reduction in the number of brief awakenings correlated with the increase of SWA (Franken et al., 1991a; Trachsel et al., 1991; Tobler et al., 1993, 1996). This inverse relationship indicates that brief awakenings represent a behavioral correlate of sleep intensity (Franken et al., 1991a; Figure 13.2). In mice such brief awakenings or microarousals have been shown to occur independently of breathing irregularities (Le´na et al., 2004). Another correlate of sleep homeostasis is motor activity during sleep. In humans, motor activity is reduced during recovery sleep after sleep deprivation (Naitoh et al., 1973). Similar results were obtained in the dog (Tobler and Sigg, 1986), rat (Borbe´ly and Neuhaus, 1979), and mouse (Palchykova et al., 2006). In mice also
nBA SWA 50
150 48
60
72
84
96
Time (hours)
Fig. 13.2. Sleep continuity in the rat is affected by sleep deprivation. The curves represent mean values of 10 rats recorded for 48 hours during recovery from 24 hours’ sleep deprivation. The number of brief awakenings (nBA) decreases under sleep pressure (note inverse scale), and the curve is negatively correlated with slow-wave activity (SWA) in nonrapid eye movement sleep. SWA is expressed as a percentage of the 24-hour baseline mean. (Adapted from Franken et al. (1991a).)
the amount of rest and its consolidation were increased after sleep deprivation (Palchykova et al., 2006). Recording motor activity is useful in experiments in which polysomnography is not possible or in studies of animals in which sleep cannot be defined by electrophysiological criteria (see below).
MODELING SLEEP REGULATION The two-process model postulates that a homeostatic process (process S) rises during waking and declines during sleep (Figure 13.3). It interacts with a circadian process (process C) that is independent of sleep and waking. The time course of the homeostatic variable S was derived from EEG SWA. Different aspects of human sleep regulation were simulated by the original qualitative version of the two-process model (Borbe´ly, 1982). In the quantitative version process S varies between an upper and a lower threshold that are modulated by a circadian process (Daan and Beersma, 1984; Daan et al., 1984). This model is able to account for such diverse phenomena as recovery from sleep deprivation, circadian phase dependence of sleep duration, sleep during shift work, sleep fragmentation during continuous bed rest, and internal desynchronization in the absence of time cues (Daan et al., 1984). The two-process model triggered numerous experimental studies to test its predictions. For example, it was applied to predict the response of habitual short and long sleepers to sleep deprivation (Aeschbach et al., 1996, 2001). An elaborated version of the model was subjected to an optimization procedure (Achermann et al., 1993) yielding in general a close fit between
A.A. BORBE´LY AND I. TOBLER
208
has been applied to the mouse to analyze the dynamics underlying the buildup and dissipation of sleep pressure in different strains (Huber et al., 2000a; Franken et al., 2001).
S – C Waking 7
Sleep 23
Waking 7
CORRELATES OF SLEEP HOMEOSTASIS IN THE WAKING EEG
Sleep 23
7
S – C Sleep
Waking 7
23 7 Time of day
23
8
Fig. 13.3. Two-process model of sleep regulation. The homeostatic process S (represented by the hourglass) increases during wakefulness and declines exponentially during sleep. The circadian process C (represented by the clock face) interacts with process S and delimits the threshold for awakening. The lower panel represents an episode of prolonged wakefulness. Process S increases according to a saturating exponential function until the onset of recovery sleep. The high level of S at sleep onset corresponds to the increased sleep intensity.
simulated and empirical SWA data and their time course. Also the occurrence of late SWA peaks during extended sleep could be accounted for. The basic assumption of the two-process model, that a homeostatic and a circadian process underlie sleep, was validated by the forced desynchrony protocol in which sleep episodes are scheduled to occur at different circadian phases. This allows the separation of homeostatic (i.e., sleep–waking-dependent) and circadian components of sleep and sleep EEG. Various claims of the two-process model were supported by experimental data (Dijk and Czeisler, 1995). For example, SWA proved to be determined mainly by a homeostatic (i.e., sleep–waking-dependent) factor, whereas the REM/non-REM sleep ratio was shown to be controlled by both homeostatic and circadian factors. The two-process model was also successfully applied to animal sleep. Its original version was based on an extensive data set derived from experiments in the rat (Borbe´ly, 1980). The time course of SWA under baseline conditions and after sleep deprivation could be closely simulated (Franken et al., 1991b). The model
While SWA (i.e., power in the delta band) is the homeostatic marker in the sleep EEG, theta activity (i.e., power in the theta band) is the marker in the ˚ kerstedt, human waking EEG. Total (Torsvall and A 1987) or partial (Brunner et al., 1993) sleep deprivation enhances power in the theta and alpha band. Spectral analysis revealed that during prolonged waking the largest changes in the EEG occur in the theta band (see Borbe´ly and Achermann, 1999, for review; Finelli et al., 2000). Their time course can be approximated by a saturating exponential function (Cajochen et al., 1995). In contrast to SWA in the sleep EEG, theta in the waking EEG undergoes circadian modulation in addition to the homeostatic factor (Aeschbach et al., 1997, 2001; Finelli et al., 2000; Cajochen et al., 2001, 2002). An analysis of individuals subjected to sleep deprivation revealed that the rise rate of theta activity in the waking EEG is correlated with the increase of SWA in the first non-REM sleep episode of recovery sleep (Finelli et al., 2000). Both effects were largest in frontal areas (Figure 13.4). These observations indicate that theta activity in waking and SWA in sleep may be markers of a common homeostatic sleep process. In rodents, SWA is present also in the waking EEG. It increases as a function of waking. However, this increase does not predict the subsequent SWA increase during recovery (Figure 13.5). Instead, the rise in power in the theta band (5–7 Hz) during quiet wakefulness epochs correlated with SWA in subsequent non-REM sleep (Vyazovskiy and Tobler, 2005).
USE-DEPENDENT CHANGES SWA in the sleep EEG increases as a function of prior waking. Is this effect merely due to the absence of sleep or rather to some specific aspect of waking? The upright posture and the normal waking activities are not a crucial factor, because the rise in SWA after a waking episode in a recumbent position with minimal activity was comparable to that seen after an ordinary sleep deprivation period (Dijk and Czeisler, 1993). Animal studies have shown that locomotion is not a critical factor. Neither forced locomotion (Borbe´ly and Neuhaus, 1979; Friedman et al., 1979) nor voluntary locomotion (Hanagasioglu and Borbe´ly, 1982) was correlated with the effect on SWA in the rat.
MANIFESTATIONS AND FUNCTIONAL IMPLICATIONS OF SLEEP HOMEOSTASIS N
L
R
2.20
2.75
3.30
130
135
140
N
L
R
Fig. 13.4. Topographic distribution of the rise rate (%/h) of theta activity in the human waking electroencephalogram (power in the 5.0–8.0-Hz band) in the course of extended waking (top) and of the increase (%) of slow-wave activity (power in the 0.75–4.5-Hz band) from baseline sleep to recovery sleep (bottom). Note that the largest changes occur in frontal areas. L, left; R, right; N, nasal. (Adapted from Finelli et al. (2000).)
Similarly, in mice electromyogram activity, motor activity recorded by an infrared device, or wheel running did not show a clear correlation with SWA in the subsequent sleep interval (Vyazovskiy et al., 2006). Sleep deprivation induced by forced locomotion or by gentle handling (rat: Franken et al, 1991a; Syrian hamster: Tobler and Jaggi, 1987) resulted in similar changes during recovery sleep. It is unlikely that a major stress component could be involved because neither the forced locomotion procedure nor a sleep deprivation of 4–24 hours performed by “gentle handling” (consisting of mild stimuli such as tapping on the cages and providing objects and tissues, but not touching the animals) caused a significant increase in the level of plasma corticosterone (Tobler et al., 1983; Palchykova et al., 2006); in line with this interpretation, the expression patterns of genes were similar after 3 hours of spontaneous and enforced wakefulness (Cirelli and Tononi, 1999). In mice and ground squirrels, SWA in non-REM sleep increased
209
also after spontaneous, undisturbed bouts of waking, the magnitude of the effect depending on the duration of waking (Larkin and Heller, 1998; Huber et al., 2000a). Use-dependent changes in sleep may not encompass the entire brain but only those parts that have been most activated. A clear dissociation of EEG signs of sleep was observed in the dolphin, where “deep” SWS is present only in one hemisphere at a time (Oleksenko et al., 1992). There were early indications that regional use-dependent changes are present also in human sleep. Thus recordings from multiple sites along the anteroposterior axis revealed a fronto-occipital gradient of SWA which was most prominent in the initial phase of sleep (Werth et al., 1996). This hyperfrontality at the beginning of sleep is compatible with the interpretation that frontal association areas are particularly vulnerable to sleep loss. Also in rodents, sleep deprivation led to a more prominent increase of SWA in the frontal derivation compared to the parietal derivation (e.g., hamster: Palchykova et al., 2002; rat: Schwierin et al., 1999; mouse: Huber et al., 2000b). The tenet of a local, use-dependent increase of sleep intensity was directly tested (Kattler et al., 1994). An intermittent vibratory stimulus was applied to the left or right hand during the 6-hour period prior to sleep to activate the contralateral somatosensory cortex (Figure 13.6). Stimulation of the right (dominant) hand resulted in a shift of power in the non-REM sleep EEG toward the left hemisphere. This effect was most prominent in the delta range. It was limited to the first hour of sleep and was restricted to the central derivation situated over the somatosensory cortex (Kattler et al., 1994). In another study, subjects performed a learning task prior to sleep which involved a specific brain region (Huber et al., 2004a). There was a local increase of SWA over that particular brain region and the increase correlated with the performance of the task after sleep. Also animal studies support the notion of a local use-dependent facet of sleep regulation (Figure 13.6). In the rat, the usual interhemispheric asymmetry of EEG power was enhanced during recovery from sleep deprivation, and stimulation of the whiskers on one side led to a contralateral interhemispheric shift of low-frequency power in both rat and mouse (Vyazovskiy et al., 2000, 2004). Taken together, the results suggest that the sleep process may occur in a topographically graded manner by involving preferentially those neuronal populations that have been most activated during waking. Tononi and Cirelli (2003) proposed that synaptic homeostasis accounts for the phenomenon of local sleep homeostasis. According to this theory, specific cortical circuits undergo synaptic potentiation during waking. During
A.A. BORBE´LY AND I. TOBLER
210
400
300 250 200 150 100
int
2
er va ls
3
50 25
20
15
10 Frequency (Hz)
1 5
2-h
EEG power density
350
0
Fig. 13.5. Electroencephalogram (EEG) power density during 6 hours of enforced wakefulness (by gentle handling) in male C57BL/6 mice. Mean values of nine mice for 2-hour intervals for frequencies between 0.75 and 25 Hz expressed as a percentage of the corresponding baseline interval. Note the increase in EEG power in the delta band and in the theta/alpha band (approximately 7–12 Hz). (From Huber & Tobler, unpublished report.) Rat
Human
sleep, SWA allows a synaptic downscaling which in turn is associated with the beneficial effects of sleep.
LEFT
*
*
PERSPECTIVES
110
0
*
*
2
3
105
RIGHT
EEG asymmetry (%)
3
−3
100 1 2 3 NREMS episode
1
2-h intervals
Fig. 13.6. Specific sensory stimulation during waking leads to a use-dependent increase of slow-wave activity (SWA) in nonrapid eye movement sleep (NREMS). (Left) In humans, intermittent sensory stimulation (vibration) of the right, dominant hand for several hours before sleep onset led to a significant increase in the left–right asymmetry of SWA in the first nonREM sleep episode. Mean values with SEM of eight subjects for three consecutive NREMS episodes. (Right) In the rat the whiskers on the left side were trimmed, and those on the right side were spontaneously stimulated by providing the rats with objects to explore. After 6 hours this procedure led to an increase in electroencephalogram (EEG) power in the 0.75– 6.0 Hz range during subsequent NREMS recorded over the contralateral somatosensory cortex. Mean EEG power (0.75– 6.0 Hz range) of 12 rats for 2-hour intervals expressed as percentage increase relative to the ipsilateral derivation. Asterisks designate significant differences (P < 0.05). (Adapted from Kattler et al. (1994) and Vyazovskiy et al. (2000).)
The concept of sleep homeostasis has opened the door for exploring sleep in invertebrates. When cockroaches (Tobler, 1983; Tobler and Neuner-Jehle, 1992) or scorpions (Tobler and Stalder, 1988) were prevented from resting they showed a compensatory increase in resting behavior. Recent studies performed in the fruit fly Drosophila have unequivocally established that these invertebrates exhibit the major characteristics of sleep (Huber et al., 2004b). Homeostatic regulation is a key feature, since both duration and continuity of sleep are a function of the duration of prior waking. Sleep loss was shown to impair vigilance and performance. A mutant fly line designated “minisleep” exhibited drastically reduced sleep duration with a preserved homeostatic response (Cirelli et al., 2005). These flies carry a point mutation in a conserved domain of the Shaker gene. This gene encodes a voltage-dependent potassium channel controlling membrane repolarization and transmitter release. The studies in Drosophila provide an excellent opportunity for investigating the genetic mechanisms involved in sleep regulation. Another promising avenue is the study of the development of sleep homeostasis during ontogeny. In rat pups homeostatic markers of sleep intensity were absent until postnatal day 12 (Frank et al., 1998). Based
MANIFESTATIONS AND FUNCTIONAL IMPLICATIONS OF SLEEP HOMEOSTASIS 2 months 1000 µV2 0 25 0 9 months 7000 µV2 0 80 0 0
1
2
3
4 5 6 Time (hours)
7
8
9
10
Fig. 13.7. Development of the nocturnal sleep electroencephalogram (EEG) in a human infant from the age of 2 to 9 months. Time course of low delta (EEG power in the 0.75–1.75 range) and theta activity (6.5–9 Hz). Power is depicted for 20-second epochs. Gaps in EEG power represent either wakefulness or data loss (e.g., disconnection from head box during feeding of the infant). Delta activity showed an alternating pattern with a high level occurring in every other quiet sleep/nonrapid eye movement (non-REM) sleep episode. In contrast, theta activity exhibited a monotonic decline over consecutive quiet sleep/non-REM sleep episodes. The declining trend at 9 months was closely approximated by an exponential function. (Adapted from Jenni et al. (2004).)
on other markers (myoclonic twitches and sensory threshold), homeostatic responses to sleep deprivation were already present in 5-day-old rats (Blumberg et al., 2004). A longitudinal study in the first year of infancy in humans showed that EEG markers of sleep homeostasis appear in the first postnatal months and that they undergo progressive maturation (Jenni et al., 2004). Interestingly, not SWA (i.e., power in the delta band) but theta activity appeared to be the marker of sleep homeostasis (Figure 13.7). The latter could be only inferred from the time course of the dissipation of sleep propensity. Maturational changes in the buildup of process S are still occurring during adolescence (Jenni et al., 2005).
REFERENCES Achermann P, Borbe´ly AA (1987). Dynamics of EEG slow wave activity during physiological sleep and after administration of benzodiazepine hypnotics. Hum Neurobiol 6: 203–210. Achermann P, Dijk DJ, Brunner DP et al. (1993). A model of human sleep homeostasis based on EEG slow-wave activity: quantitative comparison of data and simulations. Brain Res Bull 31: 97–113.
211
Aeschbach D, Cajochen C, Landolt HP et al. (1996). Homeostatic sleep regulation in habitual short sleepers and long sleepers. Am J Physiol 270: R41–R53. Aeschbach D, Matthews JR, Postolache TT et al. (1997). Dynamics of the human EEG during prolonged wakefulness: evidence for frequency-specific circadian and homeostatic influences. Neurosci Lett 239: 121–124. Aeschbach D, Postolache TT, Sher L et al. (2001). Evidence from the waking electroencephalogram that short sleepers live under higher homeostatic sleep pressure than long sleepers. Neuroscience 102: 493–502. Beersma DGM, Daan S, Dijk DJ (1987). Sleep intensity and timing: a model for their circadian control. In: GA Carpenter (Ed.), Some Mathematical Questions in Biology – Circadian Rhythms, vol. 19. The American Mathematical Society, Providence, Rhode Island, pp. 39–62. Blake H, Gerard RW (1937). Brain potentials during sleep. Am J Physiol 119: 692–703. Blumberg MS, Middlemis-Brown JE, Johnson ED (2004). Sleep homeostasis in infant rats. Behav Neurosci 118: 1253–1261. Borbe´ly AA (1980). Sleep: circadian rhythm versus recovery process. In: M Koukkou, D Lehmann, J Angst (Eds.), Functional States of the Brain. Their Determinants. Elsevier, Amsterdam, pp. 151–161. Borbe´ly AA (1982). A two process model of sleep regulation. Hum Neurobiol 1: 195–204. Borbe´ly AA, Achermann P (1999). Sleep homeostasis and models of sleep regulation. J Biol Rhythms 14: 557–568. Borbe´ly AA, Achermann P (2005). Sleep homeostasis and models of sleep regulation. In: MH Kryger, T Roth, WC Dement (Eds.), Principles and Practice of Sleep Medicine. Elsevier Saunders, Philadelphia, pp. 405–417. Borbe´ly AA, Neuhaus HU (1979). Sleep-deprivation: effects on sleep and EEG in the rat. J Comp Physiol [A] 133: 71–87. Borbe´ly AA, Baumann F, Brandeis D et al. (1981). Sleep deprivation: effect on sleep stages and EEG power density in man. Electroencephalogr Clin Neurophysiol 51: 483–493. Brunner DP, Dijk DJ, Borbe´ly AA (1993). Repeated partial sleep deprivation progressively changes the EEG during sleep and wakefulness. Sleep 16: 100–113. Cajochen C, Brunner DP, Kra¨uchi K et al. (1995). Power density in theta/alpha frequencies of the waking EEG progressively increases during sustained wakefulness. Sleep 18: 890–894. Cajochen C, Knoblauch V, Kra¨uchi K et al. (2001). Dynamics of frontal EEG activity, sleepiness and body temperature under high and low sleep pressure. Neuroreport 12: 2277–2281. Cajochen C, Wyatt JK, Czeisler CA et al. (2002). Separation of circadian and wake duration-dependent modulation of EEG activation during wakefulness. Neuroscience 114: 1047–1060. Cannon WB (1932). The Wisdom of the Body. W.W. Norton, New York. Cirelli C, Tononi G (1999). Differences in brain gene expression between sleep and waking as revealed by mRNA
212
A.A. BORBE´LY AND I. TOBLER
differential display and cDNA microarray technology. J Sleep Res 8: 44–52. Cirelli C, Bushey D, Hill S et al. (2005). Reduced sleep in Drosophila Shaker mutants. Nature 434: 1087–1092. Daan S, Beersma D (1984). Circadian gating of human sleep–wake cycles. In: MC Moore-Ede, CA Czeisler (Eds.), Mathematical Models of the Circadian Sleep– Wake Cycle. Raven Press, New York, pp. 129–155. Daan S, Beersma DGM, Borbe´ly AA (1984). Timing of human sleep: recovery process gated by a circadian pacemaker. Am J Physiol 246: R161–R178. Deboer T, Vyazovskiy VV, Tobler I (2000). Long photoperiod restores the 24-h rhythm of sleep and EEG slowwave activity in the Djungarian hamster (Phodopus sungorus). J Biol Rhythms 15: 429–436. Deboer T, Vansteensel MJ, De´ta´ri L et al. (2003). Sleep states alter activity of suprachiasmatic nucleus neurons. Nat Neurosci 6: 1086–1090. Dijk DJ (1995). EEG slow waves and sleep spindles: windows on the sleeping brain. Behav Brain Res 69: 109–116. Dijk DJ, Czeisler CA (1993). Body temperature is elevated during the rebound of slow-wave sleep following 40-h of sleep deprivation on a constant routine. J Sleep Res 2: 117–120. Dijk DJ, Czeisler CA (1995). Contribution of the circadian pacemaker and the sleep homeostat to sleep propensity, sleep structure, electroencephalographic slow waves, and sleep spindle activity in humans. J Neurosci 15: 3526–3538. Dijk DJ, Daan S (1989). Sleep EEG spectral analysis in a diurnal rodent: Eutamias sibiricus. J Comp Physiol [A] 165: 205–215. Dijk DJ, Beersma DGM, Daan S (1987a). EEG power density during nap sleep: reflection of an hourglass measuring the duration of prior wakefulness. J Biol Rhythms 2: 207–219. Dijk DJ, Beersma DGM, Daan S et al. (1987b). Quantitative analysis of the effects of slow wave sleep deprivation during the first 3 h of sleep on subsequent EEG power density. Eur Arch Psychiatry Neurol Sci 236: 323–328. Dijk DJ, Brunner DP, Beersma DGM et al. (1990). Electroencephalogram power density and slow wave sleep as a function of prior waking and circadian phase. Sleep 13: 430–440. Finelli LA, Baumann H, Borbe´ly AA et al. (2000). Dual electroencephalogram markers of human sleep homeostasis: correlation between theta activity in waking and slow-wave activity in sleep. Neuroscience 101: 523–529. Frank MG, Morrissette R, Heller CH (1998). Effects of sleep deprivation in neonatal rats. Am J Physiol Regul Integr Comp Physiol 275: 148–157. Franken P, Dijk DJ, Tobler I et al. (1991a). Sleep deprivation in rats: effects on EEG power spectra, vigilance states, and cortical temperature. Am J Physiol 261: R198–R208. Franken P, Tobler I, Borbe´ly AA (1991b). Sleep homeostasis in the rat: simulation of the time course of EEG slowwave activity [published erratum appeared in Neurosci Lett 1991;132:279]. Neurosci Lett 130: 141–144.
Franken P, Tobler I, Borbe´ly AA (1995). Varying photoperiod in the laboratory rat: profound effect on 24-h sleep pattern but no effect on sleep homeostasis. Am J Physiol 269: R691–R701. Franken P, Malafosse A, Tafti M (1998). Genetic variation in EEG activity during sleep in inbred mice. Am J Physiol 275: R1127–R1137. Franken P, Chollet D, Tafti M (2001). The homeostatic regulation of sleep need is under genetic control. J Neurosci 21: 2610–2621. Friedman L, Bergmann BM, Rechtschaffen A (1979). Effects of sleep deprivation on sleepiness, sleep intensity, and subsequent sleep in the rat. Sleep 1: 369–391. Hanagasioglu M, Borbe´ly AA (1982). Effect of voluntary locomotor activity on sleep in the rat. Behav Brain Res 4: 359–368. Huber R, Deboer T, Tobler I (2000a). Effects of sleep deprivation on sleep and sleep EEG in three mouse strains: empirical data and simulations. Brain Res 857: 8–19. Huber R, Deboer T, Tobler I (2000b). Topography of EEG dynamics after sleep deprivation in mice. J Neurophysiol 84: 1888–1893. Huber R, Ghilardi MF, Massimini M et al. (2004a). Local sleep and learning. Nature 430: 78–81. Huber R, Hill SL, Holladay C et al. (2004b). Sleep homeostasis in Drosophila melanogaster. Sleep 27: 628–639. Jenni OG, Borbe´ly AA, Achermann P (2004). Development of the nocturnal sleep electroencephalogram in human infants. Am J Physiol Regel Integr Comp Physiol 286: R528–R538. Jenni OG, Achermann P, Carskadon MA (2005). Homeostatic sleep regulation in adolescents. Sleep 28: 1446–1454. Kattler H, Dijk DJ, Borbe´ly AA (1994). Effect of unilateral somatosensory stimulation prior to sleep on the sleep EEG in humans. J Sleep Res 3: 159–164. Larkin JE, Heller HC (1998). The disappearing slow wave activity of hibernators. Sleep Res Online 1: 96–101. Le´na CDP, Grailhe R, Escourrou P et al. (2004). B2-containing nicotinic receptors contribute to the organization of sleep and regulate putative micro-arousals in mice. J Neuroscience 24: 5711–5718. Mistlberger RE, Bergmann BM, Waldenar W et al. (1983). Recovery sleep following sleep deprivation in intact and suprachiasmatic nuclei-lesioned rats. Sleep 6: 217–233. Naitoh P, Muzet A, Johnson LC et al. (1973). Body movements during sleep after sleep loss. Psychophysiology 10: 363–368. Oleksenko AI, Mukhametov LM, Polyakova IG et al. (1992). Unihemispheric sleep deprivation in bottlenose dolphins. J Sleep Res 1: 40–44. Palchykova S, Deboer T, Tobler I (2002). Selective sleep deprivation after daily torpor in the Djungarian hamster. J Sleep Res 11: 313–319. Palchykova S, Winsky-Sommerer R, Meerlo P et al. (2006). Sleep deprivation impairs object recognition in mice. Neurobiol Learn Mem 85: 263–271. Pappenheimer JR, Koski G, Fencl V et al. (1975). Extraction of sleep-promoting factor S from cerebrospinal fluid and from brains of sleep-deprived animals. J Neurophysiol 38: 1299–1311.
MANIFESTATIONS AND FUNCTIONAL IMPLICATIONS OF SLEEP HOMEOSTASIS Schwierin B, Achermann P, Deboer T et al. (1999). Regional differences in the dynamics of the cortical EEG in the rat after sleep deprivation. Clin Neurophysiol 110: 869–875. Tobler I (1983). Effect of forced locomotion on the rest– activity cycle of the cockroach. Behav Brain Res 8: 351–360. Tobler I (2005). Phylogeny of sleep regulation. In: MH Kryger, T Roth, Dement (Eds.), Principles and Practice of Sleep Medicine. Elsevier Saunders, Philadelphia, pp. 77–90. Tobler I, Jaggi K (1987). Sleep and EEG spectra in the Syrian hamster (Mesocricetus auratus) under baseline conditions and following sleep deprivation. J Comp Physiol [A] 161: 449–459. Tobler I, Neuner-Jehle M (1992). 24-h variation of vigilance in the cockroach Blaberus giganteus. J Sleep Res 1: 231–239. Tobler I, Scherschlicht R (1990). Sleep and EEG slow-wave activity in the domestic cat: effect of sleep deprivation. Behav Brain Res 37: 109–118. Tobler I, Sigg H (1986). Long-term motor activity recording of dogs and the effect of sleep deprivation. Experientia 42: 987–991. Tobler I, Stalder J (1988). Rest in the scorpion – a sleep-like state? J Comp Physiol [A] 163: 227–235. Tobler I, Borbe´ly AA, Groos G (1983). The effect of sleep deprivation on sleep in rats with suprachiasmatic lesions. Neurosci Lett 42: 49–54. Tobler I, Franken P, Scherschlicht R (1990). Sleep and EEG spectra in the rabbit under baseline conditions and following sleep deprivation. Physiol Behav 48: 121–129. Tobler I, Franken P, Jaggi K (1993). Vigilance states, EEG spectra, and cortical temperature in the guinea pig. Am J Physiol 264: R1125–R1132. Tobler I, Gaus SE, Deboer T, Achermann P et al. (1996). Altered circadian activity rhythms and sleep in mice devoid of prion protein. Nature 380: 639–642. Tobler I, Herrmann M, Cooper HM et al. (1998). Rest– activity rhythm of the blind mole rat Spalax ehrenbergi
213
under different lighting conditions. Behav Brain Res 96: 173–183. Tononi G, Cirelli C (2003). Sleep and synaptic homeostasis: a hypothesis. Brain Res Bull 62: 143–150. ˚ kerstedt T (1987). Sleepiness on the job: Torsvall L, A continuously measured EEG changes in train drivers. Electroencephalogr Clin Neurophysiol 66: 502–511. Trachsel L, Tobler I, Borbe´ly AA (1986). Sleep regulation in rats: effects of sleep deprivation, light, and circadian phase. Am J Physiol 251: R1037–R1044. Trachsel L, Tobler I, Achermann P et al. (1991). Sleep continuity and the REM-nonrem cycle in the rat under baseline conditions and after sleep deprivation. Physiol Behav 49: 575–580. Trachsel L, Edgar DM, Seidel WF et al. (1992). Sleep homeostasis in suprachiasmatic nuclei-lesioned rats: effects of sleep deprivation and triazolam administration. Brain Res 589: 253–261. Vyazovskiy VV, Tobler I (2005). Theta activity in the waking EEG is a marker of sleep propensity in the rat. Brain Res 1050: 64–71. Vyazovskiy VV, Borbe´ly AA, Tobler I (2000). Unilateral vibrissae stimulation during waking induces interhemispheric EEG asymmetry during subsequent sleep in the rat. J Sleep Res 9: 367–371. Vyazovskiy VV, Welker E, Fritschy JM et al. (2004). Regional pattern of metabolic activation is reflected in the sleep EEG after sleep deprivation combined with unilateral whisker stimulation in mice. Eur J Neurosci 20: 1363–1370. Vyazovskiy VV, Ruijgrok G, Deboer T et al. (2006). Running wheel accessibility affects the regional electroencephalogram during sleep in mice. Cereb Cortex 16: 328–336. Webb WB, Agnew HWJr (1971). Stage 4 sleep: influence of time course variables. Science 174: 1354–1356. Werth E, Dijk DJ, Achermann P et al. (1996). Dynamics of the sleep EEG after an early evening nap: experimental data and simulations. Am J Physiol 271: R501–R510.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 14
Thermoregulation in wakefulness and sleep in humans VERONIQUE BACH, * FREDERIC TELLIEZ, KAREN CHARDON, PIERRE TOURNEUX, VIRGINIE CARDOT, AND JEAN-PIERRE LIBERT Laboratory DMAG-INERIS (EA 3901), Faculty of Medicine, University of Picardy Jules Verne, Amiens, France
It has been known since the 1930s that there is a close relationship between thermoregulation and sleep processes: initial work by Magnussen and colleagues (1939, cited by Kleitman, 1987) on body temperature and sleep rhythms was followed by a study by Parmeggiani and Rabini (1970) demonstrating that body temperature regulation was abolished during rapid eye movement (REM) sleep. These studies were performed mainly on adult animals and humans and, more occasionally, on neonates. However, a number of questions remain subject to debate, notably in terms of the functional interaction between sleep and thermoregulation and its clinical implications. The aim of this chapter is to review thermoregulation– sleep interactions in humans. Several aspects will be taken into account: (1) how thermoregulatory responses can be modified by sleep stages; (2) how skin and internal body temperatures vary according to the sleep–wake cycle; and (3) how manipulation of thermal parameters can influence sleep quantity and structure. Particular attention will be paid to comparisons between the elderly, adults, and neonates, since these populations differ as regards thermoregulation and sleep.
THERMOREGULATION Thermal exchanges Heat transfers between the body and the environment occur via four channels: (1) conduction – transfer between the skin surface area and any materials with which the body is in contact; (2) convection – transfer induced by air movements around the body; (3)
radiation – transfer between the skin surface and the surrounding surfaces in the form of invisible, electromagnetic energy; and (4) evaporation – transfer via respiratory and transepidermal water losses and from sweating. With the exception of evaporation, which always represents body heat loss, the other three transfers (referred to as dry heat transfers) can be either negative (heat loss from the body) or positive (heat gain by the body). To maintain homeothermy, heat exchanges must be accomplished at such a rate as to preserve an almost constant internal temperature (36.5–37.5 C): heat gain and metabolic heat production must be balanced by heat loss so that the resulting body heat storage is nil. Heat exchanges depend not only on the ambient parameters but also on morphological and anatomical parameters. From the latter point of view, neonates are at a disadvantage when compared with adults, since a neonate’s high skin surface area to body volume ratio increases heat losses to the environment. The neonate’s low weight (body mass acts as a heat buffer) and the poorly insulating body shell are responsible for greater fluctuations in internal temperature than in adults. Moreover, high skin permeability in premature neonates enhances evaporative water loss, particularly during the first weeks of life. Thus, the risk of hypothermia increases and neonates have a greater need for additional heat than adults. The elderly are characterized by a lower ratio of skin surface area to body mass than younger adults. However, they also have less insulating subcutaneous tissue, which thus leads to greater heat losses. Finally, the heat reservoir in the elderly is lower than in young adults (Van Someren et al., 2002).
*Correspondence to: Ve´ronique Bach, Laboratory PERITOX (EA 428: UM1 01), Faculty of Medicine, University of Picardy Jules Verne, 3 rue des Louvels, F-80 036 Amiens, France. Tel: þ33 322 82 78 99, Fax: þ33 322 82 78 96, E-mail: veronique.
[email protected]
216
V. BACH ET AL. temperature than for skin temperature. This ratio Thermoneutrality depends on the type of thermoregulatory effectors Homeothermia is easily achieved in the thermoneutral activated (Frank et al., 1999). zone, defined as the range of air temperatures within In neonates, the relative contribution of internal verwhich the metabolic rate is minimal and where the body sus skin thermal inputs has never been assessed: nevertemperature is essentially regulated by changing periphtheless, it is commonly supposed that the internal eral blood flow. Outside the thermoneutral zone, the temperature has less importance than in adults. In parbody temperature rises (warm environments) or falls ticular, certain thermoreceptive areas (such as the (cold environments) slightly at around the time when facial skin) seem to play an important role in thermosweating starts or when metabolic heat production regulation, since local cooling of this region increases increases, respectively, in order to prevent a further metabolic heat production in premature and full-term change in body temperature. When thermoregulatory neonates (Mestyan et al., 1964). responses cannot balance heat gains by heat losses (or According to the model proposed by Hammel et al. vice versa), the body heat storage is no longer zero (1963), the central structures operate as a thermostatic and the likelihood of body hyperthermia or hypothermia system with a set point temperature. A comparator is augmented. The lower and upper limits of the thermoadjusts an error signal which is proportional to the neutral range vary according to body size and the therbody temperature’s deviation from the set point. The moregulatory system’s sensitivity. It is thus difficult to thermal responses to heat and cold are activated as a define exact values for these limits, especially in result of this central drive. The magnitude of the neonates. responses depends on the gain, i.e., the value of the In contrast to thermoneutrality, thermal comfort slope for the relationship between thermal response refers to a subjective judgment of the degree of pleasand body temperature. In adults, the gain and the set antness or unpleasantness. Since the two ranges are point value are not invariable and can be modified by usually quite similar (although not strictly identical), the sleep–wake cycle (Hammel et al., 1963), the differthermal comfort is an interesting parameter and one ent sleep stages (Sagot et al., 1987), thermal acclimawhich is easily obtained from adults via use of a tion (Libert et al., 1983), fever, sleep deprivation, questionnaire. aging (Van Someren et al., 2002), and so on. In neoWhen faced with a thermal challenge, neonates, nates, it is usually assumed that other endogenous facadults, and the elderly respond differently, as a result tors (such as prematurity (Bru¨ck, 1968) and age of differences in their respective thermal exchanges (Sulyok et al., 1973)) can also influence the set point and thermoregulatory capabilities. value. A decrease in the set point can explain the rapid adaptation to mild cold stress observed over the first 3 Regulation of body temperature days of life (Perlstein et al., 1973). The response’s gain Differences in body temperature regulation during is probably also influenced by a number of parameters: ontogenesis can be judged in terms of the capacity of however, to the best of our knowledge, no studies have the effectors and differences in the central integrating been performed in this respect (Bach et al., 1996, system. Thermoregulatory processes are mediated by 2002). hypothalamic structures, which are activated by neural When exposed to a heat-losing environment, the thermal inputs from cutaneous and internal thermorebody needs to decrease body heat loss and increase ceptors: the hypothalamus thus acts as an integration body heat production. These responses can be classicenter for thermoregulation. Other centers exist in the fied as either behavioral or autonomic processes. cerebral cortex, medulla, and spinal cord, with the latBehavioral responses are generally triggered by skin ter being particularly thermosensitive. Skin temperatemperature changes and the corresponding thermal ture plays a major role in thermoregulation (and in discomfort (Weiss and Laties, 1961). If behavioral sleep) (Van Someren, 2000). In animals, it has been responses do not succeed in resolving the cold stress, shown that peripheral inputs alone may be sufficient more metabolically expensive, autonomic responses to activate all the thermoregulatory areas at the maxiare evoked. mal level, as pointed out by c-fos in situ hybridization Hence, initial changes in posture, the state of dress, (Bratincsak and Palkovits, 2005). However, when or the extent of body coverage with bed linen reduce sweating in young adults is considered, the relative body heat loss by decreasing the body surface area contribution of core versus skin temperatures greatly available for heat exchange. Another aspect concerns varies from one individual to another: in one study an increase in heat-generating physical activity. This (Libert et al., 1978), this parameter ratio ranged from physical contribution is attenuated in the elderly, where 2.2 to 8.8, showing that a unit rise is greater for rectal the behavioral response is impaired by a perturbed
THERMOREGULATION IN WAKEFULNESS AND SLEEP IN HUMANS 217 perception of thermal comfort (Frank et al., 2000) and this response is not sustainable for more than a few lower thermosensitivity (Van Someren et al., 2002). dozen minutes (Silverman and Agate, 1964). Naked neonates seek to adopt a crouched position, When exposed to a hot environment, peripheral even though their muscles are very weak (Stothers vasodilation occurs and thus increases cutaneous blood and Warner, 1984). Furthermore, cool stress results in flow. The set point for vasodilation is shifted upwards more frequent body movement in neonates. This in unfit adults and the elderly when compared with fit, increase is also observed during sleep (Fleming et al., young adults: skin blood flow is reduced and the 1988; Azaz et al., 1992) but typically only during active response is delayed. Whether the same situation is sleep (AS) (Bach et al., 1994). The efficiency of this observed in fit elderly persons is subject to debate process in terms of maintaining body homeothermia (Van Someren et al., 2002; Inoue et al., 2004). In chilis probably low, since muscular heat production repredren, the transfer of heat from core to skin is limited sents only a small part of total energy expenditure. as a result of lower blood volume (even when normalHowever, body activity does not always attest to therized to body surface area). mal discomfort alone (Bach et al., 1994, 1996; Telliez Logically, body activity should decrease in hot et al., 1997). environments in order to limit heat production. StrikVasoconstriction of peripheral vessels diminishes ingly, although this process is observed in some neothe skin temperature and therefore the dry heat losses. nates, others move more. The latter are usually older This orthosympathetic response is attenuated in the infants and it has been assumed that this behavioral elderly: compared with young adults, the set point response serves to alert the mother to the child’s therabove which vasoconstriction occurs is shifted downmal discomfort. The neonates also adopt a stretched, wards and the gain and the maximal response are spread-eagle position, increasing the available body lower. This failure seems to be the main cause of poor surface area for heat loss to the environment. cold defense in old age (Van Someren et al., 2002). In Evaporation of sweat from apocrine sweat glands is contrast, neonates (and even preterm ones) are able to the main way of cooling the body through evaporation. control this response effectively after the first 5 days The sweating response is less intense in unfit elderly of life (Lyon et al., 1997). people, who have a lower maximal response and a In addition to physical activity, heat production is higher set point. This is less true in fit elderly people, increased by shivering, i.e., involuntary skeletal muscle and indeed the age-related decrease in sweating effitremor. This mechanism is more efficient in young cacy can be slowed with regular exercise. The ageadults than in the elderly: the elderly generally have related sweat dysfunction may be due to decreases in less muscle mass and a higher thermal stress threshold. thermoreceptor sensitivity and/or sweat gland output Moreover, an age-related impairment is also observed rather than a decrease in gland recruitment, which only independently of changes in body mass (Frank et al., occurs later in life (Inoue et al., 2004). Sweat gland 2000). Contrary to the common belief that the ability dysfunction can be accompanied by a skin blood flow to shiver does not arise until some time after birth, dysfunction, and both exhibit regional heterogeneity: neonates may occasionally shiver, notably in cases the lower limbs are affected first, leading to decreased of severe hypothermia or when nonshivering thermoheat loss efficiency. Furthermore, sweating efficiency genesis is blocked (Adamsons et al., 1965; Bru¨ck and is lower in the elderly, since a greater proportion of Wu¨nnenberg, 1966; Darnall, 1987). the sweat drips off the body immediately and thus canNonshivering thermogenesis is negligible in adults not contribute to evaporative heat loss (Inbar et al., but is the prevailing mechanism of heat production 2004). during the first 3–6 months of life. In neonates, heat In neonates, sweating can be elicited even in preproduction can be doubled by activation of the brown term babies, since the sweating glands are functional adipose tissue, which is located principally in the interfrom the last trimester of pregnancy onward (Foster scapular region, between the ribs and near the kidneys. et al., 1969). Sweating activity appears successively on Heat production is principally due to oxidation of trithe forehead, arms, hands, thighs, feet, and abdominal glycerides, and this lipolytic activity is controlled by region. Although the set point for sweating is higher sympathetic nervous stimulation. The set point for than in adults and the maximal response of the sweat nonshivering thermogenesis is lower in low-birthglands is only one-third as great, this is almost fully weight neonates than in normal neonates (Bru¨ck, compensated for by a higher sweat gland density. The 1968) but does not seem to vary between the first week set point value decreases progressively with postnatal and the third month of life in full-term infants (Azaz development (Sulyok et al., 1973). et al., 1992). However, despite the high efficiency of In summary, and despite the fact that neonates, brown adipose tissue lipolysis, it can be supposed that young adults, and the elderly are all homeotherms,
218 V. BACH there are considerable age-related differences in thermal exchanges and thermoregulatory capabilities in humans. The elderly are more sensitive to thermal loads than younger adults: the combination of impaired autonomic thermal responses (and especially vascular responses) with altered perception of thermal comfort reduces the contribution of behavioral control to the maintenance of body temperature. As a result, the elderly are less able to regulate body temperature, which thus becomes more unstable (Van Someren et al., 2002). Neonates have a great need for additional heat, even though their thermoregulatory processes are fully efficient. This may be explained by the fact that their energy reserves are limited. Hence, premature, small-for-gestational-age or ill neonates are currently nursed in incubators in order to reduce their energy consumption when fighting against cold. The incubator environment is widely assumed to be thermoneutral: however, in view of considerable interindividual and intraindividual variability in the thermoneutral range (especially in immature and/or ill infants), the air temperature will rarely be thermoneutral. As a result, neonates nursed in incubators can be nevertheless exposed to mild thermal challenges.
SLEEP STRUCTURE AND AGE When compared with young adults, total sleep time in the elderly is reduced as a result of increased nighttime wakefulness. Slow-wave sleep (SWS) is less plentiful (particularly sleep stage 4). There is less REM sleep and it tends to take place earlier in the night. Sleep patterns appear to be phase-advanced, with earlier bedtimes and final awakenings (Maher, 2004). Neonatal sleep can be divided into three stages: active, intermediate, and quiet sleep (QS). During QS, the electroencephalogram (EEG) shows a discontinuous pattern, with bursts of high-voltage activity and superimposition of rapid, low-voltage waves. Just like SWS in adults, QS is characterized by the absence of eye movements, whereas heart and respiratory rates are very regular. In contrast, during AS, eye and body movements occur frequently, while respiratory and heart rates are irregular. Low-voltage, fast activity is observed on the EEG. On the basis of these observations, neonatal AS and adult REM sleep are often considered to be homologous sleep states. However, AS in neonates only partly corresponds to REM sleep: there is no muscle atonia during AS and the total duration of AS (50–80% of total sleep time) and the duration of episodes are greater than is seen for REM sleep. Furthermore, AS occurs prior to QS. The results of animal studies suggest that both REM sleep and SWS could develop from AS (Frank and Heller, 1997; Frank
ET AL. et al., 1997) but this hypothesis remains subject to debate. In neonates, intermediate sleep (IS) is scored by the simultaneous presence of AS and QS criteria.
SLEEP AND THERMOREGULATION The facts that the thermoregulatory capabilities differ in the various sleep stages and that sleep is disturbed in a nonthermoneutral environment attest to a functional interaction between sleep and thermoregulatory processes. Indeed, in addition to autonomic, behavioral, and thermal responses, hypothalamic structures also control sleep mechanisms. Furthermore, many structures involved in sleep–wake regulation are thermosensitive (Van Someren, 2000).
Thermoregulatory responses as a function of the sleep stage Differences in thermoregulatory responses were first demonstrated in sleeping cats, whose body temperature regulation disappeared during REM sleep (Parmeggiani and Rabini, 1970). In contrast to REM sleep, the body temperature change during non-REM sleep is negatively correlated with environmental temperatures, suggesting that homeothermic regulation is still operative. A transition from a homeothermic state to a poikilothermic state occurs when switching from non-REM sleep to REM sleep. As a result, sleeping in a nonthermoneutral environment leads to a conflict between sleep pressure and maintenance of homeothermia. Alterations in sleep (and especially REM sleep deprivation) can thus be seen to prevent hypo- or hyperthermia in animals sleeping in a cold or warm environment, respectively (Parmeggiani, 1988). The blockage of thermal responses during REM sleep has been interpreted as transient inactivation of the central controller. According to the model proposed by Parmeggiani (1988), the transition between the different sleep stages corresponds to a change in the hierarchical functional control of the central nervous structures involved in thermoregulation: the diencephalic structures (including the hypothalamus) are activated in SWS but not in REM sleep, during which autonomic responses are only controlled by the rhombencephalon. In REM sleep, the central controller may thus be disconnected from the spinal cord and the brainstem. In humans sleeping in a cold environment, Haskell et al. (1981) did not find the marked decreases in oxygen consumption typically observed in animals during REM sleep. In the same way, during transient rises in air temperature, local sweating rates recorded from a sweat collection capsule stuck on the skin of the right pectoral region persisted in all sleep stages (Libert
THERMOREGULATION IN WAKEFULNESS AND SLEEP IN HUMANS et al., 1982a). However, the sweat gland output was lower in REM sleep than in SWS, and the sweating onset was delayed. Sagot et al. (1987) and Amoros et al. (1986) pointed out that the greater sweating rate recorded during SWS was accounted for by a downshift in the hypothalamic set point for sweating when compared with sleep stages 1 and 2. In contrast, during REM sleep, the reduced thermal response was due to a decrease in the central controller’s gain. Strikingly, repeated heat exposure during the day (for 7 days) triggered thermoregulatory adaptive mechanisms in SWS only (Di Nisi et al., 1989), highlighting an incompatibility between REM sleep and adaptive thermal processes. To our knowledge, this aspect has never been studied in the elderly. In neonates, the linear relationship between thermal responses and body temperatures during AS episodes (in both cool and warm environments: Figure 14.1) demonstrates that closed-loop regulation operates during this sleep stage (Bach et al., 1994). The thermal response during AS is sometimes greater than that recorded during QS; QS is characterized by low energy utilization (Stothers and Warner, 1977, 1984; Darnall and Ariagno, 1982; Fleming et al., 1988; Azaz et al., 1992). However, this finding was not confirmed by other studies dealing with skin evaporative heat losses, either at thermoneutrality or in a warm environment
5
•
VO2 (mL.min-1.kg-1)
10
0 36.2
36.4
36.6
36.8 Tes (⬚C)
37
37.2
37.4
•
msw (mg.min-1.cm-2)
.7 .6 .5 .4 .3 .2 .1 0 35.5
36
36.5
37
37.5
Tes (⬚C)
Fig. 14.1. Individual relationships between energy expenditure (V_ o2 , oxygen consumption (ml/min/kg), top panel) or mean sweating rate (msw (mg/min/cm2), bottom panel) and internal temperature (esophageal temperature, Tes ( C)) during active sleep episodes in 11 different neonates (see different symbols). (Modified from Bach et al. (1994).)
219
(Azaz et al., 1992; Bach et al., 1994). Hence, in contrast to what is seen in adults during REM sleep, neonatal thermoregulatory responses are not depressed during AS – at least in the range of environmental temperatures usually studied. Thus, AS is a well-protected sleep stage (Bach et al., 1996). This may be important with regard to the duration of AS and its role in maturation of the neuronal network; the maintenance of thermoregulatory responses during AS protect the neonate from long periods of poikilothermy (Darnall and Ariagno, 1982). The above-cited studies prompt the conclusion that thermoregulatory responses differ between sleep stages. However, in contrast to animals, thermoregulation in adults is not completely abolished during REM sleep but is merely impaired. In neonates, the AS response is at least as efficient as that measured during QS.
Temperature as a function of sleep Many studies have pointed out that body temperature and sleep–wake cycle rhythms are closely related. Early in the night, skin temperature has been shown to increase (due to peripheral vasodilation). As a result, body heat is redistributed from the core to the peripheral skin layers. Peripheral heat losses increase and, consequently, core temperature decreases. These changes are already significant 100 minutes before sleep onset and continue afterwards (Van den Heuvel et al., 1998). Although a range of factors (prone body position, circadian rhythm) may contribute concomitantly to peripheral vasodilation, it has been shown that sleep onset per se reduces the core temperature (Gilbert et al., 2004). As a result, a microclimate becomes established in the air layer between the skin and the sheet (Muzet et al., 1979). After sleep onset, a subsequent increase in heat loss has been observed and is correlated with SWS duration (Horne and Staff, 1983; Montgomery et al., 1988). This is due to increased evaporative skin cooling, which is particularly intense during SWS as a result of a decreased set point for sweating (Di Nisi et al., 1989). Since skin heat losses increase the likelihood of sleep (as will be discussed later), this decrease helps reinforce sleep maintenance (Gilbert et al., 2004). Therefore, total sleep time is longer and the SWS duration increases when body temperature before sleep onset is high, i.e., when body heat losses are intense. In contrast, cooling the subject with a fan prevented the increase in SWS (Horne and Staff, 1983). One can hypothesize that this decrease in body temperature may help achieve a “gate temperature” required for entry into REM sleep, as observed by Parmeggiani et al. (1975) in animals. This has never been studied in adults,
220
V. BACH ET AL.
and we were not able to confirm the existence of a gate temperature in neonates (Bach et al., 2001). In the elderly, the decreased ability to sleep is related to circadian rhythm changes, such as phase advance and a decreased body temperature rhythm amplitude (Van Someren, 2000; Liao, 2002). Decreased vasodilation may be involved in the flattening of the body temperature rhythm curve. Elevated core temperatures are associated with difficulties in maintaining sleep (Lushington et al., 2000). In children aged from 5 months to 4 years, Day (1941) described peripheral skin vasodilation and an increase in body water loss at sleep onset. During sleep, the fall in rectal temperature was more marked when the daytime body temperature was higher. Day suggested that sleep onset was associated with a lowered threshold for heat loss responses, when compared with wakefulness. Little is known about body temperature rhythms during sleep in neonates, especially as regards periods of wakefulness. Indeed, these periods are very short when compared with adults, and neonates are often handled and/or agitated during these short episodes. When considering the sleeping period per se, some studies have reported that the internal temperature during AS did not differ from that recorded during QS, despite greater metabolic heat production (Stothers and Warner, 1977; Azaz et al., 1992; Bach et al., 1994). We observed slightly higher esophageal temperatures in AS and also noted that internal and skin temperatures (as well as heat production) decrease as a QS episode progresses (Figure 14.2). These decreases
Body temperatures (⬚C)
-0.03 ± 0.06 ⬚C p < 0.01
37.1 Tes
37.0 36.9 36.7 36.6
Tsk
36.5 0
5
10
15
20
25
0
min
-0.03 ± 0.06 ⬚C p < 0 .01
Fig. 14.2. Typical example of oesophageal (Tes, C) and mean skin (Tsk, C) temperature evolution during one episode of quiet sleep in one neonate. Statistical results (mean SD, P values) are calculated over 111 episodes of quiet sleep recorded in 37 neonates. (From results of Bach et al. (2001).)
had already commenced during the AS episode preceding the QS (Bach et al., 2001).
Sleep is influenced by the thermal load Temperature and sleep rhythms may be at least partly independent, since sleep prohibition does not completely suppress the nocturnal variation in body temperature (Lack and Lushington, 1996). Hence, the body temperature rhythm does not appear to be simply a direct consequence of the sleep–wake cycle. One can, however, question whether sleep and its propensity, depth, and maintenance are due to thermal modifications. This has been tested in a number of studies by manipulating thermal parameters and looking at sleep alterations. However, these studies led to different findings according to whether ambient temperatures were drastically manipulated or were kept within the normal circadian range.
Adults and the elderly External heat load variations (and especially downward thermal transients) greatly alter sleep (Candas et al., 1982; Libert et al., 1982b). These thermal transients (0.8–1.6 C/min) lead to sleep stage interruptions which are more frequently observed in REM sleep than in SWS. REM sleep interruptions always result in awakening, whereas SWS can change into sleep stage 1 or 2 or awakening. These alterations are not observed with less pronounced rates of temperature change (0.02 C/min) (Dewasmes et al., 1996). With acute nighttime thermal load, Haskell et al. (1981) observed that the sleep of naked subjects was more disturbed by cold conditions (an air temperature of 21 C) than by hot exposure (34 and 37 C): wakefulness and sleep stage 1 increased, whereas the durations of sleep stage 2 and REM sleep decreased. Muzet et al. (1979) reported that the most appropriate air temperature for a covered, sleeping adult was 16 C, since the duration and number of wakefulness episodes after sleep onset were lowest at this temperature value. Under these environmental thermal conditions, a microclimate inside the bed of 29.5 C was measured. High air temperatures (up to 39.5 C) increase the number and duration of wakefulness episodes, whereas SWS and REM sleep durations are sometimes reduced. In adults sleeping with a heated blanket (39 C), SWS latency was delayed (Karacan et al., 1978). In some cases, the number of REM sleep episodes and REM sleep cycle length was also decreased. Sleep may become more efficient as the night progresses, as indicated by the fact that SWS was only depressed during the first part of the night. In contrast, REM sleep was suppressed throughout the entire night
THERMOREGULATION IN WAKEFULNESS AND SLEEP IN HUMANS 221 (Karacan et al., 1978). However, for prolonged and thermal changes (sleep promotion) is explained by thercontinuous warm exposure (120 hours at an air tempermal discomfort. However, several studies indicate that ature of 35 C), sleep alterations did not vary from one comfort and thermally induced sleep effects may well night to another, despite an improvement in the effibe independent. For example, by assessing presleep ciency of thermoregulatory processes (Libert et al., thermal comfort and temperature sensations during 1988). multiple sleep latency tests, Raymann et al. (2005) Hence, sleep becomes disturbed and restless as observed that the shortest sleep onset latencies were soon as thermoregulatory mechanisms are stimulated. paradoxically recorded in the least comfortable experiAlthough human REM sleep is not as thermally dismental conditions, i.e., when the individual was subrupted as in animals, it appears to be more subject to jected to increasing proximal skin temperature during thermal stress than SWS. REM sleep alterations can the presleep period. be viewed as an adaptive mechanism for the mainteSimultaneous recordings of core body temperature nance of homeothermia. and sleep rhythms indicate that sleep initiation and In contrast, when body thermal changes remain maintenance are facilitated when the core temperature within the everyday circadian range, warm challenge is dropping. The contradiction between results from promotes sleep. This is true for direct skin warming, core and skin-warming experiments is merely apparent, as observed by Raymann et al. (2005): slightly warming since these body temperature paradigms exhibit oppothe skin surface area of the proximal region (torso, site response patterns. Warm exposure first increases arms, abdomen, and thighs) within the normal, physiothe core temperature and triggers skin heat loss logical range of skin temperature variation (þ0.78 mechanisms (especially peripheral vasodilation): the 0.03 C on average) reduced the sleep latency. Howlatter increases skin temperature, which ultimately ever, the warming of distal regions (torso, arms, legs) leads to a core temperature decrease. and core regions was ineffective. Interestingly, manipulating body temperature levels Prior to sleep, passive body heating in the evening and patterns via nonthermal stimuli (endogenous therenhances SWS and reduces REM sleep and sleep-onset mal loads due to drugs, a meal, physical exercise, latency (Putkonen et al., 1973; Horne and Reid, 1985) bright light levels) can lead to the same results as direct as long as the thermal load ends at most 1.5 hours thermal manipulation (Van Someren, 2000). For exambefore sleep onset (Shapiro et al., 1989). In contrast, ple, increasing the body temperature via a spicy evenbody heating earlier in the day does not modify sleep. ing meal can decrease the amount of SWS, just as Intranight changes can be found, with stronger effects direct thermal manipulation does (Edwards et al., during the first sleep cycle (Putkonen et al., 1973; 1992). The same can hold true with experiments inducHorne and Reid, 1985; Bunnell et al., 1988; Jordan ing peripheral vasodilation or vasoconstriction. Indeed, et al., 1990). Total sleep time may (Shapiro et al., Krauchi et al. (1999) observed that sleep onset latency 1989) or may not (Jordan et al., 1990) increase. was shorter when distal vasodilation (as measured by The improvement in sleep following evening therincreased values for the distal–proximal temperature mal manipulation of healthy young adults was congradient and distal blood flow) was greater in the late firmed in studies on the elderly (Liao, 2002). Sleep evening. This positive correlation was observed with a quality was improved, SWS duration was increased, number of processes that changed the vasomotor tone and wakefulness and body motion were decreased (bright light, administration of melatonin, a copious, after a 10–30-minute bath (at 40–40.5 C, 90–120 mincarbohydrate-rich meal) and indicated a functional link utes before sleep, increasing core body temperature by between distal vasodilation and ability to fall asleep. 0.60–0.92 C), whereas the time of the temperature A model has been proposed taking into account nadir was delayed by 88–94 minutes. The greater the anticipation of sleep as well as sleep-induced thermal temperature phase shift (with earlier bedtime and final changes. When an individual attempts to sleep, vasodiawakening), the greater the improvement in sleep quallation occurs and increases the skin temperature. Heat ity (Dorsey et al., 1999). losses increase and the core temperature decreases. The above results are generally in agreement, and Skin thermoreceptors activate the thermosensitive any discrepancies may be related to differences in the hypothalamic neurons involved in sleep initiation. time period between body heating and sleep onset Changes in the set point after sleep onset further and/or in the magnitude of the thermal load, i.e., the increase body heat losses to the environment and conbody heat storage at the time of sleep onset. solidate sleep maintenance. Thus, skin temperature Furthermore, it can be hypothesized that the dismay play a major role by producing a nervous signal crepancy between the results reported for drastic therwhich promotes sleep. Van Someren (2000) suggested mal conditions (i.e., sleep deterioration) and everyday a model assessing “sleep state probability” from the
222
V. BACH ET AL.
circadian patterns of proximal, distal, and core body temperatures and their respective effects on sleepand wake-related structures of the central nervous system. The practical implication is that the impact of insomnia and sleep maintenance disorders can be reduced with a warm bath prior to bedtime or by slightly increasing skin temperature during the night. These manipulations could be very useful for nightshift work and jetlag – situations in which sleep needs to occur when sleep propensity is inconveniently low. In general, Krauchi et al. (2004) assumed that any behavior which helps induce distal vasodilation will increase sleepiness. Relaxation, autogenous training, and lying down could thus be as efficient as direct or indirect thermal manipulations (Van Someren, 2000) and could contribute to the “vegetative preparedness for sleep” mentioned by Magnussen et al. (cited in Kleitman, 1987). In contrast, lower skin temperatures may help maintain wakefulness, especially when sleep pressure is high (Raymann et al., 2005). However, Reyner and Horne (1998) pointed out that thermal manipulation (such as cold air flowing over the face of car drivers) did not reduce sleepiness significantly and durably. According to Van den Heuvel et al. (1998), when an individual attempts to delay his or her usual bedtime, the body’s thermoregulatory changes (both before and after sleep onset) are attenuated. The closed relationship between sleep and body temperature regulation seems also to be implicated in different sleep disturbances recorded in depressed patients, insomniacs, or menopausal women suffering from hot flashes. Sleep of depressed patients is characterized by a disruption of continuity and efficiency; SWS is decreased while REM sleep is increased. The major thermal disturbance related is a flattened amplitude of the temperature rhythm rather than a phase shift (Tsujimoto et al., 1990; Koorengevel et al., 2002). In insomniacs, the hypothesis is that anxiety due to sleep attempt could provoke reduced distal skin temperature increase which could explain the typical lengthened sleep latency. Compared with good sleepers, insomniacs have been found to have significantly lower finger skin temperatures from lights out to stage 2 sleep onset (Freedman and Sattler, 1982). However, in one study (Gradisar et al., 2006), contradictory results have been found with greater finger skin temperature increase in insomniacs than in good sleepers during sleep latency trials. Interestingly, the only circadian difference was that core body temperature mesor is significantly higher in insomniacs than in good sleepers (Gradisar et al., 2006), indicating greater heat production.
Hot flashes, which occur in about 75% of perimenopausal and postmenopausal women (Avis et al., 1997), are characterized by enhanced body heat dissipation with widespread cutaneous vasodilatation, increased skin temperature, and profuse upper-body sweating. These changes typically occur within the first few seconds of the reported onset of the flash (Kronenberg, 1990), and hot flashes occur from 5 per year to 50 per day. It is generally believed that hot flashes produce arousals and awakenings from sleep, leading to fatigue. However, although most epidemiologic studies, based on self-reported sleep quality, report increased sleep disturbance at menopause, this is not supported by laboratory studies using polygraphical techniques (Vitiello et al., 2004), nor has the role of hot flashes in producing sleep disturbances been proved. The efficiency of warm skin temperature manipulation (producing a 26% reduction in sleep onset latency) (Raymann et al., 2005) is quite similar to that observed with hypnotics. Interestingly, sedative/hypnotic effects may partly be due to changes in thermoregulation (Libert et al., 1984). Indeed, Echizenya et al. (2003) pointed out that the benzodiazepine-induced increase in the gradient between distal and proximal skin temperatures (due to distal skin temperature warming) was positively correlated with sleepiness. Moreover, development of tolerance to temazepam is accompanied by a dampening of the typical hypnotic-induced increase in foot and core temperatures (Gilbert et al., 2000).
Neonates As in adults, cold exposure disturbs neonatal sleep continuity and structure more than warm exposure (Bach et al., 2002). In a cool environment, sleep duration is reduced as a result of earlier final awakening (Telliez et al., 1998a; Bach et al., 2000) and increased intrasleep wakefulness (Azaz et al., 1992). QS duration is reduced and the episodes become shorter and less frequent (Fleming et al., 1988). Concomitantly, the AS duration increases. Azaz et al. (1992) reported that this finding was only observed during the first week of life and was not seen in older (1–3-month-old) infants: the latter often woke briefly at the beginning of the cooling procedure. The neonates switched into AS more frequently, as characterized by a greater increase in metabolic heat production under cool conditions. This switching is therefore relevant from a thermoregulatory viewpoint. The neonates exhibiting the greatest increase in metabolic heat production during QS (þ41%) did not switch into AS (Fleming et al., 1988). Interestingly, the above-reported results emphasize that when faced with a cool challenge, the neonate’s
THERMOREGULATION IN WAKEFULNESS AND SLEEP IN HUMANS thermoregulatory function overcomes the need for energy conservation: this latter factor would tend to increase QS, a sleep stage which otherwise promotes energy conservation. For prolonged cool exposure (75 hours, 1.5 C below thermoneutrality), sleep structure and duration do not improve (and in fact even deteriorate: Figure 14.3) from one day to another, even though adaptive thermal responses to cool exposure do occur, as inferred from increased metabolic heat production when comparing the first cool exposure with the last (Telliez et al., 1998b). Hence, protective mechanisms for maintaining body temperature do not interact with sleep mechanisms, in contrast to what is seen in adults. To the best of our knowledge, only a few studies have analyzed the effects of warm conditions on sleeping neonates. The work did not show any sleep modifications (Bru¨ck et al., 1962) other than a decrease in body movement (Bach et al., 1994). However, indirect assumptions can be put forward by considering the Newborn Individualized Developmental Care and Assessment Program (NIDCAP) (Als et al., 1986), the goal of which is to promote comfort and reduce stress in premature neonates using a range of techniques. One consists in wrapping the neonate in a sheet or swaddling clothes. This procedure is based on the neonate’s need to have enveloping contact with materials,
223
as experienced within the uterus during pregnancy. However, the NIDCAP does not consider thermal needs at all. Some studies have pointed out that neonates are quieter under NIDCAP conditions (Heller et al., 1997; Becker et al., 1999). Although it is difficult to separate a specific thermal effect from a broad set of potentially influencing factors, it can be hypothesized that a slight increase in skin temperature under the sheet or the pyjamas (if confirmed) could be involved in this improvement. Sleep effects are seldom studied and those that have been observed did not provide evidence of significant improvements under NIDCAP conditions (Ariagno et al., 1997; Ohlsson, 2002; Westrup et al., 2002). These striking results disagree with the usual observations of medical staff, and so the subject merits further investigation. Epidemiological studies suggest that thermoregulation and sleep may be involved in sudden infant death syndrome (SIDS), which in western countries remains the most frequent cause of infant death between 1 month and 1 year (see Chapter 33). As mentioned above, dysfunction of thermoregulation during a specific sleep stage can be ruled out. However, thermoregulation and sleep may well be involved, probably via interaction with other factors. It can be hypothesized that thermal stress can lead to death by disruption of the central control mechanisms involved in respiratory
% of total sleep time
100 %
∗
Quiet sleep Intermediate sleep
∗
Active sleep
Wakefulness %
∗
∗
Prolonged cool exposure
Thermoneutrality
Acute cool condition
Chronic cool condition
Fig. 14.3. Wakefulness and sleep stage relative durations during thermoneutral, acute (first 3 hours), and chronic cool condition (75 hours, 2 C below thermoneutrality) measured on preterm neonates. *Significant difference. (From results of Telliez et al. (1998b).)
224
V. BACH ET AL.
drive, the laryngeal closure reflex, and/or depression of arousal mechanisms. This leads to an additional hypothesis whereby sleep and thermoregulation may be involved in a failure to respond adequately to a cardiovascular (Harper et al., 2000) and/or respiratory (Chardon et al., 2003) challenge. In particular, difficulties in arousal when faced with a vegetative challenge may lead to death. This hypothesis has been reinforced by the observation that the arousability threshold is increased when sleeping in warm conditions (Franco et al., 2001).
CONCLUSIONS The close link between thermoregulation and sleep processes is obvious. However, a degree of independence between body temperature and sleep–wake rhythms may exist. Thus, some studies demonstrate that alterations in one rhythm do not systematically modify the other. This has been found with sleep deprivation, bright light stimulation, and melatonin administration, amongst others. In contrast, many other studies support evidence of a very close link. The causality remains subject to debate. The hypothesis is that, in normal conditions, temperature rhythms are under the control of the circadian clock and act on the sleep–wake cycle by reinforcing circadian control (Gilbert et al., 2004). Sleep onset is facilitated during the declining phase of core temperature. This is mainly obtained by increasing heat loss through peripheral vasodilation. Conversely, it is difficult to maintain sleep when the core temperature is rising. From a practical point of view, this demonstrates that sleep cannot be scheduled no matter when – it needs to be prepared, as suggested by the discrete thermoregulatory changes observed prior to sleep. Having a regular bedtime makes it more likely that sleep onset will occur during the decreasing phase of core body temperature. Should the occasion arise, awareness of delayed sleep onset seems to reduce discrepancy with the core temperature rhythm. A similar conclusion was reached when anticipating awakening (Aschoff et al., 1974). As a result, any drug or behavior that enhances peripheral heat losses would be expected to improve sleep, as do mild, warm manipulations before sleep. Conversely, when heat losses are reduced and/or heat production is increased, sleep is disturbed. Thus, age-related impairment of heat loss mechanisms and/ or phase advance in body temperature rhythms may explain (at least in part) difficulties in falling asleep or maintaining sleep in the elderly. However, the impairment can be counterbalanced by thermal manipulation.
The consequences of direct or indirect thermal manipulations on core and skin temperature patterns should also be kept in mind for neonates and ill patients, whose sleep is of great importance for nervous maturation and recovery, respectively. In particular, sleep quality is often downgraded in neonatal or critical care departments as a result of, amongst other things, the ambient conditions (high light and noise levels) and the high frequency of interventional care. Although certain thermal conditions can improve sleep, one must nevertheless remember that any thermal challenge that elicits thermoregulatory mechanisms will disturb sleep. Therefore, the sleep environment should be thermoneutral and presleep thermal stresses should be minimized or at least curtailed as long as possible before bedtime.
ACKNOWLEDGMENTS Financial support was provided by the Regional Council of Picardie and by the French Ministry of Research. The authors thank D. Fraser for critically reviewing the English text.
REFERENCES Adamsons KJ, Gandy GM, James LS (1965). The influence of thermal factors upon oxygen consumption of the newborn human infant. J Pediatr 66: 495–508. Als H, Lawhon G, Brown E et al. (1986). Individualized behavioral and environmental care for the very low birth weight preterm infant at high risk for bronchopulmonary dysplasia: neonatal intensive care unit and developmental outcome. Pediatrics 78: 1123–1132. Amoros C, Sagot JC, Libert JP et al. (1986). Sweat gland response to local heating during sleep in man. J Physiol (Paris) 81: 209–215. Ariagno RL, Thoman EB, Boeddiker MA et al. (1997). Developmental care does not alter sleep and development of premature infants. Pediatrics 100: E9. Aschoff J, Fatranska M, Gerecke U et al. (1974). Twentyfour-hour rhythms of rectal temperature in humans: effects of sleep-interruptions and of test-sessions. Pflugers Arch 346: 215–222. Avis NE, Crawford SL, McKinlay SM (1997). Psychosocial, behavioral, and health factors related to menopause symptomatology. Women’s Health 3: 103–120. Azaz Y, Fleming PJ, Levine MR et al. (1992). The relationship between environmental temperature, metabolic rate, sleep state, and evaporative water loss in infants from birth to three months. Pediatr Res 32: 417–423. Bach V, Bouferrache B, Kremp O et al. (1994). Regulation of sleep and body temperature in response to exposure to cool and warm environments in neonates. Pediatrics 93: 789–796. Bach V, Telliez F, Krim G et al. (1996). Body temperature regulation in the newborn infant: interaction with sleep and clinical implications. Neurophysiol Clin 26: 379–402.
THERMOREGULATION IN WAKEFULNESS AND SLEEP IN HUMANS Bach V, Telliez F, Zoccoli G et al. (2000). Interindividual differences in the thermoregulatory response to cool exposure in sleeping neonates. Eur J Appl Physiol 81: 455–462. Bach V, Telliez F, Leke A et al. (2001). Interaction between body temperatures and the direction of sleep stage transition in neonates. Sleep Res Online 4: 43–49. Bach V, Telliez F, Libert JP (2002). Sleep and thermoregulation: clinical implications. Sleep Med Rev 6: 481–492. Becker PT, Grunwald PC, Brazy JE (1999). Motor organization in very low birth weight infants during caregiving: effects of a developmental intervention. J Dev Behav Pediatr 20: 344–354. Bratincsak A, Palkovits M (2005). Evidence that peripheral rather than intracranial thermal signals induce thermoregulation. Neuroscience 135: 525–532. Bru¨ck K (1968). Which environmental temperature does the premature infant prefer? Pediatrics 41: 1027–1030. Bru¨ck K, Wu¨nnenberg B (1966). Influence of ambient temperature on the process of replacement of nonshivering by shivering thermogenesis during postnatal development. Fed Proc 25: 1332. Bru¨ck K, Parmelee AH, Bru¨ck M (1962). Neutral temperature range and range of “thermal comfort” in premature infants. Biol Neonate 4: 32–51. Bunnell DE, Agnew JA, Horvath SM et al. (1988). Passive body heating and sleep: influence of proximity to sleep. Sleep 11: 210–219. Candas V, Libert JP, Muzet A (1982). Heating and cooling stimulation during SWS and REM sleep in man. J Therm Biol 7: 155–158. Chardon K, Bach V, Telliez F et al. (2003). Peripheral chemoreceptor activity in sleeping neonates exposed to warm environments. Clin Neurophysiol 33: 196–202. Darnall RA (1987). The thermophysiology of the newborn infant. Med Instrum 21: 16–22. Darnall RA, Ariagno RL (1982). The effect of sleep state on active thermoregulation in the premature infant. Pediatr Res 16: 512–514. Day R (1941). Regulation of body temperature during sleep. Am J Dis Child 61: 734–746. Dewasmes G, Signoret P, Nicolas A et al. (1996). Advances of human core temperature minimum and maximal paradoxical sleep propensity by ambient thermal transients. Neurosci Lett 215: 25–28. Di Nisi J, Ehrhart J, Galeou M et al. (1989). Influence of repeated passive body heating on subsequent night sleep in humans. Eur J Appl Physiol 59: 138–145. Dorsey CM, Teicher MH, Cohen-Zion M et al. (1999). Core body temperature and sleep of older female insomniacs before and after passive body heating. Sleep 22: 891–898. Echizenya M, Mishima K, Satoh K et al. (2003). Heat loss, sleepiness, and impaired performance after diazepam administration in humans. Neuropsychopharmacology 28: 1198–1206. Edwards SJ, Montgomery IM, Colquhoun EQ et al. (1992). Spicy meal disturbs sleep: an effect of thermoregulation? Int J Psychophysiol 13: 97–100.
225
Fleming PJ, Levine MR, Azaz Y et al. (1988). The effect of sleep state on the metabolic response to cold stress in newborn infants. In: CT Jones (Ed.), Fetal and neonatal development. Perinatology Press, Ithaca, NY, pp. 635–639. Foster KG, Hey EN, Katz G (1969). The response of the sweat glands of the new-born baby to thermal stimuli and to intradermal acetylcholine. J Physiol (London) 203: 13–29. Franco P, Scaillet S, Valente F et al. (2001). Ambient temperature is associated with changes in infants’ arousability from sleep. Sleep 24: 325–329. Frank MG, Heller HC (1997). Development of REM and slow wave sleep in the rat. Am J Physiol Regul Integr Comp Physiol 272: R1792–R1799. Frank MG, Page J, Heller HC (1997). The effects of REM sleep-inhibiting drugs in neonatal rats: evidence for a distinction between neonatal active sleep and REM sleep. Brain Res 778: 64–72. Frank SM, Raja SN, Bulcao CF et al. (1999). Relative contribution of core and cutaneous temperatures to thermal comfort and autonomic responses in humans. J Appl Physiol 86: 1588–1593. Frank SM, Raja SN, Bulcao C et al. (2000). Age-related thermoregulatory differences during core cooling in humans. Am J Physiol Regul Integr Comp Physiol 279: R349–R354. Freedman RR, Sattler HL (1982). Physiological and psychological factors in sleep-onset insomnia. J Abnorm Psychol 91: 380–389. Gilbert SS, Burgess HJ, Kennaway DJ et al. (2000). Attenuation of sleep propensity, core hypothermia, and peripheral heat loss after temazepam tolerance. Am J Physiol Regul Integr Comp Physiol 279: R1980–R1987. Gilbert SS, van den Heuvel CJ, Ferguson SA et al. (2004). Thermoregulation as a sleep signalling system. Sleep Med Rev 8: 81–93. Gradisar M, Lack L, Wright H et al. (2006). Do chronic primary insomniacs have impaired heat loss when attempting sleep? Am J Physiol Regul Integr Comp Physiol 290: R1115–R1121. Hammel HT, Jackson DC, Stolwijk JAJ et al. (1963). Temperature regulation by hypothalamic proportional control with an adjustable set-point. J Appl Physiol 18: 1146–1154. Harper RM, Kinney CH, Fleming PJ et al. (2000). Sleep influences on homeostatic functions: implications for sudden infant death syndrome. Resp Physiol 119: 123–132. Haskell EH, Palca JW, Walker JM et al. (1981). Metabolism and thermoregulation during stages of sleep in humans exposed to heat and cold. J Appl Physiol 51: 948–954. Heller C, Constantinou JC, VandenBerg K et al. (1997). Sedation administered to very low birth weight premature infants. J Perinatol 17: 107–112. Horne JA, Reid AJ (1985). Night-time sleep EEG changes following body heating in a warm bath. Electroencephalogr Clin Neurophysiol 60: 154–157. Horne JA, Staff LHE (1983). Exercise and sleep: bodyheating effects. Sleep 6: 36–46.
226
V. BACH ET AL.
Inbar O, Morris N, Epstein Y et al. (2004). Comparison of thermoregulatory responses to exercise in dry heat among prepubertal boys, young adults and older males. Exp Physiol 89: 691–700. Inoue Y, Kuwahara T, Araki T (2004). Maturation- and aging-related changes in heat loss effector function. J Physiol Anthropol Appl Human Sci 23: 289–294. Jordan J, Montgomery I, Trinder J (1990). The effect of afternoon body heating on body temperature and slow wave sleep. Psychophysiology 27: 560–566. Karacan I, Thornby JI, Anch AAM et al. (1978). Effects of high ambient temperature on sleep in young men. Aviat Space Environ Med 855–860. Kleitman NN (1987). Sleep and wakefulness. 3rd edn. University of Chicago Press, Chicago, pp. 71–80. Koorengevel KM, Beersma DG, den Boer JA et al. (2002). A forced desynchrony study of circadian pacemaker characteristics in seasonal affective disorder. J Biol Rhythms 17: 463–475. Krauchi K, Cajochen C, Werth E et al. (1999). Warm feet promote the rapid onset of sleep. Nature 401: 36–37. Krauchi K, Cajochen C, Wirz-Justice A (2004). Waking up properly: is there a role of thermoregulation in sleep inertia? J Sleep Res 13: 121–127. Kronenberg F (1990). Hot flashes: epidemiology and physiology. Ann N Y Acad Sci 592: 52–86; discussion 123–133. Lack LC, Lushington K (1996). The rhythms of human sleep propensity and core body temperature. J Sleep Res 5: 1–11. Liao WC (2002). Effects of passive body heating on body temperature and sleep regulation in the elderly: a systematic review. Int J Nurs Stud 39: 803–810. Libert JP, Candas V, Vogt JJ (1978). Sweating response in man during transient rises of air temperature. J Appl Physiol 44: 284–290. Libert JP, Candas V, Vogt JJ et al. (1982a). Central and peripheral inputs in sweating regulation during thermal transients. J Appl Physiol 52: 1147–1152. Libert JP, Candas V, Muzet A et al. (1982b). Thermoregulatory adjustments to thermal transients during slow wave sleep and REM sleep in man. J Physiol (Paris) 78: 251–257. Libert J, Candas V, Vogt JJ (1983). Modifications of sweating responses to thermal transient following heat acclimation. Eur J Appl Physiol 50: 235–246. Libert JP, Weber LD, Amoros C et al. (1984). Influence of triazolam on thermal heat balance in poor sleepers. Eur J Clin Pharmacol 27: 173–179. Libert JP, Di Nisi J, Fukuda H et al. (1988). Effect of continuous heat exposure on sleep stages in humans. Sleep 11: 195–209. Lushington K, Dawson D, Lack L (2000). Core body temperature is elevated during constant wakefulness in elderly poor sleepers. Sleep 23: 504–510. Lyon AJ, Pikaar ME, Badger P et al. (1997). Temperature control in very low birthweight infants during first five days of life. Arch Dis Child Fetal Neonatal Ed 76: F47–F50.
Maher S (2004). Sleep in the older adult. Nurs Older People 16: 30–34. Mestyan J, Jarai I, Bata G et al. (1964). The significance of facial skin temperature in the chemical heat regulation of premature infants. Biol Neonate 7: 243–254. Montgomery I, Trinder J, Paxton S et al. (1988). Physical exercise and sleep: the effect of the age and sex of the subjects and type of exercise. Acta Physiol Scand 133: 36–40. Muzet A, Ehrhart J, Libert JP et al. (1979). The effect of thermal environment on sleep stages. In: PO Fanger, O Valbjorn (Eds.), Indoor Climate: Effects on Human Comfort, Performance, and Health. Danish Building Research Institute, Copenhagen, pp. 753–761. Ohlsson A (2002). No indications of increased quiet sleep in infants who receive care based on the Newborn Individualized Care and Assessment Program (NIDCAP). Acta Paediatr 91: 262–263. Parmeggiani PL (1988). Thermoregulation during sleep from the view point of homeostasis. Clinical Physiology of Sleep, American Physiological Society, pp. 159–169. Parmeggiani PL, Rabini C (1970). Sleep and environmental temperature. Arch Ital Biol 108: 369–387. Parmeggiani PL, Agnati LF, Zamboni G et al. (1975). Hypothalamic temperature during the sleep cycle at different ambient temperatures. Electroencephalogr Clin Neurophysiol 38: 589–596. Perlstein PH, Hersh CB, Glueck CJ et al. (1973). Homeothermic adaptation in the newborn. Pediatr Res 7: 406–506. Putkonen PTS, Eloman E, Kotilanen PV (1973). Increase in delta (3–4) sleep after heat stress in sauna. J Clin Lab Invest 32: 19. Raymann RJ, Swaab DF, Van Someren EJ (2005). Cutaneous warming promotes sleep onset. Am J Physiol Regul Integr Comp Physiol 288: R1589–R1597. Reyner LA, Horne JA (1998). Evaluation “in-car” countermeasures to sleepiness: cold air and radio. Sleep 21: 46–50. Sagot JC, Amoros C, Candas V et al. (1987). Sweating responses and body temperatures during nocturnal sleep in humans. Am J Physiol 252: R462–R470. Shapiro CM, Allan M, Driver H et al. (1989). Thermal load alters sleep. Biol Psychiatry 26: 733–736. Silverman WA, Agate FJ (1964). Variation in cold resistance among small newborn infants. Biol Neonate 6: 113–127. Stothers JK, Warner RM (1977). Thermal balance and sleep state in the newborn infant in a cool environment. J Physiol 273: 57–58. Stothers JK, Warner RM (1984). Thermal balance and sleep state in the newborn. Early Hum Dev 9: 313–322. Sulyok E, Je´quier E, Prod’hom LS (1973). Thermal balance of the newborn in a heat-gaining environment. Pediatr Res 7: 888–900. Telliez F, Bach V, Krim G et al. (1997). Consequences of a small decrease of air temperature from thermal equilibrium on thermoregulation in sleeping neonates. Med Biol Eng Comput 35: 516–520. Telliez F, Bach V, Dewasmes G et al. (1998a). Effects of medium and long chain triglycerides on sleep and thermoregulatory processes in neonates. J Sleep Res 7: 31–39.
THERMOREGULATION IN WAKEFULNESS AND SLEEP IN HUMANS Telliez F, Bach V, Dewasmes G et al. (1998b). Sleep modifications during cool acclimation in human neonates. Neurosci Lett 245: 25–28. Tsujimoto T, Yamada N, Shimoda K et al. (1990). Circadian rhythms in depression. Part II: Circadian rhythms in inpatients with various mental disorders. J Affect Disord 18: 199–210. Van den Heuvel CJ, Noone JT, Lushington K et al. (1998). Changes in sleepiness and body temperature precede nocturnal sleep onset: evidence from a polysomnographic study in young men. J Sleep Res 7: 159–166. Van Someren EJW (2000). More than a marker: interaction between the circadian regulation of temperature and sleep, age-related changes, and treatment possibilities. Chronobiol Int 17: 313–354.
227
Van Someren EJ, Raymann RJ, Scherder EJ et al. (2002). Circadian and age-related modulation of thermoreception and temperature regulation: mechanisms and functional implications. Ageing Res Rev 1: 721–778. Vitiello MV, Larsen LH, Moe KE (2004). Age-related sleep change: gender and estrogen effects on the subjective–objective sleep quality relationships of healthy, noncomplaining older men and women. J Psychosom Res 56: 503–510. Weiss B, Laties VG (1961). Behavioral thermoregulation. Science 133: 1338–1344. Westrup B, Hellstrom-Westas L, Stjernqvist K et al. (2002). No indications of increased quiet sleep in infants receiving care based on the Newborn Individualized Developmental Care and Assessment Program (NIDCAP). Acta Paediatr 91: 318–322; discussion 262–313.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 15
Cytokines in immune function and sleep regulation JAMES M. KRUEGER, * JEANNINE A. MAJDE, AND DAVID M. RECTOR Department of Veterinary and Comparative Anatomy, Pharmacology and Physiology, Washington State University, Pullman, WA, USA
SLEEP There are two independent literatures concerning the fundamental mechanisms of sleep regulation. One is based on neurophysiological methods: this literature has led to the identification of circuits involved in nonrapid eye movement sleep (NREMS) regulation such as corticothalamic projections, ventrolateral preoptic (VLPO), and median preoptic (MnPO) circuits (Lu et al., 2002; McGinty and Szymusiak, 2003). Satisfactory explanations of how these circuits impose sleep on the brain and how they keep track of past sleep– wake activity are not yet available. A second sleepregulatory literature is based on biochemical methods. This work has its basis in the homeostatic nature of sleep and the 100-year-old finding that the transfer of cerebrospinal fluid from sleep-deprived, but not control, animals enhances sleep in the recipients (Obal and Krueger, 2003). Within the past 20 years several sleep-regulatory substances (SRSs) have been identified and extensively tested in that they have met all the criteria for SRSs (Jouvet, 1984; Borbely and Tobler, 1989; Krueger and Obal, 1994). This literature provides a mechanistic explanation for sleep homeostasis but has only begun to address the issues of the cellular mechanisms leading to sleep. This review discusses SRS that are linked to host defense; we focus on interleukin-1b (IL-1b), tumor necrosis factor-a (TNF-a) and interferons (IFNs). We also briefly discuss how sleep is part of the acute-phase response (APR) induced by viral challenge.
humoral agents (Borbely and Tobler, 1989; Obal and Krueger, 2003). However, what it is about wakefulness that causes enhanced production of SRSs has not, until recently, been characterized. Sleep is posited to be linked to prior neuronal use via adenosine triphosphate (ATP) released during neurotransmission (Burnstock, 2007; Krueger et al., 2007). ATP, via purine type 2 receptors, in turn releases cytokines from glia (Hide et al., 2000; Solle et al., 2001; Suzuki et al., 2004; Ferrari et al., 2006). Many substances can affect sleep (Figure 15.1). However, only a handful of humoral agents are strongly implicated in sleep regulation. The list includes TNF-a, IL-1b, growth hormone-releasing hormone (GHRH), prostaglandin D2, and adenosine for NREMS and vasoactive intestinal peptide, nitric oxide (NO) (Kapa´s et al., 1994a, b) and prolactin (Roky et al., 1995) for rapid eye movement sleep (REMS) (Obal and Krueger, 2003). Substantial evidence implicating additional substances in sleep regulation is beginning to accumulate; these molecules include hypocretin (Kilduff and Peyron, 2000), oleamide (Boger et al., 1998), nerve growth factor (NGF) (Yamuy et al., 1995; Takahashi and Krueger, 1999), epidermal growth factor (Kushikata et al., 1998; Foltenyi et al., 2007), and brain-derived neurotrophic factor (BDNF) (Kushikata et al., 1999; Faraguna et al., 2008). It is important to recognize that those agents implicated in NREMS and REMS affect each other’s production and act in concert with each other to affect sleep (Figure 15.1) (Obal and Krueger, 2003). For instance, TNF-a induces IL-1b, NGF, prostaglandin, NO, adenosine, and growth hormone production.
HUMORAL REGULATION OF SLEEP
CYTOKINES IN SLEEP REGULATION
The accumulation of SRSs in cerebrospinal fluid during prolonged wakefulness (W) provides very strong support of the hypothesis that sleep is regulated, in part, by
Detailed discussion of the involvement of IL-1b, TNF-a, and other cytokines in sleep regulation has been reviewed (Obal and Krueger, 2003). Briefly, injection
*
Correspondence to: Dr. James M. Krueger, Department of VCAPP, Washington State University, PO Box 646520, Pullman, WA 99164-6520, USA. Tel: 509-335-8212, Fax: 509-335-6450, E-mail:
[email protected]
230
J.M. KRUEGER ET AL. IL1RA sIL1R anti IL1 CRH PGE2 αMSH
BDNF NGF
Stimuli for cytokine production • Increase in ambient temperature
GHRH
IL1
• Diurnal rhythm
NFκB
sTNFR anti-TNF
NOS COX-2 IL2 IL15 IL6 IL18 IL8
TNF
• Feeding
A1R
adenosine
• Sleep deprivation • Microbes LPS, MPs, viral, dsRNA
anti GHRH GHRH antagonist somatostatin
L-NAME
IL10 IL4 IL13 glucocorticoids
NO
NREM sleep
PGD2
insulin
Fig. 15.1. Molecular networks are involved in sleep regulation. Substances in boxes inhibit sleep and inhibit the production or actions of sleep-promoting substances illustrated via feedback mechanisms. Inhibition of one step does not completely block sleep, since parallel sleep-promoting pathways exist. These redundant pathways provide stability to sleep regulation. Our knowledge of the biochemical events involved in sleep regulation is more extensive than that illustrated. The molecular network shown here possesses many of the characteristics of biological networks and engineered systems (this topic is reviewed in several lead articles in Science 2003; 301:5641). Thus, the network is modular in that several proteins (cytokines) are working in “overlapping coregulated groups” in this pathway. Second, the molecular network is robust in that removal of one of the components does not result in complete sleep loss. Third, the network operates as a recurring circuit element with multiple feedback loops affecting other pathways to the extent that similar networks involving many of the same substances and component network parts are used to regulate body temperature, inflammatory responses, the microcirculation, memory, and food intake, and these systems, to a limited degree, coregulate. Specificity for any one physiological process, such as sleep, results from multiple interacting molecular and cellular circuits, each possessing different, but similar to each other, reactivity. IL-1RA, IL1 receptor antagonist; sIL1R, soluble IL-1 receptor; anti-IL1; anti-IL1 antibodies; CRH, corticotrophin-releasing hormone; PGD2, prostaglandin D2; a-MSH, a-melanocyte-stimulating hormone; sTNFR, soluble TNF receptor; anti-TNF, anti-TNF antibodies; TGFb, transforming growth factor b; IGF1, insulin-like growth factor; A1R, adenosine A1 receptor; COX2, cyclooxygenase 2; LPS, lipopolysaccharide; MPs, muramyl peptides, BDNF, brain-derived neurotrophic factor; NGF, nerve growth factor; L-NAME, N-nitro-L-arginine methyl ester; GHRH, growth hormone-releasing hormone; NO, nitric oxide; NOS, nitric oxide synthase; NF-kB, nuclear factor kappa B; NREM, nonrapid eye movement.
of exogenous low doses of IL-1b or TNF-a enhances NREMS (Figure 15.2) (Krueger et al., 1984; Shoham et al., 1987). Conditions that enhance endogenous production of IL-1b or TNF-a, e.g., excessive food intake (Hansen et al., 1998) or infectious disease (Majde and Krueger, 2005), promote NREMS (Figure 15.1). Conversely, inhibition of endogenous IL-1b and TNF-a, using antibodies or endogenous inhibitors such as their soluble receptors, inhibits spontaneous sleep (Opp and Krueger, 1994). These inhibitors of IL-1b and TNF-a also inhibit sleep rebound after sleep deprivation. Brain levels of IL-1b mRNA (Mackiewicz et al., 1996; Taishi et al., 1997) and IL-1 (Lue et al., 1998) and plasma levels of IL-1b (Nguyen et al., 1998) vary with the sleep–wake cycle with highest levels correlating with
high sleep propensity. Brain levels of TNF-a (Floyd and Krueger, 1997) and TNF-a mRNA (Bredow et al., 1997) also vary with sleep propensity in a similar fashion. Both IL-1b mRNA and TNF-a mRNA increase in the brain during sleep deprivation (Taishi et al., 1999). Microinjection of TNF-a (Kubota et al., 2002) into the basal forebrain/anterior hypothalamus (BF/AH) enhances NREMS while injection of the TNF soluble receptor into the same area inhibits sleep. IL-1b enhances the firing rate of BF/AH sleep-active neurons while it inhibits wake-active neurons (Alam et al., 2004). Some hypothalamic neurons receptive for GHRH are also receptive for IL-1b (De et al., 2002). These data suggest that this BF/AH NREMS regulatory network is responsive to IL-1b and TNF-a. The IL-1
CYTOKINES IN IMMUNE FUNCTION AND SLEEP REGULATION 90 80 NREMS
% Time In Sleep
70 60 50 40 30
REMS
20 10 0 1 Injection
5
9
13
17
21
Hours
Fig. 15.2. Murine tumor necrosis factor-a (TNF-a) enhances nonrapid eye movement sleep (NREMS) in mice. TNF-a, 3 mg, was injected intraperitoneally at time 0. Mice were kept on a 12-hour light–dark cycle with lights out at 0 hour. Circles are NREMS values SE; squares are rapid eye movement sleep (REMS) values SE. (Data are from Fang et al. (1997).)
type I receptor and the TNF 55 kD receptor are responsible for IL-1- and TNF-enhanced NREMS since mice lacking these receptors do not respond to IL-1 or TNF respectively (Fang et al., 1997, 1998). Both IL-1b and TNF-a affect, or are affected by, several neurotransmitter systems involved in the activational networks. For example, IL-1b or TNF injected into the locus coeruleus (De Sarro et al., 1997) enhances sleep. IL-1b injected into the dorsal raphe also promotes NREMS (Manfridi et al., 2003). Both IL-1b and TNF-a have been linked to a variety of clinical conditions involving sleep disorders (Obal and Krueger, 2003). For instance, clinical conditions associated with sleepiness correlate with higher blood levels of TNF. TNF-a is elevated in sleep apnea (Entzian et al., 1996; Vgontzas et al., 1997; Minoguchi et al., 2004), chronic fatigue (Moss et al., 1999), acquired immunodeficiency syndrome (AIDS) (Darko et al., 1995), chronic insomnia (Vgontzas et al., 2002), myocardial infarct (Francis et al., 2004), excessive daytime sleepiness (Vgontzas et al., 2003), postdialysis fatigue (Dreisbach et al., 1998), and pre-eclampsia patients (Majde and Krueger, 2002). Cancer patients receiving TNF report fatigue (Eskander et al., 1997). There are TNF-a-associated sleep disturbances in alcoholics (Irwin et al., 2004). There also may be a relationship between TNF and narcolepsy (Okun et al., 2004). Rheumatoid arthritis patients receiving the soluble TNF receptor (sTNFR) report reduced fatigue (Franklin, 1999). Sleep apnea patients treated with the sTNFR
231
have reduced sleepiness (Vgontzas et al., 2004). If obstructive sleep apnea patients are surgically treated, their elevated TNF-a plasma levels return to normal (Kataoka et al., 2004). Systemic TNF, like IL1, likely signals the brain via multiple mechanisms; one involves vagal afferents since vagotomy attenuates intraperitoneal TNF-a-induced NREMS responses (Kubota et al., 2001b). The effects of systemic bacterial products such as endotoxin may also involve TNF (Mullington et al., 2000). For instance, in humans, endotoxin doses that induce transient increases in sleep also induce concomitant increases in circulating TNF-a (Haack et al., 2001). There is substantial evidence linking sleep deprivationenhanced IL-1, and TNF, to symptoms associated with sleep deprivation, such as sensitivity to kindling (Yi et al., 2004) and pain stimuli (Honore et al., 2006; Kawasaki et al., 2008; Kundermann et al., 2008), cognitive (Gambino et al., 2007; Baune et al., 2008; Trompet et al., 2008), and memory (Dantzer, 2004; Banks and Dinges, 2007; Pickering and O’Connor, 2007) impairments, performance impairments (Banks and Dinges, 2007), depression (Anisman and Marali, 2003; Vollmer-Conna et al., 2004), sleepiness (Moldofsky, 1995; Tringall et al., 2000; Krueger et al., 2007), and fatigue (Anisman and Marali, 2003; Omdal and Gunnarsson, 2005; Carmichael et al., 2006), and to chronic sleep loss-associated pathologies such as metabolic syndrome (Hristova and Aloe, 2006; Jager et al., 2007; Larsen et al., 2007), chronic inflammation (Hu et al., 2003; Frey et al., 2007), and cardiovascular disease (Yndestad et al., 2007). These sleep deprivationassociated symptoms can be induced by injection of exogenous IL-1 and/or TNF (Obal and Krueger, 2003), or in some cases blocked if these cytokines are inhibited (Opp and Krueger, 1991; Depino et al., 2004; Larsen et al., 2007). There is an inhibitor of IL-1 approved for clinical use, anakinra, the IL1-receptor antagonist (IL-1RA), a naturally occurring substance whose levels are altered by sleep loss (Frey et al., 2007) and that inhibits sleep (Takahashi et al., 1996). IL-1RA reduces fatigue (Omdal and Gunnarsson, 2005) and improves pancreatic beta cell function (Larsen et al., 2007). Cytokines discovered by neurobiologists also promote sleep. For instance, NGF induces NREMS (Takahashi and Krueger, 1999) and REMS (Yamuy et al., 1995). Giant reticular cells and neurons in the mesencephalic trigeminal nucleus are immunoreactive for the p75 and trkA NGF receptors. These neurons may modify NGF-induced REMS (Yamuy et al., 2000). Further, if NGF-receptive basal forebrain cholinergic neurons are selectively removed using an immunotoxin conjugated to an anti-p75 NGF receptor, there is a transient loss of NREMS and a more permanent
232 J.M. KRUEGER ET AL. loss of REMS (Kapa´s et al., 1996). NGF, in cortical well as several of the prosomnogenic cytokines (Obal pyramidal cells, upregulates with sleep loss (Brandt and Krueger, 2003). NF-kB is activated within the coret al., 2001). BDNF may also play a role in sleep regutex during sleep deprivation (Chen et al., 1999). Adenlation. BDNF promotes both NREMS and REMS in osine also elicits NF-kB nuclear translocation in basal forebrain slices (Basheer et al., 2001) and that action rabbits, although in rats, only NREMS increases after is mediated by the A1 receptor. A cell-soluble peptide intracerebroventricular injection (Kushikata et al., inhibitor of NF-kB nuclear translocation inhibits 1999; Faraguna et al., 2008). BDNF mRNA upregulates NREMS (Kubota et al., 2000). during sleep deprivation and downregulates during sleep (Taishi et al., 2001). The regulation of cytokines in the brain is complex INTERFERONS AND SLEEP and not very well understood. Nevertheless, some IFNs fall into two classes, type I and type II (IFN-g). cytokine-associated substances, such as the IL-1RA Type I IFNs, particularly IFN-as, are commonly assoand the TNF and IL-1 soluble receptors seem to act as ciated with viral infections and their primary function endogenous antagonists, and indeed these substances is thought to be blockade of viral replication. Type I inhibit spontaneous sleep (Obal and Krueger, 2003). IFNs are quite distinct structurally and functionally Antisomnogenic cytokines act, in part, by inhibiting from IFN-g, as they bind to different receptors and production of prosomnogenic cytokines and release use distinct (but overlapping) signal transduction pathof other substances implicated in sleep regulation, ways. Type I IFNs were the first cytokines to be discove.g., NO (Kasai et al., 1995). ered (in 1957), purified, cloned, commercialized, and Some of the prosomnogenic cytokines, such as ILused clinically. Despite this long history, their physiol1b and TNF-a, promote inducible nitric oxide synthase ogy and pathophysiology remain somewhat mysteri(iNOS) activity (Figure 15.1) (Obal and Krueger, 2003). ous. This is in part due to the research focus on their This observation prompted investigations into the role antiviral action, and also to the lack of specificity of that NO may have in sleep (Kapa´s et al., 1994a, b; the assay used to detect them, i.e., the antiviral activity Kapa´s and Krueger, 1996). There are three types of assay also detects cytokines such as TNF-a that induce NOSs: neuronal (nNOS), iNOS, and endothelial IFN-b (Jacobsen et al., 1989). Only recently have (eNOS). nNOS colocalizes with cholinergic neurons in specific immunoassays become available for IFN-as the peduculopontine tegmental nuclei (PPT), the latero(Hayden et al., 1998). dorsal tegmental nucleus (LDT). These neurons project IFN-a (Hori et al., 1998) and type I IFN receptors to the thalamus and basal forebrain as well as the (Krueger and Majde, 1994) are found in the brain, medial pontine reticular formation (mPRF), which is and IFN-a and IFN-g both cross the blood–brain crucial in REMS generation (Sakai et al., 2001). The barrier (Pan et al., 1997). Thus circulating IFNs can cholinergic cells in the LDT/PPT have ascending projecact directly on the brain, and central nervous system tions to thalamic and basal forebrain nuclei that in turn responses such as fever, fatigue, and somnolence project to the cortex (Jones, 2003). Microinjection of are consistently seen with the pharmacological doses NO donors into the PPT enhances REMS while injeccommonly employed in the clinic (Smedley et al., tion of NOS inhibitors into the PPT reduces REMS 1983). Several studies demonstrate that different sub(Datta et al., 1997). Similarly, inhibition of NOS in types of IFN-a are somnogenic and enhance NREMS the mPRF (Leonard and Lydic, 1995, 1997) or dorsal (Majde and Krueger, 2005). As is the case with antiraphe nuclei (Burlet et al., 1999) also results in reduced viral activity, the somnogenic actions of IFNs are REMS. The role of NO in NREMS is not as well studspecies-specific (Kimura et al., 1994); this specificity ied or clear. However, manipulation of NOS does is determined by receptor-binding affinities (Uze´ affect NREMS (Kapa´s and Krueger, 1996). Specific et al., 1992). IFN-b has no demonstrable somnogenic effects depend on route of administration of drugs, activity (De Sarro et al., 1990; Kimura et al., 1994), time of day they are given, and the specific drugs used possibly because it does not circulate (Billiau, 1981) (Obal and Krueger, 2003). For example, mice lacking or because it associates with the type I receptor difnNOS have less REMS whereas mice lacking iNOS ferently than IFN-a (Lewerenz et al., 1998). Mice defihave more REMS, but less NREMS (Chen et al., 2003). cient in a functional type I IFN receptor (IFNRI NF-kB and c-Fos (AP-1) are transcription factors knockouts) have a 30% reduction in spontaneous that are activated by IL-1b, TNF-a, and NGF (Obal REMS (Bohnet et al., 2004). and Krueger, 2003) (Figure 15.1). NF-kB activation proThe role of IFN-g in sleep has received little study. motes the production of several other substances impliClinical trials with pharmacological doses of IFN-g cated in NREMS regulation, including the adenosine generally report fevers and the “flu syndrome,” and A1 receptor, cyclooxygenase-2, the GHRH receptor as
CYTOKINES IN IMMUNE FUNCTION AND SLEEP REGULATION 233 occasionally describe profound somnolence (Sriskandan products and cytokines (Majde and Krueger, 2002; et al., 1986). IFN-g is also somnogenic in rabbits, but its Krueger and Majde, 2005). A picture is emerging that effect appears to be due to its interaction with TNF-a suggests that sleep, like fever, is a stereotypic response (Kubota et al., 2001c). Because IFN-g is a potent to inflammation that may represent a basic host priming agent for cytokine induction, especially IL-12 defense mechanism. and somnogenic IL-18 (Kubota et al., 2001a), regulates Clinicians have long recognized that it is difficult to tryptophan metabolism and thus serotonin metabolism distinguish between the APR symptoms induced by (Werner-Felmayer et al., 1989), stimulates prolactin bacterial and viral diseases on clinical grounds. In the release (Walton and Cronin, 1990), potentiates the toxlast 20 years extensive evidence has accumulated that icity of double-stranded (ds)RNA (Chapekar and the APR associated with bacterial infections is Glazer, 1986) and potentiates NO induction by TNF-a mediated by proinflammatory cytokines (Krueger and (Zhang et al., 1994), it would seem likely that IFN-g Majde, 2005) released by infected target tissues or has an important role in sleep regulation during viral invading inflammatory cells. These cytokines activate infections. However, analysis of sleep responses to not only the physiological changes such as fever and low-dose influenza virus in IFN-g knockouts did not sleep, but also the biochemical markers characteristic reveal a substantial role for this cytokine in infectionof the APR, by acting upon the liver, bone marrow, altered sleep (Toth and Hughes, 2004). and brain (Steel and Whitehead, 1994). While the mediators of the viral APR are poorly defined, most of the same cytokines induced by bacterial infections are also ALTERED SLEEP AS AN ACUTE-PHASE induced by viruses, along with substantial amounts of RESPONSE: MEDIATORS AND type I IFNs (Hayden et al., 1998; Gendrel et al., 1999; MECHANISMS Majde, 2000). It is highly likely that these virusThe APR is a complex array of physiological changes associated cytokines also mediate the viral APR, though that occur within a few days following an acute minimal direct evidence is available (Kozak et al., 1995, infection or other systemic inflammatory challenges. 1997; Kurokawa et al., 1996). Further, pharmacological The most apparent components of the APR are the levels of the IFNs, which are expressed during viral behavioral changes, which include body temperature infections, can induce an APR in the absence of other changes, anorexia, immobility, sleepiness, excess sleep, cytokines (Quesada et al., 1986), and can also alter the and a feeling of being sick or toxic (malaise). It is well expression of proinflammatory cytokines known to be established in bacterial infections that proinflammatory essential for the bacterial APR (Reznikov et al., 1998; cytokines are largely responsible for these symptoms. Begni et al., 2005). Excess NREMS, increased electroencephalogram Whether the changes in sleep associated with infec(EEG) delta-frequency brain waves and often reduced tious disease aid the host’s recovery remains to be REMS accompany systemic inflammation. SRSs that determined. However, chronic loss of sleep in rats induce sleep alterations also can induce body temperaleads to septicemia (Everson and Toth, 2000). Further, ture changes as well as reduced locomotor activity, sleep loss affects a variety of immune parameters, e.g., though by different mechanisms. The APR is generally the ability of leukocytes to produce IFN (Krueger and considered adaptive (Hart, 1988), particularly the fever Majde, 1994). The strongest evidence that sleep is proresponse (Kluger et al., 1996). Physiologically regulated tective in infections is from observations in rabbits hyperthermia enhances a number of immunological funcinfected experimentally with Staphylococcus aureus; tions while inhibiting the replication of heat-sensitive infected rabbits that exhibit reduced NREMS either microorganisms (Mackowiak, 1981). die or express more severe clinical symptoms than do One reason fever has remained the hallmark of sysinfected rabbits that exhibit more NREMS in response temic inflammation is that it is easy to measure. Excess to infection (Toth et al., 1993). Apart from such corresleep, being more difficult to measure, has received lational studies, the only approach we currently have to much less attention, though changes in sleep during assess the role of sleep in infections is to sleep-deprive disease were noted by Aristotle (Pollmacher et al., animals that are subsequently infected and then deter1995). The importance of sleep for health and recovery mine disease outcomes. There are a number of methfrom disease has been recognized intuitively if not sciodological issues associated with such studies, not the entifically; few physicians fail to recommend to their least of which is the stress associated with sleep loss infected patients that they should get plenty of rest. and its impact on immune function (Dunn, 2002). SevHowever, whether such rest/sleep truly has an adaptive eral laboratories have specifically examined the impact value remains unknown. There are close ties between of sleep deprivation on influenza, with variable outregulation of the sleep response to diverse microbial comes that appear to depend on subtle changes in
234
J.M. KRUEGER ET AL.
experimental parameters. Although it is likely that infection-altered sleep promotes recovery from infection, direct evidence is lacking and the mechanism is unknown. While toxic mechanisms involved in both triggering and downregulating the bacterial APR have been intensively investigated (Majde and Krueger, 2002), viral toxicity mechanisms have received little attention since the 1940s. Indirect evidence, using both the synthetic dsRNA pI:C and viral dsRNA, supports a major role for viral dsRNA in triggering the viral APR, including sleep responses (Majde, 2000).
Brain-signaling mechanisms underlying the viral APR From the above discussion it is apparent that many cytokines, hormones, and other inflammatory regulators may play a role in sleep and temperature alterations induced by microbes. Cytokines are posited to activate the central nervous system-regulated APRs via several routes (Dunn, 2002; Banks, 2005; Romanovsky et al., 2005): saturable transendothelial translocation via specific endothelial transporters (Banks, 2005); penetration via circumventricular organs lacking a substantial blood–brain barrier (Banks, 2004); signal transduction via sensory nerves, specifically the vagus (Kubota et al., 2001b; Romanovsky et al., 2005); induction of prostaglandin production in brain endothelial cells (Dunn, 2002; Romanovsky et al., 2005); and diffusion through extracellular spaces (Banks, 2004). To date, the relative contributions of these various mechanisms to signaling the central nervous system from the periphery during infections are unknown.
A THEORY OF THE BRAIN ORGANIZATION OF SLEEP: CYTOKINE INVOLVEMENT IN “LOCAL” SLEEP Sleep is an unusual physiological process. Until recently (Rector et al., 2005) we did not know exactly what slept and we still do not know with experimental certainty why we sleep. There are several road blocks to understanding whether sleep helps host defense. Regardless, new evidence from several laboratories now suggests that cytokines play an essential role in determining the functional state of cortical assemblies. A theory of brain organization of sleep posits that, as synapses and circuits are used, ATP is released and it in turn induces SRS release from glia (Krueger et al., 2007). The released cytokines, including neurotrophins, are then responsible for synaptic sculpturing. In an autocrine fashion, these activity-dependent SRSs alter synaptic efficacy via nuclear transcription events and translation
mechanisms targeted to the specific synapses that were activated. For example, TNF enhances a-amino-3hydroxyl-5-methyl-4-isoxazole-propionate (AMPA) receptor and the adenosine A1 receptor; excess expression of either one would change cell sensitivity to glutamate and adenosine respectively. SRSs also act in a paracrine fashion to affect the electrical properties of nearby neurons such that a given input results in a different output (Alam et al., 2004). Within a neuronal assembly, the SRS-induced altered input–output relationships can, by definition, be considered a state shift. It is posited that sleep-regulatory networks modulate and coordinate neuronal assembly state and thereby produce sleepiness and sleep at the whole-organism level. Within a population of neuronal assemblies, as wakefulness becomes prolonged, the fraction of neuronal assemblies into the “sleep” mode would increase. At some point a predicted emergent property of the system (brain) would be a system-wide state shift (Roy et al., 2008). This emergent property would be associated with unconsciousness because a large fraction of the neuronal groups would be in a state where environmental input is divorced from a functional output. Thus, sleep-associated unconsciousness is needed, because output activity would be out of phase with environmental input. Further, it is the consequence of the process itself (Krueger and Obal, 1993, 2003). There are many ramifications of this theory of brain organization of sleep. Some of the important ones and supporting evidence as it is related to cytokines are: 1. 2. 3. 4. 5.
SRS levels are dependent on prior neural activity and sleep history. SRSs act locally to affect a sleep-regulatory biochemical network. Sleep intensity of one part of the brain can be more intense than other parts. Changes in SRS levels locally within the cortex will activate neural pathways. Sleep is a fundamental property of neural assemblies.
SRS levels are dependent on prior neural activity and sleep history Activity-dependent expression of NGF and BDNF by neurons is well known (Brandt et al., 2001). Cellular electrical activity alters the synthesis and actions of these regulatory molecules and, in turn, they directly alter electrical properties of cells containing their receptors and alter the expression of many molecules necessary for synaptic efficacy and plasticity. These mechanisms are posited to be responsible for Hebbian synaptic regulation and collectively form the basis for
CYTOKINES IN IMMUNE FUNCTION AND SLEEP REGULATION the neurotrophin hypothesis (Schinder and Poo, 2000). The synthesis of TNF-a (Turrin and Rivest, 2004) and IL-1b (Plata-Salaman et al., 2000; Rizzi et al., 2003) is also enhanced by neural activity. Although the actions of these substances are usually not discussed within the context of Hebbian mechanisms, there are data suggesting TNF-a could influence neuronal connectivity via its actions on AMPA receptors. Thus, TNF-a enhances AMPA receptor expression and cytosolic calcium levels (De et al., 2003). These actions of TNF-a appear to be physiological because an inhibitor of TNF-a inhibits AMPA-induced postsynaptic potentials (Beattie et al., 2002) and AMPA-induced changes in cytosolic Ca2þ (De et al., 2003). AMPA receptors play a key role in EEG synchronization (Bazhenov et al., 2002) and synaptic plasticity. For example, TNF-a plays a role in synaptic scaling (Stellwagen and Melenka, 2006). Further, afferent stimulation of somatosensory cortex neurons is associated with enhanced TNF-a expression (Churchill et al., 2008).
SRSs act locally to affect a sleep-regulatory biochemical network Unilateral application of TNF-a (Yoshida et al., 2004), IL-1b (Yasuda et al., 2005b), GHRH (Szentirmai et al., 2007), or BDNF (Faraguna et al., 2008) on to the surface of the somatosensory cortex induces unilateral dose-dependent and state-dependent increases in EEG delta wave power. Conversely, the soluble TNF receptor or the soluble IL-1 receptor unilaterally reduces EEG power during the NREMS occurring after sleep deprivation. Associated with the changes in the TNF- or IL1-altered EEG power are enhancements of Fos-IR and IL-1-immunoreactivity unilaterally in the somatosensory cortex and reticular thalamus.
Sleep intensity of one part of the brain can be more intense than other parts This was the first prediction of the original theory (Krueger and Obal, 1993) that was experimentally tested. Kattler et al. (1994) showed that, using righthand vibration stimulation, the amplitude of EEG slow waves (indicative of the intensity of sleep) during the first subsequent sleep episode was higher on the contralateral side somatosensory cortex than on the ipsilateral side (the contralateral side receives the input from the stimulated hand). Subsequently similar results were obtained from rats (Vyazovskiy et al., 2000) and mice (Vyazovskiy et al., 2004). Further, Huber et al. (2004) showed that EEG slow-wave power was greater over cortical areas during sleep that were “used” in a prior learning paradigm. Those results confirmed the work of Maquet et al. (2003) and Ferrara et al. (2002),
235
using brain-imaging techniques, concluded that the brain areas activated during sleep were those most active during prior wakefulness. Natural variation in spontaneous activity is also correlated with EEG delta power. Thus, EEG delta power from the visual cortex is relatively higher during daylight hours than that from the somatosensory cortex of rats. Conversely, at night when the rats are using their whiskers for location, EEG delta power is relatively higher in the somatosensory cortex than in the visual cortex (Yasuda et al., 2005a).
Changes in SRS levels locally within the cortex will activate neural pathways Unilateral injection of either TNF-a (Churchill et al., 2005) or IL-1b on to the surface of the somatosensory cortex activates a pathway unilaterally, as determined by Fos expression, that includes corticoreticular thalamic projections as well as anterior hypothalamic neurons. These circuits are known to be involved in sleep regulation. The results suggest a pathway by which information concerning the state of cortical columns is conveyed to the sleep-regulatory circuits. Such circuits could indeed provide homeostatic input to the hypothalamic “sleep switches.”
Sleep is a fundamental property of neural assemblies This prediction, although made in 1993 (Krueger and Obal, 1993), was not directly demonstrated until 2005 (Rector et al., 2005). Using either auditory or whisker stimulation to induce cortical evoked response potentials, somatosensory and auditory cortical columns were shown to oscillate between two functional states. During the functional state that correlated with sleep, the amplitude of the evoked response potential is higher than during the wake-like state. Further, the probability of a cortical column being in the sleep-like state was dependent upon prior time in the wake-like state. Finally, in a preliminary study using a conditioning paradigm, the error rate of a learned licking response induced by whisker stimulation is greater if the cortical column receiving the input from the stimulated whisker is in the sleep-like state (Walker et al., 2005). Finally, microinjection of TNF-a on to cortical columns induces the sleep-like functional state (Churchill et al., 2008). Collectively, the theory and supporting data suggest that sleep begins as a local process fundamental to cortical assemblies. Cytokines play a role in functional state determination and such states are neuron activity-dependent. Changes in sleep associated with the APR are likely driven by inflammatory mediators such
236
J.M. KRUEGER ET AL.
as cytokines, adenosine, NO, and prostaglandins since these molecules are also implicated in physiological sleep regulation. The pathological response likely reflects an amplified physiological sleep mechanism.
ACKNOWLEDGMENTS This work was supported in part by the National Institutes of Health, grant numbers NS25378, NS31453, and HD36520.
REFERENCES Alam MN, McGinty D, Bashir T et al. (2004). Interleukin1beta modulates state-dependent discharge activity of preoptic area and basal forebrain neurons: role in sleep regulation. Eur J Neurosci 20: 207–216. Anisman H, Marali Z (2003). Cytokines, stress and depressive illness: brain–immune interactions. Ann Med 35: 2–11. Banks WA (2004). Are the extracellular pathways a conduit for the delivery of therapeutics to the brain? Curr Pharm Des 10: 1365–1370. Banks WA (2005). Blood–brain barrier transport of cytokines: a mechanism for neuropathology. Curr Pharm Des 11: 973–984. Banks S, Dinges DF (2007). Behavioral and physiological consequences of sleep restriction. J Clin Sleep Med 3: 519–528. Basheer R, Rainnie DG, Porkka-Heiskanen T et al. (2001). Adenosine, prolonged wakefulness, and A1-activated NF-kB DNA binding in the basal forebrain of the rat. Neuroscience 104: 731–739. Baune BT, Ponath G, Rothermundt M et al. (2008). Association between genetic variants of IL-1beta, IL-6 and TNFalpha cytokines and cognitive performance in the elderly general population of the MEMO-study. Psychoneuroendocrinology 33: 68–76. Bazhenov M, Timofeev I, Steriade M et al. (2002). Model of thalamocortical slow-wave sleep oscillations and transitions to activated states. J Neurosci 22: 8691–8704. Beattie EC, Stellwagen D, Morishita W et al. (2002). Control of synaptic strength by glial TNF alpha. Science 295: 2282–2285. Begni B, Amadori M, Ritelli M et al. (2005). Effects of IFN-a on the inflammatory response of swine leukocytes to bacterial endotoxin. J Interferon Cytokine Res 25: 202–208. Billiau A (1981). Pharmacokinetic and pharmacological aspects of interferon therapy in man. Acta Microbiol Acad Sci Hung 28: 257–262. Boger DL, Henriksen SJ, Cravatt BF (1998). Oleamide: an endogenous sleep-inducing lipid and prototypical member of a new class of biological signaling molecules. Curr Pharm Des 4: 303–314. Bohnet SG, Traynor TR, Majde JA et al. (2004). Mice deficient in the interferon type I receptor have reduced REM sleep and altered hypothalamic hypocretin, prolactin and
20 ,50 -oligoadenylate synthase expression. Brain Res 1027: 117–125. Borbely AA, Tobler I (1989). Endogenous sleep-promoting substances and sleep regulation. Physiol Rev 69: 605–670. Brandt J, Churchill L, Guan Z et al. (2001). Sleep deprivation but not a whisker trim increases nerve growth factor within barrel cortical neurons. Brain Res 898: 105–112. Bredow S, Taishi P, Guha-Thakurta N et al. (1997). Diurnal variations of tumor necrosis factor-alpha mRNA and alpha-tubulin mRNA in rat brain. Neuroimmunomodulation 4: 84–90. Burlet S, Leger L, Cespuglio R (1999). Nitric oxide and sleep in the rat: a puzzling relationship. Neuroscience 92: 627–639. Burnstock G (2007). Physology and pathophysiology of purinergic neurotransmission. Physiol Rev 87: 659–797. Carmichael MD, Davis JM, Murphy EA et al. (2006). Role of brain IL-1beta on fatigue after exercise-induced muscle damage. Am J Physiol Regul Integr Comp Physiol 291: R1344–R1348. Chapekar MS, Glazer RI (1986). Potentiation of the cytocidal effect of human immune interferon by different synthetic double-stranded RNAs in the refractory human colon carcinoma cell line BE. Cancer Res 46: 1698–1702. Chen Z, Gardi J, Kushikata T et al. (1999). Nuclear factor kappa B-like activity increases in murine cerebral cortex after sleep deprivation. Am J Physiol 45: R1812–R1818. Chen L, Majde JA, Krueger JM (2003). Spontaneous sleep in mice with targeted disruptions of neuronal or inducible nitric oxide synthase genes. Brain Res 973: 214–222. Churchill L, Yasuda K, Yasuda T et al. (2005). Unilateral cortical application of tumor necrosis factor alpha induces asymmetry in Fos- and interleukin-1beta-immunoreactive cells within the corticothalamic projection. Brain Res 1055: 15–24. Churchill L, Rector DM, Yasuda K et al. (2008). Tumor necrosis factor a: activity dependent expression and promotion of cortical column sleep in rats. Neuroscience 156: 71–80. Dantzer R (2004). Cytokine-induced sickness behavior: a neuroimmune response to activation of innate immunity. Eur J Pharmacol 500: 399–411. Darko DF, Miller JC, Gallen C et al. (1995). Sleep electroencephalogram delta-frequency amplitude, night plasma levels of tumor necrosis factor alpha, and human immunodeficiency virus infection. PNAS 92: 12080–12084. Datta S, Patterson EH, Siwek DF (1997). Endogenous and exogenous nitric oxide in the pedunculopontine tegmentum induces sleep. Synapse 27: 69–78. De A, Churchill L, Obal F et al. (2002). GHRH and IL1beta increase cytoplasmic Ca2þ levels in cultured hypothalamic GABAergic neurons. Brain Res 949: 209–212. De A, Krueger JM, Simasko SM (2003). Tumor necrosis factor alpha increases cytosolic calcium response AMPA and KCl in primary cultures of rat hippocampal neurons. Brain Res 981: 133–142. Depino AM, Alonso M, Ferrari C et al. (2004). Learning modulation by endogenous hippocampal IL-1: blockade
CYTOKINES IN IMMUNE FUNCTION AND SLEEP REGULATION of endogenous IL-1 facilitates memory formation. Hippocampus 14: 526–535. De Sarro GP, Masuda Y, Ascioti C et al. (1990). Behavioral and ECoG spectrum changes by intracerebral infusion of interferons and interleukin 2 in rats are antagonized by naloxone. Neuropharmacology 29: 167–179. De Sarro G, Gareri P, Sinopoli VA et al. (1997). Comparative, behavioural and electrocortical effects of tumor necrosis factor-alpha and interleukin-1 microinjected into the locus coeruleus of rat. Life Sci 60: 555–564. Dreisbach AW, Hendrickson T, Beezhold D et al. (1998). Elevated levels of tumor necrosis factor alpha in postdialysis fatigue. Int J Artif Organs 21: 83–86. Dunn AJ (2002). Mechanisms by which cytokines signal the brain. Int Rev Neurobiol 52: 43–65. Entzian P, Linnemann K, Schlaak M et al. (1996). Obstructive sleep apnea syndrome and circadian rhythms of hormones and cytokines. Am J Respir Crit Care Med 153: 1080–1086. Eskander ED, Harvey HA, Givant E et al. (1997). Phase I study combining tumor necrosis factor with interferonalpha and interleukin-2. Am J Clin Oncol 20: 511–514. Everson CA, Toth LA (2000). Systemic bacterial invasion induced by sleep deprivation. Am J Physiol Regul Integr Compar Physiol 278: R905–R916. Fang J, Wang Y, Krueger JM (1997). Mice lacking the TNF 55 kD receptor fail to sleep more after TNF alpha treatment. J Neurosci 17: 5949–5955. Fang J, Wang Y, Krueger JM (1998). The effects of interleukin-1 beta on sleep are mediated by the type I receptor. Am J Physiol 274: R655–R660. Faraguna U, Vyazovskiy VV, Nelson AB et al. (2008). A causal role for brain-derived neurotrophic factor in the homeostatic regulation of sleep. J Neurosci 28: 4088–4095. Ferrara M, De Gennaro L, Curcio G et al. (2002). Regional differences of the human sleep electroencephalogram in response to selective slow-wave sleep deprivation. Cereb Cortex 12: 737–748. Ferrari D, Pizzirani C, Adinolfi E et al. (2006). The P2X7 receptor: a key player in IL-1 processing and release. J Immunol 176: 3877–3883. Floyd RA, Krueger JM (1997). Diurnal variations of TNF alpha in the rat brain. Neuroreport 8: 915–918. Foltenyi K, Greenspan RJ, Newport JW (2007). Activation of EGFR and ERK by rhomboid signaling regulates the consolidation and maintenance of sleep in Drosophila. Nat Neurosci 10: 1160–1167. Francis J, Chu Y, Johnson AK et al. (2004). Acute myocardial infarction induces hypothalamic cytokine synthesis. Am J Physiol Heart Circ Physiol 286 (6): H2264–H2271. Franklin CM (1999). Clinical experience with soluble TNF p75 receptor in rheumatoid arthritis. Semin Arthritis Rheum 29: 171–181. Frey DJ, Fleshner M, Wright KP Jr (2007). The effects of 40 hours of total sleep deprivation on inflammatory markers in healthy young adults. Brain Behav Immun 21: 1050–1057. Gambino F, Pavlowsky A, Be´gle´ A et al. (2007). IL1receptor accessory protein-like 1 (IL1RAPL1), a protein
237
involved in cognitive functions, regulates N-type Ca2þ-channel and neurite elongation. Proc Natl Acad Sci U S A 104: 9063–9068. Gendrel D, Raymond J, Coste J et al. (1999). Comparison of procalcitonin with C-reactive protein, interleukin 6 and interferon-alpha for differentiation of bacterial vs. viral infections. Pediatr Infect Dis J 18: 875–881. Haack M, Schuld A, Kraus T et al. (2001). Effects of sleep on endotoxin-induced host responses in healthy men. Psychosom Med 63: 568–578. Hansen MK, Taishi P, Chen Z et al. (1998). Cafeteriafeeding induces interleukin-1 beta mRNA expression in rat liver and brain. Am J Physiol 43: R1734–R1739. Hart BL (1988). Biological basis of the behavior of sick animals. Neurosci Biobehav Rev 12: 123–137. Hayden FG, Fritz RS, Lobo MC et al. (1998). Local and systemic cytokine responses during experimental human influenza A virus infection. Relation to symptom formation and host defense. J Clin Invest 101: 643–649. Hide I, Tanaka M, Inoue A et al. (2000). Extracellular ATP triggers tumor necrosis factor-alpha release from rat microglia. J Neurochem 75: 965–972. Honore P, Donnelly-Roberts D, Namovic MT et al. (2006). A-740003 [N-(1-{[(Cyanoimino)(5-quinolinylamino) methyl] amin}-2,2-dimethylpropyl)-2-(3,4-dimethoxyphenyl) acetamide], a novel and selective P2X7 receptor antagonist, dose-dependently reduces neuropathic pain in the rat. J Pharmacol Exp Therap 319: 1376–1385. Hori T, Katafuchi T, Take S et al. (1998). Neuroimmunomodulatory actions of hypothalamic interferon-a. Neuroimmunomodulation 5: 172–177. Hristova M, Aloe L (2006). Metabolic syndromeneurotrophic hypothesis. Med Hypotheses 66: 545–549. Huber R, Ghilardi MF, Massimini M et al. (2004). Local sleep and learning. Nature 430: 78–81. Hu J, Chen Z, Gorczynski CP et al. (2003). Sleep-deprived mice show altered cytokine production manifest by perturbations in serum IL-1ra, TNFa, and IL-6 levels. Brain Behav Immun 17: 498–504. Irwin M, Rinetti G, Redwine L et al. (2004). Nocturnal proinflammatory cytokine-associated sleep disturbances in abstinent African American alcoholics. Brain Behav Immun 18: 349–360. Jacobsen H, Mestan J, Sibylle M et al. (1989). Beta interferon subtype I induction by tumor necrosis factor. Mol Cell Biol 9: 3037–3042. Jager J, Gre´meaux T, Cormont M et al. (2007). Interleukin1beta-induced insulin resistance in adipocytes through down-regulation of insulin receptor substrate-1 expression. Endocrinology 148: 241–251. Jones BE (2003). Arousal systems. Front Biosci 8: s438–s451. Jouvet M (1984). Neuromediateurs et facteurs hypnogenes. Rev Neurol (Paris) 140: 389–400. Kapa´s L, Krueger JM (1996). Nitric oxide donors SIN-1 and SNAP promote nonrapid-eye-movement sleep in rats. Brain Res Bull 41: 293–298. Kapa´s L, Fang J, Krueger JM (1994a). Inhibition of nitric oxide synthesis inhibits rat sleep. Brain Res 664: 189–196.
238
J.M. KRUEGER ET AL.
Kapa´s L, Shibata M, Kimura M et al. (1994b). Inhibition of nitric oxide synthesis suppresses sleep in rabbits. Am J Physiol 266: R151–R157. Kapa´s L, Obal F, Book AA et al. (1996). The effects of immunolesions of nerve growth factor-receptive neurons by 192 IgG-saporin on sleep. Brain Res 712: 53–59. Kasai K, Hattori Y, Nakanishi N et al. (1995). Regulation of inducible nitric oxide production by cytokines in human thyrocytes in culture. Endocrinology 136: 4261–4270. Kataoka T, Enomoto F, Kim R et al. (2004). The effect of surgical treatment of obstructive sleep apnea syndrome on the plasma TNF-alpha levels. Tohoku J Exp Med 204: 267–272. Kattler H, Dijk DJ, Borbely AA (1994). Effect of unilateral somatosensory stimulation prior to sleep on the sleep EEG in humans. J Sleep Res 3: 159–164. Kawasaki Y, Zhang L, Cheng J-K et al. (2008). Cytokine mechanisms of central sensitization: distinct and overlapping role of interleukin-1b, interleukin-6 and tumor necrosis factor-a in regulating synaptic and neuronal activity in the superficial spinal cord. J Neurosci 28: 5189–5194. Kilduff TS, Peyron C (2000). The hypocretin/orexin ligandreceptor system: implications for sleep and sleep disorders. Trends Neurosci 23: 359–365. Kimura M, Majde JA, Toth LA et al. (1994). Somnogenic effects of rabbit and recombinant human interferons in rabbits. Am J Physiol 267: R53–R61. Kluger M, Kozak W, Conn CA et al. (1996). The adaptive value of fever. Infect Dis Clin North Am 10: 1–20. Kozak W, Zheng H, Conn CA et al. (1995). Thermal and behavioral effects of lipopolysaccharide and influenza in interleukin-1b deficient mice. Am J Physiol 269: R969–R977. Kozak W, Poli V, Soszynski D et al. (1997). Sickness behavior in mice deficient in interleukin-6 during turpentine abscess and influenza pneumonitis. Am J Physiol 272: R621–R630. Krueger JM, Obal F Jr (1993). A neuronal group theory of sleep function. J Sleep Res 2: 63–69. Krueger JM, Oba´l F Jr (1994). Sleep factors. In: NA Saunders, CE Sullivan (Eds.), Sleep and Breathing. Marcel Dekker, New York, pp. 79–112. Krueger JM, Obal F Jr (2003). Sleep function. Front Biosci 8: 511–519. Krueger JM, Majde JA (1994). Microbial products and cytokines in sleep and fever regulation. Crit Rev Immunol 14: 355–379. Krueger JM, Majde JA (2005). Host defense. In: M Kryger (Editor-in-Chief), Principles and Practice of Sleep Medicine. 4th edn. Elsevier Science, Philadelphia, PA, pp. 256–265. Krueger JM, Walter J, Dinarello CA et al. (1984). Sleeppromoting effects of endogenous pyrogen (interleukin-1). Am J Physiol 246: R994–R999. Krueger JM, Rector DM, Churchill L (2007). Sleep and cytokines. Sleep Med Clinics 2: 161–169. Kubota T, Kushikata T, Fang J et al. (2000). A nuclear factor kappa b (NFkB) inhibitor peptide inhibits spontaneous
and interleukin-1b-induced sleep. Am J Physiol 279: R404–R413. Kubota T, Fang J, Brown RA et al. (2001a). Interleukin-18 promotes sleep in rabbits and rats. Am J Physiol Regul Integr Compar Physiol 281: R828–R838. Kubota T, Fang J, Guan Z et al. (2001b). Vagotomy attenuates tumor necrosis factor-alpha-induced sleep and EEG delta-activity in rats. Am J Physiol 280: R1213–R1220. Kubota T, Majde JA, Brown RA et al. (2001c). Tumor necrosis factor receptor fragment attenuates interferon-b-induced non-REM sleep in rabbits. J Neuroimmunol 119: 192–198. Kubota T, Li N, Guan Z et al. (2002). Intrapreoptic microinjection of TNF-alpha enhances non-REMS in rats. Brain Res 932: 37–44. Kundermann B, Hemmeter-Spernal J, Huber MT et al. (2008). Effects of total sleep deprivation in major depression: overnight improvement of mood is accompanied by increased pain sensitivity and augmented pain complaints. Psychosom Med 70: 92–101. Kurokawa M, Imakita M, Kumeda CA et al. (1996). Cascade of fever production in mice infected with influenza virus. J Med Virol 50: 152–158. Kushikata T, Fang J, Chen Z et al. (1998). Epidermal growth factor enhances spontaneous sleep in rabbits. Am J Physiol 275: R509–R514. Kushikata T, Fang J, Krueger JM (1999). Brain-derived neurotrophic factor enhances spontaneous sleep in rats and rabbits. Am J Physiol 276: R1334–R1338. Larsen CM, Faulenbach M, Vaag A et al. (2007). Interleukin-1receptor antagonist in type 2 diabetes mellitus. N Engl J Med 356: 1517–1526. Leonard TO, Lydic R (1995). Nitric oxide synthase inhibition decreases pontine acetylcholine release. Neuroreport 6: 1525–1529. Leonard TO, Lydic R (1997). Pontine nitric oxide modulates acetylcholine release, rapid eye movement sleep generation, and respiratory rate. J Neurosci 17: 774–785. Lewerenz M, Mogensen KE, Uze´ G (1998). Shared receptor components but distinct complexes for alpha and beta interferons. J Mol Biol 282: 585–599. Lu J, Bjorkum AA, Xu M et al. (2002). Selective activation of the extended ventrolateral preoptic nucleus during rapid eye movement sleep. J Neurosci 22: 4568–4576. Lue FA, Bail FA, Jephthah-Ocholo J et al. (1998). Sleep and cerebrospinal fluid interleukin-1 like activity in the cat. Int J Neurosci 42: 179–183. McGinty D, Szymusiak R (2003). Hypothalamic regulation of sleep and arousal. Front Biosci 8: d1074–d1083. Mackiewicz M, Sollars PJ, Ogilvie MD et al. (1996). Modulation of IL-1beta gene expression in the rat CNS during sleep deprivation. Neuroreport 7: 529–533. Mackowiak PA (1981). Direct effects of hyperthermia on pathogenic microorganisms: teleologic implications with regard to fever. Rev Infect Dis 3: 508–520. Majde JA (2000). Viral double-stranded RNA, cytokines and the flu. J Interferon Cytokine Res 20: 259–272. Majde JA, Krueger JM (2002). Neuroimmunology of sleep. In: H D’haenen, JA den Boer, P Willner (Eds.), Biological Psychiatry. John Wiley, London, pp. 1247–1257.
CYTOKINES IN IMMUNE FUNCTION AND SLEEP REGULATION Majde JA, Krueger JM (2005). Links between the innate immune system and sleep. In: WT Shearer, LJ Rosenwasser, BS Bochner (Eds.), Molecular Mechanisms in Allergy and Clinical Immunology. Manfridi A, Brambilla D, Bianchi S et al. (2003). Interleukin-1 beta enhances non-rapid eye movement sleep when microinjected into the dorsal raphe nucleus and inhibits serotonergic neurons in vitro. Eur J Neurosci 18: 1041–1049. Maquet P, Peigneux P, Laureys S et al. (2003). Memory processing during human sleep as assessed by functional neuroimaging. Rev Neurol (Paris) 159: 6S27–6S29. Minoguchi K, Tazaki T, Yokoe T et al. (2004). Elevated production of tumor necrosis factor-alpha by monocytes in patients with obstructive sleep apnea syndrome. Chest 126: 1473–1479. Moldofsky H (1995). Sleep, neuroimmune and neuroendocrine functions in fibromyalgia and chronic fatigue syndrome. Adv Neuroimmunol 5: 39–56. Moss RB, Mercandetti A, Vojdani A (1999). TNF-alpha and chronic fatigue syndrome. J Clin Immunol 19: 314–316. Mullington J, Korth C, Hermann DM et al. (2000). Dosedependent effects of endotoxin on human sleep. Am J Physiol Regul Integr Comp Physiol 278: R947–R955. Nguyen KT, Deak T, Owens SM et al. (1998). Exposure to acute stress induces brain interleukin-1 beta protein in the rat. J Neurosci 18: 2239–2246. Obal F Jr, Krueger JM (2003). Biochemical regulation of sleep. Front Biosci 8: 520–550. Okun ML, Giese S, Lin L et al. (2004). Exploring the cytokine and endocrine involvement in narcolepsy. Brain Behav Immun 18: 326–332. Omdal R, Gunnarsson R (2005). The effect of interleukin-1 blockade on fatigue in rheumatoid arthritis – a pilot study. Rheumatol Int 25: 481–484. Opp MR, Krueger JM (1991). Interleukin 1 receptor antagonist blocks interleukin 1-induced sleep and fever. Am J Physiol 260: R453–R457. Opp MR, Krueger JM (1994). Anti-interleukin-1 beta reduces sleep and sleep rebound after sleep deprivation in rats. Am J Physiol 266: R688–R695. Pan W, Banks WA, Kastin AJ (1997). Permeability of the blood–brain and blood–spinal cord barriers to interferons. J Neuroimmunol 76: 105–111. Pickering M, O’Connor JJ (2007). Pro-inflammatory cytokines and their effects in the dentate gyrus. Prog Brain Res 163: 339–354. Plata-Salaman CR, Ilyin SE, Turrin NP et al. (2000). Kindling modulates the IL1 beta system, TNF-alpha, TGF-beta 1, and neuropeptide mRNAs in specific brain regions. Mol Brain Res 75: 248–258. Pollmacher T, Mullington J, Korth C et al. (1995). Influence of host defense activation on sleep in humans. Adv Neuroimmunol 5: 155–169. Quesada JR, Talpaz M, Rios A et al. (1986). Clinical toxicity of interferons in cancer patients: a review. J Clin Oncol 4: 234–243.
239
Rector DM, Topchiy IA, Carter KM et al. (2005). Local functional state differences between rat cortical columns. Brain Res 1047: 45–55. Reznikov LL, Puren AJ, Fantuzzi G et al. (1998). Spontaneous and inducible cytokine responses in healthy humans receiving a single dose of IFN-alpha2b: increased production of interleukin-1 receptor antagonist and suppression of IL-1-induced IL-8. J Interferon Cytokine Res 18: 897–903. Rizzi M, Perego C, Aliprandi M et al. (2003). Glia activation and cytokine increase in rat hippocampus by kainic acidinduced status epilepticus during postnatal development. Neurobiol Dis 14: 494–503. Roky R, Oba´l F, Valatx JL et al. (1995). Prolactin and rapid eye movement. Sleep 18: 536–542. Romanovsky A, Almeida MC, Aronoff DM et al. (2005). Fever and hypothermia in systemic inflammation: recent discoveries and revisions. Front Biosci 10: 2193–2216. Roy S, Krueger JM, Rector DM et al. (2008). A network model for activity-dependent sleep regulation. J Theor Biol 253: 462–478. Sakai K, Crochet S, Onoe H (2001). Pontine structures and mechanisms involved in the generation of paradoxical (REM) sleep. Arch Ital Biol 139: 93–107. Schinder AF, Poo M (2000). The neurotrophin hypothesis for synaptic plasticity. Trends Neurosci 23: 639–645. Shoham S, Davenne D, Cady AB et al. (1987). Recombinant tumor necrosis factor and interleukin 1 enhance slowwave sleep. Am J Physiol 253: R142–R149. Smedley H, Katrak M, Sikola K et al. (1983). Neurological effects of recombinant human interferon. Brit Med J 286: 262–264. Solle M, Labsi J, Perragaux DG et al. (2001). Altered cytokine production in mice lacking P2X(7) receptors. J Biol Chem 276: 125–132. Sriskandan K, Garner P, Watkinson J et al. (1986). A toxicity study of recombinant interferon-gamma given by intravenous infusion to patients with advanced cancer. Cancer Chemother Pharmacol 18: 63–68. Steel DM, Whitehead AS (1994). The major acute phase reactants: C-reactive protein, serum amyloid P component and serum amyloid A protein. Immunol Today 15: 81–88. Stellwagen D, Malenka RC (2006). Synaptic scaling mediated by glial TNF-a. Nature 440: 1054–1059. Suzuki T, Hide I, Ido K et al. (2004). Production and release of neuroprotective tumor necrosis factor by P2X7 receptoractivated microglia. J Neurosci 24: 1–7. Szentirmai E, Yasuda T, Taishi P et al. (2007). Growth hormone-releasing hormone: cerebral cortical sleeprelated EEG actions and expression. Am J Physiol Regul Integr Comp Physiol 293: R922–R930. Taishi P, Bredow S, Guha-Thakurta N et al. (1997). Diurnal variations of interleukin-1 beta mRNA and beta-actin mRNA in rat brain. J Neuroimmunol 75: 69–74. Taishi P, Gardi J, Chen Z et al. (1999). Sleep deprivation increases the expression of TNF alpha mRNA and TNF 55kD receptor mRNA in rat brain. Physiologist 42: A4.
240
J.M. KRUEGER ET AL.
Taishi P, Sanchez C, Wang Y et al. (2001). Conditions that affect sleep alter the expression of molecules associated with synaptic plasticity. Am J Physiol 281: R839–R845. Takahashi S, Krueger JM (1999). Nerve growth factor enhances sleep in rabbits. Neurosci Lett 264: 149–152. Takahashi S, Kapa´s L, Fang J et al. (1996). An interleukin-1 receptor fragment inhibits spontaneous sleep and muramyl dipeptide-induced sleep in rabbits. Am J Physiol 271: R101–R108. Toth LA, Hughes LF (2004). Macrophage participation in influenza-induced sleep enhancement in C57BL/6J mice. Brain Behav Immun 18: 375–389. Toth LA, Tolley EA, Krueger JM (1993). Sleep as a prognostic indicator during infectious disease in rabbits. Proc Soc Exp Biol Med 203: 179–192. Tringall G, Dello Russo C, Preziosi P et al. (2000). Interleukin-1 in the central nervous system: from physiology to pathology. Therapie 55: 171–175. Trompet S, de Craen AJ, Slagboom P et al. (2008). Genetic variation in the interleukin-1 beta-converting enzyme associates with cognitive function. The PROSPER study. Brain 131: 1069–1077. Turrin NP, Rivest S (2004). Innate immune reaction in response to seizures: implications for the neuropathology associated with epilepsy. Neurobiol Dis 16: 321–334. Uze´ G, Lutfalla G, Bandu M-T et al. (1992). Behavior of a cloned murine interferon a/b receptor expressed in homospecific or heterospecific background. Proc Natl Acad Sci U S A 89: 4774–4778. Vgontzas AN, Papanicolaou DA, Bixler EO et al. (1997). Elevation of plasma cytokines in disorders of excessive daytime sleepiness: role of sleep disturbance and obesity. J Clin Endocrinol Metab 82: 1313–1316. Vgontzas AN, Zoumakis M, Papanicolaou DA et al. (2002). Soluble TNF-alpha receptor 1 and IL-6 plasma levels in humans subjected to the sleep deprivation model of spaceflight. Metabolism 51: 887–892. Vgontzas AN, Bixler EO, Chrousos GP (2003). Metabolic disturbances in obesity versus sleep apnoea: the importance of visceral obesity and insulin resistance. J Intern Med 254: 32–44. Vgontzas AN, Zoumakis E, Lin HM et al. (2004). Marked decrease in sleepiness in patients with sleep apnea by etanercept, a tumor necrosis factor-a antagonist. J Clin Endocrinol Metab 89: 4409–4413. Vollmer-Conna U, Fazou C, Cameron B et al. (2004). Production of pro-inflammatory cytokines correlateswith the symptoms of acute sickness behavior in humans. Psychol Med 34: 128–1297.
Vyazovskiy V, Borbely AA, Tobler I (2000). Unilateral vibrissae stimulation during waking induces interhemispheric EEG asymmetry during subsequent sleep in the rat. Sleep Res 9: 367–371. Vyazovskiy V, Welker E, Fritschy J et al. (2004). Regional cortical metabolism and dynamics of slow wave activity during sleep after unilateral whisker stimulation and sleep deprivation in mice. Sleep 27: A5. Walker AJ, Topchiy I, Kouptsou K et al. (2005). ERP differences during conditioned lick response in the rat. Sleep 28: A15. Walton PE, Cronin MJ (1990). Tumor necrosis factor-a and interferon-g reduce prolactin release in vitro. Am J Physiol 259: E672–E676. Werner-Felmayer G, Werner ER, Fuchs D et al. (1989). Characteristics of interferon induced tryptophan metabolism in human cells in vitro. Biochem Biophys Acta 1012: 140–147. Yamuy J, Morales FR, Chase MH (1995). Induction of rapid eye movement sleep by microinjection of nerve growth factor into the pontine reticular formation of the cat. Neuroscience 66: 9–13. Yamuy J, Sampogna S, Chase MH (2000). Neurotrophinreceptor immunoreactive neurons in mesopontine regions involved in the control of behavioral states. Brain Res 866: 1–14. Yasuda T, Yasuda K, Brown RA et al. (2005a). Statedependent effects of light-dark cycle on somatosensory and visual cortex EEG in rats. Am J Physiol Regul Integr Comp Physiol 289: R1083–R1089. Yasuda T, Yoshida H, Garcia-Garcia F et al. (2005b). Interleukin-1b has a role in cerebral cortical statedependent electroencephalographic slow-wave activity. Sleep 28: 177–184. Yi PL, Tsai CH, Lin JG et al. (2004). Kindling stimuli delivered at different times in the sleep–wake cycle. Sleep 27: 203–212. Yndestad A, Dama˚s JK, ie E et al. (2007). Role of inflammation in the progression of heart failure. Curr Cardiol Rep 9: 236–241. Yoshida H, Peterfi Z, Garcia-Garcia F et al. (2004). Statespecific asymmetries in EEG slow wave activity induced by local application of TNF alpha. Brain Res 1009: 129–136. Zhang X, Alley EW, Russell SW et al. (1994). Necessity and sufficiency of beta interferon for nitric oxide production in mouse peritoneal macrophages. Infect Immun 62: 33–40.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 16
Endocrine and metabolic changes during sleep ALEX STEIGER * Max Planck Institute of Psychiatry, Munich, Germany
INTRODUCTION Sleep is a time of distinct activity in various endocrine systems. Two major methods of sleep research in various species including humans are the sleep electroencephalogram (EEG) and the assessment of sleep-related endocrine activity (e.g., by collection of hormone profiles). The combination of these methods helps to elucidate the interaction of sleep EEG and hormones in normal and disturbed sleep. Simultaneous investigations of sleep endocrine activity have been performed in healthy females and males of different ages, in patients with psychiatric, endocrine, and sleep disorders, during spontaneous sleep, after manipulation of sleep–wake behavior, and after administration of drugs and hormones. Furthermore, related animal models have been studied. These studies showed a bidirectional interaction between sleep EEG and endocrine activity. Certain neuropeptides and steroids were shown to play a specific role in sleep regulation. Sleeping and eating are two kinds of behavior that are essential for the survival of humans and higher animals. While sleeping and eating do not occur at the same time, certain hormones appear to influence, depending on time and concentration, both of these phenomena. Furthermore changes in sleep–wake behaviour may affect metabolism. During nocturnal sleep 3–5 sleep cycles occur in humans. Each cycle consists of one episode of nonrapid eye movement sleep (NREMS) and one episode of rapid eye movement sleep (REMS). The first NREMS period contains the major portion of slow-wave sleep (SWS) and, as assessed by EEG spectral analysis (Borbe´ly et al., 1981; Trachsel et al., 1992), the major portion of slow-wave activity (SWA). The secretion of various hormones shows distinct patterns. In short, during the first half of the night the growth hormone (GH)
surge is preponderant whereas adrenocorticotropic hormone (ACTH) and cortisol levels are low. In contrast, during the second half of the night, ACTH and cortisol are high while GH is low (Figure 16.1) (Weitzman, 1976). This pattern suggests: (1) a reciprocal interaction of the hypothalamo-pituitary-somatotrophic (HPS) and the hypothalamo-pituitary-adrenocortical (HPA) systems (their peripheral endpoints are GH and cortisol respectively); and (2) common regulators of the sleep EEG and nocturnal hormone secretion. Indeed, there is good evidence that a reciprocal interaction of the key hormones of the HPS and HPA systems, GHreleasing hormone (GHRH) and corticotropin-releasing hormone (CRH) plays a major role in sleep regulation. Sleep EEG (Bliwise, 1993) and nocturnal hormone secretion (Van Coevorden et al., 1991) change throughout the life span. In women the menopause is a major turning point towards impaired sleep (Ehlers and Kupfer, 1997), whereas in men sleep quality declines continuously with aging. Renin is the hormone which is most clearly linked to the NREMS–REMS cycle. Plasma renin activity (PRA) shows oscillations over about a 90-minute period. PRA reaches its peak during NREMS and its acrophases during REMS in humans (Brandenberger et al., 1988) and in rats (Oba´l et al., 1994). A link between SWS and the peaks of renin secretion was particularly observed.
HYPOTHALAMO-PITUITARYSOMATOTROPHIC SYSTEM Basic activity GH stimulates tissue growth and protein anabolism. These effects are mediated in part by insulin-like growth factor-1 (IGF-1). The synthesis and secretion of GH are promoted by GHRH and inhibited by
*Correspondence to: Axel Steiger, M.D., Max Planck Institute of Psychiatry, Department of Psychiatry, Kraepelinstrasse 10, 80804 Munich, Germany. Tel.: þþ49-89-30622-236, Fax: þþ49-89-30622-552, E-mail:
[email protected]
242
A. STEIGER Patients with depression 25 yrs
Controls 25 yrs EEG
Wake REM I II III IV
EEG
300 200 100 0
CORTISOL ng/ml
40
GH ng/ml
Wake REM I II III IV 300
CORTISOL ng/ml
GH ng/ml
200 100 0
20
h
0 23.00
01.00
03.00
05.00
40 20
h
0 23.00
07.00
01.00
65 yrs EEG
CORTISOL ng/ml
GH ng/ml
EEG
300 200 100 0
CORTISOL ng/ml
40
GH ng/ml
20
h
0 01.00
03.00
05.00
07.00
05.00
07.00
65 yrs
Wake REM I II III IV
23.00
03.00
05.00
07.00
Wake REM I II III IV 300 200 100 0
40 20
h
0 23.00
01.00
03.00
Fig. 16.1. Individual hypnograms and patterns of cortisol and growth hormone (GH) secretion in 4 male subjects (young and old patients with depression and normal controls). EEG, electroencephalogram; REM, rapid eye movement. (Reproduced with permission from Steiger (2002). Copyright John Wiley.)
somatostatin. Ghrelin has been identified as an additional stimulus for GH release (Kojima et al., 1999). All these components of the HPS system participate in sleep regulation. The major peak of GH secretion during the 24 hours occurs after sleep onset in rather strict but not absolute association with the first period of SWS (Quabbe et al., 1966; Takahashi et al., 1968; Steiger et al., 1987). When GH concentrations are determined every 30 seconds in normal young males, maximal GH secretion is found within minutes of SWS onset (Holl et al., 1991). However, GH may be released before sleep onset in normal males (Steiger et al., 1987). In women a presleep GH surge and one or more additional GH peaks are characteristically found (Antonijevic et al., 1999). A close temporal relationship is found between GH secretion and SWA (Gronfier et al., 1996). GH secretion appears to be sleep-dependent and is suppressed during sleep deprivation (Sassin et al., 1969; Beck et al., 1975). However, in sleep-deprived but relaxed normal young males in a supine position an unchanged nocturnal GH peak is observed (Mullington
et al., 1996). Rest is sufficient to trigger the GH surge. A weak circadian component in the regulation of GH release was delineated. About one-third of SWS periods are not associated with GH secretion (Van Cauter et al., 1992). Distinct parallel decreases of SWS, SWA, and GH secretion start during the third decade of the life span. In males it is near the onset of the fifth decade that the GH pause occurs. From then on GH release is nearly absent. In women the GH pause is related to the menopause. Hypothalamic GHRH mRNA depends on a circadian rhythm. In rats the highest concentration is found when sleep propensity reaches its maximum in these night-active animals at the onset of the light period (Bredow et al., 1996). Hypothalamic GHRH contents show sleep-related variations with low levels in the morning, increases in the afternoon, and decreases at night (Gardi et al., 1999). Calcium levels in GABAergic neurons cultured from rat fetal hypothalamus increase when perfused with GHRH (De et al., 2002). It is thought that many hypothalamic GHRH-responsive neurons are GABAergic. In the rat GABAergic
ENDOCRINE AND METABOLIC CHANGES DURING SLEEP neurons in the preoptic hypothalamus were identified as potential targets of the sleep-promoting actions of GHRH (Peterfi et al., 2010).
Effects of HPS hormone administration on the sleep EEG GROWTH
HORMONE-RELEASING HORMONE
GHRH is an important endogenous sleep-promoting substance. The GHRH gene is found in the mouse in the DNA region related to SWA (Franken et al., 2001). Intracerebroventricular (ICV) administration of GHRH increases SWS in rats and rabbits (Ehlers et al., 1986; Oba´l et al., 1988). The same effect occurs when GHRH is injected into the medial preoptic area in rats (Zhang et al., 1999) or intravenously (IV) to rats (Oba´l et al., 1996). Similarly, after repetitive hourly IV bolus injections of GHRH (22:00–01:00 hours), SWS and GH secretion increase and cortisol levels decrease in young normal men (Steiger et al., 1992). Mimicking the pulsatile endogenous release is a major methodological issue since sleep remains unchanged after GHRH infusion in controls (Marshall et al., 1999). Sleep promotion in young male subjects by GHRH was confirmed after IV (Kerkhofs et al., 1993; Marshall et al., 1999) and intranasal (Perras et al., 1999) administration. The sleep-promoting effect of IV GHRH in the elderly is weak (Guldner et al., 1997). A sexual dimorphism in the response to IV GHRH is found in drugfree patients of both sexes with depression (19–76 years) and in matched controls. In male patients and controls GHRH decreases ACTH and cortisol levels. In contrast, these hormones increase in females. Similarly, NREMS increases and wakefulness decreases in males whereas opposite changes of sleep EEG occur in women after GHRH. These data point to a reciprocal antagonism of GHRH and CRH in males, whereas a synergism of GHRH and CRH is suggested in females (Antonijevic et al., 2000a). In rats NREMS decreases after administration of a GHRH receptor antagonist (Oba´l et al., 1991) and after antibodies to GHRH (Oba´l et al., 1992b). Sleep deprivation is a major stimulus for sleep (Borbe´ly et al., 1981, 1984; Franken et al., 1991). GHRH appears to mediate this effect. GHRH antibodies (Oba´l et al., 1992b) and microinjections of a GHRH antagonist into the area preoptica inhibits the sleep rebound after sleep deprivation in rats (Zhang et al., 1999). Sleep deprivation prompts a depletion of hypothalamic GHRH and low hypothalamic GHRH contents in rats (Gardi et al., 1999) whereas hypothalamic GHRH mRNA increases and hypothalamic somatostatin decreases (Toppila et al., 1997; Zhang et al., 1999). Probably the high rate of GHRH release stimulates
243
transcription. GHRH receptor mRNA and GHRH binding decline by 50% in the hypothalamus of rats after sleep deprivation. It is thought that a distinct intrahypothalamic release explains the downregulation of hypothalamic GHRH receptors (Oba´l and Krueger, 2004).
GROWTH HORMONE, INSULIN-LIKE GROWTH FACTOR-1 Negative-feedback inhibition of GHRH after administration of GH in humans (Mendelson et al., 1980), cats (Stern et al., 1975), and rats (Drucker-Colin et al., 1975; Oba´l and Krueger, 2004) or high doses of IGF-1 (Oba´l et al., 1999) decrease NREMS. On the other hand antagonizing GH impairs sleep (Oba´l et al., 1997a). Low-dose ICV IGF-1 increases NREMS in rats (Oba´l et al., 1998).
SOMATOSTATIN Selective increases of REMS were reported in rats after ICV somatostatin (Danguir, 1986). On the other hand systemic and ICV administration of the somatostatin analog octreotide decreases NREMS and GH in rats (Beranek et al., 1999). Similarly, SWS decreases and intermittent wakefulness increase in young normal men after subcutaneous octreotide (Ziegenbein et al., 2004). Octreotide is long-acting and more potent than somatostatin. This explains why IV somatostatin impairs sleep in normal elderly controls (Frieboes et al., 1997), whereas it has no effect in young men (Parker et al., 1974; Kupfer et al., 1992; Steiger et al., 1992). In cats and rats somatostatin inhibits GABAergic transmission in the sensory thalamus via presynaptic receptors (Leresche et al., 2000). This mechanism may contribute to the decrease of NREMS after somatostatin. A reciprocal interaction of GHRH and somatostatin in sleep regulation similarly to their relationship in the regulation of GH release appears likely.
INTERACTIONS
OF
HPS
SYSTEM AND OREXIN
The orexins (OX-A and OX-B) derive from their common precursor prepro-orexin. Orexins participate in the regulation of sleep (Mignot, 2004). An interaction between OX-A, GHRH, and somatostatin in the regulation of sleep, food intake, and GH release has been suggested. In patients with narcolepsy, who show orexin deficiency, changes of the circadian pattern of GH secretion were reported, pointing to a disruption of GHRH release (Overeem et al., 2003). Lopez et al. (2004) studied the interaction of these peptides in rats. In situ hybridization showed a decrease of GHRH mRNA levels in the paraventricular nucleus of the hypothalamus after OX-A treatment without changes
244
A. STEIGER
in the arcuate nucleus. The somatostatin mRNA content in the hypothalamus increases in normal rats, whereas it decreases in GH-deficient rats. In these animal models of GH deficiency (hypophysectomized rats and dwarf Lewis rats), GHRH mRNA levels in the paraventricular nucleus of the hypothalamus are reduced.
Animal models of HPS system changes Very big supermice sleep more than normal mice (Lachmansingh and Rollo, 1994). In the giant transgenic mice (MT-rGH mice) plasma GH is permanently elevated. During the light period NREMS is higher and REMS is almost doubled in these mice compared to normal mice. Also after sleep deprivation the MT-rGH mice sleep more than normal mice (Hajdu et al., 2002). In dwarf rats with deficits in the central GHRHergic transmission and reduced hypothalamic GHRH, NREMS is diminished in comparison to control rats (Oba´l et al., 2001). In dwarf homozygous (lit/lit) mice with nonfunctional GHRH receptor NREMS and REMS are reduced. In the dwarf mice infusion of GH by Alzet minipumps leads to normalization of REMS, but not of NREMS within 9 days. GHRH and octreotide exert no effect on sleep EEG in dwarf mice (Oba´l and Krueger, 2004).
Sleep in disorders of the HPS system In patients with short stature due to isolated GH deficiency, SWS and SWA are reduced in comparison to normal controls, whereas total sleep time and NREMS ˚ stro¨m and Jochumsen, 1989; stages 1 and 2 increase (A ˚ Astro¨m and Lindholm, 1990). Excessive GH levels are found in patients with acromegaly. In these patients obstructive sleep apnea syndrome is frequent due to hyperplasia of their upper-airway soft tissue (Hart et al., 1985). However, daytime sleepiness and an abnormal sleep structure are also found in patients with acromegaly without sleep apnea. After surgical therapy (adenectomy), REMS and SWS time increase in these patients ˚ stro¨m and Trojaborg, 1992). (A
HYPOTHALAMO-PITUITARYADRENOCORTICAL SYSTEM Basic activity The HPA system mediates the reaction to acute physical and psychological stress. This stress reaction starts with the release of CRH from the parvonuclear cells of the hypothalamus. This results in the secretion of ACTH from the anterior pituitary and finally in the secretion of cortisol (in humans) or corticosterone (in
rats) from the adrenocortex. Various cofactors contribute to this cascade (Holsboer, 1999). In rats CRH gene transcription levels increase during the dark period, when the animals are active, and decrease throughout the light period (Watts et al., 2004). In humans, both the nadir and the major secretion of ACTH and cortisol occur during sleep. The first few hours of the night contain their quiescent period. The first pulse of cortisol occurs in the early morning. It is followed by further pulses until awakening (Weitzman, 1976; Born and Fehm, 1998). ACTH is the prime regulator of nocturnal cortisol secretion in humans; however the secretion of ACTH and cortisol may dissociate (Fehm et al., 1984; Krishnan et al., 1990). The analysis of the relationships of the NREMS– REMS cycle and of cortisol secretion shows an association between a decrease in cortisol levels and REMS periods, particularly during the first four sleep cycles (Fehm et al., 1993). ACTH and cortisol are higher in normal male subjects with relatively short total sleep time when compared to long sleepers (Spa¨th-Schwalbe et al., 1992). A study in monozygotic and dizygotic pairs of male normal twins showed genetic control for the timing of the cortisol nadir and for the proportion of overall temporal variability associated with pulsatility. In contrast, environmental effects were identified for the 24-hour mean and the timing of the morning acrophase (Linkowski et al., 1993). Controversial reports exist on the influence of age on HPA hormones. The study including the largest sample of normal human adults reported age-dependent increases of mean cortisol levels and of the nadir and, in women only, of the acrophase. With age, the cortisol amplitude was dampened and the morning rise advanced (Van Cauter et al., 1996).
Effects of changes of sleep–wake behavior on HPA hormones Weitzman and colleagues (Weitzman, 1976) did pioneering work as they used nonpharmacological manipulations to study the interaction between sleep EEG and hormones. They showed that the pattern of cortisol secretion is widely dependent on a circadian rhythm, whereas manipulation of the sleep–wake pattern prompts subtle changes in HPA secretion. Various studies investigated HPA activity at several intervals during and after partial and total sleep deprivation. During the night of sleep deprivation either enhanced or unchanged cortisol concentrations were reported. In the recovery night after one night of sleep deprivation, cortisol was unchanged in young and elderly normal controls compared to baseline
ENDOCRINE AND METABOLIC CHANGES DURING SLEEP conditions (Murck et al., 1999). In depressed patients during sleep deprivation cortisol increased and returned to baseline values during the recovery night (Voderholzer et al., 2004). In the evening after partial or total sleep deprivation, cortisol was elevated in normal controls (Leproult et al., 1997). Similarly, evening cortisol increased when sleep in normal young men was restricted to 4 hours for 6 days (Spiegel et al., 1999). In the recovery night after 4 nights with restricted sleep, cortisol was blunted during the second half of the night (Follenius et al., 1992). In rats 72 hours of sleep deprivation resulted in increases in CRH levels in the striatum, limbic areas, and pituitary, whereas hypothalamic CRH was reduced (Fadda and Fratta, 1997). In vivo microdialysis in rats showed a marked rise in free corticosterone levels in the brain during sleep deprivation (Penalva et al., 2000). Rats were sleep-deprived during intervals up to 92 hours. ACTH and corticosterone plasma levels increased from 24 hours of sleep deprivation and decreased during the recovery period (Andersen et al., 2005). The HPA acrophase appears to be linked with the end of sleep in the morning. The expectation of waking up at a certain time induces a marked increase in ACTH before the end of sleep (Born et al., 1999). Cortisol secretion appears to be relatively stable to environmental changes. After a flight from Europe to the USA it took 2 weeks for the cortisol pattern of normal control subjects to be totally adapted to the new sleep schedule (Desir et al., 1981). Dissociation of sleep and cortisol after long-distance travel may contribute to jet lag. In shift workers a long-lasting resistance of the cortisol rhythm to adapting totally to an inverted sleep–wake schedule was found. Young male night workers who had been chronically on nightshift were compared to day-active controls. In each group sleep EEG and hormone secretion were investigated during the usual sleep time (07:00–15:00 in the night workers or 23:00–07:00 in the controls respectively). Whereas sleep EEG did not differ distinctly between groups, cortisol was enhanced in the night workers during their sleep time. Conversely, during usual work hours cortisol was blunted in this sample (Weibel and Brandenberger, 1998). Light influences the timing of neuroendocrine rhythms via the suprachiasmatic nucleus. This is supported by a study in which hormone profiles were determined in normal controls on two separate occasions, once after they were chronically exposed to simulated short (8 hours) “summer nights” and once after they were chronically exposed to simulated long (14 hours) “winter nights.” During the “winter nights” the period of rising cortisol levels was longer than during the “summer nights” (Wehr, 1998).
245
Effects of HPA hormone administration on the sleep EEG CORTICOTROPIN-RELEASING
HORMONE
Various preclinical and human studies show that administration of HPA hormones or their antagonists affect sleep. After ICV CRH, SWS decreases in rats (Ehlers et al., 1986) and rabbits (Opp et al., 1989). CRH reduces SWS in rats even following 72 hours of sleep deprivation. Furthermore, sleep latency is prolonged and REMS increases (Marrosu et al., 1990). After repetitive hourly IV injections of 4 50 µg CRH in young normal men, SWS and REMS and the GH surge decrease and cortisol levels increase during the first half of the night (Holsboer et al., 1988). A dose of CRH which was not effective in young normal men impaired sleep in middle-aged men (Vgontzas et al., 2001). Obviously the vulnerability of sleep to CRH increases during aging. After treatment with a CRH receptor-1-antagonist, sleep EEG changes in patients with depression were counteracted, as the number of awakenings and REM density decreased and SWS increased (Held et al., 2004). These results support the view that CRH is involved in the pathophysiology of sleep EEG changes during depression.
CORTISOL Continuous nocturnal infusion (Born et al., 1991) and pulsatile IV administration of cortisol increase SWS (Friess et al., 1994), GH, and SWA (Friess et al., 2004) and decrease REMS in young normal controls. Similarly, SWS, SWA, and GH increase and REMS decreases after pulsatile IV cortisol in elderly males (Bohlhalter et al., 1997). Since CRH (Holsboer et al., 1988) and cortisol exert opposite effects on SWS (Born et al., 1991; Friess et al., 1994) and GH levels (Friess et al., 1994; Bohlhalter et al., 1997), it appears unlikely that these effects are mediated via stimulation of cortisol. In contrast, these changes may be explained by negative-feedback inhibition of endogenous CRH. In contrast to the effects of acute cortisol administration, treatment of female patients with multiple sclerosis with the glucocorticoid receptor agonist methylprednisolone for 9 days resulted in changes resembling the sleep EEG alterations in depression, e.g., shortened REMS latency, increased REMS density, and a shift of the major portion of SWS from the first to the second NREMS period (Antonijevic and Steiger, 2003).
Animal models of HPA system changes In the Lewis rat the synthesis of CRH is reduced due to a hypothalamic gene defect. Lewis rats spend less time awake and more time in SWS than intact rat strains
246
A. STEIGER
(Opp, 1997). Similarly, spontaneous wakefulness of rats is reduced by a CRH antisense oligodeoxynucleotide (Chang and Opp, 2004). A role of CRH in the maintenance of wakefulness and its sleep-disturbing effects are confirmed by this study. Sleep EEG of mice overexpressing CRH in the forebrain REM was compared to the wild type. The amount of REM sleep was higher in the transgenic mice than in the control animals (Kimura et al., 2010). This finding supports the view that REM disinhibition serves as a biomarker of disorders associated with enhanced CRH secretion, particularly depression.
Sleep in disorders with pathological HPA activity In Addison’s disease the capacity of the adrenal glands to produce corticosteroids is severely reduced. No major alterations of their sleep were found in these patients (Gillin et al., 1974; Krieger and Glick, 1974). In contrast to Addison’s disease, hypercortisolism and disturbed sleep are frequent symptoms in Cushing’s disease. In these patients, SWS is reduced (Krieger and Glick, 1974; Shipley et al., 1992). In addition, changes in sleep continuity (increased sleep latency and enhanced waketime) were reported (Shipley et al., 1992). Similar symptoms are frequent in depression, whereas dysregulation of the HPA system is more subtle in affective disorders. Characteristic sleep EEG changes in depression include disturbed sleep continuity (prolonged sleep latency, increased number of awakenings, earlymorning awakening), decreased NREMS (decreases of stage 2 sleep and SWS, a shift of the major portion of SWS from the first to the second sleep cycle in younger patients) and REMS disinhibition (shortened REMS latency, prolonged first REMS period, elevated REMS density) (Ehlers and Kupfer, 1987). Well-documented endocrine changes include HPA overactivity (Holsboer, 1999) and HPS dysfunction (Steiger et al., 1989). Most sleep endocrine studies in depressed patients report elevated cortisol and ACTH (Linkowski et al., 1987; Steiger et al., 1989; Antonijevic et al., 2000b) throughout the night or 24 hours (Linkowski et al., 1987), respectively, when compared to controls. GH was blunted in most (Steiger et al., 1989; Jarrett et al., 1990; Voderholzer et al., 1993) but not all (Linkowski et al., 1987) studies. These findings point to a causal relationship between shallow sleep, low GH, and HPA overactivity in depression. Furthermore similar sleep endocrine changes are found during depression and during normal aging (Figure 16.1). Intraindividual comparison of depressed patients who were drugfree at least 14 days before each examination between acute depression and recovery showed a decrease of cortisol after recovery. The pathological
sleep EEG and low GH levels, however, remained unchanged (Steiger et al., 1989). This finding corroborates that HPA hypersecretion is a state marker of depression. The persistence of most sleep EEG (Kupfer et al., 1993) and GH changes (Jarrett et al., 1990) after recovery has been confirmed over 3 years. Obviously cortisol levels normalize independently from sleep. It is thought that the metabolic alterations during acute depression result in a biological scar, as reflected by the persisting changes of sleep EEG and GH levels in patients during remission. This hypothesis is supported by findings in male patients who survived severe brain injury (Frieboes et al., 1999). Several months later their cortisol levels did not differ from controls, whereas their GH levels and sleep stage 2 were reduced. Although cortisol levels were normal at the time of the examination, in this study it appears likely that either HPA overactivity due to stress associated with brain injury or treatment with glucocorticoids in some patients contributes to the changes of sleep EEG and of GH levels. Patients with primary insomnia had increased nocturnal cortisol and a shorter quiescent period than controls (Rodenbeck et al., 2002). The 24-hour ACTH and cortisol secretion were higher in young insomniacs than in controls. Patients with a high degree of objective sleep disturbance (shortened sleep time) secreted more cortisol than those with a low degree (Vgontzas et al., 2001). In another sample, however, nocturnal cortisol levels did not differ between patients with insomnia and controls, whereas their melatonin levels were blunted (Riemann et al., 2002).
HYPOTHALAMO-PITUITARY-THYROID (HPT) SYSTEM The secretion of thyroid-stimulating hormone (TSH) and of the thyroid hormone thyroxine is related to circadian rhythm (Chan et al., 1978; Brabant et al., 1987). The minimum TSH levels occur during daytime. During the night TSH rises and reaches its maximum by midnight. The course of thyroxine release is inverse to that of TSH. Thyroxine concentrations are low during the night and increase during daytime. One study reported declining TSH levels during REMS periods (Follenius et al., 1988). Pulsatile IV thyrotropin-releasing hormone decreases sleep efficiency and prompts the advanced occurrence of the cortisol morning rise in young normal male control subjects (Hemmeter et al., 1998). Changes of sleep–wake behavior are well-known symptoms of disorders of the thyroid gland. Hyperthyroidism is linked with insomnia. In contrast, fatigue is frequent in patients with hypothyroidism. Reduced
ENDOCRINE AND METABOLIC CHANGES DURING SLEEP SWS was reported in patients with hypothyroidism and normalized after therapy (Kales et al., 1967).
LEPTIN AND GHRELIN Leptin, the protein product of the obese (ob) gene is released from adipocytes. It acts within the hypothalamus and reduces food intake (Tomaszuk et al., 1996). Serum leptin reaches its maximum between 00:00 and 04:00 hours. Leptin levels are higher in women than in men (Deuschle et al., 1996; Saad et al., 1997). An inverse relationship exists between leptin and cortisol, particularly in women (Licinio et al., 1997; Antonijevic et al., 1998). Ghrelin, which is the first peptide identified as an endogenous ligand of the GH secretagogue receptor was delineated as the orexigenic counterpart of leptin in the energy balance (Horvath et al., 2001). Similar to GHRH, repetitive IV (4 50 µg) ghrelin enhances SWS and GH in young normal men (Weikel et al., 2003). In contrast to GHRH, which blunted cortisol in men (Steiger et al., 1992), ghrelin increased ACTH and cortisol levels, particularly during the first half of the night (Weikel et al., 2003). Ghrelin may act as an interface between the HPA and the HPS systems. The sleep-promoting effect of ghrelin was confirmed in elderly men (Kluge et al., 2010). In contrast, sleep remained unchanged after ghrelin in young (Kluge et al., 2007a) and elderly (Kluge et al., 2010) and healthy women and after ghrelin administration during the early-morning hours in young healthy men (Kluge et al., 2007b). In mice ghrelin promotes NREMS (Oba´l et al., 2003). An intact GHRH receptor is the prerequisite for this effect, since in mice with nonfunctional GHRH receptors sleep remains unchanged after ghrelin. A higher dose (100 µg) of ghrelin at 22:00 hours distinctly induced hunger in one subject (Weikel et al., 2003). Similarly, self-rated appetite increased when this dose was given in controls in the morning (Schmid et al., 2005). The increase of wakefulness after intracerebroventricular (Szentirmai et al., 2006) and intrahypothalamic (Szentirmai et al., 2007) injection of ghrelin in rats may be related to increased hunger. Bodosi et al. (2004) investigated the relationships among plasma ghrelin and leptin concentrations and hypothalamic ghrelin contents and sleep and feeding. Rats were examined under three conditions: (1) freefeeding rats with normal diurnal rhythms; (2) feeding restricted to the 12-hour light period; and (3) 5 hours of sleep deprivation at the beginning of the light period. The ghrelin peak preceded and the leptin peak followed the major daily feeding peak after dark onset, and the rats showed vigorous eating in the first hour of the light period after food restriction. The diurnal
247
rhythms of ghrelin and leptin reversed, but they maintained their relationship with respect to one another and to feeding activity. The ghrelin peak continued to precede the feeding peak. Consequently the maximum ghrelin was found towards the end of the dark period. The leptin peak followed the major feeding activity. The nocturnal ghrelin peak during restrictive feeding was almost double that of the diurnal ghrelin peak in rats on normal feeding conditions. Sleep deprivation did not change leptin but it stimulated plasma ghrelin and induced eating. Hypothalamic ghrelin contents increased during sleep deprivation and returned to baseline after sleep deprivation. These results suggest a strong relationship between feeding and the rhythm of leptin and a major influence of feeding on the rhythm of ghrelin. The variations in the hypothalamic ghrelin contents point to an association with the sleep–wake activity in rats. When young normal men who were semirecumbent for 24 hours were allowed to sleep they showed a sharp increase of ghrelin by sleep onset, followed by a decline throughout the night. This rise of ghrelin was blunted when the subjects were sleep-deprived (Dzaja et al., 2004). In another study ghrelin levels were determined between 20:00 and 07:00 hours in normal female and male subjects who were active during daytime. Ghrelin concentrations differed before sleep onset. In males there was a continuous rise of ghrelin between 20:00 and 23:00 hours. In females, however, ghrelin levels at 20:00 hours were already in the same range as during the sleeping period. No relationships between ghrelin and sleep stages or the nocturnal secretion of GH, cortisol, and ACTH were found (Schu¨ssler et al., 2008). In a large sample of more than 1000 subjects short sleep time was associated with higher ghrelin levels (Taheri et al., 2004). Similarly elevated ghrelin levels and blunted leptin levels at daytime were found in sleep restricted to 4 hours for 6 days when compared to extended (12 hours) sleep in controls (Spiegel et al., 2004). Furthermore, restricted sleep resulted in a lower glucose tolerance (Spiegel et al., 1999). In night-eating disorder sleep is disrupted due to nocturnal hunger and food intake. In a patient with this disorder distinctly elevated ghrelin levels were found (Rosenhagen et al., 2005).
INSULIN Insulin stimulates glucose uptake in adipocytes and skeletal muscles. Both circadian rhythmicity and sleep influence the profiles of glucose and the insulin secretion rate throughout 24 hours. This results in higher mean levels during nocturnal sleep (Van Cauter et al., 1991). For both glucose and the insulin secretion rate,
248
A. STEIGER
slow oscillations with a periodicity of 50–150 minutes occur in animals and humans. To determine whether these oscillations are influenced by sleep young normal subjects were investigated over 24 hours during continuous enteral nutrition, once with a normal sleep from 23:00 to 07:00 hours and once with a shifted sleep from 07:00 to 15:00 hours. The amplitude of glucose and the insulin secretion rate oscillations increased distinctly during the sleep periods, regardless of whether at night or in the daytime. Hence the changes are related to sleep rather than to the time of the day (Simon et al., 1994). Systemic insulin injection (Sangiah et al., 1982) and ICV insulin infusion for 3 days (Danguir and Nicolaidis, 1984) increase NREMS in rats. Rats with experimental diabetes mellitus show decreases of NREMS and REMS. Their sleep normalizes after systemic insulin infusion (Danguir, 1984).
PROLACTIN Basic activity Prolactin is a circulating hormone and a neuroprotein. It is localized particularly in the hypothalamus (Roky et al., 1995). In humans prolactin rises after sleep onset and reaches its peak during the second or the third third of the sleeping period (Weitzman, 1976). In contrast to various other hormones, prolactin is affected neither by normal aging (Van Coevorden et al., 1991) nor by an episode of depression (Steiger and Holsboer, 1997). During the recovery night after sleep deprivation prolactin levels increase in normal subjects (Murck et al., 1999). A study on the circadian influences on prolactin release suggests that the nocturnal rise in prolactin is not sleep-associated but rather is rest-dependent (Wehr et al., 1993). In normal humans the prolactin secretory rate is elevated throughout sleep independently from sleep quality (Spiegel et al., 1994). A twin study showed that the secretory response of prolactin to a standardized sleep/circadian stimulus is partly genetically controlled (Linkowski et al., 1998).
Effects of hormone administration PROLACTIN Prolactin administration promotes REMS in cats, rabbits, and rats (Roky et al., 1994). An experimental prolactin-secreting tumor under the kidney capsule prompts long-term hyperprolactinemia in rats and increases in nocturnal REMS whereas REMS during the day decreases (Valatx et al., 1994). In adult rats rendered chronically hyperprolactinemic by bearing juvenile rat anterior grafts under the capsule of the
kidney, increases in REMS and in the duration of NREMS were found (Oba´l et al., 1992a). On the other hand antiserum to prolactin (Oba´l et al., 1997b) and intrahypothalamic injection of prolactin antiserum decreases REMS in rats (Roky et al., 1994). These data point to promotion of REMS after prolactin.
VASOACTIVE
INTESTINAL POLYPEPTIDE
ICV injection of vasoactive intestinal polypeptide (VIP) also enhances REMS in laboratory animals (Drucker-Colin et al., 1984). When VIP was given to rats during the dark period, NREMS and REMS increased (Riou et al., 1982; Oba´l et al., 1994). Similarly, VIP microinjections into the pontine reticular tegmentum enhance REMS in rats up to 8 days (Bourgin et al., 1997). Interaction with the cholinergic system appears to mediate this effect. The REMS-promoting effect of systemic VIP was inhibited by immunoneutralization of the circulating prolactin in the rat. Stimulation of prolactin appears to be involved in the promotion of REMS after VIP (Oba´l et al., 1992a). VIP antibodies neutralized a REMS-promoting substance that accumulated in the cerebrospinal fluid of sleep-deprived cats (DruckerColin et al., 1988). An increase of VIP was found in the cerebrospinal fluid of REMS-deprived cats (Jimenez-Anguiano et al., 1993). Central administration of VIP antibodies (Riou et al., 1982) or of a VIP antagonist (Mirmiran et al., 1988) decreases REMS in rats. Prolactin increases and the NREMS–REMS cycles are decelerated in young normal males after pulsatile IV 4 50 µg VIP (Murck et al., 1996). VIP appears to exert a specific effect on the temporal organization of the NREMS–REMS cycle.
Sleep in prolactinoma In patients with prolactinoma SWS is increased when compared to normal controls (Frieboes et al., 1998).
OTHER NEUROPEPTIDES Galanin Galanin is widely located in the mammalian brain and coexists in neurons with various peptides and classical neurotransmitters participating in sleep regulation. Sleep in the rat remains unchanged after ICV galanin, whereas REMS deprivation induced galanin gene expression (Toppila et al., 1995). After repetitive IV galanin SWS and the duration of REMS periods increase in young normal male subjects (Murck et al., 1997). A cluster of GABAergic and galaninergic neurons was identified in the ventrolateral preoptic area,
ENDOCRINE AND METABOLIC CHANGES DURING SLEEP which appears to stimulate NREMS (Saper et al., 2001). REMS latency increases and the severity of depression as measured by the Hamilton Depression Scale decreases after IV galanin or placebo to patients with depression during a steady state of antidepressive therapy with trimipramine. These findings suggest an acute antidepressive effect of galanin (Murck et al., 2004).
Neuropeptide Y Neuropeptide Y (NPY) appears to be a physiological antagonist of CRH. After ICV NPY in rats, EEG spectral activity changes similarly to the effects of benzodiazepines (Ehlers et al., 1997a). The prolongation of sleep latency by CRH is antagonized dose-dependently by NPY in rats (Ehlers et al., 1997b). In young normal males repetitive IV NPY decreases sleep latency, the first REMS period and cortisol and ACTH levels, and increases stage 2 sleep and sleep period time (Antonijevic et al., 2000a). In patients with depression of both sexes with a wide age range and in age-matched controls as well, the sleep latency is shortened and prolactin levels increase after NPY, whereas cortisol and ACTH levels and the first REMS period remain unchanged (Held et al., 2006). NPY participates in sleep regulation, particularly in the timing of sleep onset as an antagonist of CRH, acting via the GABAA receptor.
MELATONIN Melatonin secretion is related to the light–dark cycle. Melatonin levels are maximal during the dark period in light-active and in dark-active species as well. Probably melatonin is primarily a neuroendocrine transducer promoting an increased propensity for “dark-appropriate” behavior (van den Heuvel et al., 2005). Study results on a beneficial effect of melatonin on sleep are ambiguous (Baskett et al., 2001; van den Heuvel et al., 2005; Zhdanova, 2005). There is a lack of sufficient data from clinical studies in order to recommend melatonin as a hypnotic. Some studies suggest that, due to phase-shifting properties, melatonin may be helpful in the treatment of rhythm disturbances, like jet lag and disturbed rhythms in blind patients (Zhdanova et al., 1997; Sack et al., 2000).
GONADAL HORMONES Basic activity In young females during puberty the lowest values of estradiol are found during the night (Boyar et al., 1976). In a small group of adult women no clear interaction between estradiol levels and sleep was observed
249
(Alford et al., 1973). In males testosterone rises constantly throughout the night (Weitzman, 1976).
Sleep in women In women the menstrual cycle, pregnancy, and the menopause reflect distinct changes in endocrine activity and have some impact on sleep. Only a few studies have addressed these issues so far. Most studies on sleep regulation and sleep disorders were performed selectively in men or in male animals. One of the reasons why females are not included in such studies is because of the variability of the menstrual cycle (Kimura, 2005).
MENSTRUAL
CYCLE EFFECTS ON SLEEP
In normal women the percentage of REMS tended to be higher in the early follicular than in the late luteal phase and the percentage of NREMS was higher in the luteal compared to the follicular phase. In NREMS EEG power density in the upper-frequency range of the sleep spindles exhibits a large variety across the menstrual cycle, which is maximum in the luteal phase (Driver et al., 1996). Normal cycling female rats show significantly less REMS during proestrus nights than during metestrus and diestrus nights. No changes in daytime sleep patterns are found across the estrocycle (Fang and Fishbein, 1996).
SLEEP
IN PREGNANCY
In healthy women during pregnancy waking increases from the second to the third trimester, whereas REMS decreases from the first to the second trimester. In NREMS a progressive reduction of power density occurs (Brunner et al., 1994). In rats during pregnancy nocturnal NREMS increases across the entire period, whereas REMS is enhanced only during the early period. After pregnancy sleep returned to baseline (Kimura et al., 1998).
SLEEP
CHANGES IN THE MENOPAUSE
Sigma frequency declines distinctly in women during the menopause, whereas in men these changes occur more gradually (Ehlers and Kupfer, 1997). After the menopause sleep endocrine changes associated with depression are accentuated (Antonijevic et al., 2003).
Effects of gonadal hormone administration GONADAL
HORMONE ADMINISTRATION IN ADULTS
Administration of gonadotropic hormones to adult animals exerts minimal effects on sleep or on sex differences in sleep (Manber and Armitage, 1999).
250
A. STEIGER
In postmenopausal women estrogen replacement therapy by skin patch enhances REMS and reduces intermittent wakefulness during the first two sleep cycles. The normal decrease in SWS and SWA from the first to the second cycle is restored (Antonijevic et al., 2000c). Estrogen treatment after menopause appears to restore the normal sleep EEG pattern in women. For the effects of progesterone replacement, see below.
Animal models – ovariectomy, castration REMS is enhanced in adult female rats after ovariectomy and is suppressed by estradiol replacement (Colvin et al., 1969). After castration REMS increases in neonatal mice. This effect is reversed by testosterone (Yang and Fishbein, 1995).
NEUROACTIVE STEROIDS Introduction Neuroactive steroids exert direct effects on neuronal membranes and thereby rapidly affect central nervous system excitability (Paul and Purdy, 1992). It is thought that this effect is mediated by the GABAAreceptor complex. Glial cells are capable of synthesizing neuroactive steroids independently of peripheral steroid sources (Jung-Testas et al., 1989). Various neuroactive steroids exert specific effects on sleep EEG.
Effects of neuroactive steroid administration on the sleep EEG PREGNENOLONE,
PREGNENOLONE SULFATE
An oral dose of 1 mg pregnenolone prompts sleep EEG changes resembling the effects of a partial inverse agonist at the GABAA receptor in young males, as SWS increases and EEG power in the spindle frequency range decreases (Steiger et al., 1993). Similarly, SWA increases in rats after subcutaneous pregnenolone at the beginning of the light period (Lancel et al., 1994). Intraperitoneal pregnenolone sulfate, however, increases REMS in rats (Darnaudery et al., 1999).
PROGESTERONE,
ALLOPREGNANOLONE
A dose-dependent hypnotic effect of IV progesterone was reported as early as 1954 (Merryman et al., 1954). After oral progesterone NREMS increases and SWA decreases in normal young men (Friess et al., 1997). These changes are similar to those after agonists at the GABAA receptor, e.g., benzodiazepines, and appear to be mediated in part via the conversion of progesterone into allopregnanolone.
In women progesterone levels decrease after the menopause. Oral progesterone replacement increases REMS and decreases intermittent wakefulness in postmenopausal women (Schu¨ssler et al., 2008). Intraperitoneal progesterone at the onset of the dark period in rats decreases NREMS latency, wakefulness, and REMS, and increases REMS latency and pre-REMS, an intermediate state between NREMS and REMS in a dose-dependent manner. Furthermore EEG activity decreases in the lower frequencies and increases in the higher frequencies. Two doses of intraperitoneal allopregnanolone reduce NREMS latency and the higher dose increases pre-REMS in rats. Furthermore in NREMS EEG activity decreases in the lower frequencies ( 7 Hz) and increases in the higher frequencies ( 13 Hz) (Lancel et al., 1997).
DEHYDROEPIANDROSTERONE, DHEA
SULFATE
Oral dehydroepiandrosterone (DHEA) increases selectively REMS in young normal men (Friess et al., 1995). This finding is comparable to a mixed GABAA agonistic/antagonistic effect. After intraperitoneal DHEA sulfate (DHEAS), a dose-dependent effect on EEG power was observed in rats. A dose of 50 mg/kg DHEAS augments EEG power in the spindle frequency range, whereas 100 mg/kg DHEAS exerts the opposite effect (Schiffelholz et al., 2000).
CONCLUSIONS The data reviewed in this chapter point to a bidirectional interaction between sleep EEG and endocrine activity. Various hormones exert specific effects on the sleep EEG. In Figure 16.2 a model of peptidergic sleep regulation in humans is proposed. A key role of a reciprocal interaction of the neuropeptides GHRH and CRH in sleep regulation is well documented. GHRH promotes sleep, at least in males, and stimulates GH secretion. In contrast, CRH enhances vigilance, ACTH, and cortisol and impairs sleep. Changes in the CRH:GHRH ratio in favor of CRH appear to result in shallow sleep, elevated cortisol, and blunted GH during depression and aging. GHRH participates in sleep promotion after sleep deprivation. On the other hand, GHRH exerts CRH-like effects in women as it impairs sleep and stimulates HPA hormones. Some, but not all, studies suggest that CRH promotes REMS. NPY appears to be crucial in the timing of sleep onset. Somatostatin is another sleep-impairing peptide. At least in males GHRH and somatostatin exert opposite actions on GH secretion and on sleep as well. Physiological cortisol levels appear to contribute to REMS maintenance. A synergism of elevated CRH
ENDOCRINE AND METABOLIC CHANGES DURING SLEEP NPY
YOUNG NORMAL CONTROL GALANIN GHRELIN GHRH
CRH
+ SRIF
WAKE REM I II III IV
CORTISOL
GH 40 ng/ml 20
300 200 ng/ml 100
0
0
A
PATIENT WITH DEPRESSION
GHRH
+ SRIF
CRH
WAKE REM I II III IV
CORTISOL
GH 40 ng/ml 20
300 200 ng/ml 100
0
0
B
ELDERLY NORMAL CONTROL GHRH
CRH
+ SRIF
WAKE REM I II III IV
CORTISOL
GH 40 ng/ml 20
ACKNOWLEDGMENT
300 200 ng/ml 100
0
C
251
activity and enhanced glucocorticoid levels may participate in the REMS disinhibition during depression. Besides GHRH, galanin and ghrelin promote SWS. Intact GHRH receptors are the prerequisite for sleep promotion by ghrelin. Ghrelin may act as an interface between the HPA and HPS systems. Furthermore ghrelin is a distinct stimulus for food intake and, beside its counterpart leptin, is a key factor in the energy balance. Relationships between sleep and metabolism are demonstrated by the changes of ghrelin, leptin, glucose tolerance, and appetite after sleep curtailment. Galanin, ghrelin, and GHRH may either act in a synergistic fashion or these peptides may be part of a cascade resulting in the promotion of NREMS. Probably GABAergic neurons mediate the effects of these peptides. Furthermore GABAA receptors are targets of various neuroactive steroids, which exert specific effects on sleep. VIP appears to regulate the temporal organization of sleep. In young normal men VIP administration decelerates the NREMS–REMS cycle, probably by action on the suprachiasmatic nucleus. Finally the changes of sleep EEG after the menopause and the beneficial effect of estrogen and progesterone replacement therapy point to a role of these hormones in sleep regulation. The effects of CRH-1 receptor antagonism in depression, and of hormone replacement therapy in the menopause, are promising hints for a clinical application of sleep endocrine research.
0 23.00
01.00
03.00
05.00
07.00
h
Fig. 16.2. Model of peptidergic regulation. Characteristic hypnograms and patterns of cortisol and growth hormone (GH) secretion are shown in (A) a young and (C) an elderly control subject and (B) in a depressed patient. It is thought that growth hormone-releasing hormone (GHRH) is released during the first half of the night, whereas CRH is preponderant during the second half of the night. GHRH contributes to the high amounts of GH and SWS after sleep onset, whereas corticotropin-releasing hormone (CRH) is linked with cortisol release and rapid eye movement (REM) sleep in the morning hours. Neuropeptide Y (NPY) is a signal for sleep onset. In addition to GHRH, galanin and ghrelin are sleep-promoting factors, whereas somatostatin (SRIF) is a sleep-impairing factor. During depression (CRH overactivity) and during normal aging, similar changes of sleep emdocrine activity occur. It is thought that changes in the GHRH/CRH balance in favor of CRH play a key role in these alterations. (Reproduced from Steiger (1995), with kind permission of Springer Science and Business Media.)
Studies from the author’s laboratory were supported by grants from the Deutsche Forschungsgemeinschaft (Ste 486/1-2, 5-1, 5-2, 5-3, and 5-4).
REFERENCES Alford FP, Baker HW, Burger HG et al. (1973). Temporal patterns of integrated plasma hormone levels during sleep and wakefulness. II. Follicle-stimulating hormone, luteinizing hormone, testosterone and estradiol. J Clin Endocrinol Metab 37: 848–854. Andersen ML, Martins PJF, D’Almeida V et al. (2005). Endocrinological and catecholaminergic alterations during sleep deprivation and recovery in male rats. J Sleep Res 14: 83–90. Antonijevic IA, Steiger A (2003). Depression-like changes of the sleep-EEG during high dose corticosteroid treatment in patients with multiple sclerosis. Psychoneuroendocrinology 28: 401–418. Antonijevic IA, Murck H, Frieboes RM et al. (1998). Elevated nocturnal profiles of serum leptin in patients with depression. J Psychiatr Res 32: 403–410. Antonijevic IA, Murck H, Frieboes RM et al. (1999). On the gender differences in sleep-endocrine regulation in young normal humans. Neuroendocrinology 70: 280–287.
252
A. STEIGER
Antonijevic IA, Murck H, Bohlhalter S et al. (2000a). NPY promotes sleep and inhibits ACTH and cortisol release in young men. Neuropharmacology 39: 1474–1481. Antonijevic IA, Murck H, Frieboes RM et al. (2000b). Sexually dimorphic effects of GHRH on sleep-endocrine activity in patients with depression and normal controls – part II: hormone secretion. Sleep Res Online 3: 15–21. Antonijevic IA, Stalla GK, Steiger A (2000c). Modulation of the sleep electroencephalogram by estrogen replacement in postmenopausal women. J Obstet Gynecol 182: 277–282. Antonijevic IA, Murck H, Frieboes RM et al. (2003). On the role of menopause for sleep-endocrine alterations associated with major depression. Psychoneuroendocrinology 28: 401–418. ˚ stro¨m C, Jochumsen PL (1989). Decrease in delta sleep in A growth hormone deficiency assessed by a new power spectrum analysis. Sleep 12: 508–515. ˚ stro¨m C, Lindholm J (1990). Growth hormone-deficient A young adults have decreased deep sleep. Neuroendocrinology 51: 82–84. ˚ stro¨m C, Trojaborg W (1992). Effect of growth hormone A on human sleep energy. Clin Endocrinol 36: 241–245. Baskett JJ, Wood PC, Broad JB et al. (2001). Melatonin in older people with age-related sleep maintenance problems: a comparison with age-matched normal sleepers. Sleep 24: 418–424. Beck U, Brezinova V, Hunter WM et al. (1975). Plasma growth hormone and slow wave sleep increase after interruption of sleep. J Clin Endocrinol Metab 40: 812–815. Beranek L, Hajdu I, Gardi J et al. (1999). Central administration of the somatostatin analog octreotide induces captopril-insensitive sleep responses. Am J Physiol 277: R1297–R1304. Bliwise DL (1993). Sleep in normal aging and dementia. Sleep 16: 40–81. Bodosi B, Gardi J, Hajdu I et al. (2004). Rhythms of ghrelin, leptin, and sleep in rats: effects of the normal diurnal cycle, restricted feeding, and sleep deprivation. Am J Physiol Regul Integr Comp Physiol 287: R1071–R1079. Bohlhalter S, Murck H, Holsboer F et al. (1997). Cortisol enhances non-REM sleep and growth hormone secretion in elderly subjects. Neurobiol Aging 18: 423–429. Borbe´ly AA, Baumann F, Brandeis D et al. (1981). Sleep deprivation: effect on sleep stages and EEG power density in man. Electroencephalogr Clin Neurophysiol 51: 483–495. Borbe´ly AA, Tobler I, Hanagasioglu M (1984). Effect of sleep deprivation on sleep and EEG power spectra in the rat. Behav Brain Res 14: 171–182. Born J, Fehm HL (1998). Hypothalamus-pituitary-adrenal activity during human sleep: a coordinating role for the limbic hippocampal system. Exp Clin Endocrinol Diabetes 106: 153–163. Born J, De Kloet ER, Wenz H et al. (1991). Gluco- and antimineralocorticoid effects on human sleep: a role of central corticosteroid receptors. Am J Physiol 260: E183–E188. Born J, Hansen K, Marshall L et al. (1999). Timing the end of nocturnal sleep. Nature 397: 29–30.
Bourgin P, Lebrand C, Escourrou P et al. (1997). Vasoactive intestinal polypeptide microinjections into the oral pontine tegmentum enhance rapid eye movement sleep in the rat. Neuroscience 77: 351–360. Boyar RM, Wu RH, Roffwarg H et al. (1976). Human puberty: 24-hour estradiol in pubertal girls. J Clin Endocrinol Metab 43: 1418–1421. Brabant G, Brabant A, Ranft U et al. (1987). Circadian and pulsatile thyrotropin secretion in euthyroid man under the influence of thyroid hormone and glucocorticoid administration. J Clin Endocrinol Metab 65: 83–88. Brandenberger G, Follenius M, Simon C et al. (1988). Nocturnal oscillations in plasma renin activity and REM-NREM sleep cycles in humans: a common regulatory mechanism? Sleep 11: 242–250. Bredow S, Taishi P, Oba´l F Jr et al. (1996). Hypothalamic growth hormone-releasing hormone mRNA varies across the day in rat. Neuroreport 7: 2501–2505. Brunner DP, Mu¨nch M, Biedermann K et al. (1994). Changes in sleep and sleep electroencephalogram during pregnancy. Sleep 17: 576–582. Chan V, Jones A, Liendo-Ch P et al. (1978). The relationship between circadian variations in circulating thyrotrophin, thyroid hormones and prolactin. Clin Endocrinol 9: 337–349. Chang FC, Opp MR (2004). A corticotropin-releasing hormone antisense oligodeoxynucleotide reduces spontaneous waking in the rat. Regul Pept 117: 43–52. Colvin GB, Whitmoyer DI, Sawyer CH (1969). Circadian sleep–wakefulness patterns in rats after ovariectomy and treatment with estrogen. Exp Neurol 25: 616–625. Danguir J (1984). Sleep deficits in diabetic rats: restoration following chronic intravenous or intracerebroventricular infusions of insulin. Brain Res Bull 12: 641–645. Danguir J (1986). Intracerebroventricular infusion of somatostatin selectively increases paradoxical sleep in rats. Brain Res 367: 26–30. Danguir J, Nicolaidis S (1984). Chronic intracerebroventricular infusion of insulin causes selective increase of slow wave sleep in rats. Brain Res 306: 97–103. Darnaudery M, Bouyer JJ, Pallares M et al. (1999). The promnesic neurosteroid pregnenolone sulfate increases paradoxical sleep in rats. Brain Res 818: 492–498. De A, Churchill L, Oba´l F Jr et al. (2002). GHRH and IL1 beta increase cytoplasmic Ca2þ levels in cultured hypothalamic GABAergic neurons. Brain Res 949: 209–212. Desir D, Van Cauter E, Fang VS et al. (1981). Effects of “jet lag” on hormonal patterns. I. Procedures, variations in total plasma proteins, and disruption of adrenocorticotropin-cortisol periodicity. J Clin Endocrinol Metab 52: 628–641. Deuschle M, Blum WF, Englaro P et al. (1996). Plasma leptin in depressed patients and healthy controls. Horm Metab Res 28: 714–717. Driver HS, Dijk DJ, Werth E et al. (1996). Sleep and the sleep electroencephalogram across the menstrual cycle in young healthy women. J Clin Endocrinol Metab 81: 728–735.
ENDOCRINE AND METABOLIC CHANGES DURING SLEEP Drucker-Colin RR, Spanis CW, Hunyadi J et al. (1975). Growth hormone effects on sleep and wakefulness in the rat. Neuroendocrinology 18: 1–8. Drucker-Colin R, Bernal-Pedraza J, Fernandez-Cancino F et al. (1984). Is vasoactive intestinal polypeptide (VIP) a sleep factor? Peptides 5: 837–840. Drucker-Colin R, Prospero-Garcia O, Arankowsky-Sandoval G et al. (1988). Gastropancreatic peptides and sensory stimuli as REM sleep factors. In: S Inoue´, D Schneider-Helmert (Eds.), Sleep Peptides: Basic and Clinical Approaches. Scientific Society and Springer, Tokyo, pp. 73–94. Dzaja A, Dalal MA, Himmerich H et al. (2004). Sleep enhances nocturnal plasma ghrelin levels in healthy subjects. Am J Physiol Endocrinol Metab 286: E963–E967. Ehlers CL, Kupfer DJ (1987). Hypothalamic peptide modulation of EEG sleep in depression: a further application of the S-process hypothesis. Biol Psychiatry 22: 513–517. Ehlers CL, Kupfer DJ (1997). Slow-wave sleep: do young adult men and women age differently? J Sleep Res 6: 211–215. Ehlers CL, Reed TK, Henriksen SJ (1986). Effects of corticotropin-releasing factor and growth hormonereleasing factor on sleep and activity in rats. Neuroendocrinology 42: 467–474. Ehlers CL, Somes C, Lopez A et al. (1997a). Electrophysiological actions of neuropeptide Y and its analogs: new measures for anxiolytic therapy? Neuropsychopharmacology 17: 34–43. Ehlers CL, Somes C, Seifritz E et al. (1997b). CRF/NPY interactions: a potential role in sleep dysregulation in depression and anxiety. Depress Anxiety 6: 1–9. Fadda P, Fratta W (1997). Stress-induced sleep deprivation modifies corticotropin releasing factor (CRF) levels and CRF binding in rat brain and pituitary. Pharmacol Res 35: 443–446. Fang J, Fishbein W (1996). Sex differences in paradoxical sleep: influences of estrus cycle and ovariectomy. Brain Res 734: 275–285. Fehm HL, Klein E, Holl R et al. (1984). Evidence for extrapituitary mechanisms mediating the morning peak of cortisol secretion in man. J Clin Endocrinol Metab 58: 410–414. Fehm HL, Spa¨th-Schwalbe E, Pietrowsky R et al. (1993). Entrainment of nocturnal pituitary-adrenocortical activity to sleep processes in man – a hypothesis. Exp Clin Endocrinol 101: 267–276. Follenius M, Brandenberger G, Simon C et al. (1988). REM sleep in humans begins during decreased secretory activity of the anterior pituitary. Sleep 11: 546–555. Follenius M, Brandenberger G, Bandesapt JJ et al. (1992). Nocturnal cortisol release in relation to sleep structure. Sleep 15: 21–27. Franken P, Dijk DJ, Tobler I et al. (1991). Sleep deprivation in rats: effects on EEG power spectra, vigilance states, and cortical temperature. Am J Physiol 261: R198–R208. Franken P, Chollet D, Tafti M (2001). The homeostatic regulation of sleep need is under genetic control. J Neurosci 21: 2610–2621.
253
Frieboes RM, Murck H, Schier T et al. (1997). Somatostatin impairs sleep in elderly human subjects. Neuropsychopharmacology 16: 339–345. Frieboes RM, Murck H, Stalla GK et al. (1998). Enhanced slow wave sleep in patients with prolactinoma. J Clin Endocrinol Metab 83: 2706–2710. Frieboes RM, Mu¨ller U, Murck H et al. (1999). Nocturnal hormone secretion and the sleep EEG in patients several months after traumatic brain injury. J Neuropsychiatry Clin Neurosci 11: 354–360. Friess E, von Bardeleben U, Wiedemann K et al. (1994). Effects of pulsatile cortisol infusion on sleep-EEG and nocturnal growth hormone release in healthy men. J Sleep Res 3: 73–79. Friess E, Trachsel L, Guldner J et al. (1995). DHEA administration increases rapid eye movement sleep and EEG power in the sigma frequency range. Am J Physiol 268: E107–E113. Friess E, Tagaya H, Trachsel L et al. (1997). Progesteroneinduced changes in sleep in male subjects. Am J Physiol Endoc M 272: E885–E891. Friess E, Tagaya H, Grethe C et al. (2004). Acute cortisol administration promotes sleep intensity in man. Neuropsychopharmacology 29: 598–604. Gardi J, Oba´l F Jr, Fang J et al. (1999). Diurnal variations and sleep deprivation-induced changes in rat hypothalamic GHRH and somatostatin contents. Am J Physiol 277: R1339–R1344. Gillin JC, Jacobs LS, Snyder F et al. (1974). Effects of ACTH on the sleep of normal subjects and patients with Addison’s disease. Neuroendocrinology 15: 21–31. Gronfier C, Luthringer R, Follenius M et al. (1996). Hormones and sleep. A quantitative evaluation of the relationships between growth hormone secretion and delta wave electroencephalographic activity during normal sleep and after enrichment in delta waves. Sleep 19: 817–824. Guldner J, Schier T, Friess E et al. (1997). Reduced efficacy of growth hormone-releasing hormone in modulating sleep endocrine activity in the elderly. Neurobiol Aging 18: 491–495. Hajdu I, Oba´l F Jr, Fang J et al. (2002). Sleep of transgenic mice producing excess rat growth hormone. Am J Physiol Regul Integr Comp Physiol 282: R70–R76. Hart TB, Radow SK, Blackard WG et al. (1985). Sleep apnea in active acromegaly. Arch Intern Med 145: 865–866. Held K, Ku¨nzel H, Ising M et al. (2004). Treatment with the CRH1-receptor antagonist R121919 improves sleep EEG in patients with depression. J Psychiatr Res 38: 129–136. Held K, Murck H, Antonijevic IA et al. (2006). Neuropeptide Y (NPY) shortens sleep latency and enhances prolactin but does not suppress ACTH and cortisol in depressed patients and controls. Psychoneuroendocrinology 31: 100–107. Hemmeter U, Rothe B, Guldner J et al. (1998). Effects of thyrotropin-releasing hormone on the sleep EEG and nocturnal hormone secretion in male volunteers. Neuropsychobiology 38: 25–31.
254
A. STEIGER
Holl RW, Hartman ML, Veldhuis JD et al. (1991). Thirtysecond sampling of plasma growth hormone in man: correlation with sleep stages. J Clin Endocrinol Metab 72: 854–861. Holsboer F (1999). The rationale for corticotropin-releasing hormone receptor (CRH-R) antagonists to treat depression and anxiety. J Psychiatr Res 33: 181–214. Holsboer F, von Bardeleben U, Steiger A (1988). Effects of intravenous corticotropin-releasing hormone upon sleeprelated growth hormone surge and sleep EEG in man. Neuroendocrinology 48: 32–38. Horvath TL, Diano S, Sotonyi P et al. (2001). Minireview: ghrelin and the regulation of energy balance – a hypothalamic perspective. Endocrinology 142: 4163–4169. Jarrett DB, Miewald JM, Kupfer DJ (1990). Recurrent depression is associated with a persistent reduction in sleep-related growth hormone secretion. Arch Gen Psychiatry 47: 113–118. Jimenez-Anguiano A, Baez-Saldana A, Drucker-Colin R (1993). Cerebrospinal fluid (CSF) extracted immediately after REM sleep deprivation prevents REM rebound and contains vasoactive intestinal peptide (VIP). Brain Res 631: 345–348. Jung-Testas I, Hu ZY, Baulieu EE et al. (1989). Neurosteroids: biosynthesis of pregnenolone and progesterone in primary cultures of rat glial cells. Endocrinology 125: 2083–2091. Kales A, Heuser G, Jacobson A et al. (1967). All night sleep studies in hypothyroid patients, before and after treatment. J Clin Endocrinol Metab 27: 1593–1599. Kerkhofs M, Van Cauter E, Van Onderbergen A et al. (1993). Sleep-promoting effects of growth hormonereleasing hormone in normal men. Am J Physiol 264: E594–E598. Kimura M (2005). Minireview: gender-specific sleep regulation. Sleep and Biological Rhythms 3: 75–79. Kimura M, Zhang SQ, Inoue S (1998). An animal model for pregnancy-associated sleep disorder. Psychiatry Clin Neurosci 52: 209–211. Kimura M, Mu¨ller-Preuss P, Lu A et al. (2010). Conditional corticotropin-releasing hormone overexpression in the mouse forebrain enhances rapid eye movement sleep. Mol Psychiatry 15: 154–165. Kluge M, Schu¨ssler P, Zuber V et al. (2007a). Ghrelin enhances the nocturnal secretion of cortisol and growth hormone in young females without influencing sleep. Psychoneuroendocrinology 32: 1079–1085. Kluge M, Schu¨ssler P, Zuber V et al. (2007b). Ghrelin administered in the early morning increases secretion of cortisol and growth hormone without affecting sleep. Psychoneuroendocrinology 32: 287–292. Kluge M, Gazea M, Schu¨ssler P et al. (2010). Ghrelin increases slow wave sleep and stage 2 sleep and decreases stage 1 sleep and REM sleep in elderly men but does not affect sleep in elderly women. Psychoneuroendocrinology 35: 297–304. Kojima M, Hosoda H, Date Y et al. (1999). Ghrelin is a growth hormone-releasing acylated peptide from stomach. Nature 402: 656–660.
Krieger DT, Glick SM (1974). Sleep EEG stages and plasma growth hormone concentration in states of endogenous and exogenous hypercortisolemia or ACTH elevation. J Clin Endocrinol Metab 39: 986–1000. Krishnan KRR, Ritchie JC, Saunders W et al. (1990). Nocturnal and early morning secretion of ACTH and cortisol in humans. Biol Psychiatry 28: 47–57. Kupfer DJ, Jarrett DB, Ehlers CL (1992). The effect of SRIF on the EEG sleep of normal men. Psychoneuroendocrinology 17: 37–43. Kupfer DJ, Ehlers CL, Frank E et al. (1993). Electroencephalographic sleep studies in depressed patients during longterm recovery. Psychiatry Res 49: 121–138. Lachmansingh E, Rollo CD (1994). Evidence for a trade-off between growth and behavioural activity in giant “Supermice” genetically engineered with extra growth hormone genes. Can J Zool 72: 2158–2168. Lancel M, Cro¨nlein TA, Mu¨ller-Preuss P et al. (1994). Pregnenolone enhances EEG delta activity during non-rapid eye movement sleep in the rat, in contrast to midazolam. Brain Res 646: 85–94. Lancel M, Faulhaber J, Schiffelholz T et al. (1997). Allopregnanolone affects sleep in a benzodiazepine-like fashion. J Pharmacol Exp Ther 282: 1213–1218. Leproult R, Copinschi G, Buxton O et al. (1997). Sleep loss results in an elevation of cortisol levels the next evening. Sleep 20: 865–870. Leresche N, Asprodini E, Emri Z et al. (2000). Somatostatin inhibits GABAergic transmission in the sensory thalamus via presynaptic receptors. Neuroscience 98: 513–522. Licinio J, Mantzoros C, Negrao AB et al. (1997). Human leptin levels are pulsatile and inversely related to pituitary-adrenal function. Nat Med 3: 575–579. Linkowski P, Mendlewicz J, Kerkhofs M et al. (1987). 24-hour profiles of adrenocorticotropin, cortisol, and growth hormone in major depressive illness: effect of antidepressant treatment. J Clin Endocrinol Metab 65: 141–152. Linkowski P, Van Onderbergen A, Kerkhofs M et al. (1993). Twin study of the 24-h cortisol profile: evidence for genetic control of the human circadian clock. Am J Physiol 264: E173–E181. Linkowski P, Spiegel K, Kerkhofs M et al. (1998). Genetic and environmental influences on prolactin secretion during wake and during sleep. Am J Physiol 274: E909–E919. Lopez M, Seoane LM, Tovar S et al. (2004). Orexin-A regulates growth hormone-releasing hormone mRNA content in a nucleus-specific manner and somatostatin mRNA content in a growth hormone-dependent fashion in the rat hypothalamus. Eur J Neurosci 19: 2080–2088. Manber R, Armitage R (1999). Sex, steroids and sleep: a review. Sleep 22: 540–555. Marrosu F, Gessa GL, Giagheddu M et al. (1990). Corticotropinreleasing factor (CRF) increases paradoxical sleep (PS) rebound in PS-deprived rats. Brain Res 515: 315–318. Marshall L, Derad L, Starsburger CJ et al. (1999). A determinant factor in the efficacy of GHRH administration in the
ENDOCRINE AND METABOLIC CHANGES DURING SLEEP efficacy of GHRH administration in promoting sleep: high peak concentration versus recurrent increasing slopes. Psychoneuroendocrinology 24: 363–370. Mendelson WB, Slater S, Gold P et al. (1980). The effect of growth hormone administration on human sleep: a dose– response study. Biol Psychiatry 15: 613–618. Merryman W, Boiman R, Barnes L et al. (1954). Progesterone “anaesthesia” in human subjects. J Clin Endocrinol Metab 14: 1567–1569. Mignot E (2004). Sleep, sleep disorders and hypocretin (orexin). Sleep Med 5 (Suppl. 1): 2–8. Mirmiran M, Kruisbrink J, Bos NP et al. (1988). Decrease of rapid-eye-movement sleep in the light by intraventricular application of a VIP-antagonist in the rat. Brain Res 458: 192–194. Mullington J, Hermann D, Holsboer F et al. (1996). Agedependent suppression of nocturnal growth hormone levels during sleep deprivation. Neuroendocrinology 64: 233–241. Murck H, Guldner J, Colla-Mu¨ller M et al. (1996). VIP decelerates non-REM-REM cycles and modulates hormone secretion during sleep in men. Am J Physiol 271: R905–R911. Murck H, Antonijevic IA, Frieboes RM et al. (1997). Galanin has REM-sleep deprivation-like effects on the sleep EEG in healthy young men. J Psychiatr Res 33: 225–232. Murck H, Antonijevic IA, Schier T et al. (1999). Aging does not affect the sleep endocrine response to total sleep deprivation in humans. Neurobiol Aging 20: 665–668. Murck H, Held K, Ziegenbein M et al. (2004). Intravenous administration of the neuropeptide galanin has fast antidepressant efficacy and affects the sleep EEG. Psychoneuroendocrinology 29: 1205–1211. Oba´l F, Krueger JM (2004). GHRH and sleep. Sleep Med Rev 8: 367–377. Oba´l F, Alfo¨ldi P, Cady AB et al. (1988). Growth hormonereleasing factor enhances sleep in rats and rabbits. Am J Physiol 255: R310–R316. Oba´l F, Payne L, Kapa´s L et al. (1991). Inhibition of growth hormone-releasing factor suppresses both sleep and growth hormone secretion in the rat. Brain Res 557: 149–153. Oba´l F, Kacso´h B, Alfo¨ldi P et al. (1992a). Antiserum to prolactin decreases rapid eye movement sleep (REM sleep) in the male rat. Physiol Behav 52: 1063–1068. Oba´l F, Payne L, Opp M et al. (1992b). Growth hormonereleasing hormone antibodies suppress sleep and prevent enhancement of sleep after sleep deprivation. Am J Physiol 263: R1078–R1085. Oba´l F, Beranek L, Brandenberger G (1994). Sleepassociated variations in plasma renin activity and blood pressure in the rat. Neurosci Lett 179: 83–86. Oba´l F, Floyd R, Kapa´s L et al. (1996). Effects of systemic GHRH on sleep in intact and in hypophysectomized rats. Am J Physiol 270: E230–E237. Oba´l F, Bodosi B, Szilagyi A et al. (1997a). Antiserum to growth hormone decreases sleep in the rat. Neuroendocrinology 66: 9–16. Oba´l F, Kacso´h B, Bredow S et al. (1997b). Sleep in rats rendered chronically hyperprolactinemic with anterior pituitary grafts. Brain Res 755: 130–136.
255
Oba´l F, Kapa´s L, Bodosi B et al. (1998). Changes in sleep in response to intracerebral injection of insulin-like growth factor-1 (IGF-1) in the rat. Sleep Res Online 1: 87–91. Oba´l F, Kapa´s L, Gardi J et al. (1999). Insulin-like growth factor-1 (IGF-1)-induced inhibition of growth hormone secretion is associated with sleep suppression. Brain Res 818: 267–274. Oba´l F, Fang J, Taishi P et al. (2001). Deficiency of growth hormone-releasing hormone signaling is associated with sleep alterations in the dwarf rat. J Neurosci 21: 2912–2918. Oba´l F, Alt J, Taishi P et al. (2003). Sleep in mice with nonfunctional growth hormone-releasing hormone receptors. Am J Physiol Regul Integr Comp Physiol 284: R131–R139. Opp MR (1997). Rat strain differences suggest a role for corticotropin-releasing hormone in modulating sleep. Physiol Behav 63: 67–74. Opp M, Oba´l F Jr, Krueger JM (1989). Corticotropinreleasing factor attenuates interleukin 1-induced sleep and fever in rabbits. Am J Physiol 257: R528–R535. Overeem S, Kok SW, Lammers GJ et al. (2003). Somatotropic axis in hypocretin-deficient narcoleptic humans: altered circadian distribution of GH-secretory events. Am J Physiol -Endoc M 284: E641–E647. Parker DC, Rossman LG, Siler TM et al. (1974). Inhibition of the sleep-related peak in physiologic human growth hormone release by somatostatin. J Clin Endocrinol Metab 38: 496–499. Paul SM, Purdy RH (1992). Neuroactive steroids. FASEB J 6: 2311–2322. Penalva RG, Lancel M, Flachskamm C et al. (2000). Effects of sleep dprivation on hippocampal serotonin: a combined in vivo microdialysis/EEG study in rats. J Sleep Res 9 (Suppl. 1): 149. Perras B, Marshall L, Ko¨hler G et al. (1999). Sleep and endocrine changes after intranasal administration of growth hormone-releasing hormone in young and aged humans. Psychoneuroendocrinology 24: 743–757. Peterfi Z, McGinty D, Sarai E et al. (2010). Growth hormone-releasing hormone activates sleep regulatory neurons of the rat preoptic hypothalamus. Am J Physiol Regul Integr Comp Physiol 298: R147–R156. Quabbe HJ, Schilling E, Helge H (1966). Pattern of growth hormone secretion during a 24-hour fast in normal adults. J Clin Endocrinol Metab 26: 1173–1177. Riemann D, Klein T, Rodenbeck A et al. (2002). Nocturnal cortisol and melatonin secretion in primary insomnia. Psychiatry Res 113: 17–27. Riou F, Cespuglio R, Jouvet M (1982). Endogenous peptides and sleep in the rat. III. The hypnogenic properties of vasoactive intestinal polypeptide. Neuropeptides 2: 265–277. Rodenbeck A, Huether G, Ru¨ther E et al. (2002). Interactions between evening and nocturnal cortisol secretion and sleep parameters in patients with severe chronic primary insomnia. Neurosci Lett 324: 159–163. Roky R, Valatx JL, Paut-Pagano L et al. (1994). Hypothalamic injection of prolactin or its antibody alters the rat sleep–wake cycle. Physiol Behav 55: 1015–1019.
256
A. STEIGER
Roky R, Oba´l F Jr, Valatx JL et al. (1995). Prolactin and rapid eye movement sleep regulation. Sleep 18: 536–542. Rosenhagen MC, Uhr M, Schussler P et al. (2005). Elevated plasma ghrelin levels in night-eating syndrome. Am J Psychiatry 162: 813. Saad MF, Damani S, Gingerich RL et al. (1997). Sexual dimorphism in plasma leptin concentration. J Clin Endocrinol Metab 82: 579–584. Sack RL, Brandes RW, Kendall AR et al. (2000). Entrainment of free-running circadian rhythms by melatonin in blind people. N Engl J Med 343: 1070–1077. Sangiah S, Caldwell DF, Villeneuve MJ et al. (1982). Sleep: sequential reduction of paradoxical (REM) and elevation of slow-wave (NREM) sleep by a non-convulsive dose of insulin in rats. Life Sci 31: 763–769. Saper CB, Chou TC, Scammell TE (2001). The sleep switch: hypothalamic control of sleep and wakefulness. Trends Neurosci 24: 726–731. Sassin JF, Parker DC, Mace JW et al. (1969). Human growth hormone release: relation to slow-wave sleep and sleep– waking cycles. Science 165: 513–515. Schiffelholz T, Holsboer F, Lancel M (2000). High doses of systemic DHEA-sulfate do not affect sleep structure and elicit moderate changes in non-REM sleep EEG in rats. Physiol Behav 69: 399–404. Schmid DA, Held K, Ising M et al. (2005). Ghrelin stimulates appetite, imagination of food, GH, ACTH and cortisol, but does not affect leptin in man. Neuropsychopharmacology 30: 1187–1192. Schu¨ssler P, Kluge M, Yassouridis A et al. (2008). Progesterone reduces wakefulness in sleep EEG and has no effect on cognition in healthy postmenopausal women. Psychoneuroendocrinology 33: 1124–1131. Shipley JE, Schteingart DE, Tandon R et al. (1992). Sleep architecture and sleep apnea in patients with Cushing’s disease. Sleep 15: 514–518. Simon C, Brandenberger G, Saini J et al. (1994). Slow oscillations of plasma glucose and insulin secretion rate are amplified during sleep in humans under continuous enteral nutrition. Sleep 17: 333–338. Spa¨th-Schwalbe E, Scholler T, Kern W et al. (1992). Nocturnal adrenocorticotropin and cortisol secretion depends on sleep duration and decreases in association with spontaneous awakening in the morning. J Clin Endocrinol Metab 75: 1431–1435. Spiegel K, Follenius M, Simon C et al. (1994). Prolactin secretion and sleep. Sleep 17: 20–27. Spiegel K, Leproult R, Van Cauter E (1999). Impact of sleep debt on metabolic and endocrine function. Lancet 354: 1435–1439. Spiegel K, Tasali E, Penev P et al. (2004). Brief communication: sleep curtailment in healthy young men is associated with decreased leptin levels, elevated ghrelin levels, and increased hunger and appetite. Ann Intern Med 141: 846–850. Steiger A (1995). Schlafendokrinologie. Nervenarzt 66: 15–27. Steiger A (2002). Neuroendocrinology of sleep disorders. In: H D’haenen, JA den Boer, H Westenberg et al.
(Eds.), Textbook of Biological Psychiatry. John Wiley, London, pp. 1229–1246. Steiger A, Holsboer F (1997). Nocturnal secretion of prolactin and cortisol and the sleep EEG in patients with major endogenous depression during an acute episode and after full remission. Psychiatry Res 72: 81–88. Steiger A, Herth T, Holsboer F (1987). Sleep-electroencephalography and the secretion of cortisol and growth hormone in normal controls. Acta Endocrinol (Copenh) 116: 36–42. Steiger A, von Bardeleben U, Herth T et al. (1989). Sleep EEG and nocturnal secretion of cortisol and growth hormone in male patients with endogenous depression before treatment and after recovery. J Affect Disord 16: 189–195. Steiger A, Guldner J, Hemmeter U et al. (1992). Effects of growth hormone-releasing hormone and somatostatin on sleep EEG and nocturnal hormone secretion in male controls. Neuroendocrinology 56: 566–573. Steiger A, Trachsel L, Guldner J et al. (1993). Neurosteroid pregnenolone induces sleep-EEG changes in man compatible with inverse agonistic GABAA-receptor modulation. Brain Res 615: 267–274. Stern WC, Jalowiec JE, Shabshelowitz H et al. (1975). Effects of growth hormone on sleep–waking patterns in cats. Horm Behav 6: 189–196. Szentirmai E, Hajdu I, Oba´l F Jr et al. (2006). Ghrelin-induced sleep responses in ad libitum fed and food-restricted rats. Brain Res 1088: 131–140. Szentirmai E, Kapa´s L, Krueger J M (2007). Ghrelin microinjection into forebrain sites induces wakefulness and feeding in rats. Am J Physiol Regul Integr Comp Physiol 292: R575–R585. Taheri S, Lin L, Austin D et al. (2004). Short sleep duration is associated with reduced leptin, elevated ghrelin, and increased body mass index. PLoS Med 1: e62. Takahashi Y, Kipnis DM, Daughaday WH (1968). Growth hormone secretion during sleep. J Clin Invest 47: 2079–2090. Tomaszuk A, Simpson C, Williams G (1996). Neuropeptide Y, the hypothalamus and the regulation of energy homeostasis. Horm Res 46: 53–58. Toppila J, Stenberg D, Alanko L et al. (1995). REM sleep deprivation induces galanin gene expression in the rat brain. Neurosci Lett 183: 171–174. Toppila J, Alanko L, Asikainen M et al. (1997). Sleep deprivation increases somatostatin and growth hormonereleasing hormone messenger RNA in the rat hypothalamus. J Sleep Res 6: 171–178. Trachsel L, Edgar DM, Seidel WF et al. (1992). Sleep homeostasis in suprachiasmatic nuclei-lesioned rat: effects of sleep deprivation and triazolam administration. Brain Res 598: 253–261. Valatx, J. L., Roky, R., Trouillas, J. et al. (1994). Paradoxical sleep alteration by tumoral hyperprolactinemia. J Sleep Res 3 (Suppl. 1): 260. Van Cauter E, Blackman JD, Roland D et al. (1991). Modulation of glucose regulation and insulin secretion by circadian rhythmicity and sleep. J Clin Invest 88: 934–942. Van Cauter E, Kerkhofs M, Caufriez A et al. (1992). A quantitative estimation of growth hormone secretion in normal
ENDOCRINE AND METABOLIC CHANGES DURING SLEEP man: reproducibility and relation to sleep and time of day. J Clin Endocrinol Metab 74: 1441–1450. Van Cauter E, Leproult R, Kupfer DJ (1996). Effects of gender and age on the levels and circadian rhythmicity of plasma cortisol. J Clin Endocrinol Metab 81: 2468–2473. Van Coevorden A, Mockel J, Laurent E et al. (1991). Neuroendocrine rhythms and sleep in aging men. Am J Physiol 260: E651–E661. van den Heuvel CJ, Ferguson SA, Macchi MM et al. (2005). Melatonin as a hypnotic: Con. Sleep Med Rev 9: 71–80. Vgontzas AN, Bixler EO, Wittman AM et al. (2001). Middle-aged men show higher sensitivity of sleep to the arousing effects of corticotropin-releasing hormone than young men: clinical implications. J Clin Endocrinol Metab 86: 1489–1495. Voderholzer U, Laakmann G, Wittmann R et al. (1993). Profiles of spontaneous 24-hour and stimulated growth hormone secretion in male patients with endogenous depression. Psychiatry Res 47: 215–227. Voderholzer U, Hohagen F, Klein T et al. (2004). Impact of sleep deprivation and subsequent recovery sleep on cortisol in unmedicated depressed patients. Am J Psychiatry 161: 1404–1410. Watts AG, Tanimura S, Sanchez-Watts G (2004). Corticotropinreleasing hormone and arginine vasopressin gene transcription in the hypothalamic paraventricular nucleus of unstressed rats: daily rhythms and their interactions with corticosterone. Endocrinology 145: 529–540.
257
Wehr TA (1998). Effect of seasonal changes in daylength on human neuroendocrine function. Horm Res 49: 118–124. Wehr TA, Moul DE, Barbato G et al. (1993). Conservation of photoperiod-responsive mechanisms in humans. Am J Physiol 265: R846–R857. Weibel L, Brandenberger G (1998). Disturbances in hormonal profiles of night workers during their usual sleep and work times. J Biol Rhythms 13: 202–208. Weikel JC, Wichniak A, Ising M et al. (2003). Ghrelin promotes slow-wave sleep in humans. Am J Physiol Endocrinol Metab 284: E407–E415. Weitzman ED (1976). Circadian rhythms and episodic hormone secretion in man. Annu Rev Med 27: 225–243. Yang SW, Fishbein W (1995). Castration at birth induces female sleep pattern in mice; neonatal testosterone replacement reverses the effect. Sleep Res 24: 65. Zhang J, Oba´l F Jr, Zheng T et al. (1999). Intrapreoptic microinjection of GHRH or its antagonist alters sleep in rats. J Neurosci 19: 2187–2194. Zhdanova IV (2005). Reply to the comment on ’Melatonin as a hypnotic: Pro’. Sleep Med Rev 9: 69–70. Zhdanova IV, Lynch HJ, Wurtman RJ (1997). Melatonin: a sleep-promoting hormone. Sleep 20: 899–907. Ziegenbein M, Held K, Ku¨nzel H et al. (2004). The somatostatin analogue octreotide impairs sleep and decreases EEG sigma power in young male subjects. Neuropsychopharmacology 29: 146–151.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 17
Sleep, memory, and molecular neurobiology CARLYLE SMITH * AND KEVIN R. PETERS Department of Psychology, Trent University, Peterborough, Canada
The relationship of sleep states to memory processing or consolidation has been of interest for at least 100 years. Advances in the understanding of the nature of sleep states and of memory processes at the electrophysiological, neurophysiological, biochemical, and behavioral levels have provided invaluable information to help us understand a very important and practical relationship. The idea of permanent memory formation as a neurophysiological and neurochemical set of processes occurring both during and well after the end of behavioral acquisition has evolved over the years. Memory formation was at one time considered to pass through three main stages, including an early, short-term phase (seconds), a longer intermediate-term phase lasting several hours or more, finally becoming a relatively permanent long-term memory. The intermediate phase of memory was considered to be a fragile stage during which external agents such as electroconvulsive shock or protein synthesis inhibitors could disrupt memory consolidation. The intermediate memory consolidation phase was considered to be most active during the first 3–5 hours after acquisition of most tasks. It is now known that final memory formation can take much longer than a few hours and there are several kinds of memory systems involving a variety of neural structures. The understanding of the basic sleep states was firmly established by a number of laboratories around the world during the 1950s. The discovery of rapid eye movement (REM) sleep (Aserinsky and Kleitman, 1953) along with non-REM (NREM) sleep in a wide variety of mammals paved the way for the study of a possible relationship between sleep states and memory processing. Three basic approaches have been used to study the sleep–memory relationship. These include:
1.
2.
3.
Recording. Train the organism – watch the sleep state changes that subsequently occur and compare them to baseline pretraining levels of activity; retest the organism to ensure that learning has taken place. Deprivation. Train the organism – either deprive the organism of total sleep or selectively prevent some specific sleep state; retest the organism to assess levels of learning compared to rested controls. Enhancement. Train the organism – manipulate the sleep state to enhance it in some way; retest the organism later to see if the artificially enhanced sleep resulted in superior memory for the task.
These three approaches are still being used, although the techniques have become more sophisticated. Early studies were also interested in the effects of sleep deprivation prior to task acquisition (McGrath and Cohen, 1978). However, the posttraining memory consolidation phenomena have been the focus of most recent experiments.
NEW EXPERIMENTAL PARADIGMS AND TECHNOLOGICAL ADVANCES Animal studies While the traditional methods of examining sleep states in the animal have included electroencephalogram (EEG) and electromyogram measures as minimal to distinguish REM from NREM sleep, some studies have also used electro-oculogram measures as well, although they are not necessary for distinguishing REM from NREM in rodents. The EEG can be measured from both cortical electrode placements and deep brain structures. It is also possible to measure
*Correspondence to: Carlyle Smith, Department of Psychology, Trent University, 1600 West Bank Drive, Peterborough, Ontario, K9J 7B8 Canada. Tel: 1-705-748-1011 (ext. 1406), Fax: 1-705-748-1580, E-mail:
[email protected]
260 C. SMITH AND EEG quantitatively using power spectral and period amplitude analyses. Added to this is the ability to measure the unit activity of a number of single cells simultaneously to sort the behavior of these cell firing sequences in terms of temporal and spatial distribution. These kinds of measures can provide us with a much more precise picture of how neurons are behaving in response to task acquisition. REM sleep deprivation has been done mechanically in many studies using the platform, pedestal, or swimming pool method, capitalizing on the fact that in order to get REM sleep, organisms must have complete muscle relaxation, while for NREM sleep they do not. Animals prefer to avoid entering REM sleep rather than falling and getting wet. REM sleep can also be selectively reduced by drugs (e.g., acetylcholine antagonists such as scopolamine) and gentle handling at observed REM sleep onset, including the “head-lifting” method.
K.R. PETERS predominantly deep NREM sleep and REM sleep contributions to the reprocessing of recently acquired material, although it does not differentially distribute stage 2 sleep and does not allow examination of this stage with regard to learning progress. As well as visual examination of basic EEG activity before and after learning, it is now possible in many labs to do multiple electrode recording and detailed power spectral analyses. In addition, there are now attempts to count automatically some of the phasic events of the sleep night, including the sleep spindle and the REM. In terms of level of brain activity, both positron emission tomography (PET) and magnetic resonance imaging (MRI) scans have been done during sleep following learning to assess subsequent brain activity and to correlate this activity with sleep states and learning progress.
TYPES OF MEMORY Human studies One of the traditional approaches has been selective REM sleep deprivation. At the first sign of REM sleep on the polygraph, subjects are awakened and asked to do a simple task before being allowed to return to sleep. Typically, the participant does not attempt REM sleep for some time after returning to sleep, but rather enters NREM sleep. NREM sleep cannot be selectively deprived in the same manner. In order for REM sleep to occur, NREM sleep must occur first. Total sleep deprivation eliminates both NREM and REM sleep. REM sleep can also be selectively reduced by a number of drugs including ethyl alcohol and antidepressants. To avoid sleep deprivation, a new paradigm is now being used. Participants are either trained in the morning and then retested 12 hours later before any sleep has occurred or they have been trained in the evening and then tested 12 hours later (the next morning) after a night of sleep. Thus it is possible to compare memory after the same time lapse with or without sleep. Some studies have also employed a condition where subjects are tested after a 24-hour interval (starting in the morning or evening) to examine retention over periods containing both wakefulness and sleep. Another approach is the split-night design which capitalizes on the fact that the first half of the night exhibits much more delta sleep than the last half, while the last half of the night has much more REM sleep (Barrett and Ekstrand, 1972). Recent modifications include a control wake group for each half of the night. Subjects are trained either just before sleep onset and tested 3 hours later or awakened in the middle of the night, trained, and tested 3 hours later. This design makes it possible to look separately at sleep comprising
There are now believed to be at least two types of memory systems. They have been described by different theorists and given different names but are basically as follows. Declarative memory is a type of memory that is factual in nature. It is usually explicitly or consciously learned and demonstration of memory is the direct recall of this material, such as memorized facts. Nondeclarative memory refers to several kinds of learning that are usually learned implicitly or unconsciously. These include procedural, priming, simple classical conditioning, and nonassociative or reflex learning. Procedural memory has been the most extensively studied with respect to sleep states and involves the acquisition of techniques, strategies, or motor skills. Assessment of learning is observed as favorable changes in behavior rather than direct recall. Learning to ride a bicycle is a typical example of procedural memory. These two general types of memory are now well differentiated in terms of the brain structures involved and brain transmitters utilized. Several reviews of these memory types and their relationship to sleep states have been written (Squire, 1987; Milner and Squire, 1998; Smith, 2001; Walker and Stickgold, 2006). Basically, the mixed results of the earlier work can be understood by categorizing the tasks as either declarative or procedural. Some studies chose learning tasks that could be argued to have components of both of these types of memory. Another type of memory that has not received much attention is emotional memory. This type of memory is believed to be mediated by separate neural circuits and to be different at least in part from the declarative or procedural categories (Hu et al., 2006; Sterpenich et al., 2007).
SLEEP, MEMORY, AND MOLECULAR NEUROBIOLOGY
REM SLEEP AND MEMORY Animal studies The results of early animal experiments using the recording paradigm provided very encouraging results. Virtually all of the EEG recording studies reported that posttraining sleep was characterized by increases in the amount (number of minutes) or percentage of REM sleep compared to baseline levels and compared to nonlearning controls. This phenomenon is quite robust and continues to be reported (Pearlman, 1979; Smith, 1985, 1995; Datta, 2000). Compared to the recording approach, a much larger number of studies have historically used the deprivation approach, probably because of the comparative ease of doing nonrecording studies. However, the results of these studies were somewhat less consistent. Not all studies found a deficit associated with posttraining sleep deprivation (usually selective REM sleep deprivation) (Smith, 1985, 1995). One of the reasons for this was undoubtedly because memory consolidation processes appeared to take place at discrete posttraining times, and contrary to original ideas about time required for complete consolidation, often occurred many hours after the end of acquisition. In addition, some have suggested that stress can explain many of the findings reported using the recording and deprivation approaches (Siegal, 2001). There are many reasons (Smith, 2003), however, to believe that this criticism is unlikely to explain the data.
THE REM
SLEEP WINDOW
Continuous EEG sleep recording both before training and following task acquisition has revealed that REM sleep increases may begin to occur many hours after the end of training and can persist for several days. Interestingly, animals that failed to learn never showed any REM sleep increases despite identical training procedures. Conversely, selective REM sleep deprivation resulted in memory deficits for both aversive and appetitive tasks. However, the timing of the REM sleep deprivation most devastating to memory often began much later than the first 3–4 hours originally predicted, manifesting as long as 2 days later. These relatively short (4-hour duration) vulnerable REM episodes were found for a number of tasks and have resulted in the concept of the REM sleep window (RSW) (Smith, 1985, 1996). The RSW has been defined as a time after acquisition when REM sleep is occurring at above-normal baseline levels. If REM sleep deprivation is applied during this posttraining time period, memory deficits will occur. The timing of these RSWs is dependent upon the type and strain of
261
organism, the nature of the learning task, and the number of training trials to which the organism is exposed at a session. The concept of the RSW has provided several new directions for sleep–memory research. It has demonstrated that increases in REM sleep could be observed immediately, or many hours, and even days, after the end of training. In addition, it suggested that the processes connected with consolidation are not active in all of posttraining REM sleep, just at specific times. The negative results of many earlier REM deprivation studies might well have been due to the fact that they almost all imposed deprivation in the immediate (within 3–4 hours) posttraining time period (Smith, 1985). Further, the latency to above-normal increases in REM was shorter with massed training trials. These results presented a much more flexible posttraining consolidation system than had previously been envisioned (Smith, 2003).
RECORDING
AT THE CELLULAR LEVEL
More recently, a sleep window has been reported in young chickens which were exposed to an imprinting cue. The number of imprinting stimulus neurons involved in this process only achieved their maximum effect if sleep followed the training session and was allowed in the 5–12-hour sleep window after stimulus exposure. If sleep onset was delayed, and only allowed to begin after 12 hours of poststimulus exposure, although equal in time allowed, the strength of the attachment and level of neural involvement were much reduced. Later sleep restriction had no effect (Jackson et al., 2008). Results indicated that the sleep important to memory consolidation was active in the first 12 hours of posttraining sleep, especially hours 5–12. Hippocampal place cells in rodents have provided fertile ground for the understanding of spatial navigation and memory. Using a multielectrode system, it has been shown that hippocampal place cells that fired together during place acquisition in the waking state tended to fire together again during slow-wave sleep (SWS) (Wilson and McNaughton, 1994). More extensive studies (Louie and Wilson, 2001) have observed specific cell firing patterns as rats went from one section of a circular maze to another. The sequence of place cell firing was unique for each maze reward location that the rat approached and it was possible to identify the exact maze location of the rat in terms of the sequence. During SWS and even more so during REM sleep, these sequences were observed to replay again, suggesting that offline reprocessing was occurring. In more recent work simultaneous cell reactivation has been observed in both sensory cortex and
262
C. SMITH AND K.R. PETERS
hippocampus during postexperience SWS, offering additional support for the memory-processing hypothesis (Ji and Wilson, 2007). Dave and Margolish (2000) showed a replay phenomenon in songbirds learning to sing. Poe et al. (2000) showed that rats in a circular maze had firing sequences that coincided with the ongoing theta rhythm. The maximum firing rates of cells were coincident with the peak of each theta wave. However, as the rat became more familiar with the maze location, the firing sequences occurred out of synchrony with the theta peaks and when the animal became very familiar with the location, the cells fired maximally with the theta trough. It was theorized that the learning cycle began with a long-term potentiation (LTP)-like activity and ended with long-term depression (LTD) as the hippocampus was now “freed up” to deal with new material. Datta (2000) has examined the brainstem activity of the rat and recorded the P-wave. In rats, the P-wave is comparable to the pontine component of the pontogeniculo-occiptial (PGO) wave, which occurs before the onset of REM sleep and throughout the REM period. This technique, therefore, allows the direct recording of brainstem cells believed to generate the phasic activity of REM sleep. Datta trained rats in an avoidance task and recorded regular EEG as well as P-wave activity. There was a 25% increase in REM sleep and an increase in the transitional sleep state between NREM and REM (tS-R) of 180%. As well, there was a marked increase in P-wave activity during tS-R and REM sleep, suggesting that P-wave activity modulates cognitive activity. The many connections of this brainstem area to brain structures that are involved in learning are consistent with this idea. In other work, connections to the hippocampus have been established from the brainstem. Lesions of CA3 cells impair memory for the task while P-wave generation and quality of REM sleep were unchanged. Lesions of CA1 and the dentate gyrus did not interfere with postsleep memory for the task (Mavanji et al., 2004). These results indicate that, while REM sleep generation does not depend on the intact hippocampus, an intact hippocampus and P-wave generation system must exist for maximum memory reprocessing efficiency to occur. Several studies with rats have also documented experimental manipulations that enhance memory above normal levels. Using an avoidance task, rats were trained to avoid a foot shock when a conditioned stimulus (mild ear (pinna) stimulation) was presented. During subsequent REM sleep, the test animals were given the ear stimulations again as “reminders” of the task. Retesting showed these animals to be superior to rats stimulated during NREM sleep and to normally
rested, nonstimulated animals (Hennevin et al., 1995). Drug-induced enhancement of memory for a shuttle avoidance task has also been reported (Mavanji and Datta, 2003). It was shown that artificially increasing the P-wave activity by microinjection of carbachol into the P-wave-generating cells (dorsal locus subcoeruleus) enhanced subsequent memory for the task. Selective REM sleep deprivation impaired memory for the shuttle avoidance task, but this impairment was nullified if the rats received a microinjection of carbachol. Lesions of the locus subcoeruleus resulted in a large reduction in P-waves, but not a drop in number of minutes of REM sleep. Compared to control animals, these rats showed no sign of post-REM sleep improvement in shuttle avoidance performance, although initial learning was comparable. These results are consistent with the theory that postlearning memory reactivation occurs during REM sleep. Further, the results suggest that the phasic components of REM sleep are the most important.
Human studies The first studies relating sleep and memory were reported almost 100 years ago (Maquet et al., 2003b). These studies noted that memory seemed to improve following a night of sleep. In the studies that followed, there was some disappointment in that there was little change in the amount of REM sleep following task acquisition. Further, selective REM sleep deprivation did not always produce memory deficits for the tasks. In hindsight, the negative results were probably due to the nature of the tasks presented (declarative versus procedural) and to the fact that only visual scoring of the EEG was possible. A number of studies that appeared to have used procedural tasks have reported increases in either the number of minutes of REM sleep or increases in REM sleep density. Intensive learning of a second language was reported to have induced small, but significant, increases in number of minutes of REM sleep (DeKoninck et al., 1989). Smith and Lapp (1991) reported increases in number of REMs and REM densities in students following completion of exams. In a very recent study, it was reported that number of REMs and REM densities, but not time spent in REM sleep, were increased following acquisition of two procedural tasks: one with a strong cognitive component (tower of Hanoi) and a second with both a motor and a cognitive component (mirror trace task) (Smith et al., 2004b; Fogel et al., 2007: Figure 17.1). Using the split-night design, it has been shown that participants learning the procedural mirror trace task and allowed to have the REM-rich sleep of the last half of the night had superior memory for the task
SLEEP, MEMORY, AND MOLECULAR NEUROBIOLOGY
Mean number of rapid eye movements
Mean number of rapid eye movements before and after learning of two cognitive procedural tasks 2500 2000
Test group (trained) Controls (no training)
*
1500 1000 500
Baseline Post training Sleep night
Fig. 17.1. Increases in rapid eye movements following cognitive procedural task acquisition. (Reproduced from Nader and Smith (2003).)
compared to those who had SWS-rich sleep in the first half of the night (Plihal and Born, 1997). Using this same paradigm, it was observed that memory for an emotional task was also better following REM sleep but not NREM sleep (Wagner et al., 2001). Interestingly, REM sleep may also play a subtle role in declarative memory. Increases in both theta and sigma power were observed to occur in the posttraining sleep of individuals who had learned a declarative paired associate task involving emotionally neutral words (Fogel et al., 2007). Selective REM sleep deprivation is possible in human subjects while largely sparing the amount of sleep in the NREM stages. Other experimental conditions have included total sleep deprivation and NREM sleep interruption (to match the number of awakenings from REM sleep). It is not possible to deprive NREM sleep selectively while allowing REM sleep to proceed. Prevention of NREM sleep largely prevents the appearance of REM sleep as well. A number of studies have found memory impairments after selective REM deprivation using procedural types of tasks, but not declarative tasks. In several studies, the retesting of subjects was done at least several days after the end of the REM deprivation in order to ensure that the deprived subjects were rested enough to rule out fatigue as a factor (Smith, 2001). In one study, alcohol ingestion at bedtime, but not in the late afternoon, led to reductions in the REM densities of the subjects. Subjects learned both a cognitive procedural and a declarative task. The REM sleep alterations due to alcohol ingestion produced impairment on the procedural task only. Interestingly, alcohol ingestion 2 days after the end of
263
task acquisition and just before bedtime induced memory impairment for a procedural task. These results suggest that off-line memory reprocessing is active for several days after the end of acquisition and that memories are vulnerable to disruption during this time. Further, the phasic component of REM sleep was most severely disrupted by the alcohol ingestion (Smith and Smith, 2003). A few studies have attempted to enhance memory by presenting stimuli during posttraining REM sleep. The idea was to provide a “reminder” stimulus that would enhance further memory reprocessing. Superior memory was observed for a morse code auditory task (Mandai et al., 1989) and for a complex logic task (Smith and Weeden, 1990) when posttraining auditory “clicks” were presented during phasic REM sleep that coincided with REMs. Stimuli presented during tonic REM or NREM sleep did not improve memory for these tasks. Interestingly, phasic REM sleep has now been characterized as a time when a thalamocortical network including the limbic and parahippocampal areas is operative and isolated from external input. Such is not the case during tonic REM sleep (Wehrle et al., 2007). More recently, a spatial memory study was done in humans, using an odor as the conditioned stimulus (Rasch et al., 2007). Participants learned a hippocampal-dependent spatial task and a hippocampal-independent procedural finger-tapping task. When the odor was represented during subsequent deep SWS, memory for the task was enhanced and functional MRI (fMRI) activity in the hippocampus was observed to increase. The odor did not enhance memory for the procedural task. Odor presentation during REM sleep had no effect, although it was not possible to present this conditioned stimulus discretely to coincide with the REMs, as had previously been done (Mandai et al., 1989; Smith and Weeden, 1990).
EXPERIENCE-DEPENDENT
CEREBRAL
REACTIVATIONS IN HUMANS
While single-cell recording is not ethically possible in humans, brain imaging techniques allow similar kinds of studies to be conducted. If the sleep following successful acquisition of tasks in humans is also important for memory reprocessing, it seems logical that the brain structures involved in the initial learning would again be very active during posttraining sleep. One study (Maquet et al., 2000) required subjects to learn a probabilistic serial reaction time (SRT) task (Figure 17.2). When a dark circle appeared under one of six position markers, the corresponding key was to be pressed. There was also a probabilistic program whereby subjects could implicitly predict 85% of the
264
C. SMITH AND K.R. PETERS −16 mm
0 mm
16 mm
40 mm
56 mm
64 mm 8 7 6 5 4 3 2 1 10 8 7 6 5 4 3 2 1 10 8 7 6 5 4 3 2 1 10
A SRT REST
B
C
D
E
TRAINED REMS W
NON-TRAINED REMS W
3 2.5 2 1.5 1 0.5 0
INTERACTION (REMS vs W) x (TRAINED vs NON-TRAINED) CONJUNCTION
3 2.5 2 1.5 1 0.5 0
SRT REST INTERACTION (REMS vs W) x (TRAINED vs NON-TRAINED)
Fig. 17.2. Brain regions activated during the serial reaction time task. (Reproduced from Maquet et al. (2000).)
time where the circle would appear. Three groups were exposed to PET imaging. The first group learned the task and was scanned at that time during waking both when they were active and during rest periods. A second group was trained in the same way, but was scanned during the subsequent night of sleep. A third group did not learn the task but were also scanned during the night of sleep. In conjunction analyses it was found that subjects who learned the task showed higher levels of activation as measured by regional cerebral blood flow (rCBF) in the bilateral cuneus, midbrain, and left premotor cortex during REM sleep compared to the nontrained group. In further analyses, it was shown that the functional connections between structures involved in the learning of the task were stronger in those who learned compared to nonlearning controls (Laureys et al., 2001). In a subsequent study, a group was added that did not have the probabilistic component in the SRT (Peigneux et al., 2003). These subjects were slower than those who had the probabilistic program, although they expended the same amount of energy. The rCBF was higher in the left and right
cuneus of the probabilistic groups versus the random SRT trained group during the posttraining REM sleep. Further, there was a positive correlation between the level of learning of the probabilistic task and the rCBF during posttraining REM sleep. These results support the idea of experience-dependent cerebral reactivations during REM sleep. The data also indicate that the reactivations are most important for structured, higher-order procedural/implicit learning and are not as important for simple visuomotor learning.
NREM SLEEP AND MEMORY Animal studies In animals, NREM has not been considered to be of importance for memory consolidation by most researchers (Smith, 1985, 1995). In most studies, rodents did not show any increase in this sleep state after training. Since it is impossible to impair organisms of NREM sleep selectively and leave REM sleep intact, the answer to this question remains less clear. One author has identified some components of NREM
SLEEP, MEMORY, AND MOLECULAR NEUROBIOLOGY sleep that are closely associated with learning progress (Giuditta et al., 1995). Transient sleep has been identified electrophysiologically and the author has put forward the sequential hypothesis, suggesting that both NREM and REM sleep must occur for maximum efficiency in consolidation to take place. At the hippocampal EEG level, there are coincident episodes of “sharp-wave” (SPW) activity during SWS. When rats learned to navigate a rectangular maze to find food reward at various locations, they showed a particular pattern of cell firing that was unique to each location. During subsequent SWS, there were patterned “replays” of this activity which occurred such as to coincide with measured hippocampal SPW activity (McNaughton et al., 2003). Increases in spindle density were observed in the posttraining sleep of rats exposed to an odor–reward association task (Eschenko et al., 2006).
Human studies NREM sleep is a general term for stage 2 sleep as well as stages 3 and 4. While stage 2 is considered to be a separate sleep state, stages 3 and 4 are often seen as being quite similar brain states, with stage 3 simply being a transitional state from stage 2 to stage 4. Thus, for the present discussion stages 3 and 4 will be considered as a single brain state. The role of NREM sleep and memory has been less clear historically. In terms of visual sleep stage EEG recording, typically no changes in any of the NREM sleep states were reported. Further, total sleep deprivation did not result in greater memory loss for tasks than selective REM deprivation alone. Thus, in the past, NREM was not considered to be an important sleep state for memory processing (Smith, 2001). This situation has changed considerably in the last 15 years with a number of new developments and more sophisticated recording techniques.
STAGE 2 Smith and MacNeill (1994) were the first to report a relationship between stage 2 sleep and the consolidation of motor memory. These researchers used the pursuit rotor (PR) task, which is a visuomotor adaptation task that requires subjects to keep a hand-held stylus on a rotating disk for as long as possible. After learning the PR, subjects were exposed to one of several sleep deprivation conditions: total sleep deprivation, REM deprivation, NREM awakenings, and total sleep deprivation during the last half of the night. Subjects selectively deprived of REM sleep showed no memory deficits for this task when retested 1 week later. However, subjects who were deprived of total
265
sleep did show memory deficits. Also impaired were subjects deprived of the last half of the night of sleep. Since the last half of the night of sleep is composed mostly of stage 2 sleep and REM sleep, it was deduced that stage 2 was the important stage of sleep as separate from stages 3 and 4, which occur primarily in the first half of the night of sleep. A similar conclusion was reached by Walker et al. (2002), who showed that the amount of overnight improvement on a sequential finger-tapping task was correlated with the amount of stage 2 sleep in the last quarter of the night. Consistent with the hypothesis that stage 2 is important for consolidating motor skills, it has been reported that the number of minutes of stage 2 sleep and the number of stage 2 sleep spindles increases significantly after learning one or more motor tasks. Further, the density and mean duration of these spindles were also observed to increase (Nader and Smith, 2003; Fogel and Smith, 2006; Fogel et al., 2007). These increases are not likely due to random motor activity (Morin et al., 2008). The link between motor learning and sleep spindles is particularly interesting because several investigators have shown that during sleep spindles there is an increase in intracellular calcium, which may subsequently trigger various second messengers that are involved with synaptic plasticity (Steriade, 1999; Destexhe and Sejnowski, 2001). These results suggest that, for tasks with a predominantly motor component that do not require a new conceptual approach to reach solution, stage 2 sleep mechanisms are the most likely to be involved with off-line memory reprocessing (Smith et al., 2004a).
STAGES 3
AND
4
Using the split-night design, several studies have shown that deep NREM sleep has a role in the further reprocessing of declarative types of material, including improved performance on a paired-associates task (Plihal and Born, 1997) and a spatial memory task (Plihal and Born, 1999). In a memory enhancement study, transcranial magnetic stimulation (TMS) was used to enhance SWS activity following acquisition of a declarative paired-associates task. Control participants did not show behavioral or sleep state enhancement (Marshall et al., 2006). Several recent studies have also reported links between verbal declarative memory consolidation and sleep spindle density (Gais et al., 2002; Schabus et al., 2004, 2008; Clemens et al., 2005). One group has utilized the retroactive interference learning paradigm which is particularly sensitive to the beneficial aspects of sleep. While the number of word pairs remembered does not change, sleep appears to prevent
266 C. SMITH AND the confusion amongst different word pairs that is evident when sleep does not intervene (Ellenbogen et al., 2006). It is speculated that sleep differentially aids memory consolidation of word pairs that are not as strongly encoded (Drosopoulos et al., 2007). The effect of sleep on spatial memory was also investigated in a neuroimaging study conducted by Peigneux et al. (2004). In this study, participants performed a topographical memory task where they had to find their way through a complex three-dimensional virtual city. PET brain imaging was done on groups that were awake or that slept after acquisition. A third group did not learn the task but was also scanned during sleep. A fourth group that had learned the SRT task was added for structural comparison of the different task type. They found increased rCBF in the hippocampus and parahippocampus during posttraining NREM sleep (particularly in delta sleep), but not during REM sleep. The amount of hippocampal activity was correlated with degree of proficiency of task performance. These results are consistent with those reported in animals (Wilson and McNaughton, 1994) and humans (Plihal and Born, 1999) and suggest that consolidation of recently acquired spatial information occurs during deep NREM sleep. In addition to declarative memory, recent studies have also examined the relationship between deep NREM sleep and motor learning. Huber et al. (2004) examined the role of sleep in consolidating the motor skills involved in a rotation adaptation task. These investigators found a localized increase in slow-wave activity over the right parietal cortex after learning this task. Sleep was also found to have a beneficial effect on performance: performance improved over periods filled with sleep but not with wakefulness and there was a strong correlation between the amount of increase in slow wave activity and adaptation performance after sleep. Note that these investigators monitored the sleep of their subjects for only 2 hours and therefore, they could not comment on whether there were changes in REM sleep or stage 2 sleep, both of which are prominent in the second half of the night. The effects of LTP- and LTD-like plasticity on subsequent SWS in humans has been examined. Participants were trained on paired associative stimulation delivered to the right median nerve of the hand. A TMS pulse was simultaneously delivered to the left cranial M1 (hand) area. Pulse interstimulus intervals were designed to mimic LTP- or LTD-like activity and induced increases or decreases in motor evoked potentials compared to control stimulations. Stimulations favoring LTP resulted in post-SWS sleep decreases in slow spindle power, while stimulations favoring LTD resulted in increases in slow spindle power during
K.R. PETERS subsequent SWS. These changes were significantly correlated with paired associative stimulation efficacy the next morning (Bergmann et al., 2008).
REM
AND
NREM
SLEEP COMBINED
Not all studies on sleep and memory have teased apart the relative contributions of REM and NREM sleep: Some researchers have examined the role that sleep in general plays in learning and memory. A number of studies have examined the role of sleep in motor learning (Fischer et al., 2002; Walker et al., 2002, 2003, 2005). A consistent finding from these studies has been that the amount of improvement in performance is much greater after periods of sleep (diurnal or nocturnal) compared to equal periods of wakefulness. Walker et al. (2003) showed that the amount of overnight improvement did not differ between groups that had one or two training sessions during the day, suggesting that doubling the amount of initial learning had no effect on the amount of sleep-dependent consolidation. These investigators also found that the amount of improvement during initial acquisition was unrelated to the amount of sleep-dependent improvement. Using repetitive TMS, Robertson et al. (2005) have shown that disrupting the primary motor cortex after initial acquisition blocked improvement over a 12-hour period of wakefulness, but not over an equivalent period of sleep. Together these findings suggest that the consolidation processes that are occurring during postacquisition sleep might be different from those that are used during the initial acquisition of the task. Some studies have shown that the effects of sleep after initial acquisition can be seen when retested 12–36 hours later using neuroimaging. In one such study, subjects learned a sequential finger-tapping task and were then retested after a 12-hour interval of wakefulness or sleep (Walker et al., 2005). During retest, subjects performed the task again while also undergoing fMRI. Compared to the group that remained awake, individuals in the group that slept over the 12-hour interval showed increased activity in the right primary motor cortex, medial prefrontal lobe, hippocampus, and left cerebellum and decreased activity in the parietal cortices, left insular cortex, temporal pole, and frontopolar regions. The authors concluded that the patterns of increased and decreased brain activity reflected more precise memory traces and more automated performance. In a similar study (Maquet et al., 2003a), subjects learned a complex rotary pursuit task. Brain imaging using fMRI showed high levels of activity in the left supplementary eye field as well as the right dentate gyrus. However, on retest 3 days later, a normally rested group showed
SLEEP, MEMORY, AND MOLECULAR NEUROBIOLOGY more activity in the superior temporal sulcus than a totally sleep-deprived group. Further analyses showed stronger functional links between the dentate and superior temporal sulcus as well as supplementary eye field and frontal eye fields. It was concluded that sleep deprivation slows down important posttraining reprocessing that led to superior performance, although no specific sleep state was identifiable. The results of these two studies suggest that postacquisition sleep has a beneficial effect on brain activity when subjects are asked to perform the task again at a later time. Finally, Wagner et al. (2004) have reported a study indicating that the posttraining sleep activity may be doing more than simply making memories more permanent. These researchers asked subjects to perform a complex insightful task with many steps. Unknown to the subjects was the fact that one of the early steps in the long task could provide the final answer much earlier and make the situation easier and more efficient. Subjects who had sleep between training and retesting were much more likely to solve the task than were subjects who did not. Results suggest that the intervening sleep was beneficial for insightful problem-solving. In the same vein, relational memory, the ability to generalize across existing stores of information, was examined using a set of “premise” statements. Unknown to the participants, there was an overall pattern embedded in the task. Participants who had sleep following the initial task were much more likely to show understanding of this more complex pattern. It was concluded that binding of hierarchical memories is preferentially taking place during sleep and that it appears to operate at an unconscious level (Ellenbogen et al., 2007). There is also recent evidence for a hemispheric effect in the relationship between sleep and memory. Participants were exposed to novel objects in either the right or left hemisphere. Generalized memory for these shapes was better after sleep had occurred. However, if learning was followed by sleep deprivation, memory was poorer in those subjects with right hemisphere acquisition with no effect in those with left hemisphere acquisition (Peigneux et al., 2008). These results suggest that there may be hemispheric differences in terms of sleep required for memory consolidation as well.
DUAL-STEP
HYPOTHESIS
Rather than positing that either REM or NREM sleep is involved in the consolidation of memory for certain tasks, several studies have revealed that both of these types of sleep are needed to show maximum benefit. Using a visual detection task, Gais et al. (2000)
267
reported better performance on this task following a period rich in NREM sleep (early part of the night), but not after a period rich in REM sleep (late part of the night). Of particular interest, performance was much more improved after a period with both NREM and REM sleep. These findings are in agreement with those reported by Stickgold et al. (2000), who found that progress was correlated with the amount of deep NREM sleep in the first quadrant as well as REM sleep in the last quadrant of the night. These results remind us that, rather than trying to map single sleep stages to single memory types, it might be more advantageous to look at how several stages may be involved in a given task. Along these lines, Smith et al. (2004a) have proposed a model that outlines how both stage 2 and REM sleep may be involved in the consolidation of motor tasks, depending upon how novel the task is to the subject. It is proposed that if the individual perceives the task to be novel and requires new cognitive and motor strategies to master the task, then REM sleep will be more heavily involved than any of the other stages. Conversely, if the individual perceives the task to be similar to other experiences that have already been learned, then the process of mastering the task will be one of refining and improving upon previously learned strategies and motor behaviors. In this case, the most important sleep stage would be stage 2 sleep. Thus, the stage of sleep that manifests postacquisition changes depends upon the learning history of the participant. There is some experimental support for this idea (Peters et al., 2006).
NIGHTTIME
MENTAL ACTIVITY
(NTMA)
AND MEMORY
The study of NTMA (i.e., dreams) has a long history. The methods for studying NTMA have undergone a great deal of change since the discovery of the different states of sleep. While REM sleep at first dominated the stage in terms of when NTMA occurred, it is now generally agreed that NTMA occurs and can be recalled from every stage of sleep. There is controversy over whether there is a single NTMA generator or whether there are two NTMA generators (Fagioli, 2002). There are two main neuropsychological models of dream generation, the activation–synthesis hypothesis (Hobson and Stickgold, 1994) and the model of Solms (2000). The activation–synthesis model is heavily based on the REM sleep-generating system and the primary visual system. On the other hand, Solms argues that the primary visual cortex is not necessary for dreaming, whereas regions such as the parietal-occipital-temporal junction and the prefrontal region are most important.
268
C. SMITH AND K.R. PETERS
The role of dreams or NTMA in memory consolidation is not clear. One interesting possibility is that this NTMA might reflect the ongoing process of memory reprocessing or perhaps advance this process. The idea that NTMA reflects ongoing memory reprocessing has been tested by Stickgold and his colleagues. Using the Tetris game and the simulation of alpine skiing in two separate studies, it has been shown that during sleep-onset NTMA, there was a mental replay of the learned activity in a high proportion of the subjects. Further, in experienced Tetris players, this replay involved the incorporation of much earlier experiences, indicating that the recent experience was being incorporated or catalogued with the older similar experiences. This activity became more metaphorical and less precise as the night progressed (Stickgold, 2003), suggesting that reprocessing activities were occurring with time. The origin of the NTMA for the Tetris and alpine skiing tasks is not likely the hippocampus, a well-established structure necessary for the replay of episodic memories. Stickgold (2003) found that dreams do not appear to incorporate episodic memories, although they do seem to be about those activities. The Tetris game was learned by a number of participants with severe medial temporal lobe damage. These subjects showed virtually the same frequency of visual activity in the sleep-onset period following task acquisition as did normal subjects, even though they could not remember having participated in the game and did not know where the images could have come from. It seems very likely that the imagery originated from nonhippocampal memory systems and that it is recalled without the participation of the hippocampal system. Interestingly, a number of studies support the idea that there is minimal hippocampal outflow through the entorhinal cortex during REM sleep (Chrobak and Buzsaki, 1996). It seems likely that the generation of these dream images did not depend on the declarative memory system (Squire et al., 1992). It was also noticed that these dream images did not have an emotional component. It is simply not possible at this time to assess whether or not NTMA is useful for the reprocessing of recently acquired material. However, it appears that NTMA does reflect this reprocessing activity.
BIOCHEMICAL AND GENETIC FACTORS The understanding of the relationship between sleep and memory at the molecular level is still in its infancy. There is a substantial amount of information on the biochemical nature of the states of sleep and even more is known about memory processes. However, the interaction of these two important activities is not well understood.
A number of transmitters are believed to be involved with memory consolidation. These include acetylcholine (ACh), norepinephrine (NE), serotonin (5-HT), dopamine, glutamate, and adenosine. There is general agreement that the waking brain shows high levels of 5-HT, NE, and ACh. During NREM sleep the levels of ACh are low while the levels of NE and 5-HT are lower, but much higher than ACh. Interestingly, during REM sleep, levels of ACh are again very high while NE and 5-HT drop to very low levels (Aston-Jones and Bloom, 1981). While none of these transmitter systems have been extensively studied in relation to sleep states, the potential and scope for future studies involving these transmitters and their subsequent intracellular consequences is high (Graves et al., 2001). For example, increased levels of ACh and decreased levels of 5-HT could trigger a cascade via G-protein-coupled receptors. Subsequent changes in the second-messenger cyclic adenosine monophosphate (cAMP) and activation of protein kinase A and cAMP response-binding protein (CREB) could enhance memory consolidation in structures such as the hippocampus.
Acetylcholine In an animal study (Smith et al., 1991), rats were exposed to the two-way shuttle avoidance task with a well-established RSW (see above) between 9 and 12 hours after the end of training. Different groups of rats were given intraperitoneal injections of the protein synthesis inhibitor anisomycin such that the substance would be active during the RSW or at times several hours before or after the RSW. Only rats with the protein inhibitor active during the RSW showed memory loss for the task on retest. Further, analysis of both the levels of ACh and the enzyme acetylcholine esterase showed that the inhibitor had suppressed activity in groups at all of the times compared to saline controls. It was concluded that ACh was necessary for memory processing at the RSW, but not at times outside the 9–12-hour posttraining RSW. Similar behavioral results were observed with the ACh agonist, scopolamine. Utilizing the Morris water maze spatial task and the conditioned cue preference task, similar results were reported at unique RSWs using scopolamine (Smith, 2003). More recently, Legault et al. (2004) showed that systemic injections of scopolamine interfered with the consolidation of a radial arm maze task when injected to coincide with the posttraining RSW, but not at other posttraining times. In further work, it was shown that direct injections of scopolamine into the striatum were effective at blocking consolidation during the same RSW but not at other posttraining times (Legault et al., 2004). Thus, a
SLEEP, MEMORY, AND MOLECULAR NEUROBIOLOGY number of animal studies, using different tasks, strongly suggest that ACh is active in memory consolidation processes at certain posttraining times during REM sleep. As mentioned previously, Mavanji and Datta (2003) showed memory enhancement using the ACh agonist carbachol. The situation in humans is more complex and appears to depend on the type of memory. The importance of low levels of ACh during the SWS following declarative task acquisition has been reported. Enhanced ACh levels induced at this same posttraining sleep time impaired memory for the task (Gais and Born, 2004). In a study of aging individuals, it has been reported that cholinergic medication improved memory for a procedural task, but not a declarative task. It was concluded that it was cholinergic stimulation of phasic REM sleep that resulted in this improvement (Hornung et al., 2007).
Intracellular mechanisms Ribiero et al. (1999) examined expression of the immediate early gene zif-268. The expression of this gene is triggered by sustained membrane depolarization, N-methyl-D-aspartic acid channel opening, and calcium influx. This system implicates the transmitter glutamate. Rats were sleep-recorded and exposed to the informal learning situation of an enriched environment for 3 hours. The controls were kept in a more restricted environment. Different groups were sacrificed during subsequent waking, NREM, or REM sleep and the brains were examined for changes in zif-268 expression. The levels of zif-268 dropped from waking to NREM to REM sleep in the controls. However, in the enriched environment animals, zif-268 dropped during NREM sleep, but increased again during REM sleep, indicating that the learning situation resulted in increased gene expression during subsequent REM sleep. The brain areas most involved appeared to be the striatum and amygdala (Pavlides and Ribiero, 2003). In other studies, these investigators examined the effects of unilateral high-frequency stimulation of the rat hippocampus on gene expression (Ribiero et al., 2002). This procedure is known to result in LTP, a model of synaptic plasticity (Bliss and Lomo, 1973). Measuring the same gene, the authors observed that, compared to waking, the stimulated hemisphere showed a drop in zif-268 expression during NREM sleep, but an increase again during REM sleep. By contrast, the control hemisphere showed a steady drop from waking to NREM to REM sleep, providing additional evidence of gene reinduction during REM sleep following a relevant waking experience. Further, they showed that the hippocampal activity during
269
poststimulation REM sleep was essential for REMassociated zif-268 activity in the cortex and amygdala. Results from a series of genetic, biochemical, and behavioral studies in a variety of animals has confirmed that long-term memory formation involves the coupling of gene transcription and protein synthesis. Datta’s group (Datta, 2006; Datta et al., 2008) have examined the role of CREB, a transcription factor which plays a role in long-term memory formation. Using the two-way shuttle avoidance task, they observed, as previously mentioned, an increase in brainstem P-wave density as a result of successful learning. In addition, they showed an increased activation of CREB activity in the cells of the dorsal hippocampus. This activity was most prominent in the CA3 subfield of the hippocampus with lesser activity in the CA1 and dentate gyrus areas. This activity was most pronounced 3 hours after the end of training, which coincided with the peak P-wave intensity previously observed. Most recently, this group has reported that the P-wave generator is directly involved in the molecular events of the dorsal hippocampus and the amygdala following successful two-way shuttle avoidance acquisition. The P-wave generator increased phosphorylation of CREB and expression of Arc protein as well as the mRNA of Arc, brain-derived neurotrophic factor and Egr-1 in the dorsal hippocampus and amygdala. Selective lesioning of the generator, without reducing time spent in tonic REM sleep, reduced expression of these molecules and resulted in impaired task memory following training. Increased expression of these molecules was observed after direct cholinergic stimulation of the P-wave generator. These studies implicate the direct involvement of the P-wave generator in the plasticity-related genes following two-way shuttle avoidance task acquisition (Datta et al., 2008).
IMPLICATIONS There is now considerable evidence for a strong relationship between sleep states and memory consolidation, and this relationship will become more precise as research continues. In addition to the theoretical interest inherent in this research, there are also a number of practical and clinically relevant issues that remain to be explored. Compared to individuals with normal sleep patterns, those with chronically poor sleep may be at an unfair disadvantage when the rapid acquisition of new information or skills is required. There is also very little known about the connection between sleep and memory in psychopathological and medical conditions. Physicians may want to consider the fact that many pharmacological agents interfere with sleep and, thus, may have a negative impact on learning
270
C. SMITH AND K.R. PETERS
progress or potential. This point is particularly relevant when drugs need to be prescribed for children and young adults, especially when the prescription is intended to be long-term. Everyone appreciates the effect that poor sleep can have on their quality of life. In addition, when one considers the mounting evidence linking sleep states and memory processing, it becomes clear that individuals and their physicians must consider quality sleep a top medical priority.
REFERENCES Aserinsky E, Kleitman N (1953). Regularly occurring periods of eye motility, and concomitant phenomena, during sleep. Science 118: 273–274. Aston-Jones G, Bloom FE (1981). Activity of norepinephrinecontaining locus coeruleus neurons in behaving rats anticipates fluctuations in the sleep–wake cycle. J Neurosci 1: 887–900. Barrett TR, Ekstrand BR (1972). Effect of sleep on memory. III. Controlling for time of day effects. J Exp Psychol 96: 321–327. Bergmann TL, Molle M, Marshall L et al. (2008). A local signature of LTP- and LDP-like plasticity in human NREM sleep. Eur J Neurosci 27: 2241–2249. Bliss TVP, Lomo T (1973). Long lasting potentiation of synaptic transmission in the dentate area of the anaesthetized rabbit following stimulation of the perforant path. J Physiol (London) 232: 331–356. Chrobak J, Buzsaki G (1996). High-frequency oscillations in the output networks of the hippocampal–entorhinal axis of the freely behaving rat. J Neurosci 16: 3056–3066. Clemens Z, Fabo´ D, Hala´sz P (2005). Overnight verbal memory retention correlates with the number of sleep spindles. Neuroscience 132: 529–535. Datta S (2000). Avoidance task training potentiates phasic pontine-wave density in the rat: a mechanism for sleepdependent plasticity. J Neurosci 20: 8607–8613. Datta S (2006). Activation of phasic pontine-wave generator: a mechanism for sleep dependent memory processing. Sleep Biol Rhythms 4: 16–26. Datta S, Li G, Auerbach S (2008). Activation of phasic pontine-wave generator in the rat: a mechanism for expression of plasticity-related genes and proteins in the dorsal hippocampus and amygdala. Eur J Neurosci 27: 1876–1892. Dave AS, Margolish D (2000). Song replay during sleep and computational rules for sensorimotor vocal learning. Science 290: 812–816. DeKoninck J, Lorrain D, Christ G et al. (1989). Intensive language learning and increases in rapid eye movement sleep: evidence of a performance factor. Int J Psychophysiol 8: 43–47. Destexhe A, Sejnowski TJ (2001). Thalamocortical Assemblies. Oxford University Press, Oxford. Drosopoulos S, Schulze C, Fischer S et al. (2007). Sleep’s function in the spontaneous recovery and consolidation of memories. J Exp Psychol Gen 136: 169–183.
Ellenbogen JM, Hulbert JC, Stickgold R et al. (2006). Interfering with theories of sleep and memory: sleep, declarative memory and associative interference. Curr Biol 16: 1290–1294. Ellenbogen JM, Hu PT, Payne JD et al. (2007). Human relational memory requires time and sleep. Proc Natl Acad Sci 104: 7723–7728. Eschenko O, Molle M, Born J et al. (2006). Elevated sleep spindle density after learning or after retrieval in rats. J Neurosci 26: 12914–12920. Fagioli I (2002). Mental activity during sleep. Sleep Med Rev 6: 307–320. Fischer S, Hallschmid M, Elsner AL et al. (2002). Sleep forms memory for finger skills. Proc Natl Acad Sci 99: 11987–11991. Fogel SM, Smith CT (2006). Learning-dependent changes in sleep spindles and stage 2 sleep. J Sleep Res 15: 250–255. Fogel SM, Smith CT, Cote KA (2007). Dissociable learningdependent changes in REM and non-REM sleep in declarative and procedural memory systems. Behav Brain Res 180: 48–61. Gais S, Born J (2004). Low acetylcholine during slow-wave sleep is critical for declarative memory consolidation. Proc Natl Acad Sci 101: 2140–2144. Gais S, Plihal W, Wagner U et al. (2000). Early sleep triggers memory for early visual discrimination skills. Nat Neurosci 3: 1335–1339. Gais S, Molle M, Helms K et al. (2002). Learning-dependent increases in sleep spindle density. J Neurosci 22: 6830–6834. Giuditta A, Ambrosini MV, Montagnese P et al. (1995). The sequential hypothesis of the function of sleep. Behav Brain Res 69: 157–166. Graves L, Pack A, Abel T (2001). Sleep and memory: a molecular perspective. Trends Neurosci 24: 237–243. Hennevin E, Hars B, Maho C et al. (1995). Processing of learned information in paradoxical sleep: relevance for memory. Behav Brain Res 69: 125–135. Hobson JA, Stickgold R (1994). The conscious state paradigm: a neurocognitive approach to waking, sleeping, and dreaming. In: M Gazzaniga (Ed.), The Cognitive Neurosciences. M.I.T. Press, Cambridge, pp. 1373–1389. Hornung OP, Regen F, Danker-Hopfe H et al. (2007). The relationship between REM sleep and memory consolidation in old age and effects of cholinergic medication. Biol Psychiatry 61: 750–757. Hu PT, Stylos-Allan M, Walker MP (2006). Sleep facilitates consolidation of emotional declarative memory. Psychol Sci 17: 891–898. Huber R, Ghilardi MF, Massimini M et al. (2004). Local sleep and learning. Nature 430: 78–81. Jackson C, McCabe JB, Nicol AU et al. (2008). Dynamics of a memory trace: effects of sleep on consolidation. Curr Biol 18: 393–400. Ji D, Wilson MA (2007). Coordinated memory replay in the visual cortex and hippocampus during sleep. Nat Neurosci 10: 100–107. Laureys S, Peigneux P, Phillips C et al. (2001). Experiencedependent changes in cerebral functional connectivity during rapid eye movement sleep. Neuroscience 105: 521–525.
SLEEP, MEMORY, AND MOLECULAR NEUROBIOLOGY Legault G, Smith C, Beninger RJ (2004). Scopolamine during the paradoxical sleep window impairs radial arm maze learning in rats. Pharmacol Biochem Behav 49: 715–721. Louie K, Wilson MA (2001). Temporally structured replay of awake hippocampal ensemble activity during rapid eye movement sleep. Neuron 29: 145–156. McGrath MJ, Cohen DB (1978). REM sleep facilitation of adaptive waking behavior: a review of the literature. Psychol Bull 85: 24–57. McNaughton BL, Barnes CA, Battaglia FP et al. (2003). Offline reprocessing of recent memory and its role in memory consolidation: a progress report. In: P Maquet, C Smith, R Stickgold (Eds.), Sleep and Brain Plasticity. Oxford University Press, Oxford, pp. 225–246. Mandai O, Guerrien A, Sockeel P et al. (1989). REM sleep modifications following a morse code learning session in humans. Physiol Behav 46: 639–642. Maquet P, Laureys S, Peigneux P et al. (2000). Experiencedependent changes in cerebral activation during human REM sleep. Nat Neurosci 3: 831–836. Maquet P, Schwartz S, Passingham R et al. (2003a). Sleeprelated consolidation of a visuomotor skill: brain mechanisms as assessed by functional magnetic resonance imaging. J Neurosci 23: 1432–1440. Maquet P, Smith C, Stickgold R (2003b). Introduction. In: P Maquet, C Smith, R Stickgold (Eds.), Sleep and Brain Plasticity. Oxford University Press, Oxford, pp. 1–13. Marshall L, Helgadottir H, Molle M et al. (2006). Boosting slow oscillations during sleep potentiates memory. Nat Neurosci 444: 610–613. Mavanji V, Datta S (2003). Activation of the pontine-wave generator enhances improvement of learning performance: a mechanism for sleep dependent plasticity. Eur J Neurosci 17: 359–370. Mavanji V, Ulloor J, Saha S et al. (2004). Neurotoxic lesions of phasic pontine-wave generator cells impair retention of 2-way active avoidance memory. Sleep 27: 1282–1292. Milner B, Squire LR (1998). Cognitive neuroscience and the study of memory. Neuron 20: 445–468. Morin A, Doyon J, Dostie V et al. (2008). Motor sequence learning increases sleep spindles and fast frequencies in post-training sleep. Sleep 31: 1149–1156. Nader R, Smith CT (2003). A role for stage 2 sleep in memory processing. In: P Maquet, C Smith, R Stickgold (Eds.), Sleep and Brain Plasticity. Oxford University Press, Oxford, pp. 87–98. Pavlides C, Ribiero S (2003). Recent evidence of memory processing in sleep. In: P Maquet, C Smith, R Stickgold (Eds.), Sleep and Brain Plasticity. Oxford University Press, Oxford, pp. 327–362. Pearlman C (1979). REM sleep and information processing: evidence from animal studies. Neurosci Biobehav Rev 3: 57–68. Peigneux P, Laureys S, Fuchs S et al. (2003). Learned material content and acquisition level modulate cerebral deactivation during posttraining rapid-eye-movement sleep. Neuroimage 20: 125–134.
271
Peigneux P, Laureys S, Fuchs S et al. (2004). Are spatial memories strenghthened in the human hippocampus during slow wave sleep? Neuron 44: 535–545. Peigneux P, Schmitz R, Willems S (2008). Cerebral assymetries in sleep-dependent processes of memory consolidation. Learn Mem 14: 400–406. Peters KR, Smith V, Smith CT (2006). The effect of initial skill level on the relationship between stage 2 sleep spindles, rapid eye movements and motor learning. J Cogn Neurosci 19: 817–829. Plihal W, Born J (1997). Effects of early and late nocturnal sleep on declarative and procedural memory. J Cogn Neurosci 9: 534–547. Plihal W, Born J (1999). Effect of early and late nocturnal sleep on priming and spatial memory. Psychophysiology 36: 571–582. Poe GR, Nitz DA, McNaughton BL et al. (2000). Experiencedependent phase reversal of hippocampal neuron firing during REM sleep. Brain Res 855: 176–180. Rasch B, Buchel C, Gais S et al. (2007). Odor cues during slow-wave sleep prompt declarative memory consolidation. Science 315: 1426–1429. Ribiero S, Goyal V, Mello CV et al. (1999). Brain gene expression during REM sleep depends on prior waking experience. Learn Mem 6: 500–508. Ribiero S, Mello C, Velho T et al. (2002). Induction of hippocampal long-term potentiation durign waking leads to increased extra-hippocampal zif-268 expression during ensuing REM sleep. J Neurosci 22: 10914–10923. Robertson EM, Press DZ, Pascual-Leon A (2005). Off-line learning and the primary motor cortex. J Neurosci 25: 6372–6378. Schabus M, Gruber G, Parapatics S et al. (2004). Sleep spindles and their significance for declarative memory consolidation. Sleep 27: 1479–1485. Schabus M, Hoedlmoser K, Pecherstorfer T et al. (2008). Interindividual sleep spindle differences and their relation to learning-related enhancements. Brain Res 1191: 127–135. Siegal JM (2001). The REM sleep-memory consolidation hypothesis. Science 294: 1058–1063. Smith C (1985). Sleep states and learning: a review of the animal literature. Neurosci Biobehav Rev 9: 157–168. Smith C (1995). Sleep states and memory processes. Behav Brain Res 69: 137–145. Smith C (1996). Sleep states, memory processes and synaptic plasticity. Behav Brain Res 78: 49–56. Smith C (2001). Sleep states and memory processes in humans: procedural vs. declarative memory systems. Sleep Med Rev 5: 491–506. Smith CT (2003). The REM sleep window and memory processing. In: P Maquet, C Smith, R Stickgold (Eds.), Sleep and Brain Plasticity. Oxford University Press, Oxford, pp. 117–135. Smith C, Lapp L (1991). Increases in number of rems and REM density in humans following an intensive learning period. Sleep 14: 325–330.
272
C. SMITH AND K.R. PETERS
Smith C, MacNeill C (1994). Impaired motor memory for a pursuit rotor task following stage 2 sleep loss in college students. J Sleep Res 3: 206–213. Smith C, Smith D (2003). Ingestion of ethanol just prior to sleep onset impairs memory for procedural but not declarative tasks. Sleep 26: 185–191. Smith C, Weeden K (1990). Post training rems coincident auditory stimulation enhances memory in humans. Psychiatr J Univ Ott 15: 85–90. Smith C, Tenn C, Annett R (1991). Some biochemical and behavioral aspects of the paradoxical sleep window. Can J Psychol 45: 115–124. Smith C, Aubrey JB, Peters KR (2004a). Different roles for REM and stage 2 sleep in motor learning: a proposed model. Psychol Belgica 44: 81–104. Smith CT, Nixon MR, Nader RS (2004b). Posttraining increases in REM sleep intensity implicate REM sleep in memory processing and provide a biological marker of learning potential. Learn Mem 11: 714–719. Solms M (2000). Dreaming and REM sleep are controlled by different brain mechanisms. Behav Brain Sci 23: 843–850. Squire LR (1987). Memory and the Brain. Oxford University Press, New York. Squire LR, Ojemann JG, Miezin FM et al. (1992). Activation of the hippocampus in normal humans: a functional anatomical study of memory. Proc Natl Acad Sci 89: 1837–1841. Steriade M (1999). Coherent oscillations and short term plasticity in corticothalamic networks. Trends Neurosci 8: 337–345.
Sterpenich V, Albouy G, Boly M et al. (2007). Sleep-related hippo-cortical interplay during emotional memory recollection. PLoS Biol 5: 2709–2722. Stickgold R (2003). Memory, cognition, and dreams. In: P Maquet, C Smith, R Stickgold (Eds.), Sleep and Brain Plasticity. Oxford University Press, Oxford, pp. 17–39. Stickgold R, LaTanya J, Hobson JA (2000). Visual discrimination learning requires sleep after training. Nat Neurosci 3: 1237–1238. Wagner U, Gais S, Born J (2001). Emotional memory formation is enhanced across sleep intervals with high amounts of rapid eye movement sleep. Learn Mem 8: 112–119. Wagner U, Gais S, Haider H et al. (2004). Sleep inspires insight. Nature 427: 352–355. Walker MP, Stickgold R (2006). Sleep, memory and plasticity. Annu Rev Psychol 57: 139–166. Walker M, Brakefield T, Morgan A et al. (2002). Practice with sleep makes perfect: sleep-dependent motor skill learning. Neuron 35: 205–211. Walker MP, Brakefield T, Seidman J et al. (2003). Sleep and time course of motor skill learning. Learn Mem 10: 275–284. Walker MP, Stickgold R, Alsop D et al. (2005). Sleep dependent motor memory plasticity in the human brain. Neuroscience 133: 911–917. Wehrle R, Kaufmann C, Wetter TC et al. (2007). Functional microstates within human REM sleep: first evidence from fMRI of a thaloamocortical network specific for phasic REM periods. Eur J Neurosci 25: 863–871. Wilson MA, McNaughton BL (1994). Reactivation of hippocampal ensemble memories during sleep. Science 265: 676–678.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 18
Epidemiology of sleep disorders MARKKU PARTINEN * Helsinki Sleep Clinic, Vitalmed Research Centre, and Department of Neurology, University of Helsinki, Finland
Even though societies have changed a lot, present epidemiological studies about sleep length do not vary much from the results of studies that were done about 50 years ago. This may indicate that the need for sleep is relatively stable and that it depends more on intrinsic, genetic, and biological factors rather than on environmental factors. In most studies from the 1960s–1980s, the average length of sleep varied between 7 and 8 hours (McGhie and Russell, 1962; Hammond, 1964; Webb, 1970; Johns et al., 1971; Bixler et al., 1979; Partinen and Rimpela¨, 1982; Partinen et al., 1983a). In this chapter epidemiological principles are discussed first followed by epidemiological figures of some common sleep disorders.
EPIDEMIOLOGICAL METHODS IN SLEEP MEDICINE Modern applications of epidemiology include the study of chronic diseases, the evaluation of health status, and an evaluation of genetic and environmental factors associated with diseases or symptoms in defined populations (Feinstein, 1985; Miettinen, 1985; Rothman, 1986). A common misunderstanding is that epidemiological studies are limited to large population studies. Miettinen (1985) defines epidemiology as the discipline of how to study the occurrence of phenomena that are of interest in the health field. Thus, it delineates major principles of study design and data analysis in research into the frequency of occurrence of illness and related phenomena in human populations, whether in the community or in different clinical settings.
Descriptive, analytical, and intervention studies Epidemiological studies can be divided into descriptive, analytical, and intervention studies. Descriptive studies have many limitations. Classic examples are cross*
sectional studies with data collected at a defined moment and retrospective studies that are based on existing medical histories or other previously collected data. In descriptive studies distributions are given with, perhaps, computations of statistical significance between different groups of subjects. Retrospective studies are highly dependent on the quality of collected data. Ideally the data have been collected systematically by qualified researchers, clinicians, or assistants and always in the same format on a database. Data should be collected using validated instruments. If the study population, or the sample, is representative of a defined population (general population, hospital population), generalizations can be made to that base population, but not necessarily to other populations. Cross-sectional descriptive studies do not allow any causal or etiological inferences. Such inferences are more or less speculative. Are retrospective studies useless? No, they may be very useful, for example in explaining the occurrence of different or new findings or symptoms in a well-defined setting, which allows generalizations to other populations. Hundreds of descriptive epidemiological studies on various sleep disorders have been published about sleeping habits and different sleep disorders from different countries. Analytical or etiological studies allow more inferences to be done than descriptive studies, especially if the study has been prospective in time (longitudinal). A prospective cohort study may give huge amounts of valuable information. Examples of well-defined cohorts are the Framingham Cohort, Wisconsin Sleep Cohort, Sleep Heart Cohort, and the Finnish Twin Cohort. A cohort is a population of subjects identified in a defined setting at a defined time. Once a cohort has been defined it exists for ever. It remains even if all the persons in the initial cohort have died. A cohort may be static or dynamic. New persons fulfilling the
Correspondence to: Markku Partinen, M.D., Helsinki Sleep Clinic, Vitalmed Research Centre, FIN-00420 Helsinki, Finland. E-mail:
[email protected]
276 M. PARTINEN entry criteria may enter a dynamic cohort after the iniStructured questionnaires are often a practical tial cohort has been established. method. If possible, validated tools should be used. Interventions are commonly used in clinical epideTo allow comparability the wording should mean the miological research, e.g., to study the effect of a new same thing in different languages. In translating a hypnotic in insomnia, or to study the effect of weight questionnaire from one language to another, crossloss in the treatment of sleep apnea. Ideally a randotranslation or back translation should be used. Quesmized controlled trial (RCT) is designed. tionnaire studies are usually relatively cheap. If they are to be mailed one needs funding for printing of Population surveys the forms, envelopes (to send and prepaid return envelope), and mailing costs. In addition one needs funding COHORT STUDIES to enter data into a database. Population surveys may be cross-sectional or longitudiTelephone surveys may be almost as good as nal studies. Longitudinal studies may be retrospective personal interviews and considerably easier to do. or prospective in time. Prospective studies are also Computer-assisted telephone interview software can called follow-up studies, cohort studies, or prolective control the interview process and record the responses cohort studies. Retrospective follow-up studies are also as the interview proceeds. It can be combined with rancalled “trohoc” studies, retrolective cohort studies, or dom digit dialing (Waksberg, 1978) to identify subjects retrospective cohort studies (Feinstein, 1985; Rothman, and to enhance the efficiency of telephone methods for 1986). data collection. In sleep research telephone surveys Cross-sectional studies are sometimes called prevahave been used often in Europe since the beginning lence studies. The population is studied at one particuof 1980s. They are often faster to do than mailed queslar point in time. There is no longitudinal information. tionnaire studies. On the other hand they are more They can be used to find the prevalence of defined expensive and may exaggerate some figures. The conditions. Naturally, no cause-and-effect inferences National Institute of Mental Health Epidemiologic can be made, and no incidences can be calculated from Catchment Area study on psychiatric disorders includa conventional cross-sectional study. ing sleep disturbances was done in the early 1980s The quality of a retrospective study depends on the (Ford and Kamerow, 1989). The Diagnostic Interview quality of collected information in past time. We have Schedule is a structured interview, administered by only the information that has been saved. Missing data lay interviewers, that assigns a Diagnostic and Statistiare a problem. If the subjects have always been examcal Manual, 3rd edition (DSM-III) number using a ined and treated by the same personnel using the computer algorithm. More recently a similar method, same standardized methods, we can usually trust the called Sleep-EVAL, has been used mainly by one group information. of researchers (Ohayon and Caulet, 1996; Ohayon, 2005). There are problems with such closed methods CASE-CONTROL STUDIES because the studies cannot be replicated by others. This means that it is difficult to judge the correctness of the A well-designed and properly analyzed case-control results. In a properly conducted study the wording of study is an efficient way of answering many questions. each question is given, or alternatively the wordings It is both faster and cheaper than a cohort study. The of all questions are given as an attachment, or are use and understanding of case-control studies are develavailable on the internet. opments of modern epidemiology (Schlesselman, 1982; We already know quite a lot about the prevalence of Miettinen, 1985). In a case-control study, cases and condifferent sleep disorders, but many more prospective trol subjects are collected and the occurrence of defined longitudinal studies and genetic epidemiological studrisk factors preceding the onset of disease will then be ies are needed. Such studies are out of the scope of a analyzed. In this way case-control studies are retrospeccross-sectional telephone survey. It is difficult to tive in nature. In a nested case-control study the cases include names, social security information, addresses, and their controls are selected from an existing cohort. and other strictly personal information without written To prove the results a case-control study should usually permission. be followed by a prospective study or an RCT. Personal face-to-face interviews using a structured questionnaire are a very good method providing the Data collection interviewers are properly trained and unbiased. PerMost often questionnaires are used. Other possibilities sonal interviews are more expensive to carry out than include personal interviews, telephone surveys, and mailed questionnaires or telephone surveys, but on tabulation of information, e.g., from medical records. the other hand, the response rate is much better than
EPIDEMIOLOGY OF SLEEP DISORDERS for the other methods, especially if the interviewer travels to meet the interviewee. In conclusion, at least in very large-scale studies, one should usually start with a well-designed questionnaire study. Telephone survey methods do not differ from other epidemiological survey methods. They can be used to estimate prevalence but they cannot be used to make final diagnoses. If needed, the questionnaire data can be completed by telephoning those who did not answer the questionnaire, and asking them to return it. In some cases the questions can be asked by phone but caution is then needed before combining the data with the mail questionnaire data. Sometimes one can even visit persons who did not respond. Another approach is to pull a representative sample from the population to participate in thorough medical and laboratory examinations. This approach has been used in the well-known Wisconsin Sleep Cohort study (Young et al., 1993, 2002).
Size of population The most efficient, but also expensive, method of reducing random error is to increase the size of the study. Sample size and power calculations (see below) may be used to estimate adequacy of the size beforehand. The size of the population in an epidemiological study could easily be 10, or more than 100 000. Large populations may give smaller confidence intervals (CIs), but there are also several dangers that may result in wrong inferences. Statistics is a tool for the researcher, but final inferences should be plausible. Correlation coefficients are still used in medical research. To make clinically meaningful inferences the correlation coefficient (r) should generally be around 0.30 or more. If there are thousands of subjects and hundreds of variables one may have several “statistically significant” r-values even if they make no sense. For example, one may find a “significant” correlation between color of the outdoor of one’s house (if asked) and apnea–hypopnea index (AHI). If you are using correlation coefficients, a Bonferroni tranformation should be used before computing a P-value.
Power calculations Power calculations should be done before a study is started (Dixon and Massey, 1983; Kraemer and Thiemann, 1987). Before doing computations the level of clinical meaningfulness should be determined. From previous studies we can estimate the expected standard deviation. Using statistical computer programs, it is easy to compute how many subjects are needed to find significant statistical differences, say, with a power of 80% or 90%. Before starting a study, its costs should
277
also be calculated. For example, it would be illogical to spend excessive amounts of money to find a 5-minute difference in total sleeping time, which is certainly not clinically significant. In the case of small sample sizes sufficient raw data should be reported so that readers can make their own inferences. Such studies may contain a lot of useful information. Researchers and editors seem to prefer “positive” results. To avoid publishing bias, important negative results should also be published if the hypothesis has been relevant, studies have been well conducted, and proper methods have been used. When raw data are given, meta-analytic methods can be used to combine results of several studies on the same topic in order to increase the strength of the inferences.
The P-value Regarding P-value (note that the P is originally a large P) (Dixon and Massey, 1983; Feinstein, 1985), a pure statistical significance alone, that is, small P-value, does not prove anything. If the information is sparse (there are a small number of subjects), the P-value does not discriminate between the hypothesis and the null hypothesis. In such cases, the P-value is to be ignored, or at least no final inferences should be drawn from a scarce body of data. If, on the contrary, very large populations are used, even very small differences will provide a very small P-value. Such data should be analyzed quantitatively. Use of percentiles and the CI instead of P-values will solve some of the problems. Suppose that we are studying two different treatments, Th1 and Th2. The mean total sleeping time during Th1 is 480 minutes, and the standard deviation is 20 minutes. Using Th2, the respective figures are 475 and 20 minutes. If we studied 15 subjects in both groups, the P-value is 0.499 (statistically not significant), and the 95% CI for the difference between means is –10–20 minutes. If we studied 125 subjects per group, the P-value would have been less than 0.05 (the probability that the difference is caused by chance is less than 5%), and the CI would have been 0–10 minutes. In both groups, 1000 subjects would have given P less than 0.0001 (statistically highly significant difference in total sleep time), and the CI would have been 3–7 minutes. The truth is, of course, that there was only 5 minutes’ difference between the two treatments, which is not clinically significant. In this example the most valuable information for a clinician is given by the smallest study, not by the largest study.
Validity The validity of a study is divided into internal validity and external validity. Internal validity derives from the inferences that can be made based on the data.
278
M. PARTINEN
It is a measure of quality and of the study methods. Selection bias and information bias should be avoided and confounding factors should be identified and controlled. External validity is a measure of representativeness of the study population compared to a more general population. Good internal validity is necessary for good adequate external validity. As Rothman (1986) writes: “The separation of relevant from irrelevant factors is the beginning of knowledge.” For example, a study of a new drug among 18–70year-old individuals with many exclusion criteria cannot be generalized to a treating physician’s normal clinical patients, because many patients have some of the diseases that have been listed among the exclusions. The results can only be generalized to those patients who fulfill the same inclusion and exclusion criteria. Interestingly, this is often not taken into consideration when new treatments are entering the markets. For example, for most hypnotics most studies are done with patients having chronic insomnia, lasting for more than 1 month. In spite of this, in many countries, the official label writes that this same hypnotic is indicated to treat insomnia on a short-term basis. We know that ideally hypnotics might be useful in the initial short-term treatment of transient insomnia. We also know that there are no studies about long-term, say 3-year follow-up studies, of hypnotic treatments that have shown good efficacy without developing tolerance or adverse effects. Similar examples exist for almost all other types of drugs. Clinicians must use their own clinical knowledge when making final inferences. In this respect it is also interesting to note that pharmacologists, other theoreticians, and investigators of RCTs may give instructions about how to treat a specified disease even if they have rarely or never taken the responsibility for treating such patients in the real world.
Selection bias An essential element of a study is a comparison of two or more groups for the occurrence of a disease or exposure. One form of bias is a self-selection bias. Another type of bias is diagnostic bias. Many other types of selection bias exist. Some epidemiologic studies, e.g., on narcolepsy, are based on newspaper advertisements. People with given symptoms are asked to contact the researchers. Such studies may be used to have a rough estimate of prevalence of a very rare and serious disease, such as central alveolar hypoventilation, but they cannot be used for insomnia, restlesslegs syndrome (RLS), or sleep apnea. Of course one might use such selection methods when recruiting subjects into drug trials. One should keep in mind, however, that the subjects contacting a center do not
necessarily represent a typical patient with the disease concerned. If study subjects are receiving honorary fees for participation the bias may be even larger, because the motivation to participate may be to earn money, and subjects may report relief from the symptoms more easily. The same may also be true when opiates, for example, are studied. For this reason drug screens should always be used when one is studying drugs with central nervous system effects.
Information bias The information obtained and entered into a database should be based on comparable methods. To improve comparability, quantitative or semiquantitative scales should always be used when possible. Wordings such as “always,” “often,” “sometimes,” and “rarely” may be interpreted differently by different persons. For one patient having a migrainous attack once per month might mean “often.” For another person it might mean “rarely.” Having trouble sleeping “often” may mean “on 3–4 nights per month” or “on 3–4 nights per week.” It is obvious that quantitative scales allow better comparisons between individuals. The basic Nordic sleep questionnaire (BNSQ) is an example of a questionnaire with quantitative wordings (Partinen and Gislason, 1995). Similar wordings are also used in the Wisconsin Sleep Cohort studies and in many other studies. Qualitative research has its own benefits and usages that are not discussed here. Recall bias is an example of information bias. People who are ill often remember better some things that have occurred in the past. On the other hand they may also misremember some things, for example after reading an article about possible adverse effects. The time lapsed between the exposure and the recall is an important indicator of the accuracy of recall. To gain information about the effects of an intervention or treatment the same measure should be used at baseline and at a later time. Sometimes patients have been asked, e.g., “How do you find this treatment compared to another or compared to no treatment?” If the treating physician is valued and respected by the patient the placebo effect is great and the patient may evaluate the treatment effect as very good.
Confounding Understanding and controlling confounding has a central role in modern epidemiology. It must be separated from a risk factor. For example, age is not a causal risk factor but it is a potential confounding factor in many situations. For an extraneous factor to be a confounder, it must have an effect on the occurrence of disease, but it does not have to be causal. In general
EPIDEMIOLOGY OF SLEEP DISORDERS terms a confounding factor must be associated with both the exposure and the disease. Consider the following equation demonstrating development of a disease: Exposure ! altered physiology (altered body or mental functions) ! disease A variable measuring altered function is a risk factor for disease, and is correlated with exposure, because it results from exposure. However, it is not a confounding factor because the effect of exposure is mediated through the effect of altered physiology (Miettinen, 1985; Rothman, 1986).
Precision and comparability of information: randomized controlled trials Precision refers to the reduction of random error. Precision can be improved by increasing the number of subjects or the accuracy of obtained information. Commonly, errors occur during the process of selecting study subjects. The attendant random error is called sampling error. The best method to gather new valid information about a new treatment is an RCT. In an experimental study, a population is selected for a planned treatment or intervention whose effects are measured by comparing the outcome in the experimental group with the outcome in a control group. To avoid bias, members of the intervention (treatment) group and the control group should be comparable except in the regimen that is offered them (Last, 1983). Allocation of individuals is ideally by randomization. Stratified sampling may be used. In a valid experimental RCT study: 1. 2. 3.
populations are comparable (randomization in RCTs) information is comparable (use of blinding) effects are comparable (use of placebo and/or active comparator treatment).
Standardization and matching After the data are collected, the effect of covariates may be controlled by using various standardizations. Stratification and different standardization methods (direct or indirect standardization) are well described in most books on epidemiology. During the collection of the data matching can be used. However, it is important to avoid overmatching. For example, if we want to study the effects of obstructive sleep apnea syndrome (OSAS) on cerebral circulation we could compare patients with OSAS to patients without OSAS. We select one control subject without OSAS for each patient with OSAS. If we match the subjects (matching of each pair) too strictly, say, for age,
279
gender, body mass index, waist circumference and blood pressure, we risk losing most differences. Instead of matching for all these variables it is often better to analyze the results using potential modifiers and other common risk factors as covariates. One commonly used method is to apply logistic regression analysis. In all cases it is important to work with an experienced epidemiologist or statistician when designing a study.
Population-based rates PREVALENCE Prevalence is defined as the number of instances of a given disease or other condition in a given population at a designated time (Last, 1983). Often, prevalence rates represent cross-sectional events, noted at a single point in time for the state of the group under study (Jenicek and Cle´roux, 1982; Feinstein, 1985). This is called point prevalence. Period prevalence refers to the number of cases that occur during a specified period of time, e.g., 1 year. This is now rarely used. It usually takes some time to conduct a study and find all cases and in such cases it is generally possible to estimate point prevalence (which can be called just “prevalence”). The prevalence rate is given as the number of cases for a specified number of persons in the population (number of cases at a specified time/number of persons in the population at that time). Prevalence focuses on disease status, and should not be confused with incidence.
BAYES
THEOREM
In a clinical setting physicians may estimate the probability that a patient has a defined disease by using the Bayes theorem (Bayes, 1763). If you know the prevalence of the disease in the population, the occurrence rate of a symptom or of a laboratory finding among the diseased and the sensitivity of a diagnostic test one can estimate the occurrence of the disease (prevalence) in that population. According to the Bayes theorem: Probability of the disease ¼ ðsensitivity prevalence of the diseaseÞ=ðprevalence of the symptomÞ: For example, what is the probability that our snoring patient has sleep apnea? We know from the literature that about 90% of patients with OSAS snore (sensitivity). We also know that the prevalence of OSAS among men is about 4% and that about 50% of adult men, similar to our patient, snore at least sometimes. Hence the probability of OSAS in our patient is (0.9 0.04)/ 0.5 ¼ 0.072 ¼ 7.2%.
280
M. PARTINEN
INCIDENCE Incidence (I) has a focus on new events while prevalence focuses on disease status. Incidence rates represent longitudinal events, noted in the follow-up of a cohort. It is defined as the number of instances of illness commencing, or of persons falling ill, during a given period of time in a specified (cohort) population (incidence ¼ number of new cases during a specified time period/ number of persons exposed to risk of developing the disease during that time period). Incidence thus refers to the number of new events or new cases in a defined period of time, whereas prevalence refers to the number of existing cases. It is essential to give the time unit that has been used when counting incidence rate. If we know the incidence rate and the average duration of the disease concerned, we can assume that prevalence ¼ incidence duration (D) of the disease (using the same unit of time, e.g., years). More generally (Freeman and Hutchinson, 1980) one can give that prevalence ¼ (I D)/(1 þ (I D)).
MORTALITY
RATES
The mortality or death rate is the proportion of a population who die of a defined cause. The numerator is the number of persons dying, and the denominator is the total population in which the deaths occurred. The unit of time may be one calendar year or a longer period of time. In the field of sleep research, there are only a few studies in which mortality rates have been given. Those studies deal with sleep apnea syndrome. In order to avoid bias arising from disproportions in age, gender, or race between the general (denominator: reference) population and the study population the data are standardized. The indirect method is more popular than the direct method of standardization. As a result standardized mortality ratios can be given. In long-term follow-up studies survival, mortality, and also morbidity figures may be computed using different survival analyses.
RISK
RATIO AND ODDS RATIO
Risk is often used to describe the rate of occurrence of a symptom or disease. Risk refers to the probability that an event will occur within a defined period of time. A risk factor, or determinant of risk, is a causal factor or exposure that increases the probability of occurrence of a specified outcome. Risk ratio or rate ratio is the ratio of risk between two different categories of a risk factor, which is also called a determinant. In the case of a rare disease, the risk ratio approximates the odds ratio (OR). Instead of risk ratio, the OR (cross-product ratio) and its 95%
confidence limits are widely used in epidemiological studies. Whenever possible, calculation of rate ratios is recommended because rate ratios are often easier to understand than various statistical tests and P-values. If the lower limit of the 95% CI is greater than 1, the rate ratio is “statistically significant” with a P value less than 0.05, that is, the studied exposure is a “risk factor for the specified outcome.” Similarly, if the upper 95% confidence limit of a rate ratio is less than 1, the factor is “protective.”
NORMALITY
AND USE OF MEDIANS
What does “normal” mean in epidemiology? Sir Ronald Fisher regarded 95% of the inner values of a distribution as common and the remaining 5% as significantly uncommon. The outer 5% of values is traditionally considered abnormal, but statistical or epidemiological theory does not support this view. According to Feinstein (1985), “Fisher’s proposed boundary of uncommon occurrences was intended for inferential decisions about P-values, not for descriptive decisions about normality. Nevertheless, after years of exposure to 0.05 as the magic level of stochastic significance, many clinicians have become thoroughly conditioned to accept the same boundary marker for “abnormality.” Many laboratories now use the term “customary range” instead of normal range. This term is more appropriate. It is also good for patients whose laboratory values fall outside the customary range, because the values may be without any clinical significance even if they are outside the customary range. Biological data do not always fit the normal gaussian curve. The distributions are often significantly skewed, bimodal, too tall, or too short. On such occasions, the usual mean 2 standard deviations tactics are not appropriate. Unfortunately it is still used in medical literature. For example, you can read that the mean ( standard deviation) weight of children was 10 12 kg. How does a child look if his/her weight is –2 kg (10 – 12 ¼ –2)? Patients can have negative cholesterol or negative apnea index (AI) values if researchers give means and standard deviations alone. Providing the CI and range gives more information. In biological sciences and medicine, the use of medians (the “middle value”) and percentiles, even without means, is often better. The median is easy to calculate and describes the population better than the mean. It divides the population into two equal parts. To find the inner 95% of the data, we need only locate the 2.5 and the 97.5 percentile point. The procedure is simple, and by using it we will never encounter impossible ranges.
EPIDEMIOLOGY OF SLEEP DISORDERS
MEASURES
OF EFFECT SIZE
Different measures may be used to evaluate the results of interventions and clinical trials. Three measures are commonly used in evidence-based meta-analytical studies: (1) relative risk reduction (RRR); (2) absolute risk reduction (ARR); and (3) the number needed to treat (NNT). Let us take two examples. (1) Suppose that in a prospective follow-up study 10% of subjects treated with continuous positive airways pressure (CPAP) had a new cardiovascular event versus 20% among the nontreated. These rates are also called risks of having a defined event; in other words, risk can be thought of as the rate of a defined outcome. (2) Suppose that in a randomized clinical trial on RLS, 70% of those with the active drug had significant improvement of their symptoms versus 30% in the placebo control group. In the same study 1% of those with active treatment and 0.3% of those with placebo had hallucinations as an adverse effect.
RELATIVE
RISK REDUCTION
Relative risk measures how much the risk is reduced in the treatment group compared to the control group. In the first example above, 20% of the control group had a cardiovascular event compared to 10% among those treated with CPAP. The CPAP treatment would have had a 50% (0.5) RRR. The formula is: RRR ¼ (CER – EER)/CER, where CER is the control group event rate and EER is the experimental group event rate. In the second example, the RRR of having hallucinations when using a placebo instead of the experimental treatment is 70%, i.e., (1 – 0.3)/1. As we can see, the RRR is not a good indicator if the occurrence of an event is rare.
ABSOLUTE
RISK REDUCTION
ARR is the absolute difference in outcome rates between the control and treatment groups, i.e., ARR ¼ CER – EER. The ARR does not confound the effect size with the baseline risk. In the first example above, ARR is 10% (20% – 10% ¼ 10%). In the second example, ARR for hallucinations is 0.7% (1 – 0.3) when using placebo. This figure is very small and easier to interpret than the large and not clinically significant RRR of 70%. The ARR for having improvement of symptoms in this example is 70% – 30% ¼ 40%.
NUMBER
NEEDED TO TREAT
Because the ARR is sometimes difficult to interpret, better indicators are needed. The number of patients needed to treat in order to find a significant effect
281
(e.g., cure, significant improvement of symptoms) is a good indicator of a treatment effect (Cook and Sackett, 1995). The NNT is simply another way to express ARR. NNT ¼ 1/ARR and it is the number of patients that would need to be treated to prevent one additional bad outcome. For the example of CPAP above, the NNT is 10 (1/0.1) and for the second RLS example, the NNT is 1/0.4 ¼ 2.5. Thus in the first example 10 need to be treated and in the second example only 3 patients need to be treated. The number needed to have hallucinations, i.e., the number needed to harm (NNH) is in the second example 143 (1/0.007¼ 142.8). If we compare 3 patients to 143 patients we can clearly see that the benefits are much larger than harms in this respect. Of course all other adverse effects must be taken into account when the NNH is estimated. If the NNT is still larger than the NNH then the treatment could be used. It is interesting to note at this point that the NNT chronic insomniac patients in a meta-analytic study of Glass et al. (2005) was 13 but the NNH was more than twice smaller (NNH ¼ 6). This means that the probability of doing harm to a patient was larger than that of doing good. The NNT can be converted to an NNT for a given patient by estimating that patient’s susceptibility relative to an average control patient in a trial report, and dividing the reported NNT by this fraction F. For example 2 above, if a physician’s 80-year-old patient is judged to be three times as susceptible as the average control patient to have hallucinations, the F ¼ 3 and NNT/F ¼ 143/3 ¼ about 48. This means that the physician could still think about treating the patient with that drug if there is significant evidence of its effectiveness in patients above 80 years of age. The NNT can also be computed from the OR and control group rate of events. Also 95% confidence limits for the NNT should be given. Different tables and formulas exist in many statistical packages and on the internet, e.g., by searching “number needed to treat” using Google.
EFFECT
SIZE
Effect size is commonly used as an index to measure the magnitude of a treatment effect. Unlike significance tests and P-values, indices like effect size are independent of sample size. Effect size measures are especially used in evidence-based meta-analytical studies that summarize the findings from a specific topic. Effect size (ampleur d’effet in French) is computed most commonly as the standardized difference between two means. Originally Cohen (1988) defined effect size d as the difference between the means, M1 – M2, divided by standard deviation, s, of either group 1 or group 2, i.e.: Effect size d ¼ ðM1 M2 Þ=s:
282 M. PARTINEN This can be done if the two groups are homogestudents reported less than 6.5 hours of night sleep, neous, and in clinical practice to get a quick idea about and 13.4% reported more than 8.5 hours (Webb, the effect size (Cohen, 1988). Usually the means 1970). In Scotland 2446 subjects aged over 15 were between the intervention (experimental) group and questioned. Of the older subjects in the age group control group is subtracted so that we can obtain a pos65–74 years, 18% complained of waking up before itive difference means improvement and negative dif5 a.m. The percentage decreased to 12% after the age ference means deterioration. To be more correct, the of 75. Disturbed sleep was reported by less than 10% pooled standard deviation, spooled, is used giving d ¼ of men aged 15–64. In the age group 65–74 years, (M1 – M2) / spooled (Rosnow and Rosenthal, 1996). disturbed sleep was a complaint in 25% of men. The pooled standard deviation is found as the root In women the respective percentage was 43% (McGhie mean square of the two standard deviations. Modern and Russell, 1962). In one classic study from 1979, statistical programs usually automatically compute Bixler et al. determined the prevalence of sleep disorthe pooled standard deviations. That is, the pooled ders among 1006 households in the Los Angeles metrostandard deviation is the square root of the average politan area. The prevalence of past or current insomnia of the squared standard deviations. When the two stanwas 42.5%. The prevalence of current insomnia was dard deviations are similar the root mean square will 32.2%, and 7.1% complained of excessive sleep. not differ much from the simple average of the two variances.
Insomnia
EPIDEMIOLOGY OF SLEEP DISORDERS The oldest epidemiological studies on sleep length are from the end of the 18th century. Among the most respected studies were those by Clement Dukes (1905) from England on the young children’s need for sleep. Other well-known early studies are those by Hertel from Denmark, Bernhard from Germany, and Clapare`de from France (Clapare`de, 1905). About 80–100 years ago, young children slept 10.5–13.5 hours, 15-year-olds slept 9–10 hours, and adults slept between 7 hours 25 minutes and 8 hours 23 minutes (Camp, 1923; Laird, 1931). These figures do not differ significantly from present-day figures of healthy adults having an average sleep length between 7 and 8 hours. Women slept slightly longer than men, except in the case of mentally retarded subjects when the situation was reversed (Ladame, 1923; Barry and Bousfield, 1935). Sleep disturbances increased with age, as they do at present. In Laird’s study from 1931, at age 25, about 10% of men were not satisfied with their sleep. At age 95, everybody reported some wakefulness each night. In the same study more than 70% of men reported some difficulty in going to sleep, and more than 40% reported nightly awakenings. Different methods were used to help subjects to sleep. Reading was used by 25%, and 18% used relaxation techniques. Three percent of men used drugs to help them sleep. Two percent used alcohol to help them to sleep (Laird, 1931). The latter two figures differ significantly from those of present days. Many epidemiological studies have been done on sleeping habits since 1960. In these studies the average length of sleep varies between 7 and 8 hours. In a questionnaire survey 7.4% of 1278 University of Florida
Transient insomnia is very common. In one study 54% of adult men and 61% of adult women suffered from insomnia at least sometimes during the past 3 months (Urponen et al., 1988). In the same study 5.3% of men and 7.2% of women took hypnotics at least once during the past 3 months. In a more recent study 36.2% of subjects older than 14 years of age complained of insomnia symptoms at the time of interview (Ohayon et al., 1997a). This figure is very close to the classic figure of one study of Bixler et al. (1979), where 32.2% of adults had a current problem with sleep. Chronic insomnia is common. In Finland about 2% of adult, 36–50-year-old men and 7% of women complained of chronic insomnia (Urponen et al., 1988). In a French study by Ohayon (1997), 12.7% of the subjects currently had insomnia complaints with daytime consequences that had lasted for at least 1 month. Taking existing evidence together, about 2–18% of adults usually complain of clinically significant persistent insomnia depending on the definition of insomnia and of the population. On average one can say that about 10% of middle-aged adults suffer from longstanding insomnia (Bixler et al., 1979, 2002; Lack et al., 1988; Liljenberg et al., 1988; Hohagen et al., 1991; Rosekind, 1992; Henderson et al., 1995; Ohayon, 1996, 1997, 2005; Yeo et al., 1996; Ohayon et al., 1997b; Tachibana et al., 1998; Kim et al., 2000; Ohayon and Partinen, 2002; Becker, 2006). Insomnia increases with age up to the age of about 65. About one-third of subjects older than 65 years have chronic insomnia. In very old age the figures may be lower (Henderson et al., 1995; Morgan and Clarke, 1997). In an Australian study insomnia was persistent in 16.2% of the community-dwelling population and in 12.2% of institutional residents. Altogether
EPIDEMIOLOGY OF SLEEP DISORDERS 14.5% of elderly subjects living in the community used hypnotics regularly while the corresponding percentage was 39.7 among institutionalized subjects (Henderson et al., 1995). In a large US Pennsylvanian study (Bixler et al., 2002), the prevalence of insomnia was 7.5% and the occurrence of difficulty sleeping was an additional 22.4%. Insomnia complaints were more frequent in women and in non-Caucasian minorities. Depression was the strongest risk factor followed by female gender. The fact that the aging process per se is not the primary cause of insomnia among elderly people is supported by a 3-year longitudinal study (Foley et al., 1999). Altogether 6899 men and women aged 65 and older participated. Data included self-reported symptoms of insomnia, physician’s diagnosis of heart disease, stroke, cancer, diabetes, or hip fracture, selfreport of physical disability, depressive symptoms, health status, and use of medications. Nearly 15% of the 4956 participants without complaints of insomnia at baseline reported chronic difficulty falling asleep or early-morning arousal at follow-up, suggesting an annual incidence rate of approximately 5%. Incident insomnia was associated with depressed mood, respiratory symptoms, fair to poor perceived health, and physical disability. In multivariate analyses, these risk factors explained the higher incidence of insomnia among those with medical conditions such as heart disease, stroke, and diabetes. Other factors associated with an increased risk of insomnia included use of sedatives, and widowhood. Only 7% of the incident cases of insomnia occurred in the absence of associated risk factors. Of the nearly 2000 survivors with chronic insomnia at baseline, almost 50% did not report any symptoms after 3 years. They reported that their self-perceived health had improved compared to those who continued to report insomnia symptoms. Because the vast majority of incident cases of insomnia were among persons with one or more of risk factors other than aging, these data do not support a model of incident insomnia caused by the aging process per se (Foley et al., 1999). Insomnia is more common among women than men. Insomnia occurs 1.4–2 times more often in women than in men. The prevalence and incidence of insomnia are much higher among menopausal and postmenopausal women compared with middle-aged men. In a community-based sample of 301 perimenopausal women, aged between 35 and 55, the most common symptoms were dysphoric mood; vasomotor, somatic, and neuromuscular symptoms; and insomnia (Mitchell and Woods, 1996). In one Japanese study the prevalence of insomnia was 17.3% in men and 21.5% in women. Difficulty initiating sleep was
283
complained of by 8.6% of Japanese men and 16.2% of women (Doi et al., 2000).
SEASONAL
DIFFERENCES OF INSOMNIA
The occurrence of insomnia may vary depending on the season. The results from the Nordic countries agree with each other (Husby and Lingjaerde, 1990; Ohayon and Partinen, 2002). In northern Norway 41.7% of women and 29.9% of men had occasional insomnia. In general complaints of insomnia are more common during winter than during other times of the year. The reasons for this cannot be explained by the season (darker, colder climate, more rain or snow). Work and different lifestyle factors probably explain most of the variance, but we lack good evidence. In the Troms study, the occurrence of insomnia during summer (summer insomnia) decreased with age, whereas the other seasonal types of insomnia increased with age (Husby and Lingjaerde, 1990).
INSOMNIA
IN DIFFERENT OCCUPATIONS
The occurrence of sleeping problems varies by occupation and working times (Partinen et al., 1984; Ohayon, 1996; Ha¨rma¨ et al., 1998; Inoue et al., 2000). In a questionnaire survey of 6268 adults representing 40 different public sector occupations, 18.9% of bus drivers complained of having rather or very much difficulty falling asleep. Among male directors and physicians, the respective percentages were 3.7% and 4.9%. Disturbed nocturnal sleep was complained of most often by male laborers (28.1% waking up at least three times a night) and female cleaners (26.6%). Disturbed nocturnal sleep was rare among male physicians (1.6%), male directors (7.4%), female head nurses (8.9%), and female social workers (9.4%) (Partinen et al., 1984).
PSYCHIATRIC
DISORDERS AND INSOMNIA
The association of depression and other psychiatric disorders with insomnia is well known. Primary insomnia and insomnia related to mental disorders are the two most common DSM-IV insomnia diagnoses (Ohayon, 1997). The differential diagnosis may sometimes be difficult. In one study 216 patients with insomnia were interviewed by one sleep specialist and one nonsleep specialist. Using DSM-IV criteria 99 (46%) were diagnosed as having insomnia related to mental disorders, and 48 (22%) were diagnosed as having primary insomnia. A psychiatric disorder was rated as a contributing factor for 77% of patients with a first diagnosis of primary insomnia. In a large US community survey, the prevalence of insomnia uncomplicated by psychiatric disorders was
284 M. PARTINEN 4.9% (Weissman et al., 1997). Among those with compliPartinen, 1997; Larsen and Tandberg, 2001; Kumar cated insomnia in the past year, 25% had major depreset al., 2002; Brotini and Gigli, 2004; Thorpy and Adler, sion, 19% abused alcohol, 12% had dysthymia, 9% had 2005; Gjerstad et al., 2007) and dementia (Thorpy, panic disorder, 8% abused drugs, 8% had schizophrenia, 1990; Bliwise, 2004; Paavilainen et al., 2005) are typical and 2% had somatization disorder (Weissman et al., examples. Sleep disorders occur in over 70% of 1997). In a World Health Organization collaborative patients with idiopathic Parkinson’s disease, adversely study, 25 916 primary health care patients were evaluaffecting their quality of life. Among patients with ated. Sleep problems were present in 27% of patients. Parkinson’s disease sleep disruption takes the form of Of the patients with insomnia, 51% had a mental disorsleep fragmentation with frequent and prolonged awader diagnosis according to International Classification kenings and daytime sleepiness. Nocturia, difficulty in of Disease, 10th revision: this was mainly depression or turning over in bed, painful leg cramps, vivid dreams anxiety, abuse of alcohol, or a combination of different and/or nightmares, back pain, limb/facial dystonia, psychiatric disorders. Forty percent of insomniacs and leg jerks are the main causes of nocturnal awakenreported using alcohol and over-the-counter medications ings in Parkinson’s disease patients. Sleep disturbance to help them sleep (Costa e Silva et al., 1996). gradually worsens with disease progression, suggesting Unemployment, being unmarried, separated, or that it is related to the severity of the disease. Sleep widowed was associated with higher prevalence of disturbance may also be a complication of chronic insomnia complaints in Japan as well as in other levodopa therapy. In a survey of 100 Parkinson’s discountries (Doi et al., 2000). Different psychological ease patients, significant sleep complaints were found complaints as well as psychological stress were assoin 74%. Sleep complaints were unrelated to patient ciated with a higher prevalence of insomnia (Janson age and the duration of disease but increased in prevaet al., 1996; Yeo et al., 1996; Ohayon, 1997; Ohayon lence with longer periods of levodopa therapy. Sleep et al., 1997b; Tachibana et al., 1998; Kim et al., 2001; abnormalities tended to increase in severity with Ohayon and Partinen, 2002; Doghramji, 2006). Sympcontinued treatment of Parkinson’s disease. Dyskinetic toms of work-related stress and mental exhaustion are side-effects and on-off syndrome occur as well in associated with insomnia. Simple methods, such as the patients with or without sleep complaints, but up to five-item version of the Mental Health Index and other 98% of patients experiencing psychiatric side-effects questions, may be used to screen workers with mental also report sleep disruption (Nausieda et al., 1982). health and sleep problems effectively (Berwick et al., The correlation with sleep disturbance and severity 1991; Kuppermann et al., 1995; Doi et al., 2000). of Parkinson’s disease is also found in other studies. Insomnia is a risk factor for depression and other In an Indian case-control study, 149 Parkinson’s disease mental disorders. Breslau and collaborators (1996) have patients and 115 age-matched healthy controls were followed subjects with or without insomnia for about asked about sleep disturbances using a questionnaire. 3 years. The gender-adjusted relative risk for new onset Sleep problems were seen in 42% of the Parkinson’s of major depression during the follow-up period disease patients and 12% of controls. The sleep disturin subjects with history of insomnia at baseline was bances were: insomnia in 32% versus 5% of controls; 4.0 (95% CI 2.2–7.0). When history of other previous nightmares 32% versus 5%. Excessive daytime sleepidepressive symptoms (e.g., psychomotor retardation ness was complained of by 15% versus 6%. All sleep or agitation, suicidal ideation) was controlled for, complaints were statistically more common in Parkinprior insomnia remained a significant predictor of son’s disease patients compared to controls and corresubsequent major depression. In a meta-analytic study lated with increased severity of disease (Kumar et al., consisting of 20 published studies and more than 2002). 20 000 insomniac subjects older than 50 years, the In a follow-up study 142 of the initial 231 patients pooled OR of sleep disturbances for depression was were re-evaluated after 4 years and 89 patients after 2.6 (1.9–3.7) (Cole and Dendukuri, 2003). Such findings 8 years (Gjerstad et al., 2007). Complaints of insomnia imply that complaints of chronic insomnia are a useful remained almost constant while problems related to marker of increased risk of depression. turning in bed and vivid dreaming and/or nightmares increased during the follow-up. Insomnia was present in 54–60% of the patients at each of the three study visINSOMNIA AMONG PATIENTS WITH NEUROLOGICAL its. Insomnia was related to disease duration, depresAND OTHER SOMATIC DISEASES sion, and female sex (Gjerstad et al., 2007). As in many Parkinson's disease and dementia. Many neurological other studies, depression was common in Parkinson’s disorders are associated with disturbed sleep and disease patients, and contribution to sleep disturbances insomnia. Parkinson’s disease (Nausieda et al., 1982; must always be taken into account (Partinen, 1997).
EPIDEMIOLOGY OF SLEEP DISORDERS Stroke and insomnia. Insomnia is a frequent complaint among patients with stroke, and disturbed sleep may also be a risk factor of stroke or an indicator of some other underlying process, which may be either a causative factor for stroke, or associated with stroke. Poststroke depression is one such factor, but it does not explain everything. A sample of 277 stroke patients aged 55–85 had a psychiatric evaluation 3–4 months after ischemic stroke. In all, 56.7% reported some type of insomnia complaint and 37.5% fulfilled the DSM-IV criteria of insomnia. In 38.6%, insomnia complaint or insomnia had started before the stroke and in 18.1% it started after the occurrence of the stroke. Insomnia complaints were correlated with increased disability (measured by Barthel index), dementia, anxiety, and higher use of psychotropic drugs (Leppa¨vuori et al., 2002). In the Caerphilly cohort in south Wales, 1986 men aged 55–69 completed a questionnaire on sleep patterns with help from their partners. They were asked about symptoms of disturbed sleep, including insomnia, snoring, restless legs, OSAS, and complaints of daytime sleepiness. During 10 years of follow-up 107 men experienced an ischemic stroke and 213 had an ischemic heart disease event. About one-third of the men reported at least one symptom suggestive of sleep disturbance, and one-third reported daytime sleepiness. Compared with men who reported no such symptoms, the age-adjusted relative risk of an ischemic stroke was significantly increased in men with any sleep disturbance. The strongest association was with symptoms indicating sleep apnea (OR 1.97; 1.26–3.09) (Elwood et al., 2006). Other neurological and somatic disorders. Most subjects with mental retardation complain of some type of sleep disturbance (Hoban, 2000; Lindblom et al., 2002). Insomnia is frequent among many other somatic patients, including patients with different respiratory diseases (Dodge et al., 1995; Janson et al., 1996). In a study by Dodge et al. (1995), the prevalence of insomnia was 31.8–52.4% among adults with cough, dyspnea, or wheezing. Among adults without respiratory symptoms the prevalence was about 26%.
Is anticipation of coming health-related events possible with follow-up of sleeping pattern and sleep/wake rhythm? There is evidence that chronic insomnia is a risk factor of mental disorders (Breslau et al., 1996; Cole and Dendukuri, 2003). There is also evidence that sleep disturbances may precede cardiovascular disease, and chronic sleep deprivation is associated with an increased risk of type 2 diabetes and metabolic
285
syndrome (Hyyppa¨ and Kronholm, 1989; Foley et al., 1999; Janson et al., 2001; Agras et al., 2004; Flier and Elmquist, 2004; Phillips and Mannino, 2005; Vorona et al., 2005; Gottlieb et al., 2006). There is evidence that REM sleep behavioral disorder may be a preexisting symptom of a future synucleinopathy (Schenck et al., 1996; Montplaisir, 2004; Boeve and Saper, 2006; Postuma et al., 2006), and there is some evidence that in dementia disappearance or reversing of the day/night rhythm is associated with severity of dementia. For many reasons there is a need to develop unobtrusive methods for long-term monitoring of sleep/wake and circadian activity patterns among neurological patients and among elderly people both in nursing homes and at home. Our group has monitored, using a small wrist-worn intelligent watch, demented and nondemented subjects living in a nursing home, and analyzed how changes in measured sleep correlated with the subjective assessment of sleep quality, daytime alertness, use of medications, and health. The activity signal data together with subjective assessments of sleep quality and daytime vigilance were collected from 42 volunteers (56–97 years: 23 demented and 19 nondemented) for at least 10 days. The demented subjects had lower daytime activity and higher nocturnal activity than the nondemented subjects. Correlations between the activity parameters and self-assessments were weak but statistically significant. We also found a correlation between functional ability and diurnal activity (Paavilainen et al., 2005).
SLEEP LENGTH: NATURAL SHORT AND LONG SLEEPERS Several studies have shown that the average length of sleep among adults is between 7 and 8 hours. Healthy adults who sleep less than 6 or 6.5 hours per night are called “natural short sleepers” and those sleeping more than 9.5 hours of sleep “natural long sleepers” (Webb and Friel, 1971; Hartmann et al., 1972; Hublin et al., 1996; Liu et al., 2000). In a cross-sectional study of 5419 adult men, a higher prevalence of diagnosed myocardial infarction was found among those who slept more than 9 hours, whilst those sleeping less than 6 hours per night had a higher occurrence of symptomatic coronary heart disease. This relationship remained after controlling for age, sleep quality, use of sleeping pills and tranquilizers, smoking, alcohol use, type A score, neuroticism, use of cardiovascular drug, and arterial hypertension (Partinen et al., 1982). Based on the American Cancer Society data, Kripke et al. (1998) published several studies showing a relationship between short sleep and mortality, although more recently these authors wrote, again based on the same
286 M. PARTINEN patient population, that sleeping more than 8 hours or women). Almost half of those with insufficient sleep less than 6 hours increased mortality hazard as comat baseline still had it 9 years later, showing that the pared to sleeping 7 hours per night (Kripke et al., problem is often chronic. One-third of the liability to 2002). chronic insufficient sleep was attributed to genetic In Gifu, Japan, a cohort of 5322 has been followed influences (Hublin et al., 2001). for longer than 11 years. Both longer and shorter sleep, compared to 7–8-hour sleep, were related to signifiDAYTIME SLEEPINESS cantly increased risk of total mortality in men but not Prevalences of daytime sleepiness are shown in in women (Kojima et al., 2000). Also other crossTable 18.1. Depending on the study and wording, the sectional and prospective follow-up studies have shown occurrence varies from very small (0.3%) to more than that sleeping more or less than 7–8 hours per night is 30% (Table 18.1). As an average the prevalence is associated with increased hazard of mortality and also between 5% and 15%. of cardiovascular morbidity (Partinen et al., 1982; Sleepiness may be interpreted differently in different Spiegel et al., 1999; Verkasalo et al., 2005; Gangwisch languages. For example, the English word sleepiness is et al., 2006; Kohatsu et al., 2006; Bjo¨rvatn et al., defined in the Random House Unabridged Dictionary 2007; Knutson et al., 2007). In the population-based and the Scribner-Bantam Dictionary as “inclined to FIN-D2D survey, 1336 men and 1434 women aged sleep, drowsy,” and in Stedman’s Medical Dictionary 45–74 participated (Tuomilehto et al., 2008a). There as “an inclination to sleep.” Synonyms for “sleepy” was an independent association between abnormal include the words tired and somnolent. Fatigue is a much sleeping times and type 2 diabetes in middle-aged more general term describing, according to Stedman’s, a women. Even after adjustments for age, body mass state of lessened capacity for work and reduced effiindex, sleep apnea probability, smoking, physical activciency of accomplishment, usually accompanied by a ity, and medication affecting the central nervous sysfeeling of weariness, sleepiness, or irritability (Pugh, tem, sleep duration of 6 hours or less or 8 hours or 2000). A more original description of fatigue is found longer was independently associated with type 2 diabein the highly appreciated French Dictionnaire illustre tes. Interestingly, there was no increase in the prevades termes de medecine by Garnier and Delamare lence of diabetes in middle-aged men with abnormal (Garnier and Delamare, 2009), where fatigue is defined sleeping times. In conclusion, short (6 hours or less) as “a state resulting from prolonged activity of an or long (8 hours or more) sleep duration is related to organ or system. It is translated as decrease of function an increased risk of type 2 diabetes in middle-aged and a particular sensation (feeling of fatigue) which is women but not in men (Tuomilehto et al., 2008a). specific to each organ. The aim of training is to retard Lack of sleep is the most common cause of daytime the apparition of fatigue.” Tiredness comes from the fatigue and sleepiness. Lack of sleep may be due to word tired, which is a synonym for weary, wearied, poor sleep with nocturnal awakenings, too short sleep, exhausted, fatigued, jaded, and bushed. Tiredness is a or to some other cause. The lack of sleep may be due more general term and fatigued implies, according to to “bad habits,” or to a discrepancy between biological the American Heritage Dictionary, “great, though not and social circadian rhythms, or to some psychic or necessarily complete or nearly complete expenditure of somatic pathology. In a Japanese study (Liu et al., physical or mental power.” In the Random House 2000) among 3030 adults aged 20 or more, 29% slept Unabridged Dictionary, “tired” suggests a condition in less than 6 hours per night, and 23% reported having which a large part of one’s energy and vitality has been insufficient sleep. Short sleep duration was the stronconsumed. If you are “tired,” you have used up a considgest predictor of excessive daytime sleepiness (Liu erable part of your bodily or mental resources. If you are et al., 2000). Similar figures have been found in “fatigued,” you have consumed energy to a point where Europe and the USA (Bonnet and Arand, 1995; you need to rest and sleep. All in all, sleepiness is probaBroman et al., 1996; Liu et al., 2000; Hublin et al., bly a good term to describe the inclination to sleep or 2001). In Sweden 12% of adults had persistent chronic tendency to fall asleep. sleep loss; 50% of them also reported other concomiSleep-related breathing disorder is the second most tant sleeping difficulties. In subjects without sleeping common reason for excessive daytime sleepiness difficulties, the most common cause of insufficient among adults after lack of sleep (Hublin et al., 1996; sleep was too little time for sleep (Broman et al., Liu et al., 2000). The use of hypnotic agents, other 1996). In another study the prevalence of insufficient sleeping difficulties, and irregular sleep–wake schedsleep, defined as a difference of at least 1 hour ule are also related to daytime sleepiness. In most sleep between reported need of sleep and obtained sleep laboratory populations, more than 75% of patients length, was 20.4% (16.2% in men and 23.9% in
Table 18.1 Occurrence (%) of daytime sleepiness Size (n)
Population; age
Definition of sleepiness
Methods
Percentage
Sleeping too much Karacan et al., 1976 Bixler et al., 1979 Ford and Kamerow, 1989
1645 1006 7954
General population; 18–70 years General population; 18–80 years Population sample; 18–65þ years
Too much sleep Sleeping too much Over a period of 2 weeks or longer sleeping too much
Questionnaire Questionnaire Direct structured interview using Diagnostic Interview Schedule
0.3 7.1 (current 4.2) 2.8 (M), 3.5 (W)
Falls asleep at work
Questionnaire
6.4
Involuntary sleep attacks daily or almost daily Daily sleep episodes Falling asleep during the day Sleeping during lessons often or always Most of the time sleepy, forcing the individual to take a nap Becoming uncontrollably sleepy so that can’t help falling asleep Chance of dozing; ESS >10
Phone interview
3.4 (M), 2.5 (W)
Questionnaire Questionnaire Questionnaire (both subject and parents) Interview
4.9 12 3 (B), 0 (G)
Interview
ESS 10
Questionnaire including the validated ESS Questionnaire
18.9 (no gender difference) 10.9 (no gender difference) 13
ESS > 10
Questionnaire
22.6
Involuntary sleep attacks, sleeping episodes, irresistible sleep, chance of dozing Partinen, 1982 2537 M Army draftees before military service; 17–29 years Partinen and Rimpela¨, 2016 Population sample; 15–64 years 1982 Billiard et al., 1987 58 162 M Army draftees; 17–22 years Klink and Quan, 1987 2187 Population sample; 18–64 years Saarenpa¨a¨-Heikkila¨ et al. 574 Schoolchildren 7–17 years (1995) Hays et al., 1996 3962 Population sample; 65–85 þ years Ganguli et al., 1996
1050
Population sample 66–97 years
Johns and Hocking, 1997
331
Australian workers 22–59 years
Schmitt et al., 2000
668
Melamed and Oksenberg, 2002 Kaneita et al., 2005
532 28 714
Working population: post office clerks Nonshift industrial workers; mean age 46.3 7.6 years General Japanese population; 20–70þ years
Pallesen et al., 2007
2301
Population sample; 18–90 years
Do you fall asleep when you must Questionnaire not sleep (for example, when you are driving a car)? ESS > 10 Telephone interview
25.2
EPIDEMIOLOGY OF SLEEP DISORDERS
Study
2.8 (M), 2.2 (W)
17.7 Continued
287
288
Table 18.1 Continued Study
Size (n)
Population; age
Excessive daytime sleepiness, sleepiness, feeling sleepy during daytime Partinen, 1982 2537 M Army draftees; 17–29 years
2016 5713
Population sample; 15–64 years Population sample; 3–94 years
Berg Kelly et al., 1991 Martikainen et al., 1992
3543 1190
Students; 13–18 years Population sample; 36, 41, 46, 50 years categories
Saarenpa¨a¨-Heikkila¨ et al. (1995) Janson et al., 1996
574
Schoolchildren 7–17 years
2394
Population sample; 20–44 years
Hublin et al., 1996
11 354
Population sample; 33–60 years
Ohayon et al., 1997d
4952
Population sample; 15–100 years
Ohida et al., 2004
106 297
Japanese adolescents; 12–19 years; junior and senior high schools
ESS: Epworth Sleepiness Scale; M: man; W: woman; B: boy; G: girl.
Methods
Percentage
A. Do you often feel sleepy during the daytime? B. Are you more sleepy than your friends or workmates? Sleepier than fellow people Sleepiness independent of meal times Tiredness Tiredness/sleepiness (more tired than fellow people; or daily compulsory desire to sleep; or feeling tired every day) Daytime sleepiness always or often
Questionnaire
A. 35.8 B. 9.5
Phone interview Direct interview
10 (M), 14 (W) 8.7
Questionnaire Questionnaire
29.3 6.9 (M), 12.0 (W)
Questionnaire (both subjects and parents) Questionnaire
20 (B), 22 (G)
Feeling drowsy in the daytime 3 times per week Daytime sleepiness daily or almost Questionnaire daily Feeling sleepy during the day on a Telephone interview using the Sleep-Eval system daily basis for at least 1 month: a lot or greatly (severe sleepiness) or moderately (moderate sleepiness) Do you feel excessively sleepy Questionnaire during the daytime?
16.0 6.7 (M), 11.0 (W) Severe: 4.4 (M), 6.6 (W); moderate 15.2
33.3 (B), 39.2 (G)
M. PARTINEN
Partinen and Rimpela¨, 1982 Lugaresi et al., 1983a
Definition of sleepiness
EPIDEMIOLOGY OF SLEEP DISORDERS with daytime sleepiness have sleep-related breathing disorders (most commonly OSAS), 20% have narcolepsy, and 5% have restless legs, periodic movements in sleep, or other sleep disorders. This does not reflect the distribution in the general population, where insufficient and/or poor quality of sleep explains most cases of sleepiness.
NARCOLEPSY The prevalence of narcolepsy varies in most populationbased studies between 21 and 56 per 100 000 persons (Solomon, 1945; Honda, 1979; Franceschi et al., 1982; Partinen, 1982; Honda et al., 1983; Wilner et al., 1988; Martikainen et al., 1992; Tashiro et al., 1992; al Rajeh et al., 1993; Hublin, 1994; Hublin et al., 1994a, b; Wing et al., 1994, 2002; Ohayon et al., 1996, 2002; Ondze´ et al., 1998; Silber et al., 2002). The published population-based studies are shown in Table 18.2. Other studies have been done, but the sampling has been for example by newspaper advertisements and TV programs and these studies do not represent well-defined population samples. In addition there are many unknown assumptions in some of the early studies and therefore these are not included in the table (Roth et al., 1968; Dement et al., 1972; Dement et al., 1973; Ohayon et al., 2002). The highest figures, around 160 or up to 590 per 100 000, are from Japan (Honda, 1979; Honda et al., 1983; Tashiro et al., 1992). The lowest frequency, 0.23 per 100 000 population, is found in Israel (Lavie and Peled, 1987; Wilner et al., 1988). A simple screening method called the Ullanlinna Narcolepsy Scale (UNS) has been developed and validated (Hublin et al., 1994a). The UNS consists of 11 items assessing cataplexy-like symptoms and tendency to fall asleep. The score varies from 0 to 44 and the cut-off point for diagnosing narcolepsy is 14. Using the UNS the prevalence of narcolepsy with cataplexy was 26 per 100 000 population in adult Finns (Hublin et al., 1994b). Very similar figures have been published from Hong Kong. Using the validated Chinese version of UNS the prevalence rate of narcolepsy among southern Chinese was 34 per 100 000 (95% CI: 10–117). In Hong Kong all narcoleptic subjects were HLA DRB1-1501-positive and 50% were DQB1-0602positive (Wing et al., 2002). Using the same methodology the prevalence among Korean students is around 15 per 100 000 (Shin et al., 2008). Cataplexy is one of the core symptoms of narcolepsy, but occasional cataplexy-like attacks may occur also in healthy subjects. Among young men 16.5% experience at least sometimes sudden weakness in some muscle groups that are associated with emotions.
289
A total of 3.7% of young men had experienced such cataplexy-like symptoms often or almost often during the past month (Partinen, 1982). In another study 29.3% of the people reported (at least once during his or her lifetime) feelings of limb weakness associated with emotions (Hublin et al., 1994b). If this is considered as evidence of cataplexy and combined with the occurrence of daytime sleep episodes at least 3 days per week, 6.5% of the population would have narcolepsy according to the minimal diagnostic criteria for narcolepsy of the International Classification of Sleep Disorders (ICSD: American Academy of Sleep Medicine, 2005). Clinical, polysomnographic, and cerebrospinal fluid examinations of hypocretin allow more exact diagnosis and more precise occurrence rates (Nishino et al., 2001; Scammell et al., 2001; Taheri et al., 2002; Bassetti et al., 2003; Dauvilliers et al., 2003a; Oka et al., 2006). There are some interesting associations with time of birth and narcolepsy. In southern China an excess of winter births has been found in subjects with narcolepsy-cataplexy (Wing et al., 2008). In a large multicenter (Montpellier, Montreal, Stanford) study birth dates of 886 patients with a clear-cut diagnosis of narcolepsy with cataplexy were compared with birth dates of the comparative general populations. The birth rate of narcoleptic patients was highest in March (OR 1.45) and lowest in September (OR 0.63 compared to general population). No gender or country of origin differences were observed (Dauvilliers et al., 2003b).
SNORING AND SLEEPAPNEA Habitual snoring Snoring is an inspiratory noise caused by vibration of the soft upper-airway tissues, mainly soft palate and posterior faucial pillars. Snoring corresponds to partial obstruction of the upper airways, and complete obstruction is followed by an apnea. Almost everybody snores sometimes especially when sleeping in a supine position. It is well known that alcohol increases snoring. Habitual (almost every night or every night) snoring is practically always present in patients with OSAS. Children and elderly people may not snore loudly. Instead they are breathing with their mouths open. In the first large-scale epidemiological study on snoring, about 24% of San Marino men and 14% of San Marino women were reported to habitually snore (Lugaresi et al., 1980). In Finland, 9% of adult men and 3.6% of adult women reported snoring always or almost always when asleep (Koskenvuo et al., 1985a). Among Hispanic-American adults the age-adjusted prevalence rate of regular loud snoring was 27.8% in men and 15.3% in women (Schmidt-Nowara et al.,
290
Table 18.2 Prevalence of narcolepsy: studies on representative population samples Number (age range (years)), country
Population, methods, and comments
Prevalence per 100 000 (CI)
Solomon, 1945 Solomon, 1945 Honda, 1979, Honda et al., 1983 Partinen, 1982 Franceschi et al., 1982 Wilner et al., 1988 Martikainen et al., 1992 Tashiro et al., 1992 al Rajeh et al., 1993
10 000 (16–34), USA 189 196, USA 12 469 (12–16), Japan 2537 (18–29), Finland 2518 (6–92), Italy 1800 (30–57), Israel (Jews) 1190 (36–50), Finland 4559 (17–59), Japan 23 227 (all ages), Saudi Arabia
20 (0–4.8) 3 (0.6–5.7) 160 (9–230) 79 (6–287) 40 (0–118) 0.23 (N/A) 168 (18–604) 590 (369–816) 4 (0–13)
Wing et al., 1994 Hublin et al., 1994b
342 (N/A), Chinese Hong Kong 11 354 (33–60), Finland
Ohayon et al., 1996 Ondze´ et al., 1998 Silber et al., 2002
4972 (15–100), UK 14 195 (15þ), France Census data of Minnesota, USA
Wing et al., 2002
9851 Chinese Hong Kong
Ohayon et al., 2002 Shin et al., 2008
18 980, UK, Germany, Italy, Portugal, Spain 20 407 (14–19), Korea
Black men. No precise information on cataplexy Male population sample. No precise diagnosis Population sample, Que, personal interview Young male population, recruits, Que, PSG Hospital patients, Que, PSG Hospital patient sample, PSG, HLA-typing Population sample, Que Population sample, Que Population sample, personal interview, clinical examination Patient population, PSG, HLA-typing Population sample, Que, UNS, phone interview, clinical exam, PSG, HLA-typing Population sample, telephone survey Patients consulting physicians, Que Record linkage of diagnosed patients; incidence 1.4 (0.95–1.9)/100 000 persons/year Population sample, phone interview, UNS, clinical exam., PSG, HLA-typing Population samples, telephone surveys Student population, UNS, interview, PSG, HLA-typing
1–40 (N/A) 26 (0–56) with cataplexy 40 (0–96) 21 (4–62) 56 (42–73), 36 (25–50) with cataplexy 34 (10–117) with cataplexy 47 (N/A) 15 (0–31)
CI, confidence interval; N/A, not applicable, not given, or cannot be calculated; PSG, polysomnographic sleep studies; Que, questionnaire used as a screening method; HLA, human leukocyte antigen; UNS, Ullanlinna Narcolepsy Score (Hublin et al., 1994a).
M. PARTINEN
Study
EPIDEMIOLOGY OF 1990). Snoring increases with age up to 60–65 years and decreases in older age (Koskenvuo et al., 1985a; Gislason et al., 1988; Cirignotta et al., 1989; SchmidtNowara et al., 1990; Gislason and Benediksdottir, 1995; Martikainen et al., 1998; Partinen et al., 1998; Ferini-Strambi et al., 1999). In many studies prevalence of snoring has been higher but in such cases history of snoring has often been asked with only two or three possible response alternatives. Because almost everybody snores sometimes snoring figures are high. Occasional snoring or snoring as a dichotomous variable is not related to significant pathology. On the contrary, habitual almost every night snoring seems to be a risk factor for cardiovascular and cerebrovascular diseases. These studies will be discussed later in this text. For a clinician this is important. Having a positive response to snoring is not sufficient. One needs to know how often someone is snoring. When asking for frequency semiquantitative scales with defined time frames should be used. For example “often” can mean once a month for someone but almost any day for another. Snoring history is significant if someone snores at least 5 nights per week, in other words someone is a habitual snorer. One can ask further also about presence of sleep apnea. If someone snores almost every night very loudly and intermittently and someone (a cohabiting person) has noticed breathing pauses on about 3–5 nights per week the probability of OSAS is high. If the subject has been snoring for more than 13 years it is almost certain that he/she has sleep apnea (Partinen et al., 1998). The probability of sleep apnea increases further if the clinical examination is suggestive of sleep apnea. Some of the best known strong indicators of possible sleep apnea are thick neck, large waist circumference (visceral fat), increased fat under the chin, pathological Mallampati score with large tongue and/or large tonsils, and narrow upper airways with high ogival hard palate. If the snoring and apnea history are positive and the clinical examination is suggestive of sleep apnea the prior probability can be higher than 90%. In other words, the diagnostic certainty is better than that of a screening sleep recording. It is also important to recognize false-positive responses from screening recordings. Unfortunately a good clinical history and clinical examination are sometimes overlooked, trusting too much the results of sleep recordings. Heavy habitual (every night) snoring (i.e., partial upper-airway obstruction), even without apneas, may influence pulmonary arterial pressure, and it is associated with daytime sleepiness, arterial hypertension, insulin resistance, metabolic syndrome and other health consequences (Lugaresi et al., 1975, 1983b; Partinen et al., 1983b, 1998; Koskenvuo et al., 1985b; Rauscher et al.,
SLEEP DISORDERS
291
1992; Tiihonen et al., 1993; Martikainen et al., 1994; Grunstein et al., 1995; Grunstein, 1996; Young et al., 1996, 1997; Fuyuno et al., 1999; Hu et al., 1999, 2000; Bixler et al., 2000; Franklin et al., 2000; Lavie et al., 2000; Peppard et al., 2000; Leineweber et al., 2003).
Sleep apnea Sleep-related breathing disorders (SRBD) and sleepdisordered breathing (SDB) refer mostly to sleep apnea. The lowest prevalence of OSAS among adult men varies between 1% and 4%. There is an age relationship. The prevalence of OSAS among men aged 40–59 may be greater than 4% or even greater than 8% (Table 18.3). Although sleep apnea is frequently found among elderly subjects, the occurrence of clinically significant sleep apnea is less common in older age groups than among people aged 40–65 years. In young women OSAS is rare, but after menopause, up to the age of 65, it is almost as common as in men. Sleep apnea is not rare among children. Apneas with an AHI > 5 may be found in more than 14% but symptomatic sleep apnea syndrome is rare (Telakivi et al., 1987; Cirignotta et al., 1989; Stradling and Crosby, 1991; Haraldsson et al., 1992; Bearpark et al., 1995; Gislason and Benediktsdottir 1995; Kripke et al., 1997; Marin et al., 1997; Zamarron et al., 1999a; Lavie, 1983). The prevalence of OSAS varies on average between 1% and 4%. Men have higher figures than premenopausal women. Among adults, children, and also among subjects with mental retardation, OSAS is highly associated with central obesity (Lavie, 1983; Bixler et al., 1985, 1998, 2001; Peter et al., 1985; Telakivi et al., 1987; Cirignotta et al., 1989; Ancoli-Israel et al., 1991, 2000; Partinen and Telakivi, 1992; Gislason et al., 1993; Hida et al., 1993; Ohta et al., 1993; Young et al., 1993, 2002; Ancoli-Israel and Coy, 1994; Gislason and Beneditksdottir, 1995; Olson et al., 1995; Marin et al., 1997; Ohayon et al., 1997c; Neven et al., 1998; Ng et al., 1998; Hui et al., 1999; Zamarron et al., 1999b; Bixler et al., 2000; Chay et al., 2000; Friedman et al., 2001; Villa Asensi and de Miguel Diez, 2001; de Miguel-Diez ¨ zdemir et al., 2003; Halbower and Marcus, 2003; O et al., 2005; Johnson and Roth, 2006). Obstructive sleep apneas are part of the complex of “heavy snorer’s disease,” as defined by Lugaresi et al. (1983b). As stated above, heavy snoring, without sleep apnea syndrome, is a risk factor for many health outcomes. Sleep apnea should be properly quantified, not only by an AI (or AHI) but also by the number of oxygen desaturations, limitation of air flow, degree of daytime sleepiness, and by cardiovascular function. An AI of 5 or AHI of 10 is commonly used as a criterion for OSAS.
Table 18.3
292
Occurrence of obstructive sleep apnea and sleep apnea syndrome Population subjects
Age (years)
Criteria; comments
Prevalence (%)
Lavie, 1983, Israel Telakivi et al., 1987, Finland Gislason et al., 1988, Sweden Cirignotta et al., 1989, Italy
1262 men 1939 men 3201 men 1170 men
18–67 30–69 30–69 30–39, 40–59, 60–69
AI > 10, symptomatic Habitual snoring, EDS, RDI > 10 Habitual snoring, EDS, AHI > 10 AI > 10, symptomatic AI > 10, symptomatic AI > 10, symptomatic
Stradling & Crosby 1991, UK
893 men
35–65
ODI4 > 20, symptomatic ODI4 > 10 ODI4 > 5
Haraldsson et al., 1992, Sweden Young et al., 1993, USA
846 men 352 men, 250 women
30–69 30–60
Positive history of OSA, EDS, and PSG Hypersomnia and RDI 5
Gislason et al., 1993, Iceland Olson et al., 1995, Australia
2016 women 1233 men, 969 women
40–59 35–69
Habitual snoring, EDS, PSG AHI 15 AHI 10 AHI 5
Bearpark et al., 1995, Australia Gislason and Benediktsdottir, 1995, Iceland Ohayon et al., 1997c, UK
294 men 555 children
40–65 0.5–6
RDI 10 EDS and RDI 5 Habitual snoring or apneas, ODI4 > 3
1.0–5.9 0.4–1.4 0.7–1.9 0.2–1.0 3.4–5.0 0.5–1.1 0.3 1.0 4.6 2.8–5.5 4.0 (M) 2.0 (W) > 2.5 4–18 7–35 14–69 10.03.0 > 2.9
2078 men, 2894 women
15–100
Kripke et al., 1997, USA
165 men, 190 women
40–64
N/A, telephone survey; no PSGN/A, telephone survey; no PSG ODI4 > 20 ODI4 > 20
Marin et al., 1997, Spain
1360, men and women; quota
> 18
Bixler et al., 1998, USA
4364 men, 741 in lab
20–100
Habitual snoring, apneas, EDS, clinical examination, oximetry AHI 10 and daytime symptoms with EDS
Ng et al., 1998, Singapore Puvanendran & Goh, 1999, Singapore Zamarron et al., 1999a, Spain Bixler et al., 2001, USA
2298 220 interviews, 106 in lab 76; random sample 12 219 women, 1000 in lab
20–74 30–60 50–70 20–100
Questionnaire with strict criteria; no PSG Habitual loud snoring, EDS, AI > 5 Medical history, examination, AHI 5 AHI 10 and daytime symptoms with EDS
¨ zdemir et al., 2005, Turkey O
2638 men, 2701 women
20–107
Questionnaire. History of stopping to breathe when sleeping; no PSG
2.4–4.6 0.8–2.2 5.4–13.2 2.1–8.3 Men: 2.2 Women: 0.8 3.3 45–64 years: 4.7 0.43 (0.05–0.8) 15 AHI5: 28.9% OSAS: 6.8% 1.2 Pre: 0.6 PostþHRT: 0.5 Post: 2.7 6.4
In order to diagnose obstructive sleep apnea syndrome (OSAS), a subject must have verified sleep apnea and be symptomatic with EDS or other symptoms of OSAS. The highest figures in the table are in studies where the subjects may not have been symptomatic. In those cases the prevalence figures represent only occurrence of apneas and not prevalence of OSAS. AI, apnea index; EDS, presence of excessive daytime sleepiness; RDI, respiratory disturbance index; AHI, apnea–hypopnea index; ODI4, oxygen desaturation index with at least 4% desaturations; OSA, obstructive sleep apnea; PSGN/A, PSG, polysomnography; Pre, premenopause; Post, postmenopause; HRT, hormone replacement therapy; N/A, not applicable (not defined, not given).
M. PARTINEN
Reference, country
EPIDEMIOLOGY OF The diagnostic criteria should be adjusted for age (Bixler et al., 1985, 1998, 2001; Ancoli-Israel et al., 1991, 2000; Ancoli-Israel and Coy, 1994). It may be that while the occurrence of sleep apnea increases with age the clinical meaningfulness of apnea decreases among elderly people. Hence, the occurrence of clinically significant sleep apnea syndrome is rare among elderly people, who often have many other diseases that may be indirectly associated with sleep apnea (Mant et al., 1988; Phillips et al., 1994, 2000; Mant et al., 1995; Ancoli-Israel et al., 1996).
RISK
FACTORS FOR SNORING AND SLEEP APNEA
Risk factors include central obesity, thick neck, and obstructed upper airways. Central visceral obesity is the most important risk factor for snoring and sleep apnea. Obesity is commonly measured by body mass index (BMI), which is calculated as weight in kilograms divided by square of height in meters (Khosla and Lowe, 1967). According to World Health Organization criteria, adults with a BMI over 25 kg/m2 may be considered as overweight and those with BMI over 30 kg/m2 are considered as obese. In 2006 more than 60% of US and UK citizens were overweight (http://www.who.int/bmi/index.jsp) and almost 30% of US citizens were obese, with BMI over 30 kg/m2 (http://apps.nccd.cdc.gov/brfss). In the Nauru Islands almost 80% and in French Polynesia 36% are obese (http://www.who.int/bmi/index.jsp). The frequency of snoring and sleep apnea increases with obesity in all published epidemiological reports. The same is true for heavy snoring and sleep apnea. For example, in the study of Katz et al. (1990), habitual snoring was found to occur in 7% of men and 2.8% of women with a BMI of less than 27 kg/m2 and in 13.9% and 6.1%, respectively, of those above this level (Davies and Stradling, 1990). Using multivariate analysis, the Oxford group of John Stradling first reported that neck size is more closely related to severity of sleep apnea than BMI (Davies and Stradling, 1990; Katz et al., 1990; Stradling and Crosby, 1991; Kushida et al., 1997). Neck size may be easily measured, and is a useful indicator of upperbody obesity. Several lines of evidence show that especially central obesity (large waist circumference) is related to increased risk of cardiovascular disease, diabetes, and metabolic syndrome (Hartz et al., 1983; Lapidus and Bengtsson, 1988; McKeigue et al., 1991; Lakka et al., 2002; Schafer et al., 2002; Grunstein et al., 2007; Tuomilehto et al., 2008b). Other clinical markers that are risk factors of sleep apnea include high Mallampati score and small cricomental space
SLEEP DISORDERS 293 (Samsoon and Young, 1987; Bergler et al., 1997; Kushida et al., 1997; Friedman et al., 1999; Harding, 2001; Tsai et al., 2003; Gruber et al., 2006; Grunstein et al., 2007). If the cricomental space is more than 1.5 cm obstructive sleep apnea is very unlikely; in the study of Tsai et al. (2003) its negative predictive value was 100% (95% CI: 75–100%). Anatomically narrow upper airways. Lean people may have abnormal upper airways. Anything that obstructs the upper airways is a risk factor for heavy snoring and sleep apnea. Among known risk factors are large adenoids or tonsils, and rhinitis (Corbo et al., 1989; McColley et al., 1997; Nieminen et al., 1997, 2000; Young et al., 2001). Other abnormalities in the upper airways include those found in different dysmorphic syndromes, mentally disabled people, acromegaly, and familial amyloidosis (Shapiro et al., 1985; Pekkarinen et al., 1987; Freed et al., 1988; Bull et al., 1990; Cohen, 1991; Zucconi et al., 1993; Rosenow et al., 1996; Hoch and Hochban, 1998; Kiuru et al., 1999). In sum, obesity is linked with the probability of snoring and sleep apnea, but BMI is not the best indicator of obesity. Therefore at least waist circumference, neck circumference, and cricomental space should be measured in all future clinical and epidemiological studies on snoring and sleep apnea. Waist and neck circumference as well as the cricomental space may be estimated relatively well in surveys that are based on questionnaires using different pictures of the head and neck. Responders can then choose the picture that most resembles their own face. The collar size of a shirt also correlates well with neck circumference. Other risk factors for snoring and sleep apnea. Among 2187 subjects representative of a general adult population in Tucson, Arizona, major independent risk factors for snoring were male gender, age between 40 and 64 years, obesity, and cigarette smoking (Bloom et al., 1988). Snoring was more common in subjects who regularly used alcohol or hypnotics. The effect of smoking may be related to upper-airway inflammation and edema by cigarette smoke. Alcohol increases upper-airway resistance and tends to induce obstructive sleep apnea in healthy people and especially among chronic snorers (Taasan et al., 1981; Issa and Sullivan, 1982; Robinson et al., 1985; Mitler et al., 1988; Corbo et al., 1989; Scrima et al., 1989; McColley et al., 1997; Nieminen et al., 2000; Young et al., 2001). This is probably due to the acute centrally depressing effects of alcohol. Among other risk factors, hostility is also associated with habitual snoring (Koskenvuo et al., 1994).
294
ETHNIC
M. PARTINEN DIFFERENCES IN OCCURRENCE OF SNORING
AND SLEEP APNEA
The prevalence and incidence of sleep apnea seem to vary according to ethnicity. In a study in Singapore comparing the prevalence of snoring among Chinese, Malay, and Indian people, the average prevalence of snoring was 6.8% (53–83%). The ethnic differences were significant. Among Chinese 6.2% (4.4–8.1%), among Malay 8.1% (6.1–10.2%), and among Indians 10.9% (8.5–13.4%) snored. The minimum wholepopulation prevalence by the most restricted symptom criteria for defining sleep breathing-related disorder was 0.43% (0.05–0.8%) (Ng et al., 1998). In Singapore some estimations have given a prevalence of 15% for sleep apnea (Puvanendran and Goh, 1999). This figure is based, however, only on a small sample of people and it may not be representative of the whole Singapore population. Therefore the figure is probably too high. The reasons are probably related to differences in cranial-facial anatomy and also to environmental effects. An example of the latter is obesity, which seems to be significantly more common in African-Americans and Saudi Arabian women than in people of Caucasian origin (al-Shammari et al., 1994; Will et al., 1995; Ip et al., 1998; Ng et al., 1998; Tan et al., 1999; Ancoli-Israel et al., 2000). The reasons for higher occurrence of obesity are multiple, and socioeconomic factors should not be forgotten. Unemployment, alcoholism, and lack of social security are known to be associated with higher figures of obesity.
SNORING
AND SLEEP APNEA IN CHILDREN
Snoring or obstructive sleep apnea is common in children of all ages. It must be noted that among children snoring may not be loud. A manifestation of obstructed upper airways may be that the child always sleeps with open mouth. Among 1615 Italian children, aged 6–13 years, 118 children (7.3%) were habitual snorers. Children with rhinitis were more than twice as likely to be habitual snorers than others. There was a positive correlation between parental smoking and the presence of snoring in children (Corbo et al., 1989). In Iceland 3.2% of 555 children aged 6 months to 6 years snored often or always (Gislason et al., 1988). The estimated minimal prevalence of obstructive sleep apnea in that age group was 3.2%. In one study among 4–5-year-old children significant sleep and breathing disorders occurred in 0.7% (Ali et al., 1993). In a Spanish study the prevalence of sleep-disordered breathing among adolescents aged 12–16 years was 1.9% (Sanchez-Armengol et al., 2001). Adenotonsillar hypertrophy is the commonest cause of upper-airway
obstruction in infants and children (Potsic et al., 1986; Yrjo¨nen et al., 1991; Nieminen et al., 1997).
SLEEP
APNEA AMONG ELDERLY PEOPLE
Habitual snoring seems to decrease after the age of 65 or 70 years (Kayukawa et al., 1998). In a random sample of 5201 Medicare enrollees 65 years old or older, 33% of the men and 19% of the women reported loud snoring. Snoring was less frequent in people aged over 75. Observed apneas were reported by 13% of men and 4% of women (Enright et al., 1996). In California 19–24% of people older than 65 years have an AI > 5, and 62% of elderly people have a respiratory disturbance index (RDI) 10 (Ancoli-Israel et al., 1991; Ancoli-Israel and Coy, 1994; Kayukawa et al., 1998). The clinical significance of the high frequency of AI or RDI among elderly people remains to be seen. The presence of high AI or RDI in an elderly subject does not mean that he/she has OSAS, and it does not mean that all elderly subjects with an AHI or RDI over 10 should receive CPAP. In a cohort of 426 elderly people, those with an RDI 30 had significantly shorter survival but the RDI was not an independent predictor of death among the elderly subjects during 5 years of follow-up when age, cardiovascular disease, and pulmonary disease were used as covariates (Ancoli-Israel et al., 1996). The frequent occurrence of sleep apnea means, on the contrary, that we should perhaps use higher cut-off point values of AI and AHI for elderly people (Bixler et al., 1998).
Arterial hypertension Several cross-sectional and prospective studies have shown that, among middle-aged adults there is an association of habitual snoring, sleep apnea, and arterial hypertension. The causality is still not clear, but habitual snoring usually precedes the development of hypertension. In other words, snoring and especially habitual snoring is a risk factor for developing hypertension (Lugaresi et al., 1980; Partinen et al., 1983b; Koskenvuo et al., 1985b; Gislason et al., 1987; Ancoli-Israel et al., 1996; Hu et al., 1999, 2000; Nieto et al., 2000; Peppard et al., 2000; Lindberg et al., 2007). The association seems to be independent of the effects of BMI, age, gender, smoking, use of alcohol, and physical activity. In case-control studies the prevalence of sleep apnea among patients with essential hypertension was 25% or higher (Kales et al., 1984; Lavie et al., 1984; Fletcher et al., 1985; Williams et al., 1985, 2007; Bartel et al., 1995; Fletcher, 1996; Worsnop et al., 1998). In practice this means that if there is a history of habitual snoring and/or sleep apnea, and if the upperairways anatomy is suggestive of sleep apnea, a
EPIDEMIOLOGY OF polysomnographic study must be done to verify or rule out clinically significant sleep apnea. In middle-aged adults with drug-resistant hypertension the prevalence of obstructive sleep apnea may be over 80% (Logan et al., 2001). In the study of Enright et al. (1996) among elderly people, loud snoring, observed apneas, and daytime sleepiness were not statistically significantly associated with hypertension or prevalent cardiovascular disease.
Heart disease There is an association between habitual snoring and/or obstructive sleep apnea and cardiac arrhythmias (Gillis, 1985; Peiser et al., 1985; Otsuka et al., 1987; Shepard, 1992; Adlakha and Shepard, 1998; Kohler et al., 1998; Sanner et al., 1999; Porthan et al., 2004). Coronary heart disease and myocardial infarction are more common in habitual snorers and untreated patients with sleep apnea than in nonsnorers or people with treated sleep apnea. The average OR for coronary heart disease of habitual snorers versus never or occasional snorers in all published studies has been about 1.9 or higher (Crancer and McMurray, 1968; Partinen et al., 1983c; Koskenvuo et al., 1985b; D’Alessandro et al., 1990; Schmidt-Nowara et al., 1990; Zamarron et al., 1999b; Hu et al., 2000). The association remains after adjustment for arterial hypertension and BMI. In one of our studies results were adjusted for BMI, history of arterial hypertension, smoking, and alcohol, and the OR decreased only slightly to 1.71 (95% CI: 0.96–3.05) (Koskenvuo et al., 1987). In Australia, 101 male patients with myocardial infarction and 53 male control subjects were investigated (Hung et al., 1990) and a significant association of sleep apnea with myocardial infarction was found. The association was independent of age, BMI, arterial hypertension, smoking, and cholesterol level. Adjusted risk of myocardial infarction increased with increasing level of sleep apnea. Men with an AI > 5.3 had 23.3-fold (95% CI: 3.9–139.9) higher risk of myocardial infarction than did men with an AI < 0.4. The mean AI was 6.9 in patients with myocardial infarction versus 1.4 in the control subjects (Hung et al., 1990). Also cardiac insufficiency or congestive heart disease seems to be more common among patients with sleep apnea and/or Cheyne–Stokes breathing than among subjects without sleep apnea (Malone et al., 1991; Javaheri et al., 1995; Chan et al., 1997; Javaheri, 2003; Parish and Somers, 2004; Javaheri, 2006). Again, consistent with results that have been discussed above, these associations are found mainly among middle-aged subjects and are weaker among elderly people (Jennum et al., 1995, 1996).
SLEEP DISORDERS
295
Snoring and stroke Habitual snoring (snoring almost always or always when sleeping) is a significant and independent risk factor for cerebrovascular disease, but snoring per se, i.e., snoring rarely or sometimes, is not. In other words, there is an association between often or always snoring and ischemic cerebrovascular disease (Table 18.4) (Partinen and Paloma¨ki, 1985; Koskenvuo et al., 1987; Spriggs et al., 1990, 1992; Smirne et al., 1991, 1993; Jennum et al., 1994; Neau et al., 1994, 1995; Hu et al., 2000). The most important factors associated with brain infarction are age, male gender, arterial hypertension, various abnormal cardiac conditions, diabetes mellitus, and cigarette smoking. In addition to these established risk factors, however, there is evidence to suggest a link between habitual (almost every night or every night) snoring, OSAS, and stroke. In the first case-control study 50 male patients with brain infarction were compared with 100 male hospital control subjects without any vascular disease (Partinen and Paloma¨ki, 1985). The risk ratio of brain infarction between often or always snorers and occasional or never snorers was 2.8 (95% CI: 1.3–5.8). The risk ratio was 10.3 (3.5–30.1) when habitual (every night or almost every night) snorers were compared with occasional or never snorers (Partinen and Paloma¨ki, 1985). The independent contribution of habitual snoring as a risk factor for brain infarction was confirmed in another case-control study (Paloma¨ki, 1991) of 177 male patients and control subjects matched for age and sex. After adjustments for several confounding variables, the independent OR relating to often or always snoring and stroke remained at 2.13 (1.3–3.5) (Paloma¨ki, 1991). Spriggs and others (1992) used community controls, which may have altered the relationship. During the interview another person from the household was present to increase the validity of the history. In the study by Spriggs et al. 36% of hospital controls snored often or always. Among community controls 33% of men and 28% of women snored often or always. When admission to hospital because of stroke was compared, the OR for often or always (regular) snorers versus nonregular snorers was 3.2 (2.3–4.4). After adjustment for BMI, smoking, alcohol drinking, previous history of cerebrovascular disease, ischemic heart disease, hypertension, atrial fibrillation, and diabetes, the adjusted OR for stroke in regular snorers was 1.7 (1.3–2.2), which was still statistically significant (Spriggs et al., 1992). One important finding in the Spriggs study is that the prognosis after stroke was worse for regular snorers than for nonsnorers.
296
Table 18.4 Snoring as a risk factor of stroke Study
Population
Methods; outcome
Stratification/adjustment
Type of snoring
OR (95% CI)
Partinen & Paloma¨ki, 1985
50 male stroke patients and 100 hospital controls
Age, gender (men), BMI
General population 4388 men, 40–69 years
Habitual snoring Often or always snoring Often or almost always snoring
10.3 (3.5–30.1) 2.8 (1.3–5.8)
Koskenvuo et al., 1987 Paloma¨ki, 1991
177 stroke patients and 177 hospital control patients
Age, gender, alcohol, HT, IHD
Often or always snoring
2.13 (1.29–3.52)
Spriggs et al., 1990, 1992
326 IHD/stroke patients and 345 community control subjects
Case-control, personal interview, neurological examination, CT/ MRI; stroke versus others Cohort study, 3 years follow-up, questionnaire, registry data; incidence of stroke or IHD Case-control, questionnaire, neurological examination, CT/ MRI; stroke versus others Case-control, personal interview, neurological examination, CT/ MRI; stroke versus others
Age, gender, BMI, smoking, alcohol, IHD, HT, AF, DM
Often or almost snoring
Smirne et al., 1993
164 stroke patients and 330 hospital control patients 804 70-year-olds followed for 6 years
Age, gender, BMI, smoking, alcohol, HT, DM, dyslipidemia Age, gender, BMI, smoking, alcohol, HT, social class, lipids, glucose, catechol
Often or always snoring
Jennum et al., 1994
Often or always snoring
1.8 (1.1–3.6)
Neau et al., 1995
133 stroke patients and 133 nonhospital control patients
Age, gender, BMI, DM, hypertension, cardiac arrhythmia
Habitual snoring
2.93 (1.28–6.75)
Hu et al., 2000
71 779 female nurses, 40–65 years
Case-control, personal interview, neurological examination, CT/ MRI; stroke versus others Cohort of 70-year-old men and women, snoring history and other information from medical records Case-control, personal interview, spouse present, neurological examination, CT/MRI, stroke versus others Cohort study, 8 years follow-up, questionnaire, registry data; incident stroke versus no stroke
3.2 (2.3–4.4) adjusted for age and gender 1.7 (1.3–2.2) adjusted for all factors 1.86 (1.20–2.87)
Age, smoking, BMI, HT, DM, hypercholesterolemia, familial IHD history and other covariates
Snoring regulalry
1.88 (1.29–2.74) adjusted for age 1.35 (0.91–1.99) adjusted for all 1.42 (1.07–1.89) adjusted for all
Age, gender (men), BMI, smoking, alcohol, HT
OR, odds ratio; CI, confidence interval; CT, computed tomography; MRI, magnetic resonance imaging; BMI, body mass index; IHD, ischemic heart disease; HT, hypertension; AF, atrial fibrillation; DM, diabetes mellitus.
M. PARTINEN
Occasional snoring
2.08 (1.5–3.77) (stroke or IHD)
EPIDEMIOLOGY OF SLEEP DISORDERS In a study by Smirne et al. (1993), the adjusted (age, gender, obesity, diabetes, dyslipidemia, smoking, use of alcohol, hypertension) OR for “often or always snoring” in relation to ischemic brain infarction was 1.86 (1.2–2.87). Neau et al. (1995) studied 133 patients, aged 45–75 years, and 133 control subjects matched for age and gender. During the interview the spouse was present so that reliable history about snoring was obtained. Neau et al. used the same categorization for snoring as Partinen and Paloma¨ki (1985), according to which habitual snorers are those who reportedly snore always (every night). They defined as “snorers” those who snore often or always. “Nonsnores” included never snorers and also occasional snorers, which is probably the correct way of categorization (Neau et al., 1995). In that French study the prevalence of habitual snoring was 23.3% among patients with stroke and 8.3% among their controls. The OR for habitual snoring was 3.4 (95% CI 1.5–7.6). The OR for “often or always snoring” was 1.7 (95% CI 1.03– 2.93). Even after adjustment for age, sex, arterial hypertension, cardiac arrhythmia, and obesity, the OR of habitual snoring for stroke remained statistically significant (2.93; 95% CI 1.28–6.75). The risk of ischemic stroke was especially high among habitually snoring older men with arterial hypertension whilst the OR did not reach statistical significance (OR 1.42; 95% CI 0.51–3.99) (Neau et al., 1995). In conclusion, there seems to be a real association between habitual (defined as almost always or always snoring, i.e., snoring on at least 5 nights per week) snoring and brain infarction. Long-term cohort studies and more case-control studies are needed to confirm this. The problem with cohort studies is that brain infarction is not as common as ischemic heart disease and a large number of incident cases is needed. Therefore, until now there have only been two published prospective cohort studies looking for habitual snoring as a risk factor for stroke. We asked about snoring history in the Finnish Twin Cohort for the first time in 1981 and all subjects have been followed since then. We have done intermediate analyses and we expect to have enough incident cases of stroke when we have the registry data of mortality and morbidity to the end of 2009. That may be possible by the end of 2010 or in 2011. This would allow us more than 27 years’ followup time. In our first follow-up, published in 1987, we did not have enough incident stroke cases so we had to pool the cardiovascular morbidity with cerebrovascular morbidity. At that time the OR for ischemic heart
297
disease and brain infarction combined was 2.08 (1.5– 3.77) (Koskenvuo et al., 1987). The Nurses’ Health Study includes 71 779 female nurses aged 40–65 years at baseline in 1986, and is the largest cohort study including questions about snoring and other sleep-related items (Hu et al., 2000). Women with cardiovascular end points at baseline were properly excluded. The 398 incident strokes (60 never snorers, 288 occasional snorers, and 50 regular snorers) in that cohort during 8 years of followup allowed some analyses. The questions on snoring were: “Do you snore?” with three possible answers: “regularly,” “occasionally,” or “never.” Although this classification differs from the preferred classification the group, “regularly” is probably quite close to the category of “often or always snoring” or the stricter “habitual snoring” that has been used in Finland and France. Hu et al. (2000) adjusted the results for age, BMI, smoking, menopausal status, history of myocardial infarction, consumption of alcohol, physical activity, sleeping time, diabetes, and hypercholesterolemia. The age-adjusted relative risk of stroke for regular snorers compared with never snorers was 1.88 (1.29– 2.74). In a multivariate adjusted model the relative risk remained significant for occasional snorers (n ¼ 288) versus never snorers (1.42; 1.07–1.89). Because there were only 50 regular snorers, the adjusted relative risk was slightly lower (1.35; 0.91–1.99). The relative risk of combined cardiovascular and cerebrovascular events for regular snoring was 1.33 (1.06–1.67) (Hu et al., 2000). More recently, from the same Nurses’ Health Study cohort, 935 women aged 43–69 years have been studied in more detail for an association between snoring history and cardiovascular disease (Williams et al., 2007). In a multivariate analysis more frequent snoring was directly associated with triglycerides (P ¼ 0.02) and inversely with high-density lipoprotein cholesterol levels (P ¼ 0.03) and adiponectin (P ¼ 0.03). In the same study longer sleep was associated with increased levels of C-reactive protein after adjusting for age, BMI, different lifestyle factors, family history of diabetes, glycemic control, and use of medications. The usually snoring women were older (P ¼ 0.03), more obese (P < 0.0001), centrally obese with larger waist-to-hip ratio (P ¼ 0.005), physically less fit (P ¼ 0.03), using more alcohol (P ¼ 0.04), more often hypertensive (P ¼ 0.0001), more often users of insulin (P ¼ 0.006), and premenopausal (P ¼ 0.02) than never or occasional snorers (Williams et al., 2007). These results suggest that snoring history and other sleeping history should be combined with other biomarkers of cerebrovascular disease risk.
298
M. PARTINEN
Sleep apnea and stroke To analyze the relationship between sleep apnea and brain infarction, Poza et al. (2000) studied 79 consecutive patients of both sexes with cerebral infarction and 248 age- and sex-matched controls. They obtained data reflecting arterial hypertension, diabetes mellitus, hypercholesterolemia, smoking and drinking habits, coronary heart disease, cardiomyopathy, snoring, respiratory pauses during sleep and daytime sleepiness, by using a standard questionnaire to interview every subject and spouse. A total of 34% of the stroke patients and 27% of controls were snorers and complained of apnea during sleep (P ¼ 0.19). In all, 19% of patients and 11% of controls presented with snoring, respiratory pauses during sleep, and daytime sleepiness simultaneously, suggesting OSAS (P ¼ 0.06). The difference was statistically highly significant among subjects younger than 65 years. OSAS was found in 29% of patients and in 7% of controls (P ¼ 0.006). A multiple logistic regression analysis confirmed the independent effect of moderate to severe OSAS as a risk factor for ischemic stroke (adjusted OR 4.54). In people younger than 65 years, OSAS, regardless of its severity, was also an independent risk factor for ischemic stroke, with an adjusted OR of 5.78 (Poza et al., 2000).
Circadian variation of strokes and snoring Most ischemic strokes occur during the morning hours before noon. Agnoli et al. (1975) studied 200 cases of probable nonembolic brain infarctions and 56 cases of embolic infarctions. Stroke occurred most commonly during the morning between 6 and 8 a.m. In another study, the time of onset of stroke was recorded in 707 patients (Marshall, 1977). Of the 554 cerebral infarctions, 40% occurred between midnight and 6 a.m. Onset of cerebral hemorrhage was rare at night (Marshall, 1977). In some studies most strokes occur during the morning hours after awakening. In a study by Tsementzis et al. (1985), cerebral infarction was most common between 10 a.m. and noon, when the highest blood pressures are usually recorded. In another study most (57%) of the 151 strokes occurred between 6 a.m. and noon (Marsh et al., 1990). In a meta-analysis of 31 publications, Elliott (1998) reported the circadian timing of 11 816 strokes. There was a 49% increase (95% CI 44–55%) in strokes between 6 a.m. and noon as compared with expectations that there is no circadian variation. All three studied subtypes of stroke had a significantly higher risk between 6 a.m. and noon (55% for 8250 ischemic strokes; 34% for 1801 hemorrhagic strokes; and 50% for 405 transient ischemic attacks: Elliott, 1998).
Detailed information about circadian variation of different types of stroke is, however, still limited. Chaturvedi et al. (1999) analyzed stroke onset using a detailed classification of stroke subtypes. They analyzed data of 1272 patients who had a documented time of stroke symptom onset, and all stroke subtype determinations were made by a single specialist. Most atherothrombotic strokes (25.7%), cardioembolic strokes (30.5%), and strokes of other/unknown mechanism (27.1%) occurred between 6:01 a.m. and 12:00 noon. The greatest portion of lacunar strokes (31.6%) were present on awakening. More than one-half of the infarcts in this series were either present on awakening or occurred in the mid- to late-morning hours (Chaturvedi et al., 1999).
NOCTURNAL
AND EARLY-MORNING STROKES ARE
RELATED TO HABITUAL SNORING AND OBESITY
In one study relation of the time of onset of stroke and snoring history were analyzed in 167 consecutive male patients. In 70 cases (41.9%), cerebral infarction occurred during sleep or immediately after awakening (Paloma¨ki et al., 1989). Of the 70 infarctions with an onset at night or immediately after awakening, 48 patients had a history of snoring often or always (68.6%). The respective percentage among the other 97 patients was 41.2%. The difference was statistically significant; OR for often or always snoring was 3.1 (1.7–5.9; P < 0.001). The odds risk remained significant when age, arterial hypertension, BMI, smoking, consumption of alcohol, and diabetes mellitus were taken into account (Paloma¨ki et al., 1989). Changes in blood pressure after awakening in the morning may cause a breakthrough of the autoregulation of the cerebral blood flow. In normal conditions nothing happens, but under unfavorable conditions an infarction may follow. Jimenez-Conde et al. (2007) studied 813 patients with ischemic stroke: 127 of them had a stroke during sleep (15.6%). Obesity was a factor associated with sleep strokes. Adjustment for age and gender revealed that atrial fibrillation was less frequent in the group of sleep strokes. Sleep strokes were more severe and functional outcome at 3 months was worse than for strokes occurring at other times of day. The authors conclude that “whilst sleep could be associated with a lesser stroke occurrence, it could also be associated with a higher severity” (Jimenez-Conde et al., 2007). The authors did not have specific data on snoring or sleep apnea, but the finding that obesity was more prevalent among subjects with sleep strokes is suggestive that snoring and sleep apnea might explain at least part of that association.
EPIDEMIOLOGY OF SLEEP DISORDERS
Snoring, sleep apnea, and dementia In a case-control study of 46 patients with Alzheimer’s disease, 37 patients with multi-infarct dementia, and in a random sample of 124 elderly community residents, the demented patients snored twice as frequently as the controls. No difference in the occurrence of snoring was found between the two types of dementia (Erkinjuntti et al., 1987). In a study by Reynolds et al. (1985), AI > 5 was found in 42.9% of demented patients, 17.6% of depressives, and 4.3% of controls. A significant association between sleep apnea and dementia of the Alzheimer type was found in women but not in men. Moreover, severity of dementia was significantly correlated with AI. Vitiello and Prinz (1990) had the same finding that the association exists among women when 24 female patients with Alzheimer’s disease were compared with 26 control subjects. The mean AHI among the female patients with Alzheimer’s disease versus control subjects was 9 3 and 2 0.4, respectively.
Snoring, sleep apnea, and sudden death Warnes and Roberts (1984) studied 12 massively obese patients (5 women and 7 men) with a BMI from 41.5 to more than 80 kg/m2 who had died. Information on the presence or absence of episodes of sleep apnea or hypersomnia was available for 2 women and 4 men. Both women and 2 of the 4 men had a positive history for sleep apnea or hypersomnia. One of the 2 women and 1 of the 2 men with hypersomnia-sleep apnea had sudden death, and the other 2 patients (1 woman and 1 man) died with right-sided congestive heart failure. There were 3 other sudden deaths, but unfortunately the authors did not have information about possible sleep apnea in those cases. Only 2 patients had one or more major epicardial coronary arteries narrowed by more than 75%. During a 4-year follow-up of 34 obese men with suspected OSAS with a mean age of 46 years, 5 men (15%) died suddenly outside hospital (Rossner et al., 1991). In the first study analyzing relationships between history of habitual snoring and sudden death an autopsy was performed in 460 consecutive cases of sudden death among 35–76-year-old men. The closest cohabiting person to each deceased was interviewed. The mean age of the deceased was 55.4 years, and the mean BMI was 26.3 kg/m2. Among the obese snorers (n ¼ 82), apneas had been observed “occasionally,” “often,” or “habitually” in 49 cases (Seppa¨la¨ et al., 1991). Death was classified as cardiovascular in 186 cases (40.4%). Cardiovascular cause of death was more common among the habitual and often snorers than among occasional or never snorers. Habitual snorers died more often while sleeping. Habitually
299
snoring was found to be a risk (OR 4.07; 95% CI 1.45–11.45) for cardiovascular early-morning death between 4 and 8 a.m. (Seppa¨la¨ et al., 1991). A 4-year-old boy with Prader–Willi syndrome died suddenly during sleep on day 67 of growth hormone treatment. During treatment, snoring had worsened. Autopsy showed multifocal bronchopneumonia. This case and two other published cases suggest that growth hormone may be associated with obstructive apnea, respiratory infection, and sudden death in this condition (Van Vliet et al., 2004). Other cases of death during growth hormone treatment in pediatric patients with Prader–Willi syndrome have been described (Grugni et al., 2005).
Evolution of obstructive sleep apnea syndrome Untreated severe OSAS is a deadly disease. There are several studies showing an increased risk of cardiovascular complications and death in patients with at least moderate (AI > 20) or severe (AI > 40) OSAS (Partinen et al., 1986, 1988; He et al., 1988; Partinen and Guilleminault, 1990). The increased risk is found especially among middle-aged people with sleep-disordered breathing, but not in elderly people when several other comorbidities and risk factors are present (Partinen et al., 1983b; Lavie et al., 1995; Mant et al., 1995; Lindberg et al., 1998; Noda et al., 1998). CPAP treatment reduces mortality (Peker et al., 2000; Doherty et al., 2005). Two recent long-term follow-up studies have been published. In Australia, after a mean follow-up time of 13.4 years, subjects with moderate to severe sleep apnea had greater risk of all-cause mortality (fully adjusted hazard ratio (HR) ¼ 6.24, 95% CL 2.01–19.39) than subjects without sleep apnea. Mild sleep apnea with RDI 5–14.9 was not an independent risk factor for higher mortality (Marshall et al., 2008). In an 18-year follow-up of the Wisconsin Sleep Cohort, all-cause mortality risk, adjusted for age, sex, BMI, and other factors, was significantly increased with severity of sleep apnea. The adjusted HR for allcause mortality with severe versus no sleep apnea was 3.0 (1.4–6.3). After excluding persons who had used CPAP treatment, the adjusted HR for all-cause mortality with severe versus no SDB was 3.8 (1.6– 9.0). The adjusted HR for cardiovascular mortality was 5.2 (1.4–19.2) (Young et al., 2008). CPAP ameliorates quality of life of patients with OSAS (Tousignant et al., 1994; Hetzel et al., 1995; Engleman et al., 1997, 1999; Flemons and Tsai, 1997). In a 3-month randomized study of 71 patients using the Euroqol quality-of-life measurement, CPAP added 8 and a lifestyle treatment added 4.7 quality-adjusted
300 M. PARTINEN life years compared to no treatment (Chakravorty like sensory feelings, mainly in the lower limbs. Rest, et al., 2002). whether lying or sitting still, provokes the symptoms. The importance of randomization can be seen in The condition may cause trouble falling asleep and published trials, which show that CPAP is effective in nocturnal awakenings. According to current knowlthe treatment of moderate and severe sleep apnea, edge, the syndrome results from an alteration of but that the effect is very small if there are no sympdopaminergic function related to abnormalities of toms of daytime sleepiness (Lojander et al., 1996; iron transport and storage (Allen, 2004; Trenkwalder Engleman et al., 1999; Dimsdale et al., 2000; Hack et al., 2005; Paulus and Schomburg, 2006). Many et al., 2000; Barbe et al., 2001; Montserrat et al., 2001). subjects with RLS have low levels of serum ferritin OSAS also has economic consequences. Untreated (< 50 mg/l). The dysfunction may occur at cerebral patients use significantly more health care resources or spinal cord level (Clemens et al., 2006; Paulus than treated patients (Tousignant et al., 1994; Fischer and Schomburg, 2006). Epidemiologic studies have and Raschke, 1997; Ronald et al., 1998; Wittmann and shown that the condition is common in populations Rodenstein, 2004). In a study by Kryger et al. (1996), derived especially from Europe (Table 18.5). untreated subjects with OSAS had used about 82 000 RLS is common. Among adults the prevalence of Canadian dollars for their physician claims against symptoms is between 5 and 15%. According to the 41 000 Canadian dollars among the control subjects. REST study (Allen et al., 2005) the prevalence of clinically significant RLS is around 2.7%, varying PARASOMNIAS between 1.3 and 4.2%, the highest figure being from France (Table 18.5). In a large (n ¼ 10 263) French The parasomnias represent a group of undesirable physistudy (Tison et al., 2005) the average prevalence of cal events or experiences that occur during entry into RLS was 8.5 % (n ¼ 870 fulfilled the International sleep, within sleep, or during arousals from sleep (Kryger RLS Study Group criteria). Of the 731 persons with et al., 1996). The ICSD-2 lists 12 categories of parasomcomplete information, 56.1% had at least moderate nias (American Academy of Sleep Medicine, 2005). RLS, having the International RLS Study Group Parasomnias among children are quite common. Up severity score of at least 11 (Tison et al., 2005). Using to more than 60% of people have experienced some the Bayes theorem we can estimate that about 4.8% parasomnias at some time in their life. Some 1–10% of adults in France have at least moderate RLS. This of children have experienced some parasomnias figure is quite close to the 4.2% figure from the REST (Kotagal et al., 2002). In adults parasomnias are study for French adults. A total of 21.2% of the uncommon, with a prevalence of 0.1 and 1%. It is French had at least severe RLS (International RLS important to differentiate parasomnias from nocturnal score > 20), giving an estimated prevalence of 1.8% epileptic phenomena. for at least severe RLS. Similar or higher figures have An interested reader should also consult other chapbeen published from the Nordic countries (Ulfberg ters in this book as well as epidemiological reviews on et al., 2001a, b; Ulfberg and Nystro¨m, 2004; Bjo¨rvatn parasomnias (Mahowald and Ettinger, 1990; Partinen et al., 2005). and Hublin, 2000; Hublin and Kaprio, 2003; AASM, The prevalence of RLS is significantly higher 2005; Petit et al., 2007; Pressman, 2007; Tinuper among women than men, and increases with age. et al., 2007). Epidemiological studies of parasomnias About 20% or more of pregnant women suffer from are difficult because often there is only the history to RLS (Lee et al., 2001; Suzuki et al., 2003; Manconi go on. Thus, the ranges of occurrence are very variet al., 2004), especially during the third trimester, with able, and the figures must be interpreted with caution. different degrees of severity. RLS during pregnancy is Parasomnias occur in close association with other sleep related to low ferritin and folate levels. It is not only disorders. For example, patients with sleep apnea often RLS that often occurs during pregnancy: the risk of talk in their sleep, and patients with RLS may also have having RLS later in life increases with number of pregnightmares or other parasomnias. Genetic factors play nancies. In a German study (Berger et al., 2004) the an important role in different parasomnias (Hublin and overall prevalence of RLS was 10.6%. The prevalence Kaprio, 2003). among women was about twice as high as among men. The prevalence among nulliparous women did RESTLESS-LEGS SYNDROME not differ significantly from that among men up to RLS was originally described by Ekbom in his thesis in age 64, but the risk of RLS increased gradually with 1945. It is a common neurological disorder charactereach pregnancy. Having one child increased the OR ized by an urge to move associated with paresthesiato 1.98 (95% CI 1.25–3.13), 2 children increased the
Table 18.5 Prevalence of restless-legs syndrome Study, country Europe Ekbom, 1945 Sweden O’Keeffe et al., 1993 Ireland Rothdach et al., 2000 Germany
Allen et al., 2005 USA, France, Germany, Spain, UK
Methods, criteria
Prevalence (%)
Physician’s practice, n ¼ 500
Presence of restless legs (original criteria), interview and neurological examination Presence of restless legs, interview
5
Acute-care geriatric service patients, n ¼ 317 Elderly population sample, age 65–83 years, n ¼ 369 196 men, 173 women
Postal office clerks n ¼ 668
IRLSSG criteria, questionnaire
5 (31% of patients had ferritin<18 ng/ml versus 6% in controls) Overall: 9.8 M: 6.1, F: 13.9 65–69 years: 9.8 70–74 years: 12.75 75þ years: 7.4 4
Male population sample, age 18–64 years, n ¼ 4000 Female population sample, age 18–64 years, n ¼ 200 Random population samples, age 15–100 years, n ¼ 18 980
IRLSSG criteria, questionnaire
5.8
IRLSSG criteria, questionnaire
11.4
Telephone survey, Sleep-EVAL with the ICSD criteria
RLS: 5.5 PLMD: 3.9
IRLSSG criteria, questionnaire, blood examination IRLSSG criteria, questionnaire
M: 14.7, W: 24.7 women with iron deficiency: 37.5 7.1
RLS diagnosis had been done and recorded in a GP database IRLSSG criteria, interviews, and physical examination IRLSSG criteria, interview
0.25
Blood donors in a blood donation unit, n ¼ 946, 618 men, 328 women Patients in general practice > 50 years, n ¼ 1437 Primary care patients n ¼ 1 561 692 General population age 20–79 years, n ¼ 4310 General population, age 18þ years n ¼ 10 263; 4762 men, 5501 women General population (18þ years) n ¼ 15 391; 1884 in France, 1929 in Germany, 1768 in Italy, 1896 in Spain, 1950 in UK, and 5964 in USA
IRLSSG criteria, interview and neurological examination
IRLSSG criteria, interview “the REST study”
EPIDEMIOLOGY OF SLEEP DISORDERS
Schmitt et al., 2000 Switzerland Ulfberg et al., 2001a Sweden Ulfberg et al., 2001b Sweden Ohayon & Roth, 2002 UK, Germany, Italy, Portugal, Spain Ulfberg and Nystro¨m, 2004 Sweden Rijsman et al., 2004 Netherlands Van de Vijver et al., 2004 UK Berger et al., 2004 Germany Tison et al., 2005 France
Population (n)
10.6
301
8.5 M: 5.8, W: 10.8 IRLS > 10: 56.1 Any frequency: 7.2 At least once weekly 5.0 At least twice weekly 4.1 (2.7)* France: 5.5 (4.2)* Germany: 2.0 (1.3)* Italy: 3.1 (2.4)* Spain: 3.1 (2.0)* UK: 4.9 (2.3)* Continued
302
Table 18.5 Continued Study, country
Population (n)
Methods, criteria
Prevalence (%)
Ho¨gl et al., 2005 Austria
General population, 50–89 years n ¼ 701
IRLSSG criteria, interview, medical examination, laboratory examinations
10.6 M: 6.6, W: 14.2 IRLS > 10: 44.6 11.5; 18–29 years: 6.3 M: 9.4, F: 13.4
Allen et al., 2005 USA Near East Sevim et al., 2003 Turkey Asia Tan et al., 2001 Singapore Bhowmik et al., 2003 India Suzuki et al., 2003 Japan Kim et al., 2005 South Korea
General population, age 18þ years, n ¼ 5964
IRLSSG criteria, telephone interview
Leg restlessness at bedtime, face-to-face interviews Telephone interview, presence of restless legs Five or more times/month At least once per month IRLSSG criteria, interview “the REST study”
10–15 18–29 years: 3 30–79 years: 10 80þ years: 19 All ages: 19.4 4.8 2/week: 3.1
General population, adults n ¼ 3234, 1591 men, 1643 women
IRLSSG criteria, interview by neurologists
3.19 M: 2.5, F: 3.9
Population sample, n ¼ 157 aged 55þ years, and 1000 patients aged 21þ years Case-control study, n ¼ 121 hemodialysis patients and 99 control patients Japanese pregnant women, n ¼ 16 528
IRLSSG criteria
0.6 in the population 0.1 among patients
Questionnaire with RLS-criteria; ENMG
Hemodialysis: 6.6 Control patients: 0.0 19.9
General population n ¼ 9939
Questionnaire survey in 500 maternity services IRLSSG criteria, interview
12.1 M: 8.5, F: 15.4
*In the REST study the prevalences per country refer to symptoms occurring on at least 2 days per week and the figures in parentheses refer to percentage of subjects who report having restless-leg symptoms at least twice-weekly with moderate or severe impact on quality of life. The figures in parentheses reflect clinically significant restless-leg syndrome. IRLSSG, International Restless Legs Syndrome Study Group; ICSD, International Classification of Sleep Disorders; RLS, restless-leg syndrome; PLMD, periodic limb movement disorder; IRLS, International Restless Legs Severity Scale; ENMG, electroneuromyography; M, men; F, women.
M. PARTINEN
Bjo¨rvatn et al., 2005 General population, age 18þ years, Denmark, Norway n ¼ 2005 North America, USA, and Canada Lavigne and Montplaisir, 1994 Population sample, age 18þ years, Canada n ¼ 2019 Phillips et al., 2000 Population sample age 18þ years, USA n ¼ 1803
EPIDEMIOLOGY OF SLEEP DISORDERS OR to 3.04 (2.11–4.40), and three or more children increased the OR to 3.57 (2.30–5.55) (Berger et al., 2004). RLS symptoms are frequent in many diseases. Among European or Caucasian patients with end-stage renal disease (Kavanagh et al., 2004; Unruh et al., 2004; Mucsi et al., 2005) the prevalence may be much higher than 20%. In one US study among 308 patients on hemodialysis, RLS symptoms were present during the past 6 months in 68% of patients of Caucasian origin and in 48% of patients of African-American origin (Kutner and Bliwise, 2002). This figure is very different from Indian figures. Only one patient from 65 patients (1.5%) with chronic renal failure and none of the 99 control subjects complained of having RLS (Bhowmik et al., 2004). RLS is also frequent among patients with either juvenile or adult type 2 diabetes. The association is not found among young adolescent patients with diabetes (Happe et al., 2005), but it is found in older patients. The association may be explained by the increased frequency of small-fiber sensory neuropathy, which is known to be often present in patients with RLS. In a case-control study of 124 patients with type 2 diabetes and 87 controls RLS was diagnosed in 17.7% of the diabetics and 5.5% of controls. In a multivariate logistic regression analysis the presence of polyneuropathy was the only statistically significant risk factor with an OR of 7.88 (1.34–46.28) (Merlino et al., 2007). RLS has also been associated with attention deficit hyperactivity disorder, fibromyalgia, rheumatoid arthritis, familial amyloidosis, transplantation, other sensory polyneuropathies, multiple sclerosis, spinal stenosis, or other spinal pathology (Salvi et al., 1990; Lee et al., 1996; Rutkove et al., 1996; Gemignani et al., 1997, 2007; Tembl et al., 1999; Polydefkis et al., 2000; Hening, 2002; Auger et al., 2005; Clemens et al., 2006; Ferini-Strambi et al., 2006; Paulus and Schomburg, 2006; Minai et al., 2007). The associations may be explained either by central or spinal dopaminergic pathophysiology that are probably related to iron metabolism, or by peripheral neuropathic effects. Although RLS is common, it is still poorly recognized. In the UK General Practice Database Van de Vijver et al. found that only 3877 diagnoses of RLS had been done between 1994 and 1998 among almost 1.6 million persons, giving a prevalence of 0.25%. Also the incidence was small; 41 diagnoses of RLS per 100 000 person-years had been done (Van de Vijver et al., 2004). In the REST study 337 (81.0%) of 416 patients with clinically significant RLS (the RLS sufferers) reported discussing their symptoms with a primary care physician, and only 21 (6.2%) were given a diagnosis of RLS.
303
SLEEP-RELATED ISOLATED SYMPTOMS Sleep-related isolated symptoms are at the borderline between normality and abnormality. In the ICSD-2 (American Academy of Sleep Medicine, 2005) simple snoring is classified as an isolated symptom. For simple snoring, with regular and rather undisturbing sounds, this is the correct place. Snoring has been discussed in this chapter together with sleep apnea because, as Lugaresi et al. (1983b) noticed, it is often the first symptom and first stage of the heavy snorer’s disease. Other isolated symptoms, such as sleep starts (hypnic jerks), are normal phenomena and almost everybody has had such phenomena at least sometimes after going to bed.
REFERENCES Adlakha A, Shepard JW Jr (1998). Cardiac arrhythmias during normal sleep and in obstructive sleep apnea syndrome. Sleep Med Rev 2 (1): 45–60. Agnoli A, Manfredi M, Mossuto L et al. (1975). Rapport entre les rythmes he´meronyctaux de la tension arterielle et sa pathoge´nie de l’insuffisance vasculaire ce´re´brale. Rev Neurol 131: 597–606. Agras WS, Hammer LD, McNicholas F et al. (2004). Risk factors for childhood overweight: a prospective study from birth to 9.5 years. J Pediatr 145 (1): 20–25. Ali N, Pitson D, Stradling J (1993). Snoring, sleep disturbance, and behaviour in 4–5 year olds. Arch Dis Child 68 (3): 360–366. Allen R (2004). Dopamine and iron in the pathophysiology of restless legs syndrome (RLS). Sleep Med 5 (4): 385–391. Allen RP, Walters AS, Montplaisir J et al. (2005). Restless legs syndrome prevalence and impact: REST general population study. Arch Intern Med 165 (11): 1286–1292. al Rajeh S, Bademosi O, Ismail H et al. (1993). A community survey of neurological disorders in Saudi Arabia: the Thugbah study. Neuroepidemiology 12 (3): 164–178. al-Shammari S, Khoja T, al-Maatouq M et al. (1994). High prevalence of clinical obesity among Saudi females: a prospective, cross-sectional study in the Riyadh region. J Trop Med Hyg 97 (3): 183–188. American Academy of Sleep Medicine. (2005). The International Classification of Sleep Disorders. 2nd edn. American Academy of Sleep Medicine (AASM), Rochester, Minnesota. Ancoli-Israel S, Coy T (1994). Are breathing disturbances in elderly equivalent to sleep apnea syndrome? Sleep 17: 77–83. Ancoli-Israel S, Kripke DF, Klauber MR et al. (1991). Sleepdisordered breathing in community-dwelling elderly. Sleep 14 (6): 486–495. Ancoli-Israel S, Kripke DF, Klauber MR et al. (1996). Morbidity, mortality and sleep-disordered breathing in community dwelling elderly. Sleep 19 (4): 277–282. Ancoli-Israel S, Klauber MR, Stepnowsky C et al. (2000). Sleep-disordered breathing in African-American elderly. Am J Resp Crit Care Med 152: 1946–1949.
304
M. PARTINEN
Auger C, Montplaisir J, Duquette P (2005). Increased frequency of restless legs syndrome in a French-Canadian population with multiple sclerosis. Neurology 65 (10): 1652–1653. Barbe F, Mayoralas LR, Duran J et al. (2001). Treatment with continuous positive airway pressure is not effective in patients with sleep apnea but no daytime sleepiness. A randomized, controlled trial. Ann Intern Med 134 (11): 1015–1023. Barry J, Bousfield W (1935). A quantitative determination of euphoria and its relation to sleep. J Abnorm Soc Psychol 29: 385–389. Bartel PR, Loock M, van der Meyden C et al. (1995). Hypertension and sleep apnea in black South Africans. A case control study. Am J Hypertens 8 (12 Pt 1): 1200–1205. Bassetti C, Gugger M, Bischof M et al. (2003). The narcoleptic borderland: a multimodal diagnostic approach including cerebrospinal fluid levels of hypocretin-1 (orexin A). Sleep Med 4 (1): 7–12. Bayes RT (1763). An essay toward solving a problem in the doctrine of chance. Philo Trans Royal Soc 53: 370–418. Bearpark H, Elliott L, Grunstein R et al. (1995). Snoring and sleep apnea. A population study in Australian men. Am J Respir Crit Care Med 151 (5): 1459–1465. Becker PM (2006). Insomnia: prevalence, impact, pathogenesis, differential diagnosis, and evaluation. Psychiatr Clin North Am 29 (4): 855–870; abstract vii. Berger K, Luedemann J, Trenkwalder C et al. (2004). Sex and the risk of restless legs syndrome in the general population. Arch Intern Med 164 (2): 196–202. Berg Kelly K, Ehrver M, Erneholm T et al. (1991). Selfreported health status and use of medical care by 3500 adolescents in Western Sweden. Acta Pediatr Scand 80: 837–843. Bergler W, Maleck W, Baker-Schreyer A et al. (1997). Der Mallampati-Score. Vorhersage der schwierigen Intubation in der HNO-Laserchirurgie mittels MallampatiScore. [The Mallampati Score. Prediction of difficult intubation in otolaryngologic laser surgery by Mallampati Score.]. Anaesthesist 46 (5): 437–440. Berwick D, Murphy J, Goldman P et al. (1991). Performance of a five-item mental health screening test. Med Care 29: 169–176. Bhowmik D, Bhatia M, Gupta S et al. (2003). Restless legs syndrome in hemodialysis patients in India: a case controlled study. Sleep Med 4 (2): 143–146. Bhowmik D, Bhatia M, Tiwari S et al. (2004). Low prevalence of restless legs syndrome in patients with advanced chronic renal failure in the Indian population: a case controlled study. Ren Fail 26 (1): 69–72. Billiard M, Alperovitch A, Perot C et al. (1987). Excessive daytime somnolence in young men: prevalence and contributing factors. Sleep 10: 297–305. Bixler EO, Kales A, Soldatos CR et al. (1979). Prevalence of sleep disorders in the Los Angeles metropolitan area. Am J Psychiatry 136 (10): 1257–1262. Bixler EO, Kales A, Cadieux RJ et al. (1985). Sleep apneic activity in older healthy subjects. J Appl Physiol 58 (5): 1597–1601.
Bixler EO, Vgontzas AN, Ten Have T et al. (1998). Effects of age on sleep apnea in men: I. Prevalence and severity. Am J Respir Crit Care Med 157 (1): 144–148. Bixler EO, Vgontzas AN, Lin HM et al. (2000). Association of hypertension and sleep-disordered breathing. Arch Intern Med 160 (15): 2289–2295. Bixler EO, Vgontzas AN, Lin HM et al. (2001). Prevalence of sleep-disordered breathing in women: effects of gender. Am J Respir Crit Care Med 163 (3 Pt 1): 608–613. Bixler EO, Vgontzas AN, Lin HM et al. (2002). Insomnia in central Pennsylvania. J Psychosom Res 53 (1): 589–592. Bjo¨rvatn B, Leissner L, Ulfberg J et al. (2005). Prevalence, severity and risk factors of restless legs syndrome in the general adult population in two Scandinavian countries. Sleep Med 6 (4): 307–312. Bjo¨rvatn B, Sagen IM, Oyane N et al. (2007). The association between sleep duration, body mass index and metabolic measures in the Hordaland Health Study. J Sleep Res 16 (1): 66–76. Bliwise DL (2004). Sleep disorders in Alzheimer’s disease and other dementias. Clin Cornerstone 6 (Suppl 1A): S16–S28. Bloom J, Kaltenborn W, Quan S (1988). Risk factors in a general population for snoring. Importance of cigarette smoking and obesity. Chest 93: 678–683. Boeve BF, Saper CB (2006). REM sleep behavior disorder: a possible early marker for synucleinopathies. Neurology 66 (6): 796–797. Bonnet MH, Arand DL (1995). We are chronically sleep deprived. Sleep 18 (10): 908–911. Breslau N, Roth T, Rosenthal L et al. (1996). Sleep disturbance and psychiatric disorders: a longitudinal epidemiological study of young adults. Biol Psychiatry 39 (6): 411–418. Broman JE, Lundh LG, Hetta J (1996). Insufficient sleep in the general population. Neurophysiol Clin 26 (1): 30–39. Brotini S, Gigli GL (2004). Epidemiology and clinical features of sleep disorders in extrapyramidal disease. Sleep Med 5 (2): 169–179. Bull MJ, Givan DC, Sadove AM et al. (1990). Improved outcome in Pierre Robin sequence: effect of multidisciplinary evaluation and management. Pediatrics 86 (2): 294–301. Camp C (1923). Disturbance of sleep. J Michigan Med Soc 22: 133–138. Chakravorty I, Cayton RM, Szczepura A (2002). Health utilities in evaluating intervention in the sleep apnoea/ hypopnoea syndrome. Eur Respir J 20 (5): 1233–1238. Chan J, Sanderson J, Chan W et al. (1997). Prevalence of sleep-disordered breathing in diastolic heart failure. Chest 111 (6): 1488–1493. Chaturvedi S, Adams HP Jr, Woolson RF (1999). Circadian variation in ischemic stroke subtypes. Stroke 30 (9): 1792–1795. Chay OM, Goh A, Abisheganaden J et al. (2000). Obstructive sleep apnea syndrome in obese Singapore children. Pediatr Pulmonol 29 (4): 284–290. Cirignotta F, D’Alessandro R, Partinen M et al. (1989). Prevalence of every night snoring and obstructive sleep
EPIDEMIOLOGY OF SLEEP DISORDERS apnoeas among 30–69-year-old men in Bologna. Italy Acta Neurol Scand 79: 366–372. Clapare`de E (1905). The´orie biologique du sommeil. Archives de Psychologie 4: 245–349. Clemens S, Rye D, Hochman S (2006). Restless legs syndrome: revisiting the dopamine hypothesis from the spinal cord perspective. Neurology 67 (1): 125–130. Cohen J (1988). Statistical Power Analysis for the Behavioral Sciences. 2nd edn. Lawrence Earlbaum Associates, Hillsdale, NJ. Cohen MM Jr (1991). Hallermann–Streiff syndrome: a review. Am J Med Genet 41 (4): 488–499. Cole MG, Dendukuri N (2003). Risk factors for depression among elderly community subjects: a systematic review and meta-analysis. Am J Psychiatry 160 (6): 1147–1156. Cook RJ, Sackett DL (1995). The number needed to treat: a clinically useful measure of treatment effect. Br Med J 310: 452–454. Corbo G, Fuciarelli F, Foresi A et al. (1989). Snoring in children: association with respiratory symptoms and passive smoking. Br Med J 299: 1491–1494. Costa e Silva JA, Chase M, Sartorius N et al. (1996). Special report from a symposium held by the World Health Organization and the World Federation of Sleep Research Societies: an overview of insomnias and related disorders – recognition, epidemiology, and rational management. Sleep 19 (5): 412–416. Crancer AJ, McMurray L (1968). Accident and violation rates of Washington’s medically restricted drivers. JAMA 205 (5): 272–276. D’Alessandro R, Magelli C, Gamberini G et al. (1990). Snoring every night as a risk factor for myocardial infarction: a case-control study. Br Med J 300: 1557–1558. Dauvilliers Y, Baumann CR, Carlander B et al. (2003a). CSF hypocretin-1 levels in narcolepsy, Kleine-Levin syndrome, and other hypersomnias and neurological conditions. J Neurol Neurosurg Psychiatry 74 (12): 1667–1673. Dauvilliers Y, Carlander B, Molinari N et al. (2003b). Month of birth as a risk factor for narcolepsy. Sleep 26 (6): 663–665. Davies JR, Stradling JR (1990). The relationship between neck circumference, radiographic pharyngeal anatomy, and the obstructive sleep apnoea syndrome. Eur Respir J 3: 509–514. Dement W, Zarcone V, Varner V et al. (1972). The prevalence of narcolepsy. Sleep Research 1: 148. Dement WC, Caiskadon M, Ley R (1973). The prevalence of narcolepsy II. Sleep Research 2: 147. de Miguel-Diez J, Villa-Asensi JR, Alvarez-Sala JL (2003). Prevalence of sleep-disordered breathing in children with Down syndrome: polygraphic findings in 108 children. Sleep 26 (8): 1006–1009. Dimsdale JE, Loredo JS, Profant J (2000). Effect of continuous positive airway pressure on blood pressure: a placebo trial. Hypertension 35 (1 Pt 1): 144–147. Dixon WJ, Massey FJJ (1983). Introduction to Statistical Analysis. McGraw-Hill, New York. Dodge R, Cline MG, Quan SF (1995). The natural history of insomnia and its relationship to respiratory symptoms. Arch Intern Med 155 (16): 1797–1800.
305
Doghramji PP (2006). Trends in the pharmacologic management of insomnia. J Clin Psychiatry 67 (Suppl 13): 5–8. Doherty LS, Kiely JL, Swan V et al. (2005). Long-term effects of nasal continuous positive airway pressure therapy on cardiovascular outcomes in sleep apnea syndrome. Chest 127 (6): 2076–2084. Doi Y, Minowa M, Okawa M et al. (2000). Prevalence of sleep disturbance and hypnotic medication use in relation to sociodemographic factors in the general Japanese adult population. J Epidemiol 10 (2): 79–86. Dukes C (1905). Sleep in relation to education. Journal of the Royal Sanitary Institute 26: 41–44. Ekbom K (1945). Restless legs. Acta Med Scand Suppl 158: 1–123. Elliott WJ (1998). Circadian variation in the timing of stroke onset: a meta-analysis. Stroke 29 (5): 992–996. Elwood P, Hack M, Pickering J et al. (2006). Sleep disturbance, stroke, and heart disease events: evidence from the Caerphilly cohort. J Epidemiol Community Health 60 (1): 69–73. Engleman HM, Martin SE, Deary IJ et al. (1997). Effect of CPAP therapy on daytime function in patients with mild sleep apnoea/hypopnoea syndrome. Thorax 52 (2): 114–119. Engleman HM, Kingshott RN, Wraith PK et al. (1999). Randomized placebo-controlled crossover trial of continuous positive airway pressure for mild sleep apnea/hypopnea syndrome. Am J Respir Crit Care Med 159 (2): 461–467. Enright PL, Newman AB, Wahl PW et al. (1996). Prevalence and correlates of snoring and observed apneas in 5201 older adults. Sleep 19 (7): 531–538. Erkinjuntti T, Partinen M, Sulkava R et al. (1987). Sleep apnea in multiinfarct dementia and Alzheimer’s disease. Sleep 10 (5): 419–425. Feinstein A (1985). Clinical Epidemiology: The Architecture of Clinical Research. WB Saunders, Philadelphia. Ferini-Strambi L, Zucconi M, Castronovo V et al. (1999). Snoring and sleep apnea: a population study in Italian women. Sleep 22 (7): 859–864. Ferini-Strambi L, Manconi M, Fabbrini M et al. (2006). Restless legs syndrome is a common finding in multiple sclerosis and correlates with pyramidal disabililty and cervical cord damage. Sleep 29 (Suppl): A288. Fischer J, Raschke F (1997). Economic and medical significance of sleep-related breathing disorders. Respiration 64 (Suppl 1): 39–44. Flemons WW, Tsai W (1997). Quality of life consequences of sleep-disordered breathing. J Allergy Clin Immunol 99 (2): S750–S756. Fletcher EC (1996). Obstructive sleep apnoea and cardiovascular morbidity. Monaldi Arch Chest Dis 51 (1): 77–80. Fletcher E, DeBehnke R, Lavoi M et al. (1985). Undiagnosed sleep apnea in patients with essential hypertension. Ann Intern Med 103: 190–194. Flier JS, Elmquist JK (2004). A good night’s sleep: future antidote to the obesity epidemic? Ann Intern Med 141 (11): 885–886. Foley DJ, Monjan A, Simonsick EM et al. (1999). Incidence and remission of insomnia among elderly adults: an
306
M. PARTINEN
epidemiologic study of 6800 persons over three years. Sleep 22 (Suppl 2): S366–S372. Ford D, Kamerow D (1989). Epidemiologic study of sleep disturbances and psychiatric disorders. An opportunity for prevention. JAMA 262: 1479–1484. Franceschi M, Zamproni P, Crippa D et al. (1982). Excessive daytime sleepiness: a 1-year study in an unselected inpatient population. Sleep 5: 239–247. Franklin KA, Holmgren PA, Jonsson F et al. (2000). Snoring, pregnancy-induced hypertension, and growth retardation of the fetus. Chest 117 (1): 137–141. Freed G, Pearlman M, Brown A et al. (1988). Polysomnographic indications for surgical intervention in Pierre Robin sequence: acute airway management and followup studies after repair and take-down of tongue-lip adhesion. Cleft Palate J 25 (2): 151–155. Freeman J, Hutchinson G (1980). Prevalence, incidence and duration. Am J Epidemiol 112: 267–271. Friedman M, Tanyeri H, La Rosa M et al. (1999). Clinical predictors of obstructive sleep apnea. Laryngoscope 109 (12): 1901–1907. Friedman M, Landsberg R, Pryor S et al. (2001). The occurrence of sleep-disordered breathing among patients with head and neck cancer. Laryngoscope 111 (11 Pt 1): 1917–1919. Fuyuno G, Kobayashi R, Atsumi Y et al. (1999). Relationship between diabetes mellitus-associated obstructive sleep apnea syndrome and hyperinsulinemia. Nihon Kokyuki Gakkai Zasshi 37 (9): 694–698. Ganguli M, Reynolds CF, Gilby JE (1996). Prevalence and persistence of sleep complaints in a rural older community sample: the movies project. J Am Geriatr Soc 44 (7): 778–784. Gangwisch JE, Heymsfield SB, Boden-Albala B et al. (2006). Short sleep duration as a risk factor for hypertension: analyses of the first National Health and Nutrition Examination Survey [see comment]. Hypertension 47 (5): 833–839. Garnier M, Delamare V (2009). Dictionnaire illustre´ des termes de me´decine. 30th edn. Maloine, Paris. Gemignani F, Marbini A, Di GG et al. (1997). Cryoglobulinaemic neuropathy manifesting with restless legs syndrome. J Neurol Sci 152 (2): 218–223. Gemignani F, Brindani F, Vitetta F et al. (2007). Restless legs syndrome in diabetic neuropathy: a frequent manifestation of small fiber neuropathy. J Peripher Nerv Syst 12 (1): 50–53. Gillis AM (1985). Cardiac arrhythmias during sleep. Compr Ther 11 (11): 66–71. Gislason T, Benediktsdottir B (1995). Snoring, apneic episodes, and nocturnal hypoxemia among children 6 months to 6 years old. An epidemiologic study of lower limit of prevalence. Chest 107: 963–966. Gislason T, Aberg H, Taube A (1987). Snoring and systemic hypertension – an epidemiological study. Acta Med Scand 222: 415–421. Gislason T, Almqvist M, Eriksson G et al. (1988). Prevalence of sleep apnea syndrome among Swedish men – an epidemiological study. J Clin Epidemiol 41: 571–576.
Gislason T, Benediktsdottir B, Bjornsson J et al. (1993). Snoring, hypertension, and the sleep apnea syndrome. An epidemiologic survey of middle-aged women. Chest 103: 1147–1151. Gjerstad MD, Wentzel-Larsen T, Aarsland D et al. (2007). Insomnia in Parkinson’s disease: frequency and progression over time. J Neurol Neurosurg Psychiatry 78 (5): 476–479. Glass J, Lanctot KL, Herrmann N et al. (2005). Sedative hypnotics in older people with insomnia: meta-analysis of risks and benefits. Br Med J 331 (7526): 1169. Gottlieb DJ, Redline S, Nieto FJ et al. (2006). Association of usual sleep duration with hypertension: the Sleep Heart Health Study. Sleep 29 (8): 1009–1014. Gruber A, Horwood F, Sithole J et al. (2006). Obstructive sleep apnoea is independently associated with the metabolic syndrome but not insulin resistance state. Cardiovasc Diabetol 5: 22. Grugni G, Livieri C, Corrias A et al. (2005). Death during GH therapy in children with Prader–Willi syndrome: description of two new cases. J Endocrinol Invest 28 (6): 554–557. Grunstein RR (1996). Metabolic aspects of sleep apnea. Sleep 19 (10 Suppl): S218–220. Grunstein R, Stenlof K, Hedner J et al. (1995). Impact of obstructive sleep apnea and sleepiness on metabolic and cardiovascular risk factors in the Swedish Obese Subjects (SOS) Study. Int J Obes Relat Metab Disord 19: 410–418. Grunstein RR, Stenlof K, Hedner JA et al. (2007). Two year reduction in sleep apnea symptoms and associated diabetes incidence after weight loss in severe obesity. Sleep 30 (6): 703–710. Hack M, Davies RJ, Mullins R et al. (2000). Randomised prospective parallel trial of therapeutic versus subtherapeutic nasal continuous positive airway pressure on simulated steering performance in patients with obstructive sleep apnoea. Thorax 55 (3): 224–231. Halbower AC, Marcus CL (2003). Sleep disorders in children. Curr Opin Pulm Med 9 (6): 471–476. Hammond E (1964). Some preliminary findings on physical complaints from a prospective study of 1 064 004 men and women. Am J Public Health 54: 11–23. Happe S, Treptau N, Ziegler R et al. (2005). Restless legs syndrome and sleep problems in children and adolescents with insulin-dependent diabetes mellitus type 1. Neuropediatrics 36 (2): 98–103. Haraldsson PO, Carenfelt C, Tingvall C (1992). Sleep apnea syndrome symptoms and automobile driving in a general population. J Clin Epidemiol 45 (8): 821–825. Harding SM (2001). Prediction formulae for sleep-disordered breathing. Curr Opin Pulm Med 7 (6): 381–385. Ha¨rma¨ M, Tenkanen L, Sjo¨blom T et al. (1998). Combined effects of shift work and life-style on the prevalence of insomnia, sleep deprivation and daytime sleepiness. Scand J Work Environ Health 24 (4): 300–307. Hartmann E, Baekeland F, Zwilling G (1972). Psychological differences between long and short sleepers. Arch Gen Psychiatr 26: 463–468.
EPIDEMIOLOGY OF SLEEP DISORDERS Hartz A, Rupley D, Kissebah A et al. (1983). Relationship of obesity to diabetes: influence of obesity level and bodyfat distribution. Prev Med 12: 351–357. Hays JC, Blazer DG, Foley DJ (1996). Risk of napping: excessive daytime sleepiness and mortality in an older community population. J Am Geriatr Soc 44: 693–698. He J, Kryger M, Zorick F et al. (1988). Mortality and apnea index in obstructive sleep apnea. Chest 94: 9–14. Henderson S, Jorm AF, Scott LR et al. (1995). Insomnia in the elderly: its prevalence and correlates in the general population. Med J Aust 162 (1): 22–24. Hening WA (2002). Restless legs syndrome: a sensorimotor disorder of sleep/wake motor regulation. Curr Neurol Neurosci Rep 2 (2): 186–196. Hetzel C, Weess HG, Schroder A et al. (1995). Subjective well-being in obstructive sleep apnea syndrome before and after nCPAP therapy [original article in German]. Wien Med Wochenschr 145 (17–18): 510–511. Hida W, Shindoh C, Okabe S et al. (1993). Prevalence of sleep apnea syndrome in Japanese industrial workers using a home sleep monitor. Sleep 16 (Suppl 8): S126–S127. Hoban TF (2000). Sleeplessness in children with neurodevelopmental disorders. Epidemiology and management. CNS Drugs July 14 (1): 11–22. Hoch B, Hochban W (1998). Four-year-old girl with Goldenhar-sequence and severe obstructive sleep apnea, symptoms, diagnosis and therapy. Int J Pediatr Otorhinolaryngol 43 (3): 277–281. Ho¨gl B, Kiechl S, Willeit J et al. (2005). Restless legs syndrome : a community-based study of prevalence, severity, and risk factors. Neurology 64 (11): 1920–1924. Hohagen F, Grabhoff U, Ellringmann D et al. (1991). The prevalence of insomnia in different age groups and its treatment modalities in general practice. In: SFM Smirne, L Ferini-Strambi (Eds.), Sleep and Ageing. Masson, Milano, pp. 205–215. Honda Y (1979). Census of narcolepsy, cataplexy and sleep life among teen-agers in Fujisawa city. Sleep Res (8): 191. Honda Y, Asaka A, Tanimura M et al. (1983). In: C Guilleminault, E Lugaresi (Eds.), A genetic study of narcolepsy and excessive daytime sleepiness in 308 families with a narcolepsy or hypersomnia proband. Sleep/Wake Disorders: Natural History, Epidemiology, and Long-term Evolution. Raven Press, New York, pp. 187–199. Hu FB, Willett WC, Colditz GA et al. (1999). Prospective study of snoring and risk of hypertension in women. Am J Epidemiol 150 (8): 806–816. Hu F, Willett W, Manson J et al. (2000). Snoring and the risk of cardiovascular disease in women. J Am Coll Cardiol 35: 308–313. Hublin C (1994). Narcolepsy. Epidemiology, Clinical Picture and Treatment. Miina Sillanpa¨a¨ Foundation, Helsinki. Hublin C, Kaprio J (2003). Genetic aspects and genetic epidemiology of parasomnias. Sleep Med Rev 7 (5): 413–421. Hublin C, Kaprio J, Partinen M et al. (1994a). The Ullanlinna narcolepsy scale: validation of a measure of symptoms in the narcoleptic syndrome. J Sleep Res 3: 52–59.
307
Hublin C, Kaprio J, Partinen M et al. (1994b). The prevalence of narcolepsy: an epidemiological study of the Finnish Twin Cohort. Ann Neurol 35 (6): 709–716. Hublin C, Kaprio J, Partinen M et al. (1996). Daytime sleepiness in an adult, Finnish population. J Int Med 239: 417–423. Hublin C, Kaprio J, Partinen M et al. (2001). Insufficient sleep–a population-based study in adults. Sleep 24 (4): 392–400. Hui DS, Chan JK, Ho AS et al. (1999). Prevalence of snoring and sleep-disordered breathing in a student population. Chest 116 (6): 1530–1536. Hung J, Whitford E, Parsons R et al. (1990). Association of sleep apnoea with myocardial infarction in men. Lancet 336: 261–264. Husby R, Lingjaerde O (1990). Prevalence of reported sleeplessness in northern Norway in relation to sex, age and season. Acta Psychiatr Scand 81: 542–547. Hyyppa¨ M, Kronholm E (1989). Quality of sleep and chronic illnesses. J Clin Epidemiol 42: 633–638. Inoue Y, Hiroe Y, Nishida M et al. (2000). Sleep problems in Japanese industrial workers. Psychiatry Clin Neurosci 54 (3): 294–295. Ip MSM, Tsang WT, Lam WK et al. (1998). Obstructive sleep apnea syndrome: an experience in Chinese adults in Hong Kong. Chin Med J 111 (3): 257–260. Issa F, Sullivan C (1982). Alcohol, snoring and sleep apnea. J Neurol Neurosurg Psychiatry 45: 353–359. Janson C, De Backer W, Gislason T et al. (1996). Increased prevalence of sleep disturbances and daytime sleepiness in subjects with bronchial asthma: a population study of young adults in three European countries. Eur Respir J 9 (10): 2132–2138. Janson C, Lindberg E, Gislason T et al. (2001). Insomnia in men – a 10-year prospective population based study. Sleep 24 (4): 425–430. Javaheri S (2003). Heart failure and sleep apnea: emphasis on practical therapeutic options. Clin Chest Med 24 (2): 207–222. Javaheri S (2006). Sleep disorders in systolic heart failure: a prospective study of 100 male patients. The final report. Int J Cardiol 106 (1): 21–28. Javaheri S, Parker T, Wexler L et al. (1995). Occult sleepdisordered breathing in stable congestive heart failure. Ann Intern Med 122: 487–492. Jenicek M, Cle´roux R (1982). E´pide´miologie: principes, techniques, applications. Edisem, St. Hyacinthe, Que´bec. Jennum P, Schultz-Larsen K, Davidsen M et al. (1994). Snoring and risk of stroke and ischaemic heart disease in a 70 year old population. A 6-year follow-up study. Int J Epidemiol 23 (6): 1159–1164. Jennum P, Hein JO, Suadicani P et al. (1995). Risk of ischemic heart disease in self-reported snorers. A prospective study of 2937 men aged 54 to 74 years: the Copenhagen male study. Chest 108: 138–142. Jennum P, Schultz-Larsen K, Christensen NJ (1996). Snoring and atherosclerotic manifestations in a 70-year-old. Eur J Epidemiol 12 (3): 285–290.
308
M. PARTINEN
Jimenez-Conde J, Ois A, Rodriguez-Campello A et al. (2007). Does sleep protect against ischemic stroke? Less frequent ischemic strokes but more severe ones. J Neurol 254 (6): 782–788. Johns M, Hocking B (1997). Daytime sleepiness and sleep habits of Australian workers. Sleep 20 (10): 844–849. Johns M, Gay T, Goodyear M et al. (1971). Sleep habits of healthy young adults: use of a sleep questionnaire. Br J Prev Soc Med 25: 236–241. Johnson EO, Roth T (2006). An epidemiologic study of sleep-disordered breathing symptoms among adolescents. Sleep 29 (9): 1135–1142. Kales A, Bixler EO, Cadieux RJ et al. (1984). Sleep apnoea in a hypertensive population. Lancet ii: 1005–1008. Kaneita Y, Ohida T, Uchiyama M et al. (2005). Excessive daytime sleepiness among the Japanese general population. J Epidemiol 15 (1): 1–8. Karacan I, Thornby JI, Anch M et al. (1976). Prevalence of sleep disturbance in a primary urban Florida county. Soc Sci Med (10): 239–244. Katz I, Stradling J, Slutsky S et al. (1990). Do patients with obstructive sleep apnea have thick necks? Am Rev Respir Dis 141: 1228–1231. Kavanagh D, Siddiqui S, Geddes CC (2004). Restless legs syndrome in patients on dialysis. Am J Kidney Dis 43 (5): 763–771. Kayukawa Y, Kogawa S, Tadano F et al. (1998). Sleep problems in the aged in relation to senility. Psychiatry Clin Neurosci 52 (2): 190–192. Khosla T, Lowe F (1967). Indices of obesity derived from body weight and height. Br J Prev Soc Med 21: 122–128. Kim K, Uchiyama M, Okawa M et al. (2000). An epidemiological study of insomnia among the Japanese general population. Sleep 23 (1): 41–47. Kim K, Uchiyama M, Liu X et al. (2001). Somatic and psychological complaints and their correlates with insomnia in the Japanese general population. Psychosom Med 63 (3): 441–446. Kim J, Choi C, Shin K et al. (2005). Prevalence of restless legs syndrome and associated factors in the Korean adult population: the Korean Health and Genome Study. Psychiatry Clin Neurosci 59 (3): 350–353. Kiuru S, Nieminen T, Partinen M (1999). Obstructive sleep apnoea syndrome in hereditary gelsolin-related amyloidosis. J Sleep Res 8 (2): 143–149. Klink M, Quan SF (1987). Prevalence of reported sleep disturbances in a general adult population and their relationship to obstructive airway diseases. Chest 91: 540–546. Knutson KL, Spiegel K, Penev P et al. (2007). The metabolic consequences of sleep deprivation. Sleep Med Rev 11 (3): 163–178. Kohatsu ND, Tsai R, Young T et al. (2006). Sleep duration and body mass index in a rural population. Arch Intern Med 166 (16): 1701–1705. Kohler U, Bredenbroker D, Fus E et al. (1998). [Cardiac arrhythmias in sleep apnea. Increased cardiovascular risk
caused by nocturnal arrhythmia?]. Fortschr Med 116 (16): 28–31. Kojima M, Wakai K, Kawamura T et al. (2000). Sleep patterns and total mortality: a 12-year follow-up study in Japan. J Epidemiol 10 (2): 87–93. Koskenvuo M, Partinen M, Kaprio J (1985a). Snoring and disease. Ann Clin Res 17: 247–251. Koskenvuo M, Kaprio J, Partinen M et al. (1985b). Snoring as a risk factor for hypertension and angina pectoris. Lancet 1 (8434): 893–896. Koskenvuo M, Kaprio J, Telakivi T et al. (1987). Snoring as a risk factor for ischaemic heart disease and stroke in men. Br Med J 294 (6563): 16–19. Koskenvuo M, Partinen M, Kaprio J et al. (1994). Snoring and cardiovascular risk factors. Ann Med 26 (5): 371–376. Kotagal P, Costa M, Wyllie E et al. (2002). Paroxysmal nonepileptic events in children and adolescents. Pediatrics 110 (4): e46. Kraemer HC, Thiemann S (1987). How Many Subjects?. Sage Publications, Newbury Park. Kripke DF, Ancoli-Israel S, Klauber MR et al. (1997). Prevalence of sleep-disordered breathing in ages 40–64 years: a population-based survey. Sleep 20 (1): 65–76. Kripke DF, Klauber MR, Wingard DL et al. (1998). Mortality hazard associated with prescription hypnotics. Biol Psychiatry 43: 687–693. Kripke DF, Garfinkel L, Wingard DL et al. (2002). Mortality associated with sleep duration and insomnia. Arch Gen Psychiatry 59 (2): 131–136. Kryger MH, Roos L, Delaive K et al. (1996). Utilization of health care services in patients with severe obstructive sleep apnea. Sleep 19 (9 Suppl): S111–S116. Kumar S, Bhatia M, Behari M (2002). Sleep disorders in Parkinson’s disease. Mov Disord 17 (4): 775–781. Kuppermann M, Lubeck DP, Mazonson PD et al. (1995). Sleep problems and their correlates in a working population. J Gen Intern Med 10: 10–32. Kushida CA, Efron B, Guilleminault C (1997). A predictive morphometric model for the obstructive sleep apnea syndrome. Ann Intern Med 127 (8 Pt 1): 581–587. Kutner NG, Bliwise DL (2002). Restless legs complaint in African-American and Caucasian hemodialysis patients. Sleep Med 3 (6): 497–500. Lack L, Miller W, Turner D (1988). A survey of sleeping difficulties in an Australian population. Community Health Stud 12: 200–207. Ladame C (1923). Du sommeil et de quelques-unes de ses modalite´s chez les aliens. Schweiz Arch Neurol Psychiat 13: 371–390. Laird D (1931). The sleep habits of 509 men of distinction. American Journal of Medical Sciences 37: 271–275. Lakka HM, Lakka TA, Tuomilehto J et al. (2002). Abdominal obesity is associated with increased risk of acute coronary events in men. Eur Heart J 23 (9): 706–713. Lapidus L, Bengtsson C (1988). Regional obesity as a health hazard in women – a prospective study. Acta Med Scand 723 (Suppl): 53–59.
EPIDEMIOLOGY OF SLEEP DISORDERS Larsen JP, Tandberg E (2001). Sleep disorders in patients with Parkinson’s disease: epidemiology and management. CNS Drugs 15 (4): 267–275. Last J (1983). A Dictionary of Epidemiology. Oxford University Press, New York. Lavie P (1983). Sleep apnea in industrial workers. In: C Guilleminault, E Lugaresi (Eds.), Sleep/Wake Disorders: Natural History, Epidemiology, and Long-Term Evolution. Raven Press, New York, pp. 127–135. Lavie P, Peled R (1987). Narcolepsy is a rare disease in Israel. Sleep 10: 608–609. Lavie P, Ben-Yosef R, Rubin A (1984). Prevalence of sleep apnea among patients with essential hypertension. Am Heart J 108: 373–376. Lavie P, Herer P, Peled R et al. (1995). Mortality in sleep apnea patients: a multivariate analysis of risk factors. Sleep 18: 149–157. Lavie P, Herer P, Hoffstein V (2000). Obstructive sleep apnoea syndrome as a risk factor for hypertension: population study. BMJ 320 (7233): 479–482. Lavigne GJ, Montplaisir JY (1994). Restless legs syndrome and sleep bruxism: prevalence and association among Canadians. Sleep 17 (8): 739–743. Lee MS, Choi YC, Lee SH et al. (1996). Sleep-related periodic leg movements associated with spinal cord lesions. Mov Disord 11 (6): 719–722. Lee KA, Zaffke ME, Baratte-Beebe K (2001). Restless legs syndrome and sleep disturbance during pregnancy: the role of folate and iron. J Womens Health Gend Based Med 10 (4): 335–341. Leineweber C, Kecklund G, Akerstedt T et al. (2003). Snoring and the metabolic syndrome in women. Sleep Med 4 (6): 531–536. Leppa¨vuori A, Pohjasvaara T, Vataja R et al. (2002). Insomnia in ischemic stroke patients. Cerebrovasc Dis 14 (2): 90–97. Liljenberg B, Almqvist M, Hetta J et al. (1988). The prevalence of insomnia: the importance of operationally defined criteria. Ann Clin Res 20: 393–398. Lindberg E, Janson C, Svardsudd K et al. (1998). Increased mortality among sleepy snorers: a prospective population based study [see comments]. Thorax 53 (8): 631–637. Lindberg E, Berne C, Franklin KA et al. (2007). Snoring and daytime sleepiness as risk factors for hypertension and diabetes in women – a population-based study. Respir Med 101: 1283–1290. Lindblom N, Heiskala H, Kaski M et al. (2002). Sleep fragmentation in mentally retarded people decreases with increasing daylength in spring. Chronobiol Int 19 (2): 441–459. Liu X, Uchiyama M, Kim K et al. (2000). Sleep loss and daytime sleepiness in the general adult population of Japan. Psychiatry Res 93 (1): 1–11. Logan AG, Perlikowski SM, Mente A et al. (2001). High prevalence of unrecognized sleep apnoea in drug-resistant hypertension. J Hypertens 19 (12): 2271–2277. Lojander J, Maasilta P, Partinen M et al. (1996). Nasal-CPAP, surgery, and conservative management for treatment of
309
obstructive sleep apnea syndrome. A randomized study. Chest 110 (1): 114–119. Lugaresi E, Coccagna G, Farneti P et al. (1975). Snoring. Electroencephalogr Clin Neurophysiol 39: 59–64. Lugaresi E, Cirignotta F, Coggagna G et al. (1980). Some epidemiological data on snoring and cardiocirculatory disturbances. Sleep 3: 221–224. Lugaresi E, Cirignotta F, Zucconi M et al. (1983a). Good and poor sleepers: an epidemiological survey of the San Marino population. In: C Guilleminault, E Lugaresi (Eds.), Sleep/ Wake Disorders: Natural History, Epidemiology, and LongTerm Evolution. Raven Press, New York, pp. 1–12. Lugaresi E, Mondini S, Zucconi M et al. (1983b). Staging of heavy snorers’ disease. A proposal. Bull Eur Physiopathol Respir 19: 590–594. McColley SA, Carroll JL, Curtis S et al. (1997). High prevalence of allergic sensitization in children with habitual snoring and obstructive sleep apnea. Chest 111 (1): 170–173. McGhie A, Russell S (1962). The subjective assessment of normal sleep patterns. J Ment Sci 108: 642–654. McKeigue PM, Shah B, Marmot MG (1991). Relation of central obesity and insulin resistance with high diabetes prevalence and cardiovascular risk in South Asians. Lancet 337 (8738): 382–386. Mahowald MW, Ettinger MG (1990). Things that go bump in the night: the parasomnias revisited. J Clin Neurophysiol 7 (1): 119–143. Malone S, Liu PP, Holloway R et al. (1991). Obstructive sleep apnoea in patients with dilated cardiomyopathy: effects of continuous positive airway pressure. Lancet 338 (8781): 1480–1484. Manconi M, Govoni V, De Vito A et al. (2004). Restless legs syndrome and pregnancy. Neurology 63 (6): 1065–1069. Mant A, Saunders NA, Eyland AE et al. (1988). Sleeprelated respiratory disturbance and dementia in elderly females. J Gerontol 43 (5): M140–M144. Mant A, King M, Saunders NA et al. (1995). Four-year follow-up of mortality and sleep-related respiratory disturbance in non-demented seniors. Sleep 18 (6): 433–438. Marin JM, Gascon JM, Carrizo S et al. (1997). Prevalence of sleep apnoea syndrome in the Spanish adult population. Int J Epidemiol 26 (2): 381–386. Marsh IEE, Biller J, Adams H et al. (1990). Circadian variation in onset of acute ischemic stroke. Arch Neurol 47: 1178–1180. Marshall J (1977). Diurnal variation in occurrence of strokes. Stroke 8: 230–231. Marshall NS, Wong KK, Liu PY et al. (2008). Sleep apnea as an independent risk factor for all-cause mortality: the Busselton Health Study. Sleep 31 (8): 1079–1085. Martikainen K, Hasan J, Urponen H et al. (1992). Daytime sleepiness: a risk factor in community life. Acta Neurol Scand 86 (4): 337–341. Martikainen K, Partinen M, Urponen H et al. (1994). Natural evolution of snoring: a 5-year follow-up study. Acta Neurol Scand 90: 437–442. Martikainen K, Partinen M, Hasan J et al. (1998). Natural evolution of sleepiness. A 5-year follow-up study in a middle-aged population. Eur J Neurol 5 (4): 355–363.
310
M. PARTINEN
Melamed S, Oksenberg A (2002). Excessive daytime sleepiness and risk of occupational injuries in non-shift daytime workers. Sleep 25 (3): 315–322. Merlino G, Frattici L, Valente M et al. (2007). Association of restless legs syndrome in type 2 diabetes: a case-control study. Sleep 30 (7): 866–871. Miettinen O (1985). Theoretical Epidemiology. Principles of Occurrence Research in Medicine. John Wiley, New York. Minai OA, Golish JA, Yataco JC et al. (2007). Restless legs syndrome in lung transplant recipients. J Heart Lung Transplant 26 (1): 24–29. Mitchell ES, Woods NF (1996). Symptom experiences of midlife women: observations from the Seattle Midlife Women’s Health Study. Maturitas 25: 1–10. Mitler M, Dawson A, Henriksen S et al. (1988). Bedtime ethanol increases resistance of upper airways and produces sleep apneas in asymptomatic snorers. Alcoholism 12: 801–805. Montplaisir J (2004). Abnormal motor behavior during sleep. Sleep Med 5 (Suppl 1): S31–S34. Montserrat JM, Ferrer M, Hernandez L et al. (2001). Effectiveness of CPAP treatment in daytime function in sleep apnea syndrome: a randomized controlled study with an optimized placebo. Am J Respir Crit Care Med 164 (4): 608–613. Morgan K, Clarke D (1997). Longitudinal trends in late-life insomnia: implications for prescribing. Age Ageing 26 (3): 179–184. Mucsi I, Molnar Miklos Z, Ambrus C et al. (2005). Restless legs syndrome, insomnia and quality of life in patients on maintenance dialysis. Nephrol Dial Transplant 20 (3): 571–577. Nausieda PA, Weiner WJ, Kaplan LR et al. (1982). Sleep disruption in the course of chronic levodopa therapy: an early feature of the levodopa psychosis. Clin Neuropharmacol 5 (2): 183–194. Neau J-P, Ingrand P, Paquereau J et al. (1994). Habitual snoring as a risk factor for cerebral infarction. J Sleep Res 3 (Suppl 1): 177. Neau J, Meurice J, Paquereau J et al. (1995). Habitual snoring as a risk factor for brain infarction. Acta Neurol Scand 92 (1): 63–68. Neven AK, Middelkoop HA, Kemp B et al. (1998). The prevalence of clinically significant sleep apnoea syndrome in The Netherlands. Thorax 53 (8): 638–642. Ng TP, Seow A, Tan WC (1998). Prevalence of snoring and sleep breathing-related disorders in Chinese, Malay and Indian adults in Singapore. Eur Respir J 12 (1): 198–203. Nieminen P, Tolonen U, Lopponen H et al. (1997). Snoring children: factors predicting sleep apnea. Acta Otolaryngol (Suppl 529): 190–194. Nieminen P, Lopponen H, Vayrynen M et al. (2000). Nasalance scores in snoring children with obstructive symptoms. Int J Pediatr Otorhinolaryngol 52 (1): 53–60. Nieto FJ, Young TB, Lind BK et al. (2000). Association of sleep-disordered breathing, sleep apnea, and hypertension in a large community-based study. Sleep Heart Health Study. JAMA 283 (14): 1829–1836.
Nishino S, Ripley B, Overeem S et al. (2001). Low cerebrospinal fluid hypocretin (Orexin) and altered energy homeostasis in human narcolepsy. Ann Neurol 50 (3): 381–388. Noda A, Okada T, Yasuma F et al. (1998). Prognosis of the middle-aged and aged patients with obstructive sleep apnea syndrome. Psychiatry Clin Neurosci 52 (1): 79–85. Ohayon M (1996). Epidemiological study on insomnia in the general population. Sleep 19 (3 Suppl): S7–S15. Ohayon MM (1997). Prevalence of DSM-IV diagnostic criteria of insomnia: distinguishing insomnia related to mental disorders from sleep disorders. J Psychiatr Res 31 (3): 333–346. Ohayon MM (2005). Prevalence and correlates of nonrestorative sleep complaints. Arch Intern Med 165 (1): 35–41. Ohayon MM, Caulet M (1996). Psychotropic medication and insomnia complaints in two epidemiological studies. Can J Psychiatry 41 (7): 457–464. Ohayon MM, Partinen M (2002). Insomnia and global sleep dissatisfaction in Finland. J Sleep Res 11 (4): 339–346. Ohayon MM, Roth T (2002). Prevalence of restless legs syndrome and periodic limb movement disorder in the general population. J Psychosom Res 53 (1): 547–554. Ohayon MM, Priest RG, Caulet M et al. (1996). Hypnagogic and hypnopompic hallucinations: pathological phenomena? Br J Psychiatry 169 (4): 459–467. Ohayon MM, Caulet M, Priest RG et al. (1997a). DSM-IV and ICSD-90 insomnia symptoms and sleep dissatisfaction. Br J Psychiatry 171: 382–388. Ohayon MM, Caulet M, Guilleminault C (1997b). How a general population perceives its sleep and how this relates to the complaint of insomnia. Sleep 20 (9): 715–723. Ohayon MM, Guilleminault C, Priest RG et al. (1997c). Snoring and breathing pauses during sleep: telephone interview survey of a United Kingdom population sample. Br Med J 314 (7084): 860–863. Ohayon MM, Caulet M, Philip P et al. (1997d). How sleep and mental disorders are related to complaints of daytime sleepiness. Arch Intern Med 157 (22): 2645–2652. Ohayon MM, Priest RG, Zulley J et al. (2002). Prevalence of narcolepsy symptomatology and diagnosis in the European general population. Neurology 58 (12): 1826–1833. Ohida T, Osaki Y, Doi Y et al. (2004). An epidemiologic study of self-reported sleep problems among Japanese adolescents. Sleep 27 (5): 978–985. Ohta Y, Okada T, Kawakami Y et al. (1993). Prevalence of risk factors for sleep apnea in Japan: a preliminary report. Sleep 16 (8 Suppl): S6–S7. Oka Y, Inoue Y, Kanbayashi T et al. (2006). Narcolepsy without cataplexy: 2 subtypes based on CSF hypocretin1/orexin-A findings. Sleep 29 (11): 1439–1443. O’Keeffe S, Noel J, Lavan JN (1993). Restless legs syndrome in the elderly. Postgrad Med J 69 (815): 701–703. Olson L, King M, Hensley MJ et al. (1995). A community study of snoring and sleep-disordered breathing. Prevalence. Am J Respir Crit Care Med 152 (2): 711–716. Ondze´ B, Lubin S, Lavandier B et al. (1998). Frequency of narcolepsy in the population of a French “de´partement”. J Sleep Res 7 (Suppl 2): 193.
EPIDEMIOLOGY OF SLEEP DISORDERS Otsuka K, Sadakane N, Ozawa T (1987). Arrhythmogenic properties of disordered breathing during sleep in patients with cardiovascular disorders. Clin Cardiol 10: 771–782. ¨ zdemir L, Akkurt I, Sumer H et al. (2005). The prevalence O of sleep related disorders in Sivas, Turkey. Tuberk Toraks 53 (1): 20–27. Paavilainen P, Korhonen I, Lo¨tjo¨nen J et al. (2005). Circadian activity rhythm in demented and non-demented nursinghome residents measured by telemetric actigraphy. J Sleep Res 14 (1): 61–68. Pallesen S, Nordhus IH, Omvik S et al. (2007). Prevalence and risk factors of subjective sleepiness in the general adult population. Sleep 30 (5): 619–624. Paloma¨ki H (1991). Snoring and the risk of ischemic brain infarction. Stroke 22 (8): 1021–1025. Paloma¨ki H, Partinen M, Juvela S et al. (1989). Snoring as a risk factor for sleep-related brain infarction. Stroke 20 (10): 1311–1315. Parish JM, Somers VK (2004). Obstructive sleep apnea and cardiovascular disease. Mayo Clin Proc 79 (8): 1036–1046. Partinen M (1982). Sleeping habits and sleep disorders on Finnish men before, during and after military service. Ann Med Milit Fenn 57 (Suppl 1): 1–96. Partinen M (1997). Sleep disorder related to Parkinson’s disease. J Neurol 244 (4 Suppl 1): S3–S6. Partinen M, Gislason T (1995). Basic Nordic Sleep Questionnaire (BNSQ): a quantitated measure of subjective sleep complaints. J Sleep Res 4 (S1): 150–155. Partinen M, Guilleminault C (1990). Daytime sleepiness and vascular morbidity at seven-year follow-up in obstructive sleep apnea patients. Chest 97: 27–32. Partinen M, Hublin C (2000). Epidemiology of sleep disorders. In: MRT Kryger, WC Dement (Eds.), Principles and Practice of Sleep Medicine. 3rd edn. Saunders, New York, pp. 558–579. Partinen M, Paloma¨ki H (1985). Snoring and cerebral infarction. Lancet ii (8468): 1325–1326. Partinen M, Rimpela¨ M (1982). Sleeping habits and sleep disorders in a population of 2016 Finnish adults. In: The Yearbook of Health Education Research 1982, The National Board of Health, Finland, Helsinki, pp. 253–260. Partinen M, Telakivi T (1992). Epidemiology of obstructive sleep apnea syndrome. Sleep 15 (Suppl 6): S1–S4. Partinen M, Putkonen PT, Kaprio J et al. (1982). Sleep disorders in relation to coronary heart disease. Acta Med Scand 660: 69–83. Partinen M, Kaprio J, Koskenvuo M et al. (1983a). Sleeping habits, sleep quality and use of sleeping pills: a population study of 31 140 adults in Finland. In: C Guilleminault, E Lugaresi (Eds.), Sleep/Wake Disorders: Natural History, Epidemiology and Long-Term Evaluation. Raven Press, New York, pp. 29–35. Partinen M, Kaprio J, Koskenvuo M et al. (1983b). Snoring and hypertension: a cross-sectional study on 12 808 Finns aged 24–65 years. Sleep Res 12: 273. Partinen M, Alihanka J, Lang H et al. (1983c). Myocardial infarction in relation to sleep apneas. Sleep Res 12: 272.
311
Partinen M, Eskelinen L, Tuomi K (1984). Complaints of insomnia in different occupations. Scand J Work Environ Health 10 (6 Spec No): 467–469. Partinen M, Jamieson A, Guilleminault C (1986). Mortality of patients with obstructive aleep apnea syndrome: a follow-up study. Sleep Res 15: 153. Partinen M, Jamieson A, Guilleminault C (1988). Long-term outcome for obstructive sleep apnea syndrome patients. Mortality. Chest 94: 1200–1204. Partinen M, Kaprio J, Hublin C et al. (1998). Habitual snoring and coronary heart disease in men aged 40–65 years: a prospective study. J Sleep Res 7 (Suppl 2): 200. Paulus W, Schomburg ED (2006). Dopamine and the spinal cord in restless legs syndrome: does spinal cord physiology reveal a basis for augmentation? Sleep Med Rev 10 (3): 185–196. Peiser J, Ovnat A, Uwyyed K et al. (1985). Cardiac arrhythmias during sleep in morbidly obese sleep-apneic patients before and after gastric bypass surgery. Clin Cardiol 8 (10): 519–521. Peker Y, Hedner J, Kraiczi H et al. (2000). Respiratory disturbance index: an independent predictor of mortality in coronary artery disease. Am J Respir Crit Care Med 162 (1): 81–86. Pekkarinen T, Partinen M, Pelkonen R et al. (1987). Sleep apnoea and daytime sleepiness in acromegaly: relationship to endocrinological factors. Clin Endocrinol (Oxf) 27 (6): 649–654. Peppard PE, Young T, Palta M et al. (2000). Prospective study of the association between sleep-disordered breathing and hypertension. N Engl J Med 342 (19): 1378–1384. Peter J, Siegrist J, Podszus T et al. (1985). Prevalence of sleep apnea in healthy industrial workers. Klin Wochenschr 63: 807–811. Petit D, Touchette E, Tremblay RE et al. (2007). Dyssomnias and parasomnias in early childhood. Pediatrics 119 (5): e1016–e1025. Phillips B, Mannino DM (2005). Does insomnia kill? Sleep 28 (8): 965–971. Phillips B, Berry D, Schmitt F et al. (1994). Sleep-disordered breathing in healthy aged persons: two- and three-year follow-up. Sleep 17 (5): 411–415. Phillips B, Young T, Finn L et al. (2000). Epidemiology of restless legs symptoms in adults. Arch Intern Med 160 (14): 2137–2141. Polydefkis MM, Allen RPP, Hauer P et al. (2000). Subclinical sensory neuropathy in late-onset restless legs syndrome. Neurology 55 (8): 1115–1121. Porthan KM, Melin JH, Kupila JT et al. (2004). Prevalence of sleep apnea syndrome in lone atrial fibrillation: a case-control study. Chest 125 (3): 879–885. Postuma RB, Lang AE, Massicotte-Marquez J et al. (2006). Potential early markers of Parkinson disease in idiopathic REM sleep behavior disorder. Neurology 66 (6): 845–851. Potsic W, Pasquariello P, Baranak C et al. (1986). Relief of upper airway obstruction by adenotonsillectomy. Otolaryngol Head Neck Surg 94: 476–480.
312
M. PARTINEN
Poza JJ, Martinez A, Emparanza JI et al. (2000). Sleep apnea syndrome and cerebral infarction. Neurologia 15 (1): 3–7. Pressman MR (2007). Factors that predispose, prime and precipitate NREM parasomnias in adults: clinical and forensic implications. Sleep Med Rev 11 (1): 5–30; discussion 1–3. Pugh M (Ed.), (2000). Stedman’s Medical Dictionary. 27th edn. Lippincott Williams & Wilkins, Philadelphia. Puvanendran K, Goh KL (1999). From snoring to sleep apnea in a Singapore population. Sleep Res online 2 (1): 11–14. Rauscher H, Popp W, Zwick H (1992). Systemic hypertension in snorers with and without sleep apnea. Chest 102: 367–371. Reynolds CF, Kupfer DJ, Taska LS et al. (1985). Sleep apnea in Alzheimer’s dementia: correlation with mental deterioration. J Clin Psychiatry 46 (7): 257–261. Rijsman R, Neven Arie K, Graffelman W et al. (2004). Epidemiology of restless legs in The Netherlands. Eur J Neurol 11 (9): 607–611. Robinson R, White D, Zwillich C (1985). Moderate alcohol ingestion increases upper airway resistance in normal subjects. Am Rev Respir Dis 132: 1238–1241. Ronald J, Delaive K, Roos L et al. (1998). Obstructive sleep apnea patients use more health care resources ten years prior to diagnosis. Sleep Res Online 1 (1): 71–74. Rosekind MR (1992). The epidemiology and occurrence of insomnia. J Clin Psychiatry 53 (Suppl): 4–6. Rosenow F, Reuter S, Deuss U et al. (1996). Sleep apnoea in treated acromegaly: relative frequency and predisposing factors. Clin Endocrinol (Oxf) 45 (5): 563–569. Rosnow RL, Rosenthal R (1996). Computing contrasts, effect sizes, and counternulls on other people’s published data: general procedures for research consumers. Pyschol Methods 1: 331–340. Rossner S, Lagerstrand L, Persson H et al. (1991). The sleep apnoea syndrome in obesity: risk of sudden death. J Intern Med 230: 135–141. Roth B, Buuhova S, Berkova L (1968). Familial sleep paralysis. Schweiz Arch Neurol Neurochir Psychiatr 102: 321–330. Rothdach AJ, Trenkwalder C, Haberstock J et al. (2000). Prevalence and risk factors of RLS in an elderly population: the MEMO study. Memory and Morbidity in Augsburg Elderly. Neurology 54 (5): 1064–1068. Rothman K (1986). Modern epidemiology. Little, Brown, Boston. Rutkove SB, Matheson JK, Logigian EL (1996). Restless legs syndrome in patients with polyneuropathy. Muscle Nerve 19 (5): 670–672. Saarenpa¨a¨-Heikkila¨ O, Rintahaka P, Laippala P et al. (1995). Sleep habits and disorders in Finnish schoolchildren. J Sleep Res 4: 173–182. Salvi F, Montagna P, Plasmati R et al. (1990). Restless legs syndrome and nocturnal myoclonus: initial clinical manifestation of familial amyloid polyneuropathy. J Neurol Neurosurg Psychiatry 53 (6): 522–525. Samsoon GL, Young JR (1987). Difficult tracheal intubation: a retrospective study. Anaesthesia 42 (5): 487–490.
Sanchez-Armengol A, Fuentes-Pradera MA, Capote-Gil F et al. (2001). Sleep-related breathing disorders in adolescents aged 12 to 16 years: clinical and polygraphic findings. Chest 119 (5): 1393–1400. Sanner BM, Zidek W, Laschewski F et al. (1999). Prevalence of ventricular late potentials in patients with obstructive sleep apnea syndrome. Clin Cardiol 22 (3): 219–224. Scammell TE, Nishino S, Mignot E et al. (2001). Narcolepsy and low CSF orexin (hypocretin) concentration after a diencephalic stroke. Neurology 56 (12): 1751–1753. Schafer H, Pauleit D, Sudhop T et al. (2002). Body fat distribution, serum leptin, and cardiovascular risk factors in men with obstructive sleep apnea. Chest 122 (3): 829–839. Schenck CH, Bundlie SR, Mahowald MW (1996). Delayed emergence of a parkinsonian disorder in 38% of 29 older men initially diagnosed with idiopathic rapid eye movement sleep behaviour disorder. Neurology 46 (2): 388–393. Schlesselman JJ (1982). Case-Control Studies. Oxford University Press, New York. Schmidt-Nowara WW, Coultas DB, Wiggins C et al. (1990). Snoring in a Hispanic-American population. Risk factors and association with hypertension and other morbidity. Arch Intern Med 150: 597–601. Schmitt BE, Gugger M, Augustiny K et al. (2000). Prevalence of sleep disorders in an employed Swiss population: results of a questionnaire survey. Schweiz Med Wochenschr 130 (21): 772–778. Scrima L, Hartman P, Hiller F (1989). Effect of three alcohol doses on breathing during sleep in 30–49 year old nonobese snorers and nonsnorers. Alcoholism 13: 420–427. Seppa¨la¨ T, Partinen M, Penttila¨ A et al. (1991). Sudden death and sleeping history among Finnish men. J Intern Med 229 (1): 23–28. Sevim S, Dogu O, Camdeviren H et al. (2003). Unexpectedly low prevalence and unusual characteristics of RLS in Mersin. Turkey. Neurology 61 (11): 1562–1569. Shapiro J, Strome M, Crocker AC (1985). Airway obstruction and sleep apnea in Hurler and Hunter syndromes. Ann Otol Rhinol Laryngol 94 (5 Pt 1): 458–461. Shepard JJ (1992). Hypertension, cardiac arrhythmias, myocardial infarction, and stroke in relation to obstructive sleep apnea. Clin Chest Med 13 (3): 437–458. Shin YK, Yoon IY, Han EK et al. (2008). Prevalence of narcolepsy-cataplexy in Korean adolescents. Acta Neurol Scand 117 (4): 273–278. Silber MH, Krahn LE, Olson EJ et al. (2002). The epidemiology of narcolepsy in Olmsted County, Minnesota: a population-based study. Sleep 25 (2): 197–202. Smirne S, Zucconi M, Ferini-Strambi L et al. (1991). Snoring as a risk factor for acute vascular disorders of heart and brain. In: SFM Smirne, L Ferini-Strambi (Eds.), Sleep and Ageing. Masson, Milan, pp. 107–112. Smirne S, Palazzi S, Zucconi M et al. (1993). Habitual snoring as a risk factor for acute vascular disease. Eur Respir J 6: 1357–1361. Solomon P (1945). Narcolepsy in negroes. Dis Nerv Syst 6: 179–183.
EPIDEMIOLOGY OF SLEEP DISORDERS Spiegel K, Leproult R, Van Cauter E (1999). Impact of sleep debt on metabolic and endocrine function. Lancet 354 (9188): 1435–1439. Spriggs D, French J, Murdy J et al. (1990). Historical risk factors for stroke: a case control study. Age Ageing 19: 280–287. Spriggs DA, French JM, Murdy JM et al. (1992). Snoring increases the risk of stroke and adversely affects prognosis. Q J Med 83: 555–562. Stradling JR, Crosby JH (1991). Predictors and prevalence of obstructive sleep apnoea and snoring in 1001 middle aged men. Thorax 46 (2): 85–90. Suzuki K, Ohida T, Sone T et al. (2003). The prevalence of restless legs syndrome among pregnant women in Japan and the relationship between restless legs syndrome and sleep problems. Sleep 26 (6): 673–677. Taasan V, Block A, Boysen P et al. (1981). Alcohol increases sleep apnea and oxygen saturation in asymptomatic men. Am J Med 71: 240–245. Tachibana H, Izumi T, Honda S et al. (1998). The prevalence and pattern of insomnia in Japanese industrial workers: relationship between psychosocial stress and type of insomnia. Psychiatry Clin Neurosci 52 (4): 397–402. Taheri S, Zeitzer JM, Mignot E (2002). The role of hypocretins (orexins) in sleep regulation and narcolepsy. Annu Rev Neurosci 25: 283–313. Tan YK, Khoo KL, Low JA et al. (1999). Ethnicity, obstructive sleep apnoea and ischaemic heart disease. Ann Acad Med Singapore 28 (2): 214–216. Tan EK, Seah A, See SJ et al. (2001). Restless legs syndrome in an Asian population: a study in Singapore. Mov Disord 16 (3): 577–579. Tashiro T, Kanbayashi T, Iijima S et al. (1992). An epidemiological study on prevalence of narcolepsy in Japanese. J Sleep Res 1 (Suppl 1): 228. Telakivi T, Partinen M, Koskenvuo M et al. (1987). Periodic breathing and hypoxia in snorers and controls: validation of snoring history and association with blood pressure and obesity. Acta Neurol Scand 76: 69–75. Tembl JI, Ferrer JM, Sevilla MT et al. (1999). Neurologic complications associated with hepatitis C virus infection. Neurology 53 (4): 861–864. Thorpy MJ (1990). Handbook of Sleep Disorders. Marcel Dekker, New York. Thorpy MJ, Adler CH (2005). Parkinson’s disease and sleep. Neurol Clin 23 (4): 1187–1208. Tiihonen M, Partinen M, Na¨rva¨nen S (1993). The severity of obstructive sleep apnoea is associated with insulin resistance. J Sleep Res 2: 56–61. Tinuper P, Provini F, Bisulli F et al. (2007). Movement disorders in sleep: guidelines for differentiating epileptic from non-epileptic motor phenomena arising from sleep. Sleep Med Rev 11 (4): 255–267. Tison F, Crochard A, Leger D et al. (2005). Epidemiology of restless legs syndrome in French adults: a nationwide survey: the INSTANT Study. Neurology 65 (2): 239–246. Tousignant P, Cosio MG, Levy RD et al. (1994). Quality adjusted life years added by treatment of obstructive sleep apnea. Sleep 17: 52–60.
313
Trenkwalder C, Paulus W, Walters AS (2005). The restless legs syndrome. Lancet Neurol 4 (8): 465–475. Tsai WH, Remmers JE, Brant R et al. (2003). A decision rule for diagnostic testing in obstructive sleep apnea. Am J Respir Crit Care Med 167 (10): 1427–1432. Tsementzis S, Gilla J, Hitchcock E et al. (1985). Diurnal variation of and activity during the onset of stroke. Neurosurgery 17: 901–904. Tuomilehto H, Peltonen M, Partinen M et al. (2008a). Sleep duration is associated with an increased risk for the prevalence of type 2 diabetes in middle-aged women – the FIN-D2D survey. Sleep Med 9: 221–227. Tuomilehto H, Peltonen M, Partinen M et al. (2008b). Sleepdisordered breathing is related to an increased risk for type 2 diabetes in middle-aged men, but not in women – the FIN-D2D survey. Diabetes Obes Metab 10 (6): 468–475. Ulfberg J, Nystro¨m B (2004). Restless legs syndrome in blood donors. Sleep Med 5 (2): 115–118. Ulfberg J, Nystro¨m B, Carter N et al. (2001a). Prevalence of restless legs syndrome among men aged 18 to 64 years: an association with somatic disease and neuropsychiatric symptoms. Mov Disord 16 (6): 1159–1163. Ulfberg J, Nystro¨m B, Carter N et al. (2001b). Restless legs syndrome among working-aged women. Eur Neurol 46 (1): 17–19. Unruh ML, Levey AS, D’Ambrosio C et al. (2004). Restless legs symptoms among incident dialysis patients: association with lower quality of life and shorter survival. Am J Kidney Dis 43 (5): 900–909. Urponen H, Vuori I, Hasan J et al. (1988). Self-evaluations of factors promoting and disturbing sleep: an epidemiological survey in Finland. Soc Sci Med 26 (4): 443–450. Van de Vijver DAMC, Walley T, Petri H (2004). Epidemiology of restless legs syndrome as diagnosed in UK primary care. Sleep Med 5 (5): 435–440. Van Vliet G, Deal CL, Crock PA et al. (2004). Sudden death in growth hormone-treated children with Prader–Willi syndrome. J Pediatr 144 (1): 129–131. Verkasalo PK, Lillberg K, Stevens RG et al. (2005). Sleep duration and breast cancer: a prospective cohort study. Cancer Res 65 (20): 9595–9600. Villa Asensi JR, de Miguel Diez J (2001). Obstructive sleep apnea syndrome in childhood. An Esp Pediatr 54 (1): 58–64. Vitiello M, Prinz P (1990). Sleep/wake patterns and sleep disorders in Alzheimer’s disease. In: MJ Thorpy (Ed.), Handbook of Sleep Disorders. Marcel Dekker, New York, pp. 703–718. Vorona RD, Winn MP, Babineau TW et al. (2005). Overweight and obese patients in a primary care population report less sleep than patients with a normal body mass index. Arch Intern Med 165 (1): 25–30. Waksberg J (1978). Sampling methods for random digit dialing. J Am Stat Assoc 73: 30–46. Warnes C, Roberts W (1984). The heart in massive (more than 300 pounds or 136 kilograms) obesity: analysis of 12 patients studied at necropsy. Am J Cardiol 54: 1087–1091.
314
M. PARTINEN
Webb W (1970). Individual differences in sleep length. In: E Hartmann (Ed.) Sleep and Dreaming. Little, Brown, Boston, pp. 44–47. Webb W, Friel J (1971). Sleep stage and personality characteristics of “natural” long and short sleepers. Science 171: 587–588. Weissman MM, Greenwald S, Nino-Murcia G et al. (1997). The morbidity of insomnia uncomplicated by psychiatric disorders. Gen Hosp Psychiatry 19 (4): 245–250. Williams A, Houston D, Finberg S et al. (1985). Sleep apnea syndrome and essential hypertension. Am J Cardiol 55: 1019–1022. Williams CJ, Hu FB, Patel SR et al. (2007). Sleep duration and snoring in relation to biomarkers of cardiovascular disease risk among women with type 2 diabetes. Diabetes Care 30 (5): 1233–1240. Will MJ, Ester MS, Ramirez SG et al. (1995). Comparison of cephalometric analysis with ethnicity in obstructive sleep apnea syndrome. Sleep 18 (10): 873–875. Wilner AS, Lavie L, Peled P et al. (1988). Narcolepsycataplexy in Israeli Jews is associated exclusively with the HLA DR2 haplotype. Hum Immunol (21): 15–22. Wing YK, Chiu HF, Ho CK et al. (1994). Narcolepsy in Hong Kong Chinese – a preliminary experience. Aust N Z J Med 24 (3): 304–306. Wing YK, Li RH, Lam CW et al. (2002). The prevalence of narcolepsy among Chinese in Hong Kong. Ann Neurol 51 (5): 578–584. Wing YK, Chen L, Fong SY et al. (2008). Narcolepsy in southern Chinese – clinical characteristics, HLA typing and seasonality of birth. J Neurol Neurosurg Psychiatry 79: 1262–1267. Wittmann V, Rodenstein DO (2004). Health care costs and the sleep apnea syndrome. Sleep Med Rev 8 (4): 269–279. Worsnop CJ, Naughton MT, Barter CE et al. (1998). The prevalence of obstructive sleep apnea in hypertensives. Am J Respir Crit Care Med 157 (1): 111–115.
Yeo BK, Perera IS, Kok LP et al. (1996). Insomnia in the community. Singapore Med J 37 (3): 282–284. Young T, Palta M, Dempsey J et al. (1993). The occurrence of sleep-disordered breathing among middle-aged adults. N Engl J Med 328: 1230–1235. Young T, Finn L, Hla KM et al. (1996). Snoring as part of a dose–response relationship between sleep-disordered breathing and blood pressure. Sleep 19 (10 Suppl): S202–S205. Young T, Peppard P, Palta M et al. (1997). Population-based study of sleep-disordered breathing as a risk factor for hypertension. Arch Intern Med 157 (15): 1746–1752. Young T, Finn L, Palta M (2001). Chronic nasal congestion at night is a risk factor for snoring in a population-based cohort study. Arch Intern Med 161 (12): 1514–1519. Young T, Peppard PE, Gottlieb DJ (2002). Epidemiology of obstructive sleep apnea: a population health perspective. Am J Respir Crit Care Med 165 (9): 1217–1239. Young T, Finn L, Peppard PE et al. (2008). Sleep disordered breathing and mortality: eighteen-year follow-up of the Wisconsin sleep cohort. Sleep 31 (8): 1071–1078. Yrjo¨nen C, Vartia T, Partinen M (1991). Sleep disturbances of 4 to 5 years-old children in Finland. J Sleep Res (20A): 221. Zamarron C, Gude F, Otero Y et al. (1999a). Prevalence of sleep disordered breathing and sleep apnea in 50- to 70year-old individuals. A survey. Respiration 66 (4): 317–322. Zamarron C, Gude F, Otero Otero Y et al. (1999b). Snoring and myocardial infarction: a 4-year follow-up study. Respir Med 93 (2): 108–112. Zucconi M, Ferini-Strambi L, Erminio C et al. (1993). Obstructive sleep apnea in the Rubinstein–Taybi syndrome. Respiration 60 (2): 127–132.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 19
Cardiovascular and cerebrovascular physiology in sleep VIKTOR HANAK 1 * AND VIREND K. SOMERS 2 Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN, USA
1
2
Division of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA
CARDIOVASCULAR PHYSIOLOGY DURING SLEEP Neural circulatory regulation during sleep Normal human sleep is accompanied by changes in blood pressure and heart rate. These hemodynamic changes are primarily mediated by changes in the autonomic nervous system. Both invasive and noninvasive techniques can be used to monitor autonomic nervous system activity during sleep. Sympathetic activity can be measured by inserting microelectrodes into the nerves supplying the muscle blood vessels (muscle sympathetic nerve activity) or skin (skin sympathetic nerve activity) (Figure 19.1) (Somers et al., 1993; Takeuchi et al., 1994; Kodama et al., 1998). Noninvasively, autonomic cardiac control can be monitored indirectly by analyzing the power spectra of heart rate fluctuations (Akselrod et al., 1981). During nonrapid eye movement (NREM) sleep, sympathetic inhibition is associated with a decrease in blood pressure and heart rate. During REM sleep there is an intermittent sympathetic activation together with rapid fluctuations in blood pressure and heart rate (Somers et al., 1993). The cardiovascular responses to REM and NREM sleep are described below.
NREM sleep NREM sleep is characterized by autonomic stability with parasympathetic predominance and sympathetic inhibition. There is a gradual decrease in sympathetic nerve activity, blood pressure, and heart rate progressing from stage 1 to 4 NREM. Blood pressure, respiratory rate, and basal metabolic rate decrease by as much as 30% and sympathetic nervous activity decreases by as much as 50% during stage 4 compared to baseline (Mancia, 1993; Somers et al., 1993) (Figure 19.2). These
*
changes are consistent with decreased metabolic demand during sleep. The fall in blood pressure is mediated by a reduction in cardiac output and a decrease in peripheral vascular resistance. During sleep, the arterial baroreflex has a lowered set point which allows for lower blood pressure levels without activation of the sympathetic nervous system (Conway et al., 1983). Transient arousal stimuli may give rise to high-amplitude K-complexes on the electroencephalogram during stage 2 of NREM sleep, which may be accompanied by transient bursts in sympathetic activity with brief increases in blood pressure (Hornyak et al., 1991).
REM sleep REM sleep is associated with sympathetic activation and is referred to as paradoxical sleep. Although REM is predominantly a parasympathetic state, marked fluctuations in autonomic nervous system activity are typically seen. REM sleep can be divided into two distinct patterns, tonic and phasic. Tonic REM is persistent throughout the sleep stage. The phasic REM component is intermittent, superimposed, and characterized by bursts of sympathetic activity, REMs, and brief irregular “muscle twitches” superimposed on muscle atonia (Somers et al., 1993). Blood pressure is elevated during REM compared to NREM sleep, particularly during the intermittent phasic episodes. Sudden bursts of sympathetic activity can be detected by microneurography in the nerves supplying the skin or muscle blood vessels during phasic REM. The increase in sympathetic activation during phasic REM leads to abrupt surges in blood pressure (Mancia, 1993; Somers et al., 1993). Heart rate variability is increased during REM (Bonnet and Arand, 1997). Heart rate during phasic
Correspondence to: Viktor Hanak, M.D., Division of Pulmonary and Critical Care Medicine, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, USA. Tel: 507-255-1144, Fax: 507-255-7070, E-mail:
[email protected]
316
V. HANAK AND V.K. SOMERS Stage 4
Awake
SNA SNA 125 125
BP 0
0
Stage 2
REM
SNA 125
K
SNA
BP 0 Stage 3
125 BP 0
SNA
T
10 sec
125 BP 0
Fig. 19.1. Recording of the sympathetic nervous system activity (SNA) and mean blood pressure (BP) while awake, during rapid eye movement (REM) and stages 1–4 of non-REM sleep. (Reproduced from Somers et al. (1993), with permission.)
REM is faster compared to tonic REM sleep, consistent with sympathetic activation. The rapid fluctuations in autonomic activity, blood pressure, and heart rate during REM may conceivably be a potential trigger for adverse cardiovascular events, and have been linked to nocturnal angina (Guilleminault et al., 1984). There are also anecdotal reports of otherwise healthy young people who developed various forms of bradycardia and asystole in REM sleep (Guilleminault et al., 1984).
accompanied by a rapid increase in heart rate and blood pressure. A mean increase of about 20 mmHg in systolic and 15 mmHg in diastolic blood pressure can be noted with a heart rate change of about 10 beats/min (Morgan et al., 1996). These hemodynamic changes are likely mediated in part by the autonomic responses, as evidenced by the concomitant activation of the sympathetic nervous system and rapid parasympathetic withdrawal (Horner et al., 1995; Catcheside et al., 2001).
CARDIOVASCULAR EFFECTS OF AROUSAL
CIRCADIAN VARIATION IN CARDIOVASCULAR AND CEREBROVASCULAR EVENTS
Arousal in NREM sleep is most commonly defined as the appearance of an alpha rhythm on the electroencephalogram. In REM sleep there is an additional criterion of increased submental muscle activity since during REM an alpha rhythm may occur spontaneously. To be regarded as an arousal, the rhythm change must last at least 3 seconds and must be preceded by at least 10 seconds of sleep. If the duration exceeds 15 seconds, then it is considered an awakening rather than an arousal. The exact mechanism mediating cortical and autonomic arousal is unclear. Arousal from NREM experimentally induced by auditory stimuli is
The incidence of cardiovascular and cerebrovascular adverse events is highest in the early-morning hours after awakening. Acute ischemic stroke (Marler et al., 1989) and intracerebral hemorrhage (Sloan et al., 1992) are most likely to occur in the early-morning hours from 6 a.m. to noon, with a secondary early evening peak (Figure 19.3) (Casetta et al., 2002; Stergiou et al., 2002). A pattern of circadian variation has also been described in myocardial infarction (Pell et al., 1963; Muller et al., 1985; Thompson et al., 1985), sudden cardiac death (Arntz et al., 2000), and acute
CARDIOVASCULAR AND CEREBROVASCULAR PHYSIOLOGY IN SLEEP
*
*
*
20
*
35
0 Awake
*
2
*
3
4
REM
Stroke onset 15
10
5
A *
*
Systolic BP
75 140
50 mmHg
Mean Blood Pressure (mm Hg)
100
1
Stroke onset rate (%)
Heart Rate (beats/min)
70
317
25
130
0 Awake
1
2
3
4
REM 120
*
30 20
*
10
*
0 Awake
1
2
3
4
REM
250 Burst Amplitude (%)
B
*
200 150
*
*
3
4
0 Awake
1
2
80
Pulse rate
75 70 65 0
C
0
6
12 18 Time of the day (hours)
0
Fig. 19.3. Circadian variation of stroke onset. (A) Increased incidence of stroke onset correlates with (B) increase in blood pressure and (C) heart rate. (Reproduced from Stergiou et al. (2002), with permission.)
100 50
Beats per minute
Burst Frequency (bursts/min)
40
REM
Fig. 19.2. Blood pressure, heart rate, and sympathetic activity are significantly lower during nonrapid eye movement sleep compared to wakefulness or rapid eye movement (REM) sleep. (Reproduced from Somers et al. (1993), with permission.)
limb ischemia (Manfredini et al., 1998). Meta-analysis of epidemiologic studies provides further evidence that the rate of cardiovascular events is increased during the early-morning hours (Cohen et al., 1997). The reasons for the circadian variation are not clear, but are likely complex, including changes in posture, physical activity, hemodynamics, fibrinolytic activity, endothelial function (Otto et al., 2004), or autonomic tone.
CEREBROVASCULAR PHYSIOLOGY DURING SLEEP This section reviews the principles of cerebral blood flow regulation during normal sleep and the changes observed during sleep-disordered breathing. Cerebral
blood flow during sleep has been extensively studied and there are several well-written reviews on the topic (Franklin, 2002; Zoccoli et al., 2002).
Regulation of cerebral blood flow Brain circulation is tightly regulated by three basic mechanisms: (1) vasogenic autoregulation; (2) metabolic regulation; and (3) regulation by respiratory gases. Although there are differences in how these regulatory mechanisms operate during sleep compared to the awake state, these differences are relatively minor.
INTRINSIC
VASOGENIC AUTOREGULATION
OF CEREBRAL BLOOD FLOW
Cerebral blood flow is autoregulated by the change in caliber of the resistance arterioles. This mechanism is mediated by intrinsic myogenic properties of the vessel walls and maintains constant cerebral perfusion despite variations in systemic pressure. In response to changes
V. HANAK AND V.K. SOMERS
in transmural pressure the vessels dilate when systemic pressure falls and constrict when pressure rises. This mechanism helps to protect the brain from hypotensive or hypertensive damage over a wide range of perfusion pressures. The upper and lower autoregulatory limits in normal subjects correspond to mean arterial pressures of about 150 and 60 mmHg, respectively (Paulson et al., 1990). These autoregulatory limits may be exceeded in various disease states when the blood pressure is too low, too high, or when the ability of the vessel wall to respond adequately is affected. Examples of impaired regulation include acute head injury, stroke, brain lesions, central nervous system infection, vasculopathy, hypertensive crisis, and iatrogenic hypotension from antihypertensive therapy (Paulson et al., 1990). The autonomic nervous system does not directly contribute to the autoregulation process, but the increased sympathetic drive may increase the upper limits, as seen in chronic hypertension. While antihypertensive therapy is very useful in decreasing cerebrovascular morbidity, overzealous treatment (i.e., high doses of antihypertensives taken at nighttime) may lead to severe hypotension during sleep (Hayreh et al., 1994). The inability of the diseased vessels to compensate for low perfusion pressures may result in ischemic damage. It has been shown that a diastolic blood pressure reduction below 85 mmHg may increase the risk for cardiac events (Berglund, 1989; Farnett et al., 1991; Fletcher and Bulpitt, 1992). These data are less conclusive for the risk of stroke (Fletcher and Bulpitt, 1992), but some studies reveal an association between the nighttime hypotension and ischemic damage to the optic nerve (Hayreh et al., 1999). A decrease in blood pressure, even by 20%, during sleep is physiologic and is referred to as “dipping.” However, “extreme dipping,” referring to nocturnal hypotension, has been associated with lacunar infarctions and periventricular hyperlucencies on magnetic resonance imaging (Kario et al., 1996). There are also patients, “reverse dippers,” who do not reduce, but actually increase their blood pressure during sleep who are at even higher risk for stroke; the mechanism responsible for the increased mortality in this subset may be multifactorial (Kario et al., 2001; Hoshide et al., 2002) (Figure 19.4).
METABOLIC
REGULATION OF CEREBRAL BLOOD FLOW
Blood flow into metabolically active areas is increased, a mechanism that is mediated by the endproducts or byproducts of cellular metabolism. Levels of Hþ, potassium, and adenosine are increased in areas with neuronal activation and blood flow closely follows
1.0
Probability of stroke-free
318
0.9
D ND
0.8
ED D = Dippers (n=230) ND = Non-dippers (n=185) ED = Extreme dippers (n=97) RD = Reverse dippers (n=63)
0.7
RD
0.6 0
10
40 50 20 30 Duration of follow-up (months)
60
70
Fig. 19.4. Effect of the nocturnal “dipping” on the strokefree survival rates in hypertensive patients. (Reproduced from Kario et al. (2001) with permission.)
the cerebral metabolic activity (Faraci and Sobey, 1998; Phillis, 2004). The fact that neuronal activation corresponds to increased metabolism which in turn corresponds to increased blood flow is an important consideration when interpreting the results of physiologic studies, and is thought to be valid during sleep as well as during the awake state. Various radionuclide tracers can be used to study regional distribution of blood flow during sleep (see below).
ROLE OF O2 AND CO2 CONCENTRATIONS IN REGULATION OF CEREBRAL BLOOD FLOW Both hypercapnia and hypoxia lead to vasodilation in the cerebral circulation. Hypercapnia elicits a stronger vasodilatory response than hypoxia. The exact molecular mechanism by which CO2 and O2 regulate cerebral perfusion is not well characterized, but may involve nitric oxide (Schmetterer et al., 1997; Demchenko et al., 2002; Van Mil et al., 2002; Lavi et al., 2003) and prostaglandins (Wagerle and Degiulio, 1994). Vasomotor reactivity physiologically varies during the day and reaches the lowest values in the morning (Ameriso et al., 1994). Vasodilatory responses are also diminished during sleep compared to wake time (Meadows et al., 2003, 2004) (Figure 19.5). Vasodilation in response to raising CO2 can be quantified by a simple breath-hold test as the change of the blood flow in the middle cerebral artery is measured by Doppler ultrasound (Markus and Harrison, 1992). The difference in the cerebral blood flow between hypocarbia, when vessels are fully constricted, and hypercarbia, when vessels are fully dilated, was found to be a significant predictor of cerebrovascular risk. Reduction in CO2 vasoreactivity is associated with increased risk of ischemic cerebral damage in patients
CARDIOVASCULAR AND CEREBROVASCULAR PHYSIOLOGY IN SLEEP 4
3 Cerebral vascular reactivity (cm/sec/Torr)
319
differences in neuronal activity during wakefulness and during the various stages of sleep. The deactivation of the cortical association areas is the dominant characteristic of sleep and is a feature common to both REM and NREM stages (Braun et al., 1997). In REM sleep the flow is increased in the center cephalic structures mediating arousal, as well as the limbic and paralimbic areas, and flow is decreased to the cerebral cortex that is participating in the highest analytic information processing. In NREM sleep, blood flow is decreased in the brainstem, thalamus, basal forebrain, basal ganglia, and cerebellum, as well as in the prefrontal cortex.
2
1
0
Cerebral blood flow in the major cerebral arteries during sleep
–1 Wake
Sleep
Fig. 19.5. Cerebral vascular reactivity in response to CO2 is reduced from wake to sleep. Solid circles represent group means ( SE) for vascular reactivity obtained on 12 healthy nonsnoring volunteers. (Reproduced from Meadows et al. (2003), with permission.)
with internal carotid artery occlusion (Ringelstein et al., 1988), predicts the risk of severe cerebral ischemia in patients undergoing carotid endarterectomy (Lam et al., 2000), portends poor prognosis in patients with traumatic head injury (Schalen et al., 1991), and indicates vasospasm in subarachnoid hemorrhage (Hassler and Chioffi, 1989). This measure is also reduced in other disease states, including hypertension or sleep apnea (Placidi et al., 1998; Settakis et al., 2003). In obstructive sleep apnea (OSA) the reduction in vasoreactivity is more pronounced in patients with frequent sleep fragmentation and overnight CO2 retention. Sleep apnea patients have lower vasodilatory responses to CO2 throughout the day compared to healthy controls (Placidi et al., 1998), but this can be restored to normal by overnight therapy with noninvasive ventilation (Diomedi et al., 1998).
Regional distribution of cerebral blood flow during sleep Positron emission tomography (PET) scanning with injected H2(15)O tracer has been used to define brain regions that are metabolically active during sleep. The tracer is preferentially carried to areas with increased cerebral blood flow. The tight coupling between blood flow and metabolism enables one to depict the hypoor hyperperfused areas and by inference study the changes in the spatial distribution of the neuronal activity over time. The results of these PET imaging studies are well summarized in a review by Maquet (2000). The PET imaging studies compare the regional
Blood flow velocity in the basal cerebral arteries can be measured indirectly by Doppler ultrasound. Since the diameter of the basal arteries does not undergo major changes, the cerebral blood flow is directly proportional to the flow velocity (Aaslid et al., 1982). During NREM sleep the blood flow velocity in the middle cerebral artery gradually decreases with sleep progression, but rapidly increases in REM sleep (Hajak et al., 1994). Blood flow velocity may be higher during REM sleep than during wakefulness (Droste et al., 1993). Cerebral blood flow in the morning after a full night’s sleep is lower when compared to the values before sleep (Fischer et al., 1991; Kuboyama et al., 1997) (Figure 19.6). Similar findings of decreased blood flow after sleep have been described using PET scanning (Braun et al., 1997).
OBSTRUCTIVE SLEEPAPNEA Hemodynamic changes in obstructive sleep apnea Several Doppler studies have been performed to define the hemodynamic changes in OSA and have demonstrated that apneic episodes have pronounced effects on cerebral perfusion. In general, the changes in cerebral blood flow closely follow the changes of systemic arterial pressure. There is a steep increase in cerebral blood flow at the termination of apnea corresponding to the peak in systemic blood pressure, followed by a sharp decrease in perfusion afterwards. The prominent drop in the cerebral blood flow after apnea termination results in transient hypoperfusion. Changes in the flow velocities are most prominent with apneas during REM sleep, which is likely related to the fact that these apneas tend to be longer in duration, inducing more severe hypoxemia (Klingelhofer et al., 1992; Balfors and Franklin, 1994). An increase in cerebral blood flow, albeit less prominent, can be elicited in healthy subjects by voluntary apnea (Siebler and Nachtmann, 1993).
320
V. HANAK AND V.K. SOMERS 100
%CBFV (%)
* ** † ** ††
** ††
** ††
80 Before After lights out waking
Stage 1
Stage 2
Awake
Stage 3
Stage 4
REM sleep
Asleep
Fig. 19.6. The means ( SEM) of percentage cerebral blood flow velocity (CBFV) for the awake period and each sleep stage. CBFV during awake “before lights out” period is considered 100%. The CBFV during the “after waking” period was lower compared to “before lights out” period (*P < 0.05). The CBFV during nonrapid eye movement (NREM) sleep was lower compared to presleep CBFV and CBFV during rapid eye movement (REM) sleep. ** P < 0.01 versus awake period; {{ P < 0.01; { P < 0.05 versus REM sleep. (Reproduced from Kuboyama et al. (1997), with permission.)
In a study by Balfors and Franklin (1994), cerebral blood flow increased on average by 15% during apnea and decreased by 23% after apnea compared to baseline. Cerebral blood flow closely patterned the changes in systemic pressure and returned to baseline within 1 minute, except when frequent repetitive apneas were encountered. Cerebral autoregulation may be overwhelmed by the pronounced fluctuations in systemic pressure, especially if the apneas follow in rapid succession, as is generally seen in patients with severe apnea. The brain tissue is at risk for ischemic injury as cerebral perfusion is reduced while at the same time oxygen saturation reaches its nadir. Cerebral spinal fluid pressure during OSA episodes is also elevated (Siebler and Nachtmann, 1993) (Figure 19.7). Episodes of sudden reduction in cerebral perfusion and brain hypoxia may conceivably lead to transient ischemic attacks or ischemic strokes. There is evidence of graymatter involvement by magnetic resonance imaging in patients with OSA compared to matched controls (Macey et al., 2002; Morrell et al., 2003). Brain metabolism and the structure of white matter may also be affected, as demonstrated by magnetic resonance imaging, where the ratio of N-acetyl aspartate to choline inversely correlates with apnea severity (Kamba et al., 1997).
Obstructive sleep apnea and the risk of stroke OSA is associated with risk of stroke in epidemiologic studies, and there are several well-written reviews on this subject (Yaggi and Mohsenin, 2003; Bassetti, 2005). The role of OSA as an independent risk factor for stroke is difficult to untangle since multiple other risk factors for stroke are typically present in OSA
Apnea (present/absent)
60 seconds
1000 Cerebrospinal fluid pressure (mmH2O) 500
0 100% Oxygen saturation (%) 40%
Fig. 19.7. Marked episodic elevation of cerebrospinal fluid pressure during nocturnal sleep in patients with obstructive sleep apnea. Dashed line represents baseline. (Reproduced from Sugita et al. (1985), with permission.)
patients. However, one observational cohort study demonstrated that OSA significantly predicted stroke independent of other risk factors, including smoking, alcohol use, body mass index, diabetes mellitus, hyperlipidemia, atrial fibrillation, and hypertension (Yaggi et al., 2005). Increased severity of OSA at baseline was associated with an increased risk of the development of stroke or death from any cause (Figure 19.8). The risk of adverse outcomes was not reversed by OSA treatment, but the study was not designed or powered to assess the effect of treatment on outcomes. Another large observational
CARDIOVASCULAR AND CEREBROVASCULAR PHYSIOLOGY IN SLEEP
Probability of event-free survival
1.0
Controls
0.8 Patients with syndrome
0.6 0.4 0.2 P=0.003 0.0 0
No. at risk Controls 325 Patients with 697 syndrome
1
2
3 Year
4
5
6
266 559
260 543
227 452
88 173
23 33
1 3
CENTRAL SLEEPAPNEA
Fig. 19.8. Kaplan–Meier estimates of the probability of event-free survival among patients with the obstructive sleep apnea syndrome and controls. (Reproduced from Yaggi et al. (2005), with permission.)
study demonstrated that treatment of OSA with noninvasive ventilation significantly reduced the incidence of fatal and nonfatal cardiovascular events, including strokes (Marin et al., 2005). Changes induced by OSA, such as endothelial dysfunction, oxidative stress, hypercoagulability, sympathetic activation, hypertension, and arrhythmias, may all contribute to the observed association between OSA and stroke. For example, several cross-sectional studies have identified severe sleep apnea as a risk factor for hypertension (Lavie et al., 2000; Nieto et al., 2000). Data from the Wisconsin Sleep Cohort Study have shown that the likelihood of developing new-onset hypertension is increased in proportion to the severity of sleep apnea as measured by the apnea–hypopnea index (Figure 19.9) (Peppard et al., 2000). These investigators noted that, in patients with sleep apnea followed for over 4 years, there
2.89
Odds ratio
3 2.03 2 1.42 1
1
Hemodynamic changes in central sleep apnea Patients with severe congestive heart failure or stroke are commonly affected by central sleep apnea. Central sleep apnea is characterized by a waxing and waning breathing pattern with alternating hyperpneic and apneic episodes. There is no effort to breathe during the apneic episodes. The central apneas are a consequence of the variation in respiratory drive, but there is a controversy regarding the exact underlying mechanism (Franklin et al., 1997a). In general, cerebral blood flow, arterial blood pressure, and heart rate are increased during the hyperventilation phase and decrease during the apneic phase (Figure 19.11) (Franklin et al., 1997a). The pathophysiologic implications of central sleep apnea may not be as pronounced as those of
Student’s t-test * † ‡ §
Barthel Index 100 90 80 70 60 50 40 30 20 10 0
‡
0
0.1–4.9
5–14.9
>14.9
Apnea – Hypopnea Index
Fig. 19.9. Association of hypertension with the apnea– hypopnea index in the Wisconsin Sleep Cohort Study. (Reproduced from Peppard et al. (2000), with permission.)
N.S. p<.04 p<.004 p<.02 §
†
* Sleep apnea Other patients Admission 3 months Discharge
0
321
was a threefold increased risk of developing new hypertension. Similarly, atrial fibrillation is much more prevalent in patients with OSA compared to matched controls (Gami et al., 2004). These comorbidities constitute potential causal links through which OSA may contribute to an increased risk of stroke. Stroke sufferers with sleep-disordered breathing may have worse long-term functional outcome (Good et al., 1996) (Figure 19.10). The association between OSA and stroke is bidirectional. While OSA increases risk of stroke, the episode of stroke itself, once it occurs, may predispose to OSA by involving the bulbar nerves that maintain the airway tonus (Neau et al., 2002).
12 months
Fig. 19.10. Scores of impairment in the activities of daily living and cognition (Barthel index) in stroke patients with and without sleep-disordered breathing. Lower scores indicate worse outcomes. (Reproduced from Good et al. (1996), with permission.)
322
V. HANAK AND V.K. SOMERS Airflow
Mean cerebral blood flow velocity (% change) 30 0 –30 Mean arterial pressure (% change) 30 0 –30 Heart rate (% change) 30 0 –30 Intra-arterial SaO2 (%) 100 90 80
Fig. 19.11. Hemodynamic measures during a central sleep apnea episode. SaO2, arterial blood oxygen saturation. (Reproduced from Franklin et al. (1997a), with permission.)
OSA. Patients with central sleep apnea have poor quality of sleep with frequent arousals related to the hyperventilatory breathing phase. Significant hypoxemia may sometimes develop during sleep. Arousals may elicit sympathetic excitation, as evidenced by increased muscle sympathetic nerve activity and elevated plasma and urinary epinephrine concentrations (Naughton et al., 1995; van de Borne et al., 1998).
Central sleep apnea in patients with stroke The prevalence of central sleep apnea in patients with stroke is about 30–50% during the acute phase but decreases during subsequent months (Nachtmann et al., 1995; Parra et al., 2000). The topographic location or the type of the stroke does not predict the development of central sleep apnea (Parra et al., 2000). Treatment with a continuous nasal positive pressure device is often not effective in patients with heart failure (Bradley et al., 2005) or stroke (Sandberg et al., 2001). Additionally, delirium or cognitive impairment may prevent the application of noninvasive ventilation through a tight-fitting mask in patients with acute stroke. Oxygen, which
decreases the severity of central sleep apnea in combination with various modes of noninvasive ventilation, may be used for treatment (Franklin et al., 1997b).
CONCLUSIONS Widespread recognition of the important interactions between sleep and maintenance of health and prevention of disease has resulted in increased attention to sleeprelated changes in physiologic regulation of the cardiovascular and cerebrovascular systems. These complex control mechanisms differ significantly from circulatory control during wakefulness, and may also be altered by disease conditions. Disturbed cardiac and neurovascular regulation may have pathophysiologic implications: some examples include the association between REM sleep and nocturnal angina, the preponderance of cardiovascular and cerebrovascular events in the early-morning hours after waking from sleep, and the suggestion that sleep apnea-related circulatory changes may be linked to a high likelihood of sudden cardiac death occurring during sleep in patients with OSA.
CARDIOVASCULAR AND CEREBROVASCULAR PHYSIOLOGY IN SLEEP However, much remains to be determined, and this area of investigation is relatively uncharted. Some questions that need to be addressed include, for example, how sleep-related circulatory profiles are affected by conditions such as advanced age, gender, obesity, and sleep deprivation.
REFERENCES Aaslid R, Markwalder TM, Nornes H (1982). Noninvasive transcranial Doppler ultrasound recording of flow velocity in basal cerebral arteries. J Neurosurg 57 (6): 769–774. Akselrod S, Gordon D, Ubel FA et al. (1981). Power spectrum analysis of heart rate fluctuation: a quantitative probe of beat-to-beat cardiovascular control. Science 213 (4504): 220–222. Ameriso SF, Mohler JG, Suarez M et al. (1994). Morning reduction of cerebral vasomotor reactivity. Neurology 44 (10): 1907–1909. Arntz HR, Willich SN, Schreiber C et al. (2000). Diurnal, weekly and seasonal variation of sudden death. Populationbased analysis of 24 061 consecutive cases. Eur Heart J 21 (4): 315–320. Balfors EM, Franklin KA (1994). Impairment of cerebral perfusion during obstructive sleep apneas. Am J Respir Crit Care Med 150 (6 Pt 1): 1587–1591. Bassetti CL (2005). Sleep and stroke. Semin Neurol 25 (1): 19–32. Berglund G (1989). Goals of antihypertensive therapy. Is there a point beyond which pressure reduction is dangerous? Am J Hypertens 2 (7): 586–593. Bonnet MH, Arand DL (1997). Heart rate variability: sleep stage, time of night, and arousal influences. Electroencephalogr Clin Neurophysiol 102 (5): 390–396. Bradley TD, Logan AG, Kimoff RJ et al. (2005). Continuous positive airway pressure for central sleep apnea and heart failure. N Engl J Med 353 (19): 2025–2033. Braun AR, Balkin TJ, Wesenten NJ et al. (1997). Regional cerebral blood flow throughout the sleep–wake cycle. An H2(15)O PET study. Brain 120 (Pt 7): 1173–1197. Casetta I, Granieri E, Fallica E et al. (2002). Patient demographic and clinical features and circadian variation in onset of ischemic stroke. Arch Neurol 59 (1): 48–53. Catcheside PG, Chiong SC, Orr RS et al. (2001). Acute cardiovascular responses to arousal from non-REM sleep during normoxia and hypoxia. Sleep 24 (8): 895–902. Cohen MC, Rohtla KM, Lavery CE et al. (1997). Metaanalysis of the morning excess of acute myocardial infarction and sudden cardiac death. Am J Cardiol 79 (11): 1512–1516. Conway J, Boon N, Jones JV et al. (1983). Involvement of the baroreceptor reflexes in the changes in blood pressure with sleep and mental arousal. Hypertension 5 (5): 746–748. Demchenko IT, Oury TD, Crapo JD et al. (2002). Regulation of the brain’s vascular responses to oxygen. Circ Res 91 (11): 1031–1037.
323
Diomedi M, Placidi F, Cupini LM et al. (1998). Cerebral hemodynamic changes in sleep apnea syndrome and effect of continuous positive airway pressure treatment. Neurology 51 (4): 1051–1056. Droste DW, Berger W, Schuler E et al. (1993). Middle cerebral artery blood flow velocity in healthy persons during wakefulness and sleep: a transcranial Doppler study. Sleep 16 (7): 603–609. Faraci FM, Sobey CG (1998). Role of potassium channels in regulation of cerebral vascular tone. J Cereb Blood Flow Metab 18 (10): 1047–1063. Farnett L, Mulrow CD, Linn WD et al. (1991). The J-curve phenomenon and the treatment of hypertension. Is there a point beyond which pressure reduction is dangerous? JAMA 265 (4): 489–495. Fischer AQ, Taormina MA, Akhtar B et al. (1991). The effect of sleep on intracranial hemodynamics: a transcranial Doppler study. J Child Neurol 6 (2): 155–158. Fletcher AE, Bulpitt CJ (1992). How far should blood pressure be lowered? N Engl J Med 326 (4): 251–254. Franklin KA (2002). Cerebral haemodynamics in obstructive sleep apnoea and Cheyne–Stokes respiration. Sleep Med Rev 6 (6): 429–441. Franklin KA, Sandstrom E, Johansson G et al. (1997a). Hemodynamics, cerebral circulation, and oxygen saturation in Cheyne–Stokes respiration. J Appl Physiol 83 (4): 1184–1191. Franklin KA, Eriksson P, Sahlin C et al. (1997b). Reversal of central sleep apnea with oxygen. Chest 111 (1): 163–169. Gami AS, Pressman G, Caples SM et al. (2004). Association of atrial fibrillation and obstructive sleep apnea. Circulation 110 (4): 364–367. Good DC, Henkle JQ, Gelber D et al. (1996). Sleepdisordered breathing and poor functional outcome after stroke. Stroke 27 (2): 252–259. Guilleminault C, Pool P, Motta J et al. (1984). Sinus arrest during REM sleep in young adults. N Engl J Med 311 (16): 1006–1010. Hajak G, Klingelhofer J, Schulz-Varszegi M et al. (1994). Relationship between cerebral blood flow velocities and cerebral electrical activity in sleep. Sleep 17 (1): 11–19. Hassler W, Chioffi F (1989). CO2 reactivity of cerebral vasospasm after aneurysmal subarachnoid haemorrhage. Acta Neurochir (Wien) 98 (3–4): 167–175. Hayreh SS, Zimmerman MB, Podhajsky P et al. (1994). Nocturnal arterial hypotension and its role in optic nerve head and ocular ischemic disorders. Am J Ophthalmol 117 (5): 603–624. Hayreh SS, Podhajsky P, Zimmerman MB (1999). Role of nocturnal arterial hypotension in optic nerve head ischemic disorders. Ophthalmologica 213 (2): 76–96. Horner RL, Brooks D, Kozar LF et al. (1995). Immediate effects of arousal from sleep on cardiac autonomic outflow in the absence of breathing in dogs. J Appl Physiol 79 (1): 151–162. Hornyak M, Cejnar M, Elam M et al. (1991). Sympathetic muscle nerve activity during sleep in man. Brain 114 (Pt 3): 1281–1295.
324
V. HANAK AND V.K. SOMERS
Hoshide Y, Kario K, Schwartz JE et al. (2002). Incomplete benefit of antihypertensive therapy on stroke reduction in older hypertensives with abnormal nocturnal blood pressure dipping (extreme-dippers and reverse-dippers). Am J Hypertens 15 (10 Pt 1): 844–850. Kamba M, Suto Y, Ohta Y et al. (1997). Cerebral metabolism in sleep apnea. Evaluation by magnetic resonance spectroscopy. Am J Respir Crit Care Med 156 (1): 296–298. Kario K, Matsuo T, Kobayashi H et al. (1996). Nocturnal fall of blood pressure and silent cerebrovascular damage in elderly hypertensive patients. Advanced silent cerebrovascular damage in extreme dippers. Hypertension 27 (1): 130–135. Kario K, Pickering TG, Matsuo T et al. (2001). Stroke prognosis and abnormal nocturnal blood pressure falls in older hypertensives. Hypertension 38 (4): 852–857. Klingelhofer J, Hajak G, Sander D et al. (1992). Assessment of intracranial hemodynamics in sleep apnea syndrome. Stroke 23 (10): 1427–1433. Kodama Y, Iwase S, Mano T et al. (1998). Attenuation of regional differentiation of sympathetic nerve activity during sleep in humans. J Auton Nerv Syst 74 (2–3): 126–133. Kuboyama T, Hori A, Sato T et al. (1997). Changes in cerebral blood flow velocity in healthy young men during overnight sleep and while awake. Electroencephalogr Clin Neurophysiol 102 (2): 125–131. Lam JM, Smielewski P, al-Rawi P et al. (2000). Prediction of cerebral ischaemia during carotid endarterectomy with preoperative CO2-reactivity studies and angiography. Br J Neurosurg 14 (5): 441–448. Lavi S, Egbarya R, Lavi R et al. (2003). Role of nitric oxide in the regulation of cerebral blood flow in humans: chemoregulation versus mechanoregulation. Circulation 107 (14): 1901–1905. Lavie P, Herer P, Hoffstein V (2000). Obstructive sleep apnoea syndrome as a risk factor for hypertension: population study. BMJ 320 (7233): 479–482. Macey PM, Henderson LA, Macey KE et al. (2002). Brain morphology associated with obstructive sleep apnea. Am J Respir Crit Care Med 166 (10): 1382–1387. Mancia G (1993). Autonomic modulation of the cardiovascular system during sleep. N Engl J Med 328 (5): 347–349. Manfredini R, Gallerani M, Portaluppi F et al. (1998). Circadian variation in the onset of acute critical limb ischemia. Thromb Res 92 (4): 163–169. Maquet P (2000). Functional neuroimaging of normal human sleep by positron emission tomography. J Sleep Res 9 (3): 207–231. Marin JM, Carrizo SJ, Vicente E et al. (2005). Long-term cardiovascular outcomes in men with obstructive sleep apnoea-hypopnoea with or without treatment with continuous positive airway pressure: an observational study. Lancet 365 (9464): 1046–1053. Markus HS, Harrison MJ (1992). Estimation of cerebrovascular reactivity using transcranial Doppler, including the use of breath-holding as the vasodilatory stimulus. Stroke 23 (5): 668–673.
Marler JR, Price TR, Clark GL et al. (1989). Morning increase in onset of ischemic stroke. Stroke 20 (4): 473–476. Meadows GE, Dunroy HM, Morrell MJ et al. (2003). Hypercapnic cerebral vascular reactivity is decreased, in humans, during sleep compared with wakefulness. J Appl Physiol 94 (6): 2197–2202. Meadows GE, O’Driscoll DM, Simonds AK et al. (2004). Cerebral blood flow response to isocapnic hypoxia during slow-wave sleep and wakefulness. J Appl Physiol 97 (4): 1343–1348. Morgan BJ, Crabtree DC, Puleo DS et al. (1996). Neurocirculatory consequences of abrupt change in sleep state in humans. J Appl Physiol 80 (5): 1627–1636. Morrell MJ, McRobbie DW, Quest RA et al. (2003). Changes in brain morphology associated with obstructive sleep apnea. Sleep Med 4 (5): 451–454. Muller JE, Stone PH, Turi ZG et al. (1985). Circadian variation in the frequency of onset of acute myocardial infarction. N Engl J Med 313 (21): 1315–1322. Nachtmann A, Siebler M, Rose G et al. (1995). Cheyne– Stokes respiration in ischemic stroke. Neurology 45 (4): 820–821. Naughton MT, Benard DC, Liu PP et al. (1995). Effects of nasal CPAP on sympathetic activity in patients with heart failure and central sleep apnea. Am J Respir Crit Care Med 152 (2): 473–479. Neau JP, Paquereau J, Meurice JC et al. (2002). Stroke and sleep apnoea: cause or consequence? Sleep Med Rev 6 (6): 457–469. Nieto FJ, Young TB, Lind BK et al. (2000). Association of sleep-disordered breathing, sleep apnea, and hypertension in a large community-based study. Sleep Heart Health Study. JAMA 283 (14): 1829–1836. Otto ME, Svatikova A, Barretto RB et al. (2004). Early morning attenuation of endothelial function in healthy humans. Circulation 109 (21): 2507–2510. Parra O, Arboix A, Bechich S et al. (2000). Time course of sleep-related breathing disorders in first-ever stroke or transient ischemic attack. Am J Respir Crit Care Med 161 (2 Pt 1): 375–380. Paulson OB, Strandgaard S, Edvinsson L (1990). Cerebral autoregulation. Cerebrovasc Brain Metab Rev 2 (2): 161–192. Pell S, D’Alonzo CA (1963). Acute myocardial infarction in a large industrial population. Report of a 6-year study of 1356 cases. JAMA 185: 831–838. Peppard PE, Young T, Palta M et al. (2000). Prospective study of the association between sleep-disordered breathing and hypertension. N Engl J Med 342 (19): 1378–1384. Phillis JW (2004). Adenosine and adenine nucleotides as regulators of cerebral blood flow: roles of acidosis, cell swelling, and KATP channels. Crit Rev Neurobiol 16 (4): 237–270. Placidi F, Diomedi M, Cupini LM et al. (1998). Impairment of daytime cerebrovascular reactivity in patients with obstructive sleep apnoea syndrome. J Sleep Res 7 (4): 288–292. Ringelstein EB, Sievers C, Ecker S et al. (1988). Noninvasive assessment of CO2-induced cerebral vasomotor response
CARDIOVASCULAR AND CEREBROVASCULAR PHYSIOLOGY IN SLEEP in normal individuals and patients with internal carotid artery occlusions. Stroke 19 (8): 963–969. Sandberg O, Franklin KA, Bucht G et al. (2001). Nasal continuous positive airway pressure in stroke patients with sleep apnoea: a randomized treatment study. Eur Respir J 18 (4): 630–634. Schalen W, Messeter K, Nordstrom CH (1991). Cerebral vasoreactivity and the prediction of outcome in severe traumatic brain lesions. Acta Anaesthesiol Scand 35 (2): 113–122. Schmetterer L, Findl O, Strenn K et al. (1997). Role of NO in the O2 and CO2 responsiveness of cerebral and ocular circulation in humans. Am J Physiol 273 (6 Pt 2): R2005–R2012. Settakis G, Pall D, Molnar C et al. (2003). Cerebrovascular reactivity in hypertensive and healthy adolescents: TCD with vasodilatory challenge. J Neuroimaging 13 (2): 106–112. Siebler M, Nachtmann A (1993). Cerebral hemodynamics in obstructive sleep apnea. Chest 103 (4): 1118–1119. Sloan MA, Price TR, Foulkes MA et al. (1992). Circadian rhythmicity of stroke onset. Intracerebral and subarachnoid hemorrhage. Stroke 23 (10): 1420–1426. Somers VK, Dyken ME, Mark AL et al. (1993). Sympathetic-nerve activity during sleep in normal subjects. N Engl J Med 328 (5): 303–307. Stergiou GS, Vemmos KN, Pliarchopoulou KM et al. (2002). Parallel morning and evening surge in stroke onset, blood pressure, and physical activity. Stroke 33 (6): 1480–1486.
325
Sugita Y, Iijima S, Teshima Y et al. (1985). Marked episodic elevation of cerebrospinal fluid pressure during nocturnal sleep in patients with sleep apnea hypersomnia syndrome. Electroencephalogr Clin Neurophysiol 60 (3): 214–219. Takeuchi S, Iwase S, Mano T et al. (1994). Sleep-related changes in human muscle and skin sympathetic nerve activities. J Auton Nerv Syst 47 (1–2): 121–129. Thompson DR, Blandford RL, Sutton TW et al. (1985). Time of onset of chest pain in acute myocardial infarction. Int J Cardiol 7 (2): 139–148. van de Borne P, Oren R, Abouassaly C et al. (1998). Effect of Cheyne–Stokes respiration on muscle sympathetic nerve activity in severe congestive heart failure secondary to ischemic or idiopathic dilated cardiomyopathy. Am J Cardiol 81 (4): 432–436. Van Mil AH, Spilt A, Van Buchem MA et al. (2002). Nitric oxide mediates hypoxia-induced cerebral vasodilation in humans. J Appl Physiol 92 (3): 962–966. Wagerle LC, Degiulio PA (1994). Indomethacin-sensitive CO2 reactivity of cerebral arterioles is restored by vasodilator prostaglandin. Am J Physiol 266 (4 Pt 2): H1332–H1338. Yaggi H, Mohsenin V (2003). Sleep-disordered breathing and stroke. Clin Chest Med 24 (2): 223–237. Yaggi HK, Concato J, Kernan WN et al. (2005). Obstructive sleep apnea as a risk factor for stroke and death. N Engl J Med 353 (19): 2034–2041. Zoccoli G, Walker AM, Lenzi P et al. (2002). The cerebral circulation during sleep: regulation mechanisms and functional implications. Sleep Med Rev 6 (6): 443–455.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 20
Cardiovascular diseases and sleep apnea SHAHROKH JAVAHERI 1 * AND VIREND K. SOMERS 2 University of Cincinnati College of Medicine, and Sleepcare Diagnostics, Cincinnati, OH, USA
1
2
Division of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA
INTRODUCTION Cardiovascular disorders are highly prevalent and associated with excess morbidity and mortality as well as substantial economic cost (Amerian Heart Association, 2010). The most recent data from the American Heart Association indicate that, in the year 2006, approximately 85 million adult Americans (35%), or roughly 1 out of 3, suffered from cardiovascular disease. Approximately 75 million Americans have hypertension, 18 million coronary artery disease, 6 million congestive heart failure, and 6.4 million stroke. In the year 2010, the estimated cost of cardiocerebrovascular diseases is $503 billion. Sleep apnea, both obstructive and central sleepdisordered breathing, are common disorders and a large number of patients with cardiovascular diseases may suffer from obstructive sleep apnea (OSA) and central sleep apnea (CSA) (Javaheri, 2004, 2005a, b). Treatment of these two disorders may decrease morbidity and mortality due to cardiovascular disorders such as hypertension, heart failure, and stroke. In the present article, we first briefly review polysomnography and the definition of various sleep-related breathing disorders, and discuss the pathophysiological consequences of OSA and associated cardiovascular disorders, and the effects of treatment of OSA on these disorders. In the second part of the review, we discuss Cheyne–Stokes breathing (CSB) with CSA in congestive heart failure, and the mechanisms, pathophysiology, and effects of treatment.
DEFINITIONS An apnea is defined as complete cessation of airflow lasting 10 seconds or more (Figures 20.1 and 20.2). Hypopnea is defined as a reduction in airflow lasting
10 seconds or more and resulting in a decrease of 4% or more in oxyhemoglobin saturation and/or an arousal. An arousal is characterized by electroencephalographic appearance of alpha waves, the brain waves that are normally present during relaxed wakefulness. There are two major types of sleep apnea (Figures 20.1 and 20.2). CSA is a temporary cessation of breathing rhythm (Javaheri, 2006a). Central apnea occurs when medullary inspiratory activity to thoracic inspiratory pump muscles (diaphragm and other inspiratory muscles) ceases. Polygraphically, therefore, CSA is characterized both by absence of thoracoabdominal excursions and naso-oral airflow (Figure 20.2). In contrast, during OSA, there are continual rhythmic contractions of thoracic pump muscle, yet airflow into the trachea ceases because of oropharyngeal closure. The collapse of the upper airway is due to relaxation of the muscles of the upper airway, the genioglossus muscle in particular, which falls backward during inspiration, unable to resist the negative pharyngeal airway pressure generated. Polygraphically, therefore, OSA is characterized by absence of naso-oral airflow in spite of the presence of thoracoabdominal excursions (Figure 20.1). If the oropharynx is completely obstructed, the event is an obstructive apnea, whereas a partial obstruction is called obstructive hypopnea. The most common cause of CSA is heart failure due to systolic dysfunction (Javaheri, 2004, 2005b, 2006a, b), a disorder discovered more than a century ago by John Hunter, John Cheyne, and William Stokes (Javaheri, 2004, 2005b). However, the most common cause of OSA in the general population is obesity (Young et al., 2002; Almossa and Javaheri, 2005). This is because obese individuals have a narrow upper airway that is vulnerable to closure during sleep, when muscles of the upper airway are unable to compensate
*Correspondence to: Shahrokh Javaheri, M.D., 4780 Socialville-Foster Rd, Mason, OH 45040, USA. Tel: (513) 459-7750, Fax: (513) 459-8030, E-mail:
[email protected]
Fig. 20.1. A 5-minute recording of a polysomnogram showing obstructive apneas with immediate pathophysiological consequences including arousal and desaturation–reoxygenation. Note the absence of naso-oral airflow in the presence of thoracoabdominal excursions. This indicates upper-airway occlusion. EOG, electro-occulogram; ECG, electrocardiogram; Abdo, abdomen; SaO2, saturation measured by pulse oximetry. (Reproduced from Kryger (2009).)
Patient is 80 yrs old, Hypertensive Heart Failure
Fig. 20.2. A 5-minute recording of a polysomnogram showing central apneas in the background of Cheyne–Stokes breathing. Note crescendo–decrescendo changes in thoracoabdominal excursions. Patient was 80 years old with hypertensive heart failure. EOG, electro-occulogram; ECG, electrocardiogram; SaO2, saturation measured by pulse oximetry. (Reproduced from Kryger (2009).)
CARDIOVASCULAR DISEASES AND SLEEP APNEA for the narrow airway and therefore, the likelihood of upper-airway occlusion increases (for review, see Almossa and Javaheri, 2005). In general, and also in this article, we use OSA to refer to the presence of obstructive apneas and hypopneas during sleep.
POLYSOMNOGRAPHY In order to diagnose sleep apnea – both CSA and OSA – polysomnography (Somnus, god of sleep) is performed. During polysomnography a number of electrophysiological variables, including electroencephalogram, electrooculogram, chin electromyogram, naso-oral airflow, thoracoabdominal excursions, and arterial oxyhemoglobin saturation, are recorded. Recording of brain waves, electro-oculogram, and chin electromyogram differentiates wakefulness from sleep, and also allows classification of various sleep stages into nonrapid eye movement (NREM: stages 1–4) and rapid eye movement (REM) sleep. Normally, an adult spends 80% of total sleep time in NREM and 20% in REM. Recordings of respiratory variables show the number of apneas, hypopneas, and arousals, and the degree of arterial oxyhemoglobin saturation. The number of apneas and hypopneas is divided by the total sleep time to calculate an apnea–hypopnea index (AHI). Similarly, the number of arousals is divided by total sleep time to derive the arousal index. The severity of arterial oxyhemoglobin desaturation could be expressed by the minimum saturation as well as the time spent below saturation of 90%. Polysomnographic recordings
OBSTRUCTIVE SLEEPAPNEA Figure 20.1 shows epochs of a polysomnogram of a patient with OSA in our laboratory. The apnea is characterized by the absence of naso-oral airflow. As noted above, during the period of obstructive apnea, thoracoabdominal excursions are present. Resumption of breathing is characterized by an arousal (appearance of alpha waves), opening of the upper airway, and resumption of airflow. As a result of apnea, there is also a reduction in arterial oxyhemoglobin saturation, which reverses back to normal as breathing resumes (hypoxia/reoxygenation). Furthermore, if we were to monitor arterial PCO2, hypercapnia would have been observed with the apnea and would reverse back to normal with resumption of breathing. In summary, the three main pathological effects of OSA linked to cardiocerebrovascular disorders (Figure 20.3) are: (1) altered blood gas chemistry, characterized by hypoxia/reoxygenation, hypercapnia/hypocapnia; (2) arousals; and (3) large negative swings in intrathoracic pressure (for review, see Somers and Javaheri, 2005).
MANIFESTATIONS OF OBSTRUCTIVE SLEEPAPNEA Although many individuals may have OSA, only some suffer from its consequences (Figure 20.4). Patients with OSA snore habitually (almost every night), which
ßO2 delivery
Organ dysfunction
Endothelial dysfunction syndrome
Vasoconstriction, thrombosis, inflammation
Hypoxic and hypercapnic pulmonary vasoconstriction
⇑ Right ventricular afterload
⇑⇓PO2 ⇑⇓PCO2
Sleep apnea hypopnea
Arousals
⇓ Ppl
329
of respiratory variables also allow differentiation of obstructive and central apneas from each other (Figures 20.1 and 20.2).
Sympathetic activation
⇑ Transmural pressure of left and right ventricles and of pulmonary microvascular bed
⇑ SVR/other adverse effects
Changes in right and left ventricular afterload ⇑ Lung H2O
Fig. 20.3. Pathophysiological sequelae of sleep apnea and hypopnea. Ppl, pleural pressure; SVR, systemic vascular resistance; # decrease; " increase. (Reproduced from Mann (2004).)
330
S. JAVAHERI AND V. SOMERS
Excessive daytime sleepiness
OSAHS
Obstructive sleep apnea hypopnea
Hypertension (systemic/pulmonary) CAD Arrhythmias
Asymptomatic snorer
HF (systolic/diastolic) Cerebrovascular disorders (TIA, stroke, dementia)
Fig. 20.4. Clinical consequences of obstructive sleep apnea and hypopnea (OSAH). Note that there are many snorers, but only some have OSA. Similarly, there are many individuals with OSA, but only some have the syndrome (i.e., OSA þ daytime sleepiness) and also only some have the cardiovascular complications. Genetic factors may account for varied manifestations of OSA. CAD, coronary artery disease; HF, heart failure; TIA, transient ischemic attack.
disturbs the sleep of their partner. They have many arousals (Figure 20.1), which they may not be aware of. These arousals fragment sleep and result in unrefreshing sleep and/or daytime sleepiness, fatigue, lack of energy, and deficit in attention. Excessive daytime sleepiness (EDS) is a major manifestation of OSA, and together this is known as OSA–hypopnea syndrome (Figure 20.4). Why only some patients with OSA have EDS (and associated cardiovascular disorder) is not known. Patients with EDS could fall asleep even while driving, resulting in fatal crashes. Sleepiness and loss of concentration may impair the quality of work and result in loss of job. Overall, OSA could result in poor quality of life. Nocturia is another symptom of OSA. This is in part because of frequent awakenings, and in part because stretch of cardiac chambers (secondary to exaggerated negative intrathoracic and cardiac transmural pressure) results in secretion of atrial natriuretic peptide. After treatment with continuous positive airway pressure (CPAP), nocturia and other symptoms of OSA are usually eliminated. Other manifestations of OSA are a variety of cardiovascular disorders, which are described below.
OBSTRUCTIVE SLEEP APNEA IS AN INFLAMMATORY DISORDER RESULTING IN CARDIOCEREBROVASCULAR DISORDERS Disordered breathing events result in hypoxemia, reoxygenation (analogous to ischemic reperfusion), hypercapnia, and a host of neurohormonal abnormalities such as increased sympathetic activity, hypercoagulopathy, release of endothelin, abnormal endothelium-dependent vasodilatation, growth and apoptosis, activation of white blood cells, increased concentration of adhesion molecules, and oxidative stress (Figure 20.5) (Lavie, 2003; Somers and Javaheri, 2005). These pathological mechanisms are involved in endothelial dysfunction syndrome, which may underlie coronary artery disease, hypertension, and stroke. OSA is a cause of systemic hypertension, and may also cause stroke and heart failure, and contribute to coronary artery disease and increased cardiovascular mortality. Importantly, treatment of OSA results in reversal of the aforementioned neurohormonal and biochemical abnormalities, suggesting a cause-and-effect relationship.
CARDIOVASCULAR DISEASES AND SLEEP APNEA
331
F
Reoxygenation ypercapnia /hypoc mia /h e apni x o a ⇓ . Hyp DO Nocturnal & diurnal hyper tension 2; ⇓ ⇓&⇑ & ⇑C Wa l l te B Alterations in CBF n s ⇓&⇑ ion
Sleep apnea & hypopnea
Sympathetic activity
Adhesion molecules
Multiple effects
Atherosclerosis
n atio Inflamm
n matio Inflam ion mat Inflam Oxidative stress sis mbo Thro Platel y et aggre gation/Coagulopath
Transcription factors
Fig. 20.5. Pathophysiological consequences of obstructive sleep apnea in relation to atherosclerosis and coronary, carotid, and other cerebral arteries. " increase; # decrease; D_ O2, oxygen delivery; CBF, cerebral blood flow. (Modified from Javaheri (2003a).)
CARDIOVASCULAR COMPLICATIONS OF OBSTRUCTIVE SLEEPAPNEA Potential cardiovascular complications of OSA include systemic arterial hypertension, pulmonary arterial hypertension, and cor pulmonale (Young and Javaheri, 2005), arrhythmias (Somers and Javaheri, 2005), coronary artery disease (Hedner et al., 2005), and heart failure (Javaheri, 2004, 2005b; Somers and Javaheri, 2005) (Figure 20.4). There are also cerebrovascular complications, which may include stroke, neuropsychological dysfunction, and dementia. The premise that OSA could cause cardiovascular complications is based on: (1) strong biological plausibility (briefly noted above); (2) strong evidence from animal laboratory studies; (3) evidence from epidemiological studies in humans; (4) reversal of neurohormonal abnormalities and also reduction in blood pressure with treatment of OSA with CPAP; and (5) studies which show increased cardiovascular mortality of untreated OSA patients, when compared to those treated with CPAP (see later).
Systemic arterial hypertension Arterial hypertension is the most systematically studied complication of OSA (Young and Javaheri, 2005), and the Joint Commission on Hypertension has recognized OSA as a cause of systemic hypertension (Chobanian et al., 2003). In addition to the biological plausibilities, animal studies link OSA to hypertension. Studies in rats (Lesske et al., 1997) have demonstrated that repetitive episodes of hypoxia–reoxygenation induced by intermittent nitrogen–room air-breathing mimicking
sleep apnea cause systemic hypertension. Hypoxemiainduced hypertension did not occur in rats whose carotid bodies had been surgically removed, indicating that carotid bodies were involved in mediating systemic hypertension. In a canine model in which the trachea could be occluded intermittently during sleep, mimicking severe OSA, within the course of 1–2 months diurnal blood pressure increased by about 15 mmHg (Brooks et al., 1997). Importantly, blood pressure normalized in about 2 weeks after relief of OSA. In humans, there is a high prevalence of systemic hypertension in patients with OSA as well as a high prevalence of OSA in hypertensive patients (Young and Javaheri, 2005). However, OSA patients are commonly obese and obesity is a known cause of hypertension; therefore, a major criticism of a number of studies relates to the presence of confounding issues. Detailed statistical analysis of cross-sectional studies (Bixler et al., 2000; Nieto et al., 2000; Duran et al., 2001) and a well-done prospective study (Peppard et al., 2000) have demonstrated an association between OSA and hypertension, independent of confounding factors (see below). Further, several studies (Faccenda et al., 2001; Becker et al., 2003), reviewed below, demonstrate that treatment of OSA results in a decrease of blood pressure, an observation similar to that of the canine model of OSA (Brooks et al., 1997). There is a number of epidemiological studies showing relation of OSA and hypertension. In the Sleep Heart Health Study (Nieto et al., 2000), the largest cross-sectional study of about 6000 men and women aged between 40 and about 100 years, there
332
S. JAVAHERI AND V. SOMERS
was a significant dose–response trend with odds ratio for hypertension ranging from 1.1 to about 1.4 comparing quartiles of the AHIs, after corrections for a number of confounding factors, including obesity. An independent association was also found in two other major studies (Bixler et al., 2000; Duran et al., 2001). The strongest epidemiological evidence for a causal association of OSA and hypertension comes from the prospective longitudinal studies of the Wisconsin Sleep Cohort Study (Peppard et al., 2000). In this welldesigned study, a random sample of middle-aged (30–60 years) state employees underwent a full-night polysomnography along with measurements of blood pressure. A total of 709 men and women were studied and were followed over the course of 4–8 years. The incidence of new hypertension, defined as a systolic arterial blood pressure of 140 mmHg or more, diastolic blood pressure of 90 mmHg or more, or use of antihypertensive medication at follow-up, was significantly dependent on baseline status of OSA. After adjustments for confounding factors, a dose–response association between OSA and hypertension was reported. The likelihood of developing new hypertension over 4 years was about twofold greater for those with a baseline sleep study showing AHI of 5–15, and threefold greater for those with AHI of more than 15 per hour when compared to individuals with AHI less than 1 per hour at baseline. Further evidence that OSA causes hypertension stems from both animal and human studies (reviewed by Young and Javaheri, 2005) demonstrating that treatment of OSA improves hypertension. As noted earlier in the canine model of OSA, relief of obstruction resulted in the reversal of systemic hypertension and normalization of blood pressure within a few weeks (Brooks et al., 1997). Several randomized single- and double-blind trials in humans have demonstrated that, in OSA patients with hypertension, treatment of OSA with CPAP results in a reduction of blood pressure (Faccenda et al., 2001; Becker et al., 2003). The most detailed and systematic study has been reported by Becker et al. (2003), in which 32 subjects with severe OSA with an AHI of about 60 per hour were enrolled. Sixteen subjects were randomized to therapeutic CPAP (effective treatment) and 16 to subtherapeutic CPAP (ineffective treatment). After about 9 weeks of therapy with CPAP there was a significant reduction in systolic as well as diastolic blood pressure, about 10 mmHg. In patients who were randomized to subtherapeutic CPAP, there was a slight rise in blood pressure. During the 9 weeks of the study, there were no significant changes in body weight or medications. The clinical importance of studies (Bixler et al., 2000; Nieto et al., 2000; Peppard et al., 2000; Duran
et al., 2001) showing association of OSA with systematic hypertension lies in the facts that: (1) 50 million Americans have essential hypertension; (2) hypertension is a major cause of cardiac and cerebrovascular disorders; (3) in a large number of these patients, OSA most probably contributes to or is the cause of hypertension; (4) effective treatment of OSA decreases blood pressure; and (5) importantly, even a small decrement in blood pressure, in the long run, could significantly decrease the incidence of complications of hypertension such as stroke and coronary artery disease. In this regard, in a prospective study (MacMahon et al., 1990) of 420 000 individuals, a decrease of 5 mmHg in diastolic blood pressure lessened the incidence of stroke and coronary heart disease by approximately 34% and 21%, respectively, during the 9-year follow-up. In addition, there was a dose-dependent reduction in blood pressure and incidence of cerebrocardiovascular disease. In regard to the treatment of OSA and hypertension, one important point which must be emphasized is that the reduction in blood pressure is dependent upon both elimination of obstructive disordered breathing events and compliance with CPAP. Therefore, clinicians taking care of OSA patients should underscore the importance of full compliance with CPAP.
Pulmonary arterial hypertension Before OSA was recognized as a sleep disorder, pickwickian syndrome was described. This syndrome is characterized by obesity, pulmonary hypertension causing cor pulmonale, hypoxemia, and hypercapnia. Now, we recognize that OSA causes pickwickian syndrome, and in 1998 the Second World Health Organization Conference on pulmonary arterial hypertension recognized OSA as a secondary cause of pulmonary hypertension (for a review, see Young and Javaheri, 2005). Generally, pulmonary arterial hypertension secondary to OSA is mild, though during exercise as cardiac output increases, pulmonary hypertension becomes more severe, resulting in diminished exercise tolerance (Hedner et al., 2005). OSA may also cause severe pulmonary arterial hypertension in patients with pre-existing cardiopulmonary diseases who already have compromised pulmonary vasculature (Chaouat et al., 2005). OSA may cause pulmonary hypertension by several mechanisms (Young and Javaheri, 2005). First, OSA may cause left ventricular diastolic dysfunction, resulting in increased left ventricular end-diastolic pressure, causing postcapillary pulmonary hypertension; OSA causes left ventricular diastolic dysfunction by a variety of mechanisms, including the presence of nocturnal and diurnal systemic hypertension, hypoxemia, increased
CARDIOVASCULAR DISEASES AND SLEEP APNEA 333 sympathetic activity, and other trophic agents that may animal study and a number of studies in humans have affect left ventricular function. The presence of comorshown its association with OSA. In a canine model bidities such as obesity, diabetes mellitus, coronary (Parker et al., 1999) mimicking severe OSA, left venartery disease, and old age may also adversely affect tricular systolic dysfunction developed within 3 months left ventricular diastolic function. after exposure to apneas during sleep. In this model, Second, OSA may cause precapillary pulmonary left ventricular systolic volume increased and left venhypertension because of hypoxemia. It is known that tricular ejection fraction decreased. alveolar hypoxia results in pulmonary arteriolar vasoIn humans there are two kinds of studies regarding constriction via a biochemical imbalance in the concenleft ventricular systolic dysfunction in OSA (for trations of local vasodilators (nitric oxide and review, see Lavie, 2003; Somers and Javaheri, 2005): prostacyclines) versus vasoconstrictors (endothelin-1, first, reports of patients with OSA who underwent carthromboxane, and serotonin) as it occurs in endothelial diac testing to determine the presence of left ventricudysfunction syndrome. Furthermore, it is conceivable lar systolic dysfunction, and second, the study of that long-standing OSA may result in pulmonary vaspatients with established left ventricular dysfunction cular remodeling similar to that in chronic obstructive who underwent sleep study. pulmonary disease, as a number of mediators such as In two studies (Alchanatis et al., 2002; Laaban et al., vascular endothelial growth factor are proliferative 2002) of patients with OSA, technetium-99 was used to and angiogenic and may be released in the presence assess left ventricular ejection fraction and it was shown of hypoxia–reoxygenation, which occurs in OSA. that OSA was associated with a low ejection fraction. As noted above, patients with chronic obstructive Use of radionuclide ventriculography in these studies pulmonary disease and other intrinsic lung disorders, is important because in obese patients echocardiography which have already compromised the pulmonary vascumay be associated with technical difficulties and yield lar bed, may develop severe pulmonary hypertension inaccurate results. Further evidence that OSA may once OSA is superimposed (Chaouat et al., 2005). cause systolic dysfunction stems from the observation The so-called overlap syndrome has been used to coin that the application of nasal CPAP to treat OSA is assothe presence of both chronic obstructive pulmonary ciated with a mild increase in left ventricular systolic disease and OSA. function (Kaneko et al., 2003; Mansfield et al., 2004). Further evidence that OSA causes pulmonary arteOn the other hand, it is well known that in patients rial hypertension stems from the results of several with established heart failure, particularly in those with long-term studies which show that treatment of OSA left ventricular systolic dysfunction, there is a high with CPAP decreases pulmonary arterial hypertension prevalence of OSA (Javaheri et al., 1998; Sin et al., (Young and Javaheri, 2005). However, it is important 1999; Tremel et al., 1999; Lanfranchi et al., 2003; to note that, depending on the mechanisms of the pulJavaheri, 2004, 2005b, 2006c), and treatment of OSA monary hypertension in OSA, the presence or absence with CPAP increases ventricular ejection fraction of pre-existing lung disease and the presence or significantly (Kaneko et al., 2003; Mansfield et al., absence of remodeling of the pulmonary vascular bed 2004), as early as 1 month after therapy (Kaneko may affect the outcome. Furthermore, long-term comet al., 2003). We also note that many patients with syspliance with CPAP is important to decrease pulmonary tolic heart failure suffer from CSA, which will be arterial hypertension, as it is for reduction in systemic discussed in detail later in this chapter. hypertension. There are only limited data on diastolic heart failure. In one study of 20 patients with left ventricular diastolic dysfunction, half of the patients had sleep Heart failure apnea (Chan et al., 1997). Meanwhile, in another study Both systolic and diastolic heart failure, including cases of 27 consecutive patients with OSA, Arias and colleaof pulmonary edema due to OSA, have been reported. gues (2005) reported that 15 of the patients had In the Sleep Heart Health Study (Shahar et al., 2001), impaired left ventricular relaxation. In a double-blind the largest epidemiological study of its kind, the pressham-controlled crossover trial of CPAP for 12 weeks, ence of OSA conferred a 2.4-fold increase in reported the ratio of peak flow velocity in early diastole to peak diagnosis of heart failure, which could have included velocity at atrial contraction increased (P < 0.01) and both systolic and diastolic heart failure. mitral deceleration time and isovolume relaxation time Among the two forms of heart failure, left ventricdecreased significantly. It is important to emphasize ular systolic dysfunction has been most systemically that other causes of diastolic dysfunction, including studied. Only limited data are available in diastolic systemic hypertension, were not present in these heart failure. In regard to systolic heart failure, an patients. Further larger studies are needed, but based
334
S. JAVAHERI AND V. SOMERS
on the study of Arias et al. (2005), OSA should be among the various causes of diastolic heart failure, including coronary artery disease, diabetes mellitus, and hypertension.
Arrhythmias Repetitive episodes of obstructive apnea are associated with severe derangements in blood gas characterized by hypoxemia, hypercapnia/acidosis, increases in left ventricular afterload and fluctuations in cardiac wall stress, and adrenergic activation (Figure 20.3), all of which may be conducive to both atrial and ventricular arrhythmias (Somers and Javaheri, 2005). It is therefore not surprising that a variety of atrial and ventricular arrhythmias, including premature atrial and ventricular depolarizations, atrial fibrillation, asystole, complete heart block, and ventricular tachycardia, have been observed during sleep in patients with OSA. These arrhythmias are more likely in the presence of pre-existing cardiovascular disease, such as coronary artery disease. The most common alteration in cardiac rhythm, however, is brady-tachy arrhythmias during sleep, paralleling obstructive disordered breathing events, and is observed in some patients with OSA. The brady-tachy arrhythmias reflect primarily fluctuations in autonomic nervous system activity, which are associated with repetitive episodes of apneas. It is emphasized that OSA-induced arrhythmias, including heart block, asystole, and atrial fibrillation, could be abolished by effective use of CPAP. In regard to atrial fibrillation, a study by Kanagala et al. (2003) shows that in patients cardioverted for atrial fibrillation, those with untreated OSA had a 12-month recurrence rate of 82% compared to a 42% recurrence rate in OSA patients receiving effective CPAP therapy.
Coronary artery disease Pathophysiological consequences of OSA (Figure 20.3), including hypoxemia–reoxygenation, recurrent left ventricular wall stress, and release of inflammatory mediators (Figure 20.5), can result in coronary artery disease or may worsen an already existing compromised coronary vascular bed (Hedner et al., 2005). Nocturnal cardiac events should particularly increase the suspicion for the presence of OSA. Manifestations could vary from silent ST changes to nocturnal angina, arrhythmias, noted above, and myocardial infarction (Mooe et al., 2001; Peker et al., 2002; Hedner et al., 2005). Episodes of nocturnal ischemia in particular are more common in OSA patients with coronary artery disease, mainly during REM sleep. This is not surprising since, during REM sleep, episodes of apnea
could become longer with more severe hypoxemia and hypercapnia with acidosis. Furthermore, during phasic REM there is increased sympathetic outflow. Application of nasal CPAP to treat OSA has been shown to reduce manifestations of ischemic coronary artery disease. OSA is common with myocardial infarction and the prevalence of myocardial infarction is also high in OSA patients (Hedner et al., 2005). In a study of 182 men without baseline cardiopulmonary disease, psychiatric disorders, malignancy, or diabetes mellitus who were followed for 7 years (Peker et al., 2002), an oxygen desaturation (a surrogate of OSA) index 30 per hour was associated with an increase in cardiovascular disease (37% in OSA versus 7% in control group). In multiregression analysis, OSA (odds ratio 5) and age were independent predictors of cardiovascular disease. In another Swedish study (Mooe et al., 2001) of 408 patients with established coronary artery disease followed for 5 years, an oxygen desaturation index of 5 or more per hour was associated with an 11% increase in the absolute risk of a primary composite endpoint (myocardial infarction, transient ischemic attacks, stroke, and death). In multivariate analysis, an oxygen desaturation index of more than 5 per hour was independently associated with the primary composite endpoint. Importantly, after effective treatment of OSA, the incidence of cardiovascular disease decreased. Cardiovascular disease occurred in 7% of effectively treated versus 57% of incompletely treated OSA patients (Mooe et al., 2001). Once more, this study emphasizes the importance of treating OSA adequately, particularly in patients with established coronary artery disease.
OSA AS A CAUSE OF MORTALITY It is well known that patients with OSA may fall asleep while driving, resulting in fatal crashes and death. Evidence is also accumulating that OSA may contribute to mortality via cardiovascular consequences. In an early study (Lindberg et al., 1998) of a sample of 3100 men aged 30–69 years who responded to a postal questionnaire, during a 10-year follow-up, 213 men died, 88 from cardiovascular disease, and this occurred primarily in subjects with a combination of snoring and EDS. In this study polysomnography was not performed; however, the presence of snoring and EDS was presumably due to OSA. The above study was followed by studies using polysomnography and patients with OSA were either compared to normal individuals and/or those treated with CPAP. Two early studies (He et al., 1988; Partinen
CARDIOVASCULAR DISEASES AND SLEEP APNEA et al., 1988) using polysomnography confirmed the earlier observation (Lindberg et al., 1998). He et al. (1988) were the first to report that, among 385 male patients with OSA, individuals with an apnea index of more than 20 per hour had increased all-cause mortality when compared to those who had been treated with either tracheostomy or CPAP. The results of this retrospective study have been confirmed by several other studies suggesting increased vascular mortality in patients with OSA. Two Swedish studies (Mooe et al., 2001; Peker et al., 2002) of patients with established coronary artery disease, reviewed above, have shown increased mortality in those with OSA compared to those without OSA. In the study of Peker et al. (2002), 62 patients with coronary artery disease were followed for 5 years. The incidence of cardiovascular deaths was significantly higher in those with OSA (AHI 10 per hour) than those without OSA (38% versus 9%, P ¼ 0.018). These results were in agreement with another Swedish study (Mooe et al., 2001) of 408 patients. In this study, patients with coronary artery disease and AHI 10 per hour had a 10% absolute increase in the composite endpoint (death, cerebrovascular event, and myocardial infarction) during the median follow-up of 5 years. In a study from Spain, Marin and colleagues (2005) followed a large group of subjects with and without OSA. They showed that patients with untreated severe OSA, defined as AHI 30 per hour, had a higher incidence of fatal and nonfatal cardiovascular events than simple snorers and untreated mild OSA. In a multivariate analysis adjusted for confounders, untreated severe OSA significantly increased the risk of both fatal and nonfatal cardiovascular events as compared with healthy participants. More importantly, severe OSA patients treated with CPAP had significantly fewer fatal and nonfatal cardiovascular events than untreated patients. Finally, Gami et al. (2005) showed that, from midnight to 6:00 a.m., sudden deaths from cardiac causes occurred in 46% of patients with OSA as compared with 21% of people without OSA (P ¼ 0.01). Collectively, therefore, these studies strongly indicate that OSA contributes to cardiovascular morbidity and mortality with deaths occurring during sleep. Furthermore, effective treatment with CPAP decreases the incidence of cardiovascular mortality. These results are also in line with studies showing that effective treatment of OSA with CPAP reverses neurohormonal abnormalities and inflammatory mediators of OSA and studies that treatment of OSA with CPAP decreases the blood pressure of patients with hypertension.
335
TREATMENT OF OSA Management of OSA in patients with cardiovascular disorders is in large part similar to that of patients without clinically obvious cardiovascular disorder (Table 20.1). However, in practice, our threshold to treat OSA in patients with cardiovascular disorder is quite low, though we emphasize that, in general, large therapeutic randomized clinical trials are lacking. Table 20.1 shows our approach to the treatment of patients with OSA. Ingestion of alcoholic beverages and use of benzodiazepines should be avoided. Both ethanol and benzodiazepines result in relaxation of the muscles of the upper airway, promoting oropharyngeal collapse. Since obesity is the major risk factor for OSA, weight loss is advised. Weight loss has been shown to improve OSA. The gold standard for the treatment of OSA is the use of noninvasive positive airway pressure devices. These devices consist of a blower connected, through tubing, to a mask (usually nasal, but could also be naso-oral). The simplest of these devices is a CPAP device. The device pressurizes the air, hence its name. In addition, the air is filtered and humidified. Through the nasal (or naso-oral) mask, the air pressure is transmitted to the upper airway and prevents upper-airway occlusion during sleep (pneumatic splint). The pressure can be set at different levels (from 5 to 30 cm H2O), and is determined overnight by the process of CPAP titration. With the patient wearing the mask and asleep, titration begins at low pressure of 5 cm H2O and is gradually increased to eliminate apneas, hypopneas, desaturation, and eventually snoring. Recent generations of these devices are quiet and create white noise, like a fan. We usually tell the patient that “we treat one person and two people sleep Table 20.1 Treatment of obstructive sleep apnea (OSA) Aggressive therapy of heart failure, if applicable Improve sleep hygiene, if applicable Avoidance of alcoholic beverages, benzodiazepines, and narcotics, particularly at bedtime Cessation of smoking Weight reduction, if applicable Avoidance of supine position in subset of patients with positional OSA (snore-ball t-shirt) Treatment of nasal congestion and obstruction Nasal positive airway pressure devices Oral appliances Nocturnal use of supplemental oxygen Upper-airway surgery Tracheostomy For details of the treatment of OSA, see the text and Javaheri (2004, 2005b).
336
S. JAVAHERI AND V. SOMERS
better.” This is because snoring, which is usually intermittent and disruptive, is replaced by a background low-level white noise, which is not disruptive. Treatment of OSA should result in a good night’s sleep, waking up refreshed, and elimination of EDS. In addition, as noted earlier, in hypertensive patients blood pressure may decrease if the patient remains compliant with CPAP (Faccenda et al., 2001; Becker et al., 2003). Often, we see a reduction in dosage of antihypertensive medications in such patients. For noncompliant patients, bilevel devices may be used. These devices allow a lower expiratory pressure, making it easier to exhale. We have had excellent experience with such devices in patients who have not been compliant with CPAP due to difficulty with excess expiratory pressure. Other modalities of therapy of OSA include upper-airway surgical procedures and mandibular advancement (Table 20.1). However, in the presence of established cardiovascular disease, we strongly urge the use of positive airway pressure devices, which are the most effective therapy. In summary, cardiovascular disorders are highly prevalent and are the top cause of death in the USA. OSA may be present in a large number of these patients, including those with systemic and pulmonary hypertension, atrial and ventricular arrhythmias, coronary artery disease, and systolic and diastolic left and right ventricular dysfunction and heart failure. Diagnosis and treatment of OSA restore good sleep, eliminate daytime sleepiness, and improve quality of life. Furthermore, treatment of OSA may also decrease the recurrence of atrial fibrillation and coronary artery disease, and lower systemic and pulmonary hypertension and mortality. Clinicians should thus have a very low index of suspicion for the diagnosis of OSA in cardiovascular disease patients. Once OSA is suspected, referral to a sleep specialist for evaluation and testing with polysomnography should be pursued. The use of CPAP in such patients should be viewed as being as important as the use of pharmacological therapies indicated for the treatment of cardiovascular disorders (e.g., angiotensin-converting enzyme inhibitors and beta-blockers for the treatment of heart failure). Patients should be encouraged to comply with CPAP as an essential part of their overall treatment regimen.
SLEEP APNEA IN PATIENTS WITH ESTABLISHED CONGESTIVE HEART FAILURE In patients with heart failure, in contrast to the general population, CSA is the most common form of sleeprelated breathing disorder, but OSA is also highly
prevalent. These two sleep-related breathing disorders may contribute to the progressive nature of heart failure. Although CSB was described by Hunter (37 years before Cheyne’s description) more than two centuries ago, until recently it was considered a rare entity. This is because full-blown periodic breathing with central apnea (i.e., CSB) rarely occurs during wakefulness when patients are usually examined by clinicians who may observe the pattern of breathing. Sleep, however, has profound effects on breathing and for a variety of reasons unmasks CSB (Javaheri, 2004, 2005a). Studies using polysomnography have rediscovered CSB and shown that a large number of patients with heart failure suffer from severe sleep apnea (Javaheri, 2004, 2006a). In this section, we will review the mechanisms, pathophysiological consequences, and treatment options of sleep apnea in heart failure. Emphasis is placed on CSA. For details of the treatment of OSA, see the earlier discussion and Table 20.1.
Prevalence of sleep apnea in heart failure Polysomnographic studies have reported a high prevalence of both obstructive and CSA in patients with established heart failure (Javaheri et al., 1995, 1998; Sin et al., 1999; Solin et al., 1999; Tremel et al., 1999; Lanfranchi et al., 2003; Javaheri, 2006b; and reviewed in Javaheri, 2004, 2005b; Somers and Javaheri, 2005). In systolic heart failure, CSA is the predominant form, although OSA is also common and both forms of sleep apnea commonly occur in the same patient. However, for diagnostic and therapeutic reasons, arbitrary polysomnographic criteria are used to define predominant CSA versus OSA. Independent of the kind of sleep apnea, the diagnosis of sleep apnea is important, since the pathophysiological sequelae of sleep-related breathing disorders such as hypoxemia may have an impact on the natural history of heart failure. In regard to isolated diastolic heart failure, OSA is probably common, but, as noted earlier, only limited data are available (Chan et al., 1997; Arias et al., 2005).
Sleep apnea in systolic heart failure The largest prospective study in systolic heart failure (Javaheri, 2006b) involved 100 ambulatory male subjects with stable, treated heart failure. Several aspects of this study need to be emphasized. Of the 114 consecutive eligible patients, 100 accepted to be enrolled and 14 refused. Exclusion criteria were presence of a comorbiddisorder (e.g., chronic obstructive pulmonary disease) and unstable cardiovascular status. Patients were recruited from cardiology and primary care clinic without any questions asked regarding the risk factors
CARDIOVASCULAR DISEASES AND SLEEP APNEA for sleep apnea, e.g., snoring, witnessed apnea, waking up tired. Patients were on optimal therapy before sleep study was performed. However, at the time of the study, fewer than 10% of the patients were taking bblockers. There were no changes in medical therapy within the 4 weeks preceding polysomnography. Patients were hospitalized for 2 nights. Each patient spent 2 nights in the sleep laboratory, the first night for habituation. Polysomnography with simultaneous Holter monitoring was performed during the second night. Using an AHI of 15 per hour or greater as the threshold, 49 subjects (49% of all patients) had moderate to severe sleep apnea–hypopnea with an average index of 44 per hour. In comparison, in a general population of subjects aged 30–60 years, and without clinically recognized heart failure (Young et al., 1993), 9% had an AHI > 15/hour. An AHI of 5 or greater has been used to define the presence of a significant number of disordered breathing events in OSA–hypopnea syndrome (Solin et al., 1999). Therefore, with a much higher prevalence of sleep apnea observed in patients with heart failure than in the general population, systolic heart failure should be the leading risk factor for sleep apnea. As noted earlier, both forms of sleep apnea, CSA and OSA, commonly occur in the same patient. However, using arbitrary criteria, studies have reported that 5–32% of patients with systolic heart failure have predominantly OSA, and 30–60% have CSA. The major reasons for differences in the prevalence rate and the predominant form of sleep apnea have to do with the criteria used to define hypopneas, accuracy of classification of disordered breathing events (specifically, distinction of central from obstructive hypopneas), the number of heart failure patients with obesity enrolled (the more obese subjects, the more OSA), the level of arterial PCO2, and the degree of left ventricular systolic dysfunction (heart failure patients with very low left ventricular ejection fraction and low PaCO2 have the highest prevalence of CSA). Obesity is an important risk factor for the development of OSA in the general population (Young et al., 1993; Almossa and Javaheri, 2005) and also in patients with heart failure (Sin et al., 1999; Javaheri, 2006b). Subjects with systolic heart failure and OSA are significantly heavier, snore habitually, and have a higher systemic arterial blood pressure than subjects with CSA (Sin et al., 1999; Javaheri, 2006b). However, aside from snoring and obesity, for a number of reasons, there are no significant differences in daytime symptoms (e.g., sleepiness) between heart failure patients with or without sleep apnea. We believe this is partly related to the overlapping symptoms of chronic heart failure with sleep apnea. Particularly, CSA is occult (Javaheri
337
et al., 1995), since such heart failure patients are not commonly obese and do not snore much.
Sleep apnea in isolated diastolic heart failure Both sleep apnea and diastolic heart failure are prevalent in the older population and the major consequences of sleep-related breathing disorders, such as sympathetic activation, nocturnal hypertension, and hypoxemia, could impair left ventricular diastolic function. It is, therefore, conceivable that sleep-related breathing disorder is a cause of diastolic dysfunction or contributes to the progression of left ventricular disease. Yet, little is known about the prevalence of sleeprelated breathing disorders and their impact on patients with isolated diastolic heart failure. As noted earlier, in one small study (Chan et al., 1997) of 20 patients with echocardiographic evidence of diastolic heart failure, half of the patients had sleep apnea. In another study (Arias et al., 2005), treatment of OSA with CPAP improved left ventricular diastolic dysfunction. Large epidemiologic and therapeutic studies are needed to define the relation of these two disorders, and the impact of treatment of sleep apnea on the natural history of isolated diastolic heart failure.
Pathophysiologic sequelae of sleep apnea in heart failure Chronic heart failure is a progressive disorder which is associated with remodeling of the ventricle. In systolic heart failure, there is eccentric remodeling of the left ventricle, with progressive left ventricular dilation. In diastolic heart failure, there is concentric remodeling of the left ventricle with predominant abnormalities in myocardial diastolic properties and relatively preserved left ventricular systolic function. In heart failure several endogenous systems such as neurohormones and cytokines are activated. Elevated levels of neurohormones, components of the renin–angiotensin–aldosterone system, inflammatory cytokines, and oxidative stress adversely affect cardiovascular structure and function, which ultimately results in myocyte apoptosis and fibrosis. Sleep-related breathing disorders are also associated with some of the same neurohormonal abnormalities (Lavie, 2003; Javaheri, 2004, 2005a, b; Somers and Javaheri, 2005) and may therefore contribute to progression of heart failure. Hypoxemia and hypercapnia result in increased sympathetic activity and pulmonary arterial vasoconstriction (Figure 20.3). Hypoxemia may result in decreased myocardial oxygen delivery and hypoxemia–reoxygenation result in increased expression of redox-sensitive genes, encoding inflammatory mediators such as endothelin
338
S. JAVAHERI AND V. SOMERS
(Lavie, 2003; Somers and Javaheri, 2005). These adverse effects of altered blood chemistry may be more deleterious to the cardiovascular system in the setting of heart failure and coronary artery disease than when the heart is otherwise normal. The second immediate consequence of sleep apneas and hypopneas is arousal (Figure 20.3). With each arousal, there is transient reinstitution of the wakefulness, increased sympathetic (Somers et al., 1993) and decreased parasympathetic activity. Consequently, heart rate and blood pressure increase. Arousalinduced sympathetic overactivity should have deleterious cardiovascular effects, particularly in the setting of heart failure. Finally, large intrathoracic pressure swings, which occur during OSA and during the hyperpnea following a central apnea, are reflected in juxtacardiac pressure swings increasing the transmural left ventricular pressure and its wall tension (Figure 20.3) (Javaheri, 2004, 2005b). This increase in left ventricular afterload is particularly deleterious in the setting of left ventricular systolic dysfunction. In addition, increased negative pulmonary interstitial pressure promotes pulmonary edema (Fletcher et al., 1999). In the setting of heart failure and increased left ventricular end-diastolic blood pressure, transpulmonary capillary transudation is further augmented by the increased capillary hydrostatic pressure.
Mechanisms of periodic breathing and CSA The mechanisms of periodic breathing and CSA in heart failure are multifactorial (Javaheri, 2004, 2005b). For simplicity, we would like to discuss the mechanisms underlying each process separately.
PERIODIC
BREATHING
Periodic breathing is characterized by crescendo/decrescendo changes in tidal volume, and is thought to be due to mechanisms destabilizing breathing. Breathing is normally controlled by a negative-feedback system. There are many experimental and mathematical models of the negative-feedback system. Such a system consists of a controller, a plant, and a channel of communication between the plant and the controller. In the negative-feedback system controlling breathing, the chemoreceptors are controllers, the lungs are the plant, and arterial circulation transfers information from the lungs to the chemoreceptors, informing them of changes in PCO2 and PO2. In a negative-feedback system, the increased controller gain, underdampening, and increased delay of transfer of information from the plant to the controller result in destabilization. In the case of the respiratory system, this translates into increased chemosensitivity,
decreased functional residual capacity, which results in underdampening, and increased arterial circulation time, which delays the transfer of information (changes in PO2 and PCO2) from the pulmonary capillary bed to the site of the chemoreceptors. In congestive heart failure alterations occur in the various components of this negative-feedback system which increase the likelihood of developing periodic breathing. Increased arterial circulation time is an invariable pathological feature of congestive heart failure. Therefore, any alterations that may occur in the pulmonary capillary PO2 and PCO2 will be delayed before chemoreceptors become aware of them. Such a delay converts a negative-feedback system to a positive one. The second factor which increases the likelihood of development of periodic PCO2, PCO2 breathing (and also CSA), is the gain of the chemoreceptors. In individuals with increased hypercapnic ventilatory response (Javaheri, 1999), the chemoreceptors elicit a large ventilatory response whenever PCO2 changes. Therefore, if PCO2 rises (e.g., due to a respiratory pause), there is a consequent hyperventilation that could drive the PCO2 below a level (apneic threshold) when ventilation ceases. Differences in the gain of the chemoreceptors among patients with heart failure may in part explain why only some patients develop periodic breathing and CSA. The third factor that may contribute to the development of periodic breathing in patients with heart failure is the decreased functional residual capacity which is commonly observed in patients with heart failure (Javaheri et al., 1998; Javaheri, 2006b). This could be due to cardiomegaly, pulmonary congestion, and pleural effusion. Decreased functional residual capacity results in underdamping. Underdamping means that, for a given change in ventilation, for example, a pause in breathing, changes in PCO2 will be augmented. In turn, the augmented change in PCO2 results in a pronounced compensatory ventilatory response and this along with increased chemosensitivity could result in overcompensation, which tends to destabilize breathing. Because the elements facilitating periodic breathing, i.e., increased chemosensitivity, decreased functional residual capacity, and increased arterial circulation time, are not state-specific, periodic breathing, not surprisingly, occurs during both sleep and wakefulness. In contrast, central apnea is more specific to the state of sleep. For the most part, this has to do with the unmasking of the apneic threshold during sleep, as discussed below.
CENTRAL
APNEA
Normally, with the onset of sleep ventilation decreases and PCO2 increases. As long as the level of PCO2 is above the apneic threshold, rhythmic breathing
CARDIOVASCULAR DISEASES AND SLEEP APNEA 339 continues. However, when the prevailing PCO2 periodic breathing may decrease the likelihood of decreases below the apneic threshold ventilation ceases developing upper-airway occlusion. Furthermore, since and central apnea occurs. It must be emphasized that elevated right atrial and central venous pressure may the more proximal the prevailing PCO2 to the apneic result in pharyngeal congestion and edema resulting threshold, the higher the chances of developing central in upper-airway narrowing, therapeutic measures to apnea. This is because, for example, after an arousal decrease venous pressure (Shepard et al., 1996), which with hyperventilation, the PCO2 may be lowered below may increase upper-airway size, are advisable. the apneic threshold such that with the onset of Patients should be advised to avoid the use of bensleep ventilation ceases and central apnea occurs. In zodiazepines and alcoholic beverages. These chemicals contrast, when the prevailing PCO2 is increased by 1–2 result in relaxation of the muscles of upper airway and mmHg (via exogenous administration of CO2 or adding promote upper-airway occlusion. Further, by impairing dead space), by widening the difference with the apneic the arousal system, alcohol and benzodiazepines may threshold, it effectively eliminates central apneas. prolong apneas. Xie et al. (2002) have shown that the difference Obesity is associated with heart failure and between the prevailing PCO2 minus apneic threshold is increased incidence of cardiovascular death (Calle significantly lower in patients with CSA and congestive et al., 1999; Kenchaiah et al., 2002). In the general popheart failure than those without CSA. The major reaulation, weight loss improves OSA. Since patients with son for this is that patients with heart failure and heart failure and OSA are also obese (Sin et al., 1999; CSA appear to be unable to increase their PCO2 as sleep Javaheri, 2005b, 2006b), weight loss should be advised. occurs. Although the mechanisms for this are still Nasal positive airway pressure devices (e.g., CPAP unclear, it is conceivable that such patients may have and bilevel devices) have been used successfully to more impaired left ventricular diastolic dysfunction, treat OSA in the general population and in patients such that in the supine position when venous return with heart failure (Javaheri, 2000, 2003a; Kaneko increases, pulmonary congestion may occur. Pulmoet al., 2003; Mansfield et al., 2004). These devices are nary congestion may result in stimulation of J recepthe treatment of choice. Overnight application of nasal tors. This information travels through the vagus CPAP results in a significant decrease in OSA and artenerves to nuclei tracti solitarii which, via phrenic nerve rial oxyhemoglobin desaturation (Javaheri, 2000), and stimulation, results in tachypnea, lowering PCO2. Therelong-term treatment (1–3 months) results in an increase fore, patients with severe left ventricular dysfunction in left ventricular ejection fraction by about 5–10% in may be unable to increase their PCO2 during sleep in heart failure patients with depressed ejection fraction the supine position. (Kaneko et al., 2003; Mansfield et al., 2004). One study In summary, therefore, patients with heart failure reported a reduction in overnight urinary norepinephare predisposed to periodic breathing primarily because rine excretion as well (Mansfield et al., 2004). These of the pathological features that occur in patients with are important findings because left ventricular ejection heart failure. Furthermore, because of the proximity of fraction and sympathetic overactivity are major predictheir prevailing PCO2, they are more prone to develop tors of survival in patients with heart failure. central apneas. For patients who do not tolerate high expiratory pressure of CPAP, bilevel pressure devices should be Treatment of sleep apnea in heart failure tried. These devices allow a lower expiratory than inspiratory pressure. Therefore, it is easier to exhale. Treatment of sleep apnea in heart failure depends on the An overnight titration is necessary to determine appropredominant form of the apnea. Treatment of OSA in priate levels of inspiratory and expiratory pressures. It heart failure is similar to that of OSA in the absence of is hoped that bilevel devices will improve compliance in heart failure (Javaheri, 2003a). However, treatment of those who are noncompliant with CPAP, and this has CSA is more controversial (Javaheri, 2005b, c). In general, been our experience. there are no long-term randomized clinical trials. In the For patients with heart failure who cannot tolerate absence of such trials our approach to the treatment of positive pressure devices in spite of consultation with OSA and CSA is briefly discussed below. a sleep specialist, nocturnal nasal oxygen may be used. The rationale for use of nocturnal supplemental nasal TREATMENT OF OSA IN HEART FAILURE oxygen is to improve both hypoxemia and periodic Treatment of OSA in heart failure is similar to that in breathing. Minimizing desaturation and hypoxemia– the absence of heart failure, though there are some difreoxygenation may have important therapeutic implicaferences (Table 20.1) (Javaheri, 2003a). For example, tions. Furthermore, by a variety of mechanisms, optimal treatment of heart failure by improving administration of nasal oxygen improves periodic
340
S. JAVAHERI AND V. SOMERS
breathing (Javaheri, 2003b). As noted above, improvement in periodic breathing could result in a decrease in obstructive disordered breathing events which occur at the nadir of ventilation (Hudgel et al., 1987; Dowdell et al., 1990). The dose of supplemental nasal oxygen should be determined in the sleep laboratory and could be as low as 1 1/min. The dose should be sufficient to eliminate desaturation. Other modalities of therapy of OSA are given in Table 20.1, but no systematic studies are available.
TREATMENT
OF
CSA
IN HEART FAILURE
Treatment of CSA (Figure 20.6) (Javaheri, 2003a, 2005c) is more difficult than treatment of OSA. As noted above, a patient with OSA is easily treated with CPAP during an overnight titration process. However, in the case of CSA, optimization of cardiovascular function is critical, since CSA is caused by systolic heart failure, and treatment of heart failure either eliminates (in a
small subset) or improves it. As will be noted below, ultimate treatment of systolic heart failure by cardiac transplantation virtually eliminates CSA, but unfortunately the waiting list is long and many cardiac transplant recipients develop OSA due to weight gain. Intensive therapy of heart failure with diuretics, angiotensin-converting enzyme inhibitors, b-blockers, and cardiac pacing (when indicated) improves and may even eliminate CSA (Solin et al., 1999; Javaheri, 2004, 2005c). With therapy, stroke volume increases and cardiopulmonary blood volume decreases, both of which decrease arterial circulation time. Functional residual capacity may increase as well (due to a decrease in cardiac size, pleural effusion, and intraand extravascular lung water), and these changes contribute to stabilization of breathing (Solin et al., 1999; Javaheri, 2004, 2005c). These improvements in cardiovascular pulmonary systems should improve periodic breathing, as discussed earlier.
Optimize therapy: ACEI; b-blockers; diuretics; digoxin; CRT
SRBD eliminated
Persistent SRBD
Consider treatment
Follow-up clinically
Cardiac transplantation
Medications
Nocturnal nasal oxygen
nCPAP
Acetazolamide
Theophylline
APSSV
Medical devices
Cardiac pacing
HFV
Mandibular advancement
Fig. 20.6. Treatment of central sleep apnea. For details, see the text. ACEI, angiotensin-converting enzyme inhibitor; CRT, cardiac resynchronization therapy; SRBD, sleep-related breathing disorders; HFV, high-frequency ventilation; nCPAP, nasal continuous positive airway pressure; APSSV, assisted proportional support servo-ventilation. (Reproduced from Mann (2004).)
CARDIOVASCULAR DISEASES AND SLEEP APNEA ß-blockers, by increasing stroke volume and decreasing pulmonary capillary pressure, should be particularly helpful in improving periodic breathing in systolic heart failure. An additional beneficial effect of ß-blockers may relate to their counterbalancing of nocturnal cardiac sympathetic hyperactivity due to sleep apnea. This mechanism may have contributed to improved survival in trials of ß-blockers in patients with heart failure. One potentially adverse effect of ß-blockers, however, relates to their effect on melatonin. Secretion of melatonin, a sleep-promoting chemical, is via the cyclic adenosine monophosphate-mediated b-receptor signal transduction system. ß-blockers, except carvedilol, by inhibiting this process decrease melatonin secretion (Arendt et al., 1985; Stoschitzky et al., 1999). In such patients use of the melatonin agonist ramelteon, which is many times more potent than melatonin, may improve total sleep time and translate into improved daytime symptoms such as fatigue and daytime sleepiness. Cardiac pacing by improving cardiac function may also improve CSA. This will be discussed later. After optimization of cardiopulmonary function, if periodic breathing persists, several approaches are possible (Figure 20.6).
Cardiac transplantation Cardiac transplantation virtually eliminates CSA. This is not surprising since heart failure is the cause of CSA. However, with time a large number of cardiac transplant recipients develop OSA (Javaheri et al., 2004). This is because of weight gain, which is most probably due to the use of corticosteroids. In a study of 45 cardiac transplant recipients (Javaheri et al., 2004), 36% had an AHI of 15/hour. This group of patients had gained the most weight since transplantation. OSA was associated with systemic hypertension and poor quality of life. It is therefore important that cardiac transplant recipients be monitored for the development of OSA.
Nasal positive airway pressure devices Nasal CPAP and bilevel pressure devices have been used to treat CSA in patients with systolic heart failure, with different results (Buckle et al., 1992; Davies et al., 1993; Guilleminault et al., 1993; Keily et al., 1998; Solin et al., 1999; Javaheri, 2000, 2003a, 2004, 2005c; Sin et al., 2000). Nasal CPAP has been most systemically studied. One-night use of CPAP improved CSA in 43% of patients with systolic heart failure (Javaheri, 2000). Typically, these CPAP-responsive patients had mild to moderate CSA, and the average AHI decreased from 36 to 4 per hour. An important observation was that, in these patients (and in contrast
341
to CPAP nonresponsive patients), the number of premature ventricular contractions, couplets, and ventricular tachycardias decreased. Heart failure patients with severe CSA (57% of the patients) did not respond to acute CPAP titration (Javaheri, 2000), and other laboratories have also reported negative results (Buckle et al., 1992; Davies et al., 1993; Guilleminault et al., 1993; Sin et al., 2000). Chronic trials (1–3 months) of nasal CPAP devices (for review, see Javaheri, 2003a) in subjects with heart failure and CSA show a reduction in AHI, improved desaturation, decreased plasma and urinary norepinephrine, and an increase in left ventricular ejection fraction. However, a randomized controlled study of CPAP was prematurely terminated because of lack of overall efficacy (Bradley et al., 2005). We have therefore stopped using CPAP as an option to treat CSA in heart failure. If CPAP is used to treat CSA in heart failure, caution should be exercised.
Cardiac pacing Several laboratories have reported on the use of cardiac pacing to treat sleep apnea, both OSA and CSA. In a study of 15 subjects who had permanent atrialsynchronized ventricular pacemakers placed for symptomatic sinus bradycardia (Garrigue et al., 2002), atrial overdrive (average 72 beats/min versus spontaneous 57 beats/min) moderately but significantly decreased the AHI (from 28 to 11 per hour), improved arterial oxyhemoglobin desaturation, and decreased arousals. These patients had predominantly mild to moderate CSA, and some had mild left ventricular systolic dysfunction. The obstructive apnea index decreased from 6 to 3/hour, which is not clinically significant. Cardiac resynchronization therapy (CRT) has been applied for treatment of some patients with systolic heart failure. The device has been shown to improve CSA. Sinha and colleagues (2004) studied 14 patients with mean left ventricular ejection fraction of 24% who had left bundle branch block and received a CRT device. Patients had mild sleep apnea and were studied before and on average 17 weeks after CRT. The mean AHI decreased significantly from 19 to 5 per hour and minimum saturation increased from 84% to 89%. In the most comprehensive study of CRT, using full-night polysomnography, Gabor et al. (2005) studied 28 patients, 12 of whom had severe CSA. In the 10 patients who had successful implantation, mean AHI decreased significantly from 43/hour to 31/hour when studied 27 weeks later. However, only 6 patients improved with mean AHI, decreasing from 33/hour to 4/hour (P < 0.005). The mean AHI did not change significantly in the other 4 patients. Based on the above
342
S. JAVAHERI AND V. SOMERS
studies, we hypothesize that pacing, in particular, biventricular pacing, by improving hemodynamics and reversing cardiac remodeling, should improve CSA. However, further systematic studies are needed. We should emphasize, however, that CRT is ineffective for the treatment of OSA (Lu¨thje et al., 2005; Pepin et al., 2005; Simantirakis et al., 2005).
Nocturnal supplemental nasal oxygen Systematic studies (Hanly et al., 1989; Javaheri et al., 1999; see review in Javaheri, 2003b) have consistently shown that nocturnal therapy with supplemental nasal oxygen improves CSA. The dose of oxygen should be determined by an overnight study and should be sufficient to eliminate desaturation. Treatment of CSA with oxygen decreases muscle sympathetic nerve activity (Andreas et al., 2003) and overnight urinary norepinephrine excretion (Staniforth et al., 1998), and improves maximum exercise capacity (Andreas et al., 1996) and left ventricular ejection fraction (Sasayama et al., 2006). However, prospective placebo-controlled long-term studies are necessary (Javaheri, 2003b) to determine if nocturnal oxygen therapy has the potential to decrease morbidity and mortality of patients with systolic heart failure.
Theophylline Theophylline is a respiratory stimulant and has been used to treat CSA both in infants and in adults. Open (Dowdell et al., 1990) and blind studies (Javaheri et al., 1996) have shown the efficacy of theophylline in the treatment of CSA in heart failure (reviewed in American Heart Association, 2004). In a randomized, doubleblind, placebo-controlled, crossover study (Javaheri et al., 1996) of 15 patients with treated, stable systolic heart failure, oral theophylline at therapeutic plasma concentration (11 mg/ml, range 7–15 mg/ml), decreased the AHI by about 50%, and improved arterial oxyhemoglobin saturation. Potential arrhythmogenic effects and phosphodiesterase inhibition are common concerns with long-term use of theophylline in patients with heart failure. However, there are no long-term controlled studies. If theophylline is used to treat CSA, frequent and careful follow-ups are necessary.
Acetazolamide Acetazolamide is a mild diuretic and also a respiratory stimulant. Few studies have reported on the use of this medication for treatment of CSA at high altitude as well as idiopathic CSA. In a randomized double-blind placebo-controlled crossover study (Javaheri, 2006c) of 12 patients with stable severe systolic heart failure
and mean left ventricular ejection fraction of about 20%, administration of acetazolamide at a dose of about 3 mg/kg 30 minutes before bedtime resulted in considerable improvement in CSA and arterial oxyhemoglobin desaturation (Javaheri, 2006c). Comparing acetazolamide with placebo, the central apnea index decreased from 49 to 23 per hour. The obstructive AHI did not change significantly. As a result of improvement in CSA, the degree of arterial oxyhemoglobin desaturation improved. While on placebo, arterial oxyhemoglobin saturation remained below 90% for about 20% of the total sleep time. This decreased to 6% while on acetazolamide. Further long-term studies are needed to determine the efficacy and sideeffects of acetazolamide in patients with heart failure. As noted in this study (Javaheri, 2006c), acetazolamide was administered as a single dose at night in the hope of minimizing long-term potential side-effects of multi-pill dosing. In summary, therefore, sleep-related breathing disorders are common in congestive heart failure and could contribute to increased morbidity and mortality of heart failure. Depending on the kind of sleep apnea, there are a number of therapeutic modalities (Javaheri and Wexler, 2005); however, large-scale systematic studies are lacking.
REFERENCES Alchanatis M, Tourkohoriti G, Kosmas EN et al. (2002). Evidence of left ventricular dysfunction in patients with obstructive sleep apnea syndrome. Eur Respir J 20: 1239–1245. Almossa K, Javaheri S (2005). Obesity and the control of breathing. In: DS Ward, A Dahan, LF Teppema (Eds.), Pharmacology and Pathophysiology of the Control of Breathing, Vol. 202. Lung Biology in Health and Disease. Taylor and Francis, Boca Raton, pp. 383–422. American Heart Association LF (2004). Heart Disease and Stroke Statistics-2004 Update. American Heart Association, Dallas. American Heart Association LF (2010). Heart Disease and Stroke Statistics-2010 Update. American Heart Association, Dallas. Circulation 121: e46–215. Andreas S, Clemens C, Sandholzer H et al. (1996). Improvement of exercise capacity with treatment of CheyneStokes respiration in patients with congestive heart failure. J Am Coll Cardiol 27: 1486–1490. Andreas S, Bingeli C, Mohacsi P et al. (2003). Nasal oxygen and muscle sympathetic nerve activity in heart failure. Chest 123: 366–371. Arendt J, Bojkowski C, Franey C et al. (1985). Immunoassay of 6-hydroxymelatonin sulfate in human plasma and urine: abolition of the urinary 24-hour rhythm with atenolol. J Clin Endocrinol Metab 60: 1166–1173. Arias MA, Garcia-Rio F, Alonso-Fernandez A et al. (2005). Obstructive sleep apnea syndrome affects left
CARDIOVASCULAR DISEASES AND SLEEP APNEA ventricle diastolic function: effects of nasal continuous positive airway pressure in men. Circulation 112: 375–383. Becker HF, Jerrentrup A, Ploch T et al. (2003). Effect of nasal continuous positive airway pressure treatment on blood pressure in patients with obstructive sleep apnea. Circulation 107: 68–73. Bixler EO, Vgontzas AN, Lin HM et al. (2000). Association of hypertension and sleep-disordered breathing. Arch Intern Med 160: 2289–2295. Bradley T, Logan A, Kimoff R et al. (2005). Continuous positive airway pressure for central sleep apnea and heart failure. N Engl J Med 353: 2025–2033. Brooks D, Horner RL, Kozar LF et al. (1997). Obstructive sleep apnea as a cause of systemic hypertension. Evidence from a canine model. J Clin Invest 99: 106–109. Buckle P, Millar T, Kryger M (1992). The effects of shortterm nasal CPAP on Cheyne–Stokes respiration in congestive heart failure. Chest 102: 31–35. Calle EE, Thun MJ, Petrelli JM et al. (1999). Body-mass index and mortality in a prospective cohort of U.S. adults. N Engl J Med 341: 1097–1105. Chan J, Sanderson J, Chan W et al. (1997). Prevalence of sleep-disordered breathing in diastolic heart failure. Chest 111: 1488–1493. Chaouat A, Bugnet A-S, Kadaoui N et al. (2005). Severe pulmonary hypertension and chronic obstructive pulmonary disease. Am J Respir Crit Care Med 172: 189–194. Chobanian AV, Bakris GL, Black HR et al. (2003). The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation and Treatment of High Blood Pressure. The JNC report. JAMA 289: 2560–2572. Davies RJO, Harrington KJ, Ormerod JM et al. (1993). Nasal continuous positive airway pressure in chronic heart failure with sleep-disordered breathing. Am Rev Respir Dis 147: 630–634. Dowdell WT, Javaheri S, McGinnis W (1990). Cheyne– Stokes respiration presenting as sleep apnea syndrome. Clinical and polysomnographic features. Am Rev Respir Dis 141: 871–879. Duran J, Esnaola S, Rubio R et al. (2001). Obstructive sleep apnea-hypopnea and related clinical features in a population-based sample of subjects aged 30 to 70 yr. Am J Respir Crit Care Med 163: 685–689. Faccenda JF, Mackay TW, Boon NA et al. (2001). Randomized placebo-controlled trial of continuous positive airway pressure on blood pressure in the sleep apnea-hypopnea syndrome. Am J Respir Crit Care Med 163: 344–348. Fletcher EC, Proctor M, Yu J et al. (1999). Pulmonary edema develops after recurrent obstructive apneas. Am J Respir Crit Care Med 160: 1688–1696. Gabor JY, Newman DA, Barnard-Roberts V et al. (2005). Improvement in Cheyne–Stokes respiration following cardiac resynchronization therapy. Eur Respir J 26: 95–100. Gami AS, Howard DE, Olson EJ et al. (2005). Day-night pattern of sudden death in obstructive sleep apnea. N Engl J Med 352: 1206–1214. Garrigue S, Bordier P, Jaı¨s P et al. (2002). Benefit of atrial pacing in sleep apnea syndrome. N Engl J Med 346: 404–412.
343
Guilleminault C, Clerk A, Labanowski M et al. (1993). Cardiac failure and benzodiazepines. Sleep 16: 524–528. Hanly PF, Millar TW, Steljes DG et al. (1989). The effect of oxygen on respiration and sleep in patients with congestive heart failure. Ann Intern Med 111: 777–782. He J, Krygwe MH, Zorick FJ et al. (1988). Mortality and apnea index in obstructive sleep apnea: experience in 358 male patients. Chest 94: 9–14. Hedner J, Franklin K, Peker J (2005). Coronary artery disease and obstructive sleep apnea. In: MH Kryger, T Roth, WC Dement (Eds.), Principles and Practice of Sleep Medicine. 4th edn. WB Saunders, Philadelphia. Hudgel D, Chapman KR, Franks C et al. (1987). Changes in inspiratory muscle electrical activity and upper airway resistance during periodic breathing induced by hypoxemia during sleep. Am Rev Respir Dis 135: 899–906. Javaheri S (1999). A mechanism of central sleep apnea in patients with heart failure. N Engl J Med 341: 949–954. Javaheri S (2000). Effects of continuous positive airway pressure on sleep apnea and ventricular irritability in patients with heart failure. Circulation 101: 392–397. Javaheri S (2003a). Heart failure and sleep apnea: emphasis on practical therapeutic options. Clin Chest Med 24: 207–222. Javaheri S (2003b). Pembrey’s dream: the time has come for a long-term trial of nocturnal supplemental nasal oxygen to treat central sleep apnea in congestive heart failure. Chest 123: 322–325. Javaheri S (2004). Sleep related breathing disorders in heart failure. In: DL Mann (Ed.), Heart Failure: A Companion to Braunwald’s Heart Disease. WB Saunders Elsevier, Philadelphia, pp. 471–487. Javaheri S (2005a). Sleep and cardiovascular disease: present and future. In: MH Kryger, T Roth, WC Dement (Eds.), Principles and Practice of Sleep Medicine. 4th edn. WB Saunders, Philadelphia, pp. 1157–1160. Javaheri S (2005b). Heart failure. In: MH Kryger, T Roth, WC Dement (Eds.), Principles and Practice of Sleep Medicine. 4th edn. WB Saunders, Philadelphia, pp. 1208–1217. Javaheri S (2005c). Central sleep apnea in congestive heart failure: prevalence, mechanisms, impact and therapeutic options. Semin Respir Crit Care Med 26 (1): 44–55. Javaheri S (2006a). Central sleep apnea. In: TL Lee Chiong (Ed.), Sleep: A Comprehensive Handbook. Wiley-Liss, New Jersey, pp. 249–262. Javaheri S (2006b). Sleep disorders in systolic heart failure: a prospective study of 100 male patients. Int J Cardiol 106: 21–28. Javaheri S (2006c). Acetazolamide improves central sleep apnea in heart failure. Am J Crit Care Med 173: 234–237. Javaheri S, Wexler L (2005). Prevalence and treatment of breathing disorders during sleep in patients with heart failure. Curr Treatment Options Cardiovas Med 7: 295–306. Javaheri S, Parker TJ, Wexler L et al. (1995). Occult sleepdisordered breathing in stable congestive heart failure. Ann Intern Med 122: 487–492. [Published erratum appears in Ann Intern Med 1995, 123: 77.]
344
S. JAVAHERI AND V. SOMERS
Javaheri S, Parker TJ, Wexler L et al. (1996). Effect of theophylline on sleep-disordered breathing in heart failure. N Engl J Med 335: 562–567. Javaheri S, Parker TJ, Liming JD et al. (1998). Sleep apnea in 81 ambulatory male patients with stable heart failure: types and their prevalences, consequences and presentations. Circulation 97: 2154–2159. Javaheri S, Ahmed M, Parker TJ et al. (1999). Effects of nasal O2 on sleep-related disordered breathing in ambulatory patients with stable heart failure. Sleep 22: 1101–1106. Javaheri S, Abraham W, Brown C et al. (2004). Prevalence of obstructive sleep apnea and periodic limb movement in 45 subjects with heart transplantation. Eur Heart J 25: 260–266. Kanagala R, Murali N, Friedman P et al. (2003). Obstructive sleep apnea and the recurrence of atrial fibrillation. Circulation 107: 2589–2594. Kaneko Y, Floras JS, Usui K et al. (2003). Cardiovascular effects of continuous positive airway pressure in patients with heart failure and obstructive sleep apnea. N Engl J Med 248: 1233–1241. Keily JL, Deegan P, Buckley A et al. (1998). Efficacy of nasal continuous positive airway pressure therapy in chronic heart failure: importance of underlying cardiac rhythm. Thorax 53: 956–962. Kenchaiah S, Evans JC, Levy D et al. (2002). Obesity and the risk of heart failure. N Engl J Med 347: 305–313. Kryger M (2009). Atlas of Clinical Sleep Medicine. Elsevier, Philadelphia. Laaban JP, Fascal-Sebaoun S, Bloch E et al. (2002). Left ventricular systolic dysfunction in patients with obstructive sleep apnea syndrome. Chest 122: 1133–1138. Lanfranchi PA, Somers VK, Braghiroli A et al. (2003). Central sleep apnea in left ventricular dysfunction. Prevalence and implications for arrhythmic risk. Circulation 727–732. Lavie L (2003). Obstructive sleep apnea syndrome – an oxidative stress disorder. Sleep Med Rev 7: 35–51. Lesske J, Fletcher EC, Bao G et al. (1997). Hypertension caused by chronic intermittent hypoxia – influence of chemoreceptors and sympathetic nervous system. J Hypertens 15: 1593–1603. Lindberg E, Janson C, Sva¨rdsudd K et al. (1998). Increased mortality among sleepy snorers: a prospective population based sudy. Thorax 53: 631–637. Lu¨thje L, Unterberg-Buchwald C, Dajani D et al. (2005). Atrial overdrive pacing in patients with implanted pacemaker. Am J Respir Crit Care Med 172: 118–122. MacMahon S, Peto R, Cutler J et al. (1990). Epidemiology: blood pressure, stroke, and coronary heart disease. Part 1, prolonged difference in blood pressure: prospective observational studies corrected for the regression dilution bias. Lancet 335: 765–774. Mann D (2004). Heart Failure: A Companion to Braunwald’s Heart Disease. WB Saunders Elsevier, Philadelphia. Mansfield DR, Gollogly C, Kaye DM (2004). Controlled trail of continuous positive airway pressure in obstructive
sleep apnea and heart failure. Am J Respir Crit Care Med 169: 361–366. Marin JM, Carrizo SJ, Vicente E et al. (2005). Long-term cardiovascular outcomes in men with obstructive sleep apnoea-hypopnoea with or without treatment with continuous positive airway pressure: an observational study. Lancet 365: 1046–1053. Mooe T, Franklin KA, Holmstrom K et al. (2001). Sleepdisordered breathing and coronary artery disease: longterm prognosis. Am J Respir Crit Care Med 164: 1910–1913. Nieto FJ, Young TB, Lind BK et al. (2000). Association of sleep-disordered breathing, sleep apnea, and hypertension in a large community-based study. JAMA 283: 1829–1836. Parker JD, Brooks D, Kozar LF (1999). Acute and chronic effects of airway obstruction on canine left ventricuolar performance. Am J Respir Crit Care Med 160: 1888–1896. Partinen M, Jamieson A, Guilleminault C (1988). Long term outcome for obstructive sleep apnea syndrome patients: mortality. Chest 94: 1200–1204. Peker Y, Hedner J, Norum J et al. (2002). Increased incidence of cardiovascular disease in middle-aged men with obstructive sleep apnea: a seven-year follow-up. Am J Respir Crit Care 166: 159–165. Pepin JL, Defaye P, Garrigue S et al. (2005). Overdrive atrial pacing does not improve sleep apnoea syndrome. Eur Respir J 25: 343–347. Peppard PE, Young T, Palta M et al. (2000). Prospective study of the association between sleep-disordered breathing and hypertension. N Engl J Med 342: 1378–1384. Sasayama S, Izumi T, Yoshihiko S et al. (2006). Effects of nocturanl oxygen therapy on outcome measures in patients with chronic heart failure and Cheyne–Stokes respiration. Circ J 70: 1–7. Shahar E, Whitney CW, Redline S et al. (2001). Sleepdisordered breathing and cardiovascular disease: crosssectional results of the Sleep Heart Health study. Am J Respir Crit Care Med 163: 19–25. Shepard JW Jr, Pevernagie DA, Stanson AW et al. (1996). Effects of changes in central venous pressure on upper airway size in patients with obstructive sleep apnea. Am J Respir Crit Care Med 153: 250–254. Simantirakis E, Schiza S, Chrysostomakis S et al. (2005). Atrial overdrive pacing for the obstructive sleep apnea-hypopnea syndrome. N Engl J Med 353: 2568–2577. Sin DD, Fitzgerald F, Parker JD et al. (1999). Risk factors for central and obstructive sleep apnea in 450 men and women with congestive heart failure. Am J Respir Crit Care Med 160: 1101–1106. Sin DD, Logan AG, Fitzgerald FS et al. (2000). Effects of continuous positive airway pressure on cardiovascular outcomes in heart failure patients with and without Cheyne–Stokes respiration. Circulation 102: 61–66. Sinha A-M, Skobel EC, Breithardt O-A et al. (2004). Cardiac resynchonization therapy improves central sleep apnea and Cheyne–Stokes respiration in patients with chronic heart failure. J Am Coll Cardiol 44: 68–71.
CARDIOVASCULAR DISEASES AND SLEEP APNEA Solin P, Bergin P, Richardson M et al. (1999). Influence of pulmonary capillary wedge pressure on central apnea in heart failure. Circulation 99: 1574–1579. Somers V, Javaheri S (2005). Cardiovascular effects of sleeprelated breathing disorders. In: MH Kryger, T Roth, WC Dement (Eds.), Principles and Practice of Sleep Medicine. 4th edn. WB Saunders, Philadelphia, pp. 1180–1191. Somers VK, Dyken ME, Mark AL et al. (1993). Sympatheticnerve activity during sleep in normal subjects. N Engl J Med 328: 303–307. Staniforth AD, Kinneart WJM, Hetmanski DJ et al. (1998). Effect of oxygen on sleep quality, cognitive function and sympathetic activity in patients with chronic heart failure and Cheyne–Stokes respiration. Eur Heart J 19: 922–928. Stoschitzky K, Sakotnik A, Lercher P et al. (1999). Influence of beta-blockers on melatonin release. Eur J Clin Pharmacol 55: 111–115. Tremel F, Pe´pin JL, Veale D et al. (1999). High prevalence and persistence of sleep apnoea in patients referred for
345
acute left ventricular failure and medically treated over 2 months. Eur Heart J 20: 1201–1209. Xie A, Skatrud JB, Puleo DS et al. (2002). Apnea-hypopnea threshold for CO2 in patients with congestive heart failure. Am J Respir Crit Care Med 165: 1245–1250. Young T, Javaheri S (2005). Systemic and pulmonary hypertension in obstructive sleep apnea. In: MH Kryger, T Roth, WC Dement (Eds.), Principles and Practice of Sleep Medicine. 4th edn. WB Saunders, Philadelphia, pp. 1192–1202. Young T, Palta M, Dempsey J et al. (1993). The occurrence of sleep disordered breathing among middle aged adults. N Engl J Med 328: 1230–1235. Young T, Peppard PE, Gottlieb DJ (2002). Epidemiology of obstructive sleep apnea: a population health perspective. Am J Respir Crit Care Med 165: 1217–1239.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 21
Alterations in gastrointestinal functioning during sleep WILLIAM C. ORR* Lynn Health Science Institute and Oklahoma University Health Sciences Center, Oklahoma City, OK, USA
The study of sleep has progressed from a relatively obscure endeavor largely devoted to psychological and psychiatric applications to a more recent burgeoning of work which has elucidated marked alterations in respiratory functioning during sleep, hormonal functioning during sleep, and major health consequences attributable to sleep restriction and/or deprivation. Neurologists have long been the primary referral source for patients with excessive daytime sleepiness and remain the primary referral source for most primary care physicians who recognize that this is the primary symptom of narcolepsy. As a result of this neurologists have become one of the primary subspecialty homes of sleep disorders medicine. These discoveries have led to a remarkable broadening of the focus and importance of the applications of basic sleep physiology to numerous areas of clinical medicine, and require the medical disciplines involved in sleep medicine to become familiar with the changes in all organ systems dictated by the inexorable occurrence of sleep in mammalian life. Lagging somewhat behind the obvious developments in respiratory physiology and pulmonology has been the description of gastrointestinal (GI) functioning during sleep, and the possible applications of these changes to clinical medicine. Perhaps the most obvious reason for this is the relative inaccessibility of the GI tract to easy study during sleep. Studying GI physiology during sleep routinely requires the placement of measuring devices via some external orifice. This alone generally disrupts sleep; however, more recent developments in measurement technology have allowed somewhat more convenient access to the luminal GI tract. As a result, there has been a marked increase in studies describing alterations in GI functioning during sleep, and the specific applications of these changes to the practice of gastroenterology.
This review will present data related to how various GI functions are altered during sleep and how these changes impact the pathogenesis of GI diseases. Among the first issues to bring together the clinical relevance of GI functioning during sleep was the notion of the pathogenesis of duodenal ulcer disease. It was thought that vagal stimulation during sleep was instrumental in producing the hypersecretion of acid which was thought to be associated with the pathogenesis of duodenal ulcer disease. Some studies have described the hypersecretion of acid during rapid eye movement (REM) sleep, and this prompted a study from our laboratory which involved patients with duodenal ulcer disease and controls. Each of these individuals was studied for several nights with full polysomnographic (PSG) monitoring and the assessment of acid secretion and serum gastrin levels (Orr et al., 1976). This study did not document any relationship between acid secretion in the stages of sleep; however, it stimulated numerous other studies which attempted to describe GI physiology and how it may be altered by sleep. This study was among the first to examine GI function using standard GI measurement techniques during PSG.
UPPER GI FUNCTIONING DURING SLEEP Gastroesophageal reflux (GER) Clearly the most common and familiar problem related to the upper GI system is gastroesophageal reflux (GER), and its most common symptom, heartburn. It is well established that GER is a common event postprandially and in fact it is a normal physiologic response to gastric distension which induces a transient relaxation of the lower esophageal sphincter. Heartburn and regurgitation are also well established as the most common symptoms of esophageal mucosal contact. Since the sensation of heartburn is a waking conscious
*Correspondence to: William C. Orr, Ph.D., President and CEO, Lynn Health Science Institute, 3555 NW 58th St. Suite 800, Oklahoma City, OK 73112, USA. Tel: 405-602-3918, E-mail:
[email protected]
W.C. ORR
experience, and many reflux events do not necessarily produce a symptom, the occurrence of GER during sleep is difficult to estimate by symptoms alone. This is further complicated by the fact that sleep is an amnestic phenomenon and patients may not remember brief arousals which may in fact be caused by GER. GER does occur during sleep, as has been documented by recent studies, but it is clearly less common than that which occurs in the waking stage (Penzel et al., 1999) (Figure 21.1). In fact one might conclude from these data that sleep protects against GER, since reflux events were noted to be far less common during documented sleep than during brief arousals from sleep. Classic studies which involve the utilization of 24-hour esophageal pH monitoring have established that GER occurs less commonly during the sleeping interval and is generally associated with the prolongation of acid clearance (Johnson and DeMeester, 1974). As is noted in Figure 21.2, waking reflux is generally postprandial and reflux events are rapidly cleared (1–2 minutes). During sleep, however, reflux events are certainly less frequent and generally associated with a longer period of acid GER during sleep
% Reflux events
100 90 80 70 60 50 40 30 20 10 0 WASO
Stage 1
Stage 2
SWS
REM
Fig. 21.1. The occurrence of gastroesophageal reflux during the stages of sleep. WASO, wakings after sleep onset; SWS, slow-wave sleep; REM, rapid eye movement. (Adapted from Penzel et al. (1999).) Normal postprandial reflux (in normal volunteer) 8
pH
6 4 2 0 16:00
meal
heartburn 17:00
18:00
19:00
Time (PM)
Fig. 21.2. The pattern of daytime gastroesophageal reflux is demonstrated in this recording. It reveals several short episodes of reflux which occur postprandially.
Sleep reflux Supine sleep condition 8 6 pH
348
4 2 0 0:20
0:40
1:00
1:20
1:40
Fig. 21.3. This recording demonstrates the prolongation of acid clearance which is commonly associated with episodes of gastroesophageal reflux that occur during sleep.
contact time (Figure 21.3). Subsequent studies from our laboratory have confirmed these findings, in that we have demonstrated that the complications of reflux which result in discontinuity of the esophageal mucosa are generally associated with an increase in the percentage of supine (during the sleeping interval) GER (Johnson and DeMeester, 1974). Clearly, the pattern of GER is different, and the occurrence of acid mucosal contact during sleep appears to be clearly associated with esophageal complications. The utilization of 24-hour pH studies to describe GER during the circadian cycle has focused on the description of subjective reports of recumbency and the extent to which that positional report can adequately represent the sleeping interval. In a study of patients with GER disease (GERD) it was shown that recumbent waking is distinctly different from recumbency noted during the sleeping interval in that the latter is associated with overall less acid contact (Dickman et al., 2007a) (Figure 21.4). What are the sleep-related physiologic alterations that facilitate this prolongation of acid mucosal contact? There is an orchestration of responses to acid mucosal contact in the esophagus to include secretory, motor, and sensory responses (Figure 21.5). Typically, acidification of the distal esophagus will produce a marked increase in the secretion and bicarbonate concentration of saliva. This allows ample buffering potential in order to neutralize the acidic lining of the distal esophagus. Also, in response to an acidic distal esophagus, there is a marked increase in the rate of swallowing, which allows the delivery of the potent buffer of saliva into the distal esophagus. Swallowing and the subsequent primary peristaltic contractions of the esophagus allow the rapid removal of large volumes of refluxate from the distal esophagus. Finally, acid mucosal contact is associated with a sensation of substernal burning which is perceived as uncomfortable and/or painful. These responses have been determined to be present in a normal waking individual and it is immediately obvious
Mean percent total time pH < 4
ALTERATIONS IN GASTROINTESTINAL FUNCTIONING DURING SLEEP
349
*
14
12.8
12
*
10
n = 64
8.5
8
*
6
4.3
4 2 0 Upright
Supine-awake
Supine-asleep
*P < 0.0001
Fig. 21.4. Comparison of the percentage of time with acid contact time (pH < 4) during upright position and awake, the recumbent position and awake, and in the recumbent position during the sleeping interval. (Adapted from Dickman et al. (2007a).)
Salivary flow
Normal defense mechanisms against acid load
Acid-mucosal response
Heartburn (warning)
Sleep
Acid mucosal contact
Local response (2° peristalsis)
Swallowing (1° peristalsis)
No heartburn
1° Peristalsis
Salivary flow
Risk of complications
Fig. 21.5. Schematic diagram of typical responses to the contact of the esophageal mucosa by refluxed gastric contents. Normal defense mechanisms against acid load.
Fig. 21.6. Schematic diagram of alterations in typical responses to acid mucosal contact during sleep.
that swallowing and the experience of heartburn are generally assumed to be waking conscious phenomena. The combination of these responses typically results in a rapid clearance of esophageal volume of reflux gastric contents, as well as neutralization of the acidic mucosa. The dependence of this rapid acid clearance response on at least two waking, conscious responses logically raises the question of how these responses may be altered during sleep. The characteristic responses to acid mucosal contact, which are noted above in the waking state, are generally absent during sleep (Figure 21.6). It is clearly these alterations in response to acid mucosal contact during sleep that result in the marked prolongation of acid clearance noted during sleep. A study from our laboratory has demonstrated that the simple infusion of acid into the distal esophagus during polygraphically monitored sleep results in a highly significant prolongation
of acid clearance time compared to infusions in the supine waking state (Orr et al., 1981). Adding to the risks associated with reflux during sleep is the fact that the swallowing rate is markedly diminished, and salivary flow is essentially absent. Heartburn, of course, being a waking conscious phenomenon, is clearly absent during sleep. Thus, the combination of these alterations in acid mucosal response associated with sleep establishes a significant risk for the prolongation of acid mucosal contact during sleep. The prolongation of acid mucosal contact carries with it significant risks. For example, it has been shown that the back diffusion of hydrogen ions into the esophageal mucosa is directly related to the duration of esophageal acid contact time (Johnson and Harmon, 1986) (Figure 21.7). Thus, extrapolating from this, brief and rapidly cleared episodes of reflux would appear to be relatively benign, while more prolonged episodes of
350
W.C. ORR
H+ flux and duration of acid exposure
Net acid flux (µEq/10 min) Out of lumen
80
60
40 rR=.93 NAF=1.25t + 10.8 N=5
20
15
30
45
60
Time (min)
Fig. 21.7. Relationship between acid contact time infused into the esophagus and the back diffusion of hydrogen ions from the lumen of the esophagus into the mucosa. (Reproduced from Johnson and Harmon (1986).)
GER would be associated with a greater risk of mucosal damage. As has been noted above, sleep-related GER is associated with more prolonged acid mucosal contact while GER during the waking state is generally associated with more rapid acid clearance. An additional risk of prolonged acid mucosal contact relates to the higher risk of the proximal migration and eventual spillover of reflux gastric contents into the tracheobronchial tree. In a study from our laboratory, small (1 ml and 3 ml) volumes of acid were instilled into the esophagus during supine waking and sleep to evaluate the proximal migration of acid infused into the distal esophagus during sleep (Orr et al., 2000). Esophageal pH sensors were located in both the distal and proximal esophagus and proximal migration was assessed by a drop in the pH in the proximal sensor subsequent to the infusion of acid. It was noted that, in the awake, supine position, none of the normal volunteers studied showed evidence of proximal migration of 1 ml. During sleep, however, 40% of these same individuals showed evidence of a substantial proximal migration of acid infused into the distal esophagus during polygraphically determined non-REM sleep. Thus, it can be concluded from these data that sleep itself induces considerable risk of prolonged acid mucosal contact and it facilitates the occurrence of a proximal migration of refluxed gastric contents. Maintaining sleep in response to an episode of GER seems to be a maladaptive response, since an arousal from sleep is required to produce a more rapid clearance
from a sleep-related reflux event. The complications of nighttime reflux are significant in that nighttime GER can lead to the development of esophagitis, as well as other complications such as exacerbation of bronchial asthma, chronic cough, and sleep complaints. These complications appear to be primarily related to the presence of significant nighttime reflux and the consequent prolongation of esophageal acid clearance (Orr et al., 1994). Of particular interest to the sleep clinician are studies which have been done in patients with obstructive sleep apnea. The frequent occurrence of obesity, and the appreciable negative intrathoracic pressures associated with upper-airway obstruction, are certainly risk factors for the occurrence of nighttime GER. Although studies have not indicated that there is a specific relationship between obstructive events and reflux events, these patients tend to have an overall increase in esophageal acid contact time. Other studies have shown that a reduction in obstructive events, via appropriate continuous positive airways pressure treatment, results in an associated significant reduction in heartburn complaints (Ing et al., 2000; Green et al., 2003).
Clinical aspects of nighttime gastroesophageal reflux Patients with nighttime heartburn have a number of complaints related to disturbed sleep (Shaker et al., 2003). In addition to documenting the presence of a number of sleep complaints, these studies documented the fact that, in patients with both daytime and nighttime heartburn, the nighttime heartburn was significantly more bothersome. More than 50% of these individuals complained that nighttime heartburn awakened them and about 30% were awakened by coughing and choking due to regurgitation. About 40% of the patients with nighttime symptoms noted that their heartburn affected their ability to function the next day and about 60% indicated it affected their mood. The use of sleeping pills was also substantially increased in patients with nighttime GERD symptoms. A large epidemiologic study has also identified OSA as a significant predictor of nighttime heartburn (Fass et al., 2005). Furthermore, a number of studies have now related substantially diminished quality of life associated with nighttime heartburn (Dean et al., 2008; Orr, 2010). The occurrence of sleep-related acid contact as documented by PSG studies has been shown to be altered in patients with nighttime heartburn. For example, it has been demonstrated that patients with nighttime heartburn and sleep complaints have significantly more acid contact time than subjects who have nighttime heartburn but do not complain of sleep
ALTERATIONS IN GASTROINTESTINAL FUNCTIONING DURING SLEEP disturbance (Chen et al., 2008). Another study has shown that more severe GERD symptoms are associated with worse subjective sleep and that greater acid exposure during sleep was related to worse reported quality of sleep (Dickman et al., 2007b). Nighttime GER has been associated with a number of respiratory symptoms, such as wheezing, chronic cough, and hoarseness. Not uncommonly, patients with GERD-related asthma or chronic cough will not have heartburn as a symptom. Thus, the presence of nighttime reflux cannot be ruled out on the basis of a negative history of nighttime heartburn. Nighttime wheezing is quite common in asthmatics and approximately 41% of asthmatic patients have been shown to have reflux-associated respiratory symptoms (Sontag, 2000). Additional support for this association has been noted in an excellent epidemiology study published by a group of European epidemiologists (Gislason et al., 2002). In this study the authors showed that individuals who reported nighttime heartburn at least twice a week had an odds ratio of 2.0 for associated respiratory symptoms such as coughing and wheezing. In addition, this group has noted from their studies that nighttime heartburn is also an independent risk factor for sleep complaints and daytime sleepiness. Of interest is a study which has documented that a substantial proportion of patients who complain of nonrestorative sleep or sleep disturbance have significant sleep-related GER (Orr et al., 2008). In this study patients with documented subjective reports of disturbed or unrefreshed sleep for 6 of 14 nights and without complaints of heartburn were studied for 2 separate nights in the sleep laboratory. There results were compared to a group of normal controls without sleep complaint or heartburn. The patients with sleep disturbance had a marked elevation in sleep-related acid contact time compared to the controls. This raises the interesting question as to what percentage of patients with unexplained sleep disturbance could have significant GER as the underlying cause of their sleep complaint.
Gastric function during sleep The motor function of the stomach serves to deliver gastric contents into the antrum and ultimately into the duodenum at an appropriate rate and pH. Reports of alterations in gastric motility during sleep have been contradictory and there are no particularly conclusive results with regard to either the motor functioning of the stomach or its ultimate consequence, gastric emptying. The measurement of gastric emptying during sleep is nearly impossible with current technology, which requires the use of nuclear radiographic techniques which are not amenable to measurement during
351
sleep. However, the noninvasive recording of the gastric electric pacemaker provides easy access to the measurement of gastric myoelectric activity, which is a fundamental property of the stomach. By utilizing surface electrodes placed in periumbilical locations, a 3-cycle-per-minute electrical rhythm can be detected from the surface of the stomach. By subjecting this measure to spectral analysis, various properties of the gastric electrical rhythm can be determined, such as its amplitude and frequency modulation. The electrical rhythm is a product of the endogenous functioning of the enteric nervous system, and it serves to modulate the contractility of the gastric smooth muscle. Sleep studies from our laboratory have challenged the traditional belief that the pacemaker activity is without central nervous system influence. It has been shown that a significant decline in the power of the 3-cycle-per-minute activity is apparent during nonREM sleep, and there is a significant recovery during REM sleep to levels comparable to the waking state (Elsenbruch et al., 1999a). These results suggest that non-REM sleep is associated with a marked destabilization of the basic gastric electrical rhythm, and that the cerebral activation of REM sleep appears to stabilize this basic gastric pacemaker. It might be concluded from these results that higher cortical input, or a degree of central nervous system arousal, must be present in order to stabilize and promote normal gastric functioning, and consequently normal gastric emptying. Much additional work needs to be done to understand gastric functioning during sleep and its possible clinical consequences.
Intestinal motility and irritable bowel syndrome The irritable bowel syndrome (IBS) is perhaps the quintessential manifestation of alterations in the brain–gut axis. Much work has centered on the description of visceral pain modulation in this patient population via the autonomic nervous system, but there remains considerable confusion as to intestinal functioning in patients with IBS and its various subgroups (i.e., constipation predominant, diarrhea predominant, and alternating). Some work from our laboratory and others has suggested that sleep and altered autonomic function during sleep may play a role in the pathogenesis of IBS (Orr et al., 1997). Technological and practical difficulties in monitoring intestinal activity in humans have somewhat retarded the study of intestinal activity during sleep, but some data have been gradually appearing in the medical literature which reveal important changes in intestinal function in patients with chronic constipation and fecal incontinence.
352 W.C. ORR Several studies have now demonstrated a decrease et al., 1990). Several studies have shown a relationship in colonic motor activity during sleep and a clear inhibetween poor sleep and pain in IBS patients. Studies bition of the colonic motility index in the transverse, have estimated the prevalence of reported sleep comdescending, and sigmoid colon. A marked increase in plaints to be as high as 25–30% in the population of activity was noted upon awakening, or with brief aroupatients with functional bowel disorders (i.e., IBS and sals from sleep. This offers a logical explanation of the functional dyspepsia). The high prevalence of sleep common urge to defecate upon awakening in the complaints in patients with functional bowel disorders morning (Narducci et al., 1987). Studies done to date has been specifically noted in a prospective study of a clearly suggest an inhibition of colonic contractile and group of patients and healthy controls utilizing both myoelectric activity during sleep, as well as diminished bowel symptoms and sleep questionnaires (Fass et al., colonic tone (Steadman et al., 1991). Rectoanal pres2000). In this study patients were divided into groups sures have been measured continuously during sleep, with functional dyspepsia, IBS, or a combination of and results have indicated a decrease in the minutedyspepsia and IBS symptoms. This study showed that to-minute variation in the amplitude of spontaneous patients with IBS symptoms alone did not differ from anal canal activity during sleep (Orkin et al., 1991). normal controls with regard to the reported incidence Another study by Rao and Welcher (1996) has shed of sleep complaints; however, if dyspeptic symptoms light on intrinsic anorectal functioning. They have indiwere part of the symptom complex, sleep complaints cated that the intrinsic oscillation in rectal motor activity were significantly greater. In another similar study increased by 44% during sleep as compared to waking which assessed the prevalence of functional bowel disactivity. Of particular importance is that the majority orders in patients with sleep disturbances, it was shown of these contractions were propagated in a retrograde that sleep disturbance was independently associated direction. Again, this activity would clearly facilitate recwith IBS (Vege et al., 2004). tal continence during periods of depressed consciousA consensus appears to be emerging with regard to ness since other studies have documented a marked subjective and objective parameters of sleep in patients decrease in anal canal pressure during sleep. These studwith functional bowel disorders. Compared to normal ies have documented the fact that, although anal canal controls, sleep architecture appears to be quite similar pressure is decreased during sleep, it is maintained at a to normal subjects in patients with functional bowel level somewhat higher than the intrarectal pressure, thus disorders. In this sense, the pattern of behavior in these facilitating rectal continence during sleep (Orkin et al., patients appears to resemble that of many insomniac 1991; Steadman et al., 1991; Rao and Welcher, 1996). patients, in whom normal sleep patterns are quite exagThese studies collectively shed important light on gerated in terms of complaints of prolonged sleep the mechanisms of rectal continence during sleep. latency and interrupted, nonrefreshing sleep. A report There appear to be at least two mechanisms that prefrom our laboratory confirmed normal sleep architecvent the passive escape of rectal contents during sleep. ture in patients with IBS (Elsenbruch et al., 1999b). In First, rectal motor activity increases substantially duraddition, this study did not reveal any abnormalities ing sleep, but the propagation is retrograde rather than in cortisol secretion or reports of stress or anxiety. It anterograde. Furthermore, these physiologic studies was clearly demonstrated that, although IBS patients have shown that, even under the circumstances of peridid have more sleep complaints, their PSG patterns odic rectal contractions, the anal canal pressure is conwere completely indistinguishable from those of agesistently above that of the rectum. Both of these and sex-matched controls. mechanisms would tend to protect against rectal leakSimilar results have been described in another study age during sleep, and alterations in these mechanisms in which patients with self-described severer IBS sympwould explain loss of rectal continence during sleep toms reported more sleep disturbances than normal in individuals with diabetes or who have undergone controls, but the sleep architecture was not significantly ileoanal anastomosis. different (Heitkemper et al., 2005). These results are Ambulatory monitoring of the small intestine has somewhat divergent from another study which utilized been accomplished in patients with IBS. Studies have home assessments of sleep via both PSG and actigraph documented that nighttime motor patterns of the small at home (Rotem et al., 2003). In this study some sleep bowel did not differentiate patient groups from conparameters noted in the PSG data were altered in IBS trols: in fact, it was noted that there was a notable lack patients to include increased waking after sleep onset of activity in the small bowel during sleep, which led and an increase in arousal responses. These studies are the investigators to suggest that the changes in motor difficult to compare due to differences in IBS diagnosfunctioning noted were primarily the result of reactions tic group age and sex composition of the study to “stressful events” during the waking state (Kellow populations.
ALTERATIONS IN GASTROINTESTINAL FUNCTIONING DURING SLEEP In perhaps the largest PSG study to date in IBS patients, we have demonstrated that there is a substantial correlation of subjective sleep complaints and depression. Once again, the PSG parameters were, with the single exception of the REM onset latency (IBS 126.3 minutes versus controls 84.9 minutes; P< 0.05), indistinguishable from normal subjects (Robert et al., 2004). Recent studies have indicated that the autonomic nervous system appears to be a mediator of visceral pain in patients with functional bowel disorders. Studies have shown some disruption in autonomic functioning during the waking state in patients with IBS, but these studies have had conflicting results. Work from our laboratory has shown increasing sympathetic tone during REM sleep in patients with IBS (Thompson et al., 2002). In a series of studies we have evaluated autonomic regulation by conducting spectral analysis of heart rate variability, which allows a determination of the sympathetic and parasympathetic regulation of cardiac activity. Subsequent studies have noted that IBS patients who have dyspeptic symptoms did not appear to have this autonomic dysfunction: rather it was most notable in patients with IBS, but without dyspeptic symptoms (Thompson et al., 2002). Of particular interest are two studies which have shown that the administration of the sleep-promoting hormone melatonin improves IBS symptoms, but appears to do this independent of any effect on sleep disturbance (Lu et al., 2005; Song et al., 2005). The Song et al. (2005) study did select IBS patients with sleep disturbance and recorded both objective and subjective measures of sleep. There was no significant difference in any of the sleep parameters compared to placebo. Collectively, these studies from various sleep investigations in patients with functional bowel disorders suggest not only that there are sleep disturbances noted in this patient population, but also that the sleep disturbances may contribute to altered GI functioning. Certainly, these studies confirm the notion that there are central nervous system alterations in patients with functional bowel disorders, and that these alterations are perhaps uniquely identified during sleep. Future studies in sleep and patients with functional bowel disorders will undoubtedly provide additional understanding of the pathophysiology of the brain–gut axis and its alterations during sleep.
CONCLUSIONS In this review, an integration of GI functioning has been attempted with regard to its relationship to sleep and how this interaction may lead to complaints of sleep disorders, as well as the pathogenesis of some
353
GI disorders. Considerable data have been presented here to support the notion that sleep-related GER is an important factor not only in the development of esophagitis, but also in respiratory complications of GER. The relationship of GER to disturbed sleep as objectively determined by PSG has been described, and it has been shown that sleep-related GER can alter the perception of sleep and affect subsequent daytime functioning. Although sensory functioning is markedly altered during sleep with regard to most standard sensory functions (i.e., auditory), there appears to be an enhancement of some visceral sensation during sleep which would appear to protect the tracheobronchial tree from aspiration of gastric content reflux during sleep. Patients with functional bowel disorders clearly reveal an increase in sleep complaints compared to normal volunteers. The mechanisms of these disturbances remain somewhat obscure and studies have not demonstrated any consistent abnormalities in sleep patterns of these patients. Some studies have shown that autonomic functioning during sleep, particularly REM sleep, can distinguish patients with IBS and dyspeptic symptoms. Some emphasis has been placed on autonomic function during sleep and how this may be important in understanding the pathogenesis of IBS. Thus, the continued study of sleep and GI functioning promises to create a new dimension in the understanding of the pathophysiology of a variety of GI disorders.
REFERENCES Chen CL, Robert JT, Orr WC (2008). Sleep symptoms and gastroesophageal reflux. J Clin Gastroenterol 42: 13–17. Dean BB, Aguilar D, Johnson LF et al. (2008). Nighttime and daytime atypical manifestations of gastroesophageal reflux disease: frequency, severity, and impact on health related quality of life. Aliment Pharmacol Ther 27: 327–337. Dickman R, Shapiro M, Malagon IB et al. (2007a). Assessment of 24-h oesophageal pH monitoring should be divided to awake and asleep rather than upright and supine time periods. Neurogastroenterol Motil 19: 709–715. Dickman R, Green C, Fass SS et al. (2007b). Relationships between sleep quality and pH monitoring findings in persons with gastroesophageal reflux disease. J Clin Sleep Med 3: 505–513. Elsenbruch S, Harnish MJ, Orr WC et al. (1999a). Disruption of normal gastric myoelectric functioning by sleep. Sleep 22: 453–458. Elsenbruch S, Harnish MJ, Orr WC (1999b). Subjective and objective sleep quality in irritable bowel syndrome. Am J Gastroenterol 94: 2447–2452. Fass R, Fullerton S, Tung S et al. (2000). Sleep disturbances in clinic patients with functional bowel disorders. Am J Gastroenterol 95: 1195–2000.
354
W.C. ORR
Fass R, Quan S, O’Connor G et al. (2005). Predictors of heartburn during sleep in a large prospective cohort study. Chest 127: 1658–1666. Gislason T, Janson C, Vermeire P et al. (2002). Respiratory symptoms and nocturnal gastroesophageal reflux. Chest 121: 158–163. Green BT, Broughton WA, O’Connor JB (2003). Marked improvement in nocturnal gastroesophageal reflux in a large cohort of patients with obstructive sleep apnea treated with continuous positive airway pressure. Arch Intern Med 163: 341–345. Heitkemper M, Jarrett M, Burr K et al. (2005). Subjective and objective sleep indices in women with irritable bowel syndrome. Neurogastroenterol Motil 17: 523–530. Ing AJ, Ngu MC, Breslin AB (2000). Obstructive sleep apnea and gastroesophageal reflux. Am J Med 108 (Suppl 4a): 120S–125S. Johnson LF, DeMeester TR (1974). Twenty-four hour pH monitoring of the distal esophagus. Am J Gastroenterol 62: 325–332. Johnson LF, Harmon JW (1986). Experimental esophagitis in a rabbit model: clinical relevance. J Clin Gastroenterol 8: 26–44. Kellow JE, Gill RG, Wingate DL (1990). Prolonged ambulant recordings of small bowel motility demonstrate abnormalities in the irritable bowel syndrome. Gastroenterol 98: 1208–1218. Lu WZ, Gwee KA, Moochhala S (2005). Melatonin improves bowel syndromes in female patients with irritable bowel syndrome: a double blind placebo controlled study. Aliment Pharmacol Ther 22: 927–934. Narducci F, Bassotti G, Gaburri M et al. (1987). Twenty-four hour manometric recording of colonic motor activity in healthy men. Gut 28: 17–25. Orkin BA, Hanson RB, Kelly KA et al. (1991). Human anal motility while fasting, after feeding, and during sleep. Gastroenterol 100: 1016–1023. Orr WC (2010). Review article: sleep related gastroesophageal reflux as a distinct clinical entity. Aliment Pharmacol Ther 31: 47–56. Orr WC, Hall WH, Stahl ML et al. (1976). Sleep patterns and gastric acid secretion in duodenal ulcer disease. Arch Intern Med 136: 655–660. Orr WC, Robinson MG, Johnson LF (1981). Acid clearing during sleep in the pathogenesis of reflux esophagitis. Dig Dis Sci 26: 423–427. Orr WC, Allen ML, Robinson M (1994). The pattern of nocturnal and diurnal esophageal acid exposure in the
pathogenesis of erosive mucosal damage. Am J Gastro 89: 509–512. Orr WC, Crowell MD, Lin B et al. (1997). Sleep and gastric function in irritable bowel syndrome: derailing the braingut axis. Gut 41: 390–393. Orr WC, Elsenbruch S, Harnish MJ et al. (2000). Proximal migration of esophageal acid perfusions during waking and sleep. Am J Gastroenterol 95 (1): 37–42. Orr WC, Goodrich S, Fernstrom P et al. (2008). Occurrence of nighttime gastroesophageal reflux in disturbed and normal sleepers. Clin Gastroenterol Hepatol 6: 1099–1104. Penzel T, Becker HR, Brandenburg U et al. (1999). Arousal in patients with gastro-oesophageal reflux and sleep apnoea. Eur Respir J 14: 1266–1270. Rao SS, Welcher K (1996). Periodic rectal motor activity: the intrinsic colonic gatekeeper? Am J Gastroenterol 91: 890–897. Robert JJ, Orr WC, Elsenbruch S (2004). Modulation of sleep quality and autonomic functioning by symptoms of depression in women with irritable bowel syndrome. Dig Dis Sci 49 (7–8): 1250–1258. Rotem AY, Sperber AD, Kruglik P et al. (2003). Polysomnographic and actigraphic evidence of sleep fragmentation in patients with irritable bowel syndrome. Sleep 26: 747–752. Shaker R, Castell DO, Schoenfeld PS et al. (2003). Nighttime heartburn is an under-appreciated clinical problem that impacts sleep and daytime function: the results of a Gallup survey conducted on behalf of the American Gastroenterological Association. Am J Gastroenterol 1487–1493. Song GH, Leng PH, Gwee KA et al. (2005). Melatonin improves abdominal pain in irritable bowel syndrome patients who have sleep disturbances: a randomized, double blind, placebo controlled study. Gut 54: 1402–1407. Sontag SJ (2000). Gastroesophageal reflux disease and asthma. J Clin Gastroenterol 39 (Suppl): S9–S30. Steadman CJ, Phillips SF, Camilleri M et al. (1991). Variations of muscle tone in the human colon. Gastroenterol 101: 24. Thompson JJ, Elsenbruch S, Harnish MJ et al. (2002). Autonomic functioning during REM sleep differentiates IBS symptom subgroups. Am J Gastroenterol 97: 3147–3153. Vege SS, Locke R, Weaver AL et al. (2004). Functional gastrointestinal disorders among people with sleep disturbances: a population based study. Mayo Clin Proc 79: 1501–1506.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 22
Sleep and genitourinary systems: physiology and disorders 1
MAX HIRSHKOWITZ 1, 2 * AND AMIR SHARAFKHANEH 1 Michael E. DeBakey Veterans Affairs Medical Center Sleep Center and Department of Medicine, Baylor College of Medicine, Houston, TX, USA 2
Department of Psychiatry, Baylor College of Medicine, Houston, TX, USA
INTRODUCTION Physiological processes continue during sleep but in some instances they operate according to principles. For example, in men, sleep-related penile erections occur in association with rapid eye movement (REM) sleep. These erections are not a consequence of sexual dream content but rather appear to be a normal physiological correlate of the REM sleep process. However, sometimes processes may go awry, resulting in disturbed sleep. In the case of sleep-related erections (SREs), these tumescence episodes are, in rare instances, associated with pain. The pain awakens the patient, resulting in profound REM sleep deprivation, apprehension about going to sleep, and often severe insomnia. In the following chapter, sleep-related micturition, penile erections, and changes associated with menstruation will be discussed. Sleep disturbances associated with genitourinary factors will be covered, including enuresis, nocturia, painful SREs, menstrual-related sleep disorder, and menopause-related sleep disorder. Treatments for these disorders will be reviewed, where appropriate.
SLEEP AND THE GENITOURINARY SYSTEM Micturition NORMAL
FUNCTION
Healthy adults sleep 7–9 hours nightly and may micturate once (or not at all) during that entire period. If there is a need to urinate, peripheral reflexes awaken
the sleeper, who arises, goes to the toilet, and urinates. Intervals between urination at night often exceed those during the day. Of course, the lack of fluid intake and noningestion of substances with diuretic properties help in this regard. Also, there is an overall slowing of the process. Before children develop bladder control, ability to ambulate, and recognition during sleep of the peripheral signals indicating a need to micturate, they bedwet. Usually bed-wetting ceases after toilet training, before the age of 3–4 years. Thus, bladder control and selective awareness of those reflexes indicating the need to urinate develop early. Incorporation of urinary urge into dream mentation is widely experienced and may represent early learning that dates back to toilet training. Children sleep for longer durations than adults. Children also have higher slow-wave sleep amplitude and duration. Importantly, arousal threshold during slow-wave sleep is exceptionally blunted.
ENURESIS Diagnosis and classification. Sleep enuresis is the persistence of bed-wetting beyond the second and third year of life. Bed-wetting resolves after toilet training to a prevalence of 30% at age 4 years, to 10% at age 6 years, to 5% at age 10 years, and to 3% at age 12 years. As it persists after age 4, enuresis becomes increasingly problematic. Bed-wetting frequency can vary from nightly occurrences to monthly (or fewer) episodes. Individuals with enuresis usually have pronounced psychological consequences that range from mild embarrassment to severe shame and guilt (Nino-Murcia and Keenan, 1987; Scharf et al., 1987).
*Correspondence to: Max Hirshkowitz, Ph.D., VAMC Sleep Center 111 i, 2002 Holcombe Blvd., Houston, TX 77030, USA. Tel: 713 794-7562, Fax: 713 794-7558, E-mail:
[email protected]
356
M. HIRSHKOWITZ AND A. SHARAFKHANEH
Primary enuresis is a delay in the onset of achieving the ability to remain dry through the sleep period. Having a parent who had primary enuresis increases the likelihood that a child will also be enuretic. A single recessive gene is suspected that may be associated with delayed lower urinary tract neuromuscular maturation or dysfunction. By contrast, secondary enuresis refers to bedwetting that recurs at some time after the ability to sleep dry had been achieved. This may be a direct result of a concurrent or comorbid illness. Some conditions that contribute to enuresis include urethral infection, stenosis, posterior urethral valve problems, and neurogenic bladder, nocturnal seizures, sleep deprivation, and urologic anomalies. In adults, sleep enuresis is occasionally seen in patients with obstructive sleep apnea. In addition to frank medical conditions, secondary enuresis in children may represent a “cry for attention” and occur shortly after the birth of a sibling. Enuresis may also be secondary to sleep-disordered breathing. This holds for both children and adults. One-third of 326 children (age 2–18 years) with sleepdisordered breathing selected for tonsil- or adenotonsillectomy surgery were enuretic. Of patients agreeing to participate in a postsurgical follow-up study, 61% were no longer bed-wetting and 23% decreased their bed-wetting. Similarly, enuresis can be a symptom of sleep apnea in adults (Umlauf and Chasens, 2003). It is thought that the negative intrathoracic pressure evokes release of atrial natriuretic peptide resulting from cardiac distension. This in turn increases sodium and water excretion while inhibiting fluid volume regulation. When the sleep-related breathing problem is treated, the process normalizes and bed-wetting ceases. Treatment. Both behavioral and pharmacological interventions are used to treat enuresis. Behavioral treatments include bladder training, using bell and pad devices to help condition the rapid stopping of urinary stream, and fluid restriction to diminish the necessity to void during the sleep period. Behavioral treatments reportedly have good success when properly administered. Psychotherapy, hypnotherapy, and motivational strategies have also been used as treatment. A wide array of medications has also been tried in the treatment of childhood sleep enuresis, with mixed success. Glazener and colleagues (2005) reviewed 15 randomized and quasirandomized treatment trials for children. The authors concluded, “there was weak evidence to support the use of hypnosis, psychotherapy, acupuncture and chiropractic but it was provided in each case by single small trials, some of dubious methodological rigor.” Previously, these authors examined six Cochrane Reviews (Glazener
et al., 2004) evaluating: (1) simple behavioral interventions; (2) complex behavioral or educational interventions; (3) alarms; and (4) medications (specifically, desmopressin, tricyclics, and other drugs). Most evidence was poor-quality data that were not available for direct comparisons between therapies. Nonetheless, for long-term treatment, alarms were ranked highly and for acute relief desmopressin was recommended. Another major review arrived at similar conclusions after reviewing all 38 papers published between 1980 and 2002 that sampled 10 or more children (Butler and Gasson, 2005). Finally, Lyon and Schnall (2005) considered only randomized controlled trials. They found that durable results (3 months, or longer) were produced applying enuresis alarm therapy. While acutely effective, nonsustained cessation of bedwetting occurred in response to administering desmopressin and tricyclics (but the therapeutic effect ceased upon dosing termination).
NOCTURIA Description. Nocturia is the need to void during sleep. It rises to clinical significance if it exceeds two or three times nightly. It can occur without disease and may result from excessive evening fluid intake. However, nocturia can be a nonspecific symptom of prostate disease (due to bladder neck obstruction), renal dysfunction, hepatic conditions, or heart failure. Like enuresis, nocturia can be a symptom of obstructive sleep apnea. Similarly, it is thought that the negative intrathoracic pressure produced by attempting to breathe when the oropharynx is occluded stimulates atrial natriuretic peptide release, thereby increasing sodium and water excretion. Continuous positive airway pressure (CPAP) therapy significantly reduces nocturia episodes (Margel et al., 2006). In a study of 75 men and 22 women (mean age 55 years) with a mean respiratory disturbance index of 34 sleep-disordered breathing events per hour of sleep, 1–3 months of CPAP therapy decreased the number of awakenings to urinate from 2.5 to 0.7 nightly. Correlation analysis found that age, diabetes, and sleep apnea were the main factors associated with number of nightly awakenings to urinate and CPAP treatment reduced the nocturic rate (Fitzgerald et al., 2006). Treatment. In the primary care setting, a four-step process has been proposed for treating nocturia (Weatherall and Arnold, 2006): 1. 2. 3. 4.
clinical evaluation simple investigations provisional diagnosis diagnosis-driven management.
SLEEP AND GENITOURINARY SYSTEMS: PHYSIOLOGY AND DISORDERS 357 If an overactive bladder is suspected, recommended However, a more systematic evaluation by Karacan intervention includes bladder retraining, anticholinergic (1965) failed to uncover any relationship. Given how drug therapy, or both. Afternoon-administered loop few dream reports contain overt sexual content diuretics can be considered but sedative hypnotics are (McCarley and Hoffman, 1981), it is highly unlikely that discouraged, especially in the elderly. In younger this is the driving force behind SREs’ consistent appearpatients desmopressin may produce benefit but should ance during nearly each and every REM sleep episode. be used cautiously in older patients (hyponatremia Measurement and quantification. Traditional SRE risk). One trial found reduced nocturic frequency in recording technique includes comprehensive attended men with prostate-related lower urinary tract symppolysomnography with additional channels for penile toms when the adrenoreceptor antagonist terazosin circumference increase (PCI). Thus, standard montage was administered (Paick et al., 2006). would include electroencephalography (central and occipital), electrooculography (left and right eye), and Sleep-related erections electromyography (submentalis and anterior tibialis), airflow (at the nose and mouth), respiratory effort NORMAL FUNCTION (from abdominal and thoracic movement sensors), Background. In contrast to micturition, erections in boys oxygen saturation (pulse oximetry), cardiac rhythm, and men increase in activity level during sleep. In fact, and PCI (from gauges placed at the penile base and the overall duration of erectile activity during sleep is coronal sulcus). Optional channels sometimes recorded greater than during wakefulness (except perhaps for include electromyography from the bulbocavernosusteenage boys). It is a common misconception that SREs ischiocavernosus muscle, penile blood flow, and snorare related to a nocturnal urge to void. This belief likely ing sounds. Using two gauges to record PCI affords derives from REM sleep-related arousal (when arousal improved reliability by providing redundancy and threshold is lower than during slow-wave sleep) triggered greater sensitivity to erectile anomalies. by a need to urinate. The awakened sleeper misattributes As with polysomnography used for diagnosing the cause of the REM-coincident erection. sleep apnea, the expense of testing fostered the develSREs are naturally occurring, involuntary episodes opment of lower-cost home monitoring techniques. of penile erections that are temporally associated with A spectrum of alternative methods appeared, includREM sleep. Also known as nocturnal penile tumescence ing stamp bands, expanding rings, and snap devices (NPT), these erections occur in all healthy, sexually (Barry et al., 1980). In theory, a full erection will potent men. The regularity of these erection episodes break, stretch, or unsnap the apparatus; however, is so consistent that their measurable aspects apparently movements can (and do) produce these results, rendo not respond to presleep manipulations. Viewing dering such tests unreliable (Allen and Brendler, video depicting explicit heterosexual erotica and inter1990). Also, some penises have only minimal increase course did not provoke changes in volunteers’ SREs in circumference and therefore fail to trigger these (Ware et al., 1997). Additionally, having male volunteers recording devices, creating the impression that no abstain from sexual activity for up to a week before SREs occurred, when in fact they did. SRE recording did not modify erectile patterns. ThereMore sophisticated home monitoring systems after, having these same subjects engage in as much record PCI continuously and may also measure tissue sexual activity as possible (self-stimulated and/or with compressibility when an erection occurs. These devices a partner) before testing produced no apparent SRE are less prone to unidentifiable movement artifacts alteration (Karacan et al., 1970, 1979). producing erroneous interpretation as normal. HowBecause it was a REM-related phenomenon, SREs ever, a myriad of circumstances can make a man with drew the attention of early sleep researchers who were normal erectile function appear impaired according to cataloguing differences in physiology correlated with SRE measures, including poor sleep, disturbed sleep, the different sleep stages. Knowledge of the erections or reduced REM sleep. Any or all of these can result occurring during sleep in humans predates even the from sleep apnea or periodic limb movement disorder, discovery of REM sleep. After discovering REM sleep, both of which are common in men with erectile dysAserinsky (1953) speculated that sleep erections might function (ED). Without devices to monitor airflow, be REM-related. There was also speculation that SREs respiratory effort, and/or pulse oximetry one would might be related to dream content, a notion consistent miss moderate to severe sleep apnea (apnea index with freudian theory about the nature and significance >15 per hour) in 20% of men (n ¼ 1000) (Hirshkowitz of dreaming. A published case series by Fisher et al. et al., 1990) and periodic limb movement disorder (1965) supported this view, finding both manifest and (periodic movement index >15 per hour) in 54% of latent sexual content in dreams with robust erections. men (n ¼ 768) (Hirshkowitz et al., 1989).
358
M. HIRSHKOWITZ AND A. SHARAFKHANEH
In a scoring technique developed by Karacan (1982) and later refined by Ware and Hirshkowitz (1994), each SRE episode has a beginning, middle, and ending phase labeled as Tup, Tmax, and Tdown, respectively. The T in these phase names indicates tumescence. Tup begins when PCI reaches 2 mm above baseline and continues until it achieves 75% of the night’s overall maximum circumference increase (MCI). Normally Tup commences within a few minutes of the transition from NREM to REM sleep and, in response to the arterial inflow, circumference rapidly increases with observable transient pulsatile bursts called penile pulsations. Penile girth and length and corpus cavernosal pressure all increase during the Tup phase. Wide variations in penile morphology and the dynamics of erection necessitate within-subject scaling. The first step to normalize values is determining the overall MCI attained during the entire recording period. During an SRE episode, the point at which PCI first exceeds 75% of MCI is designated the Tmax starting point. The interval extending from the Tmax starting point until the episode’s final PCI drops below 75% of MCI is called the Tmax phase. Tmax phase in an episode where PCI fails to reach 75% of MCI is scored as 1 minute in duration and is centered on the episode’s maximal circumference. During the Tmax phase, circumference remains roughly at a maximum plateau. However, PCI sometimes drops below 75% of MCI during an episode and, when this happens, it is called a fluctuation. Fluctuations may occur spontaneously or may be associated with central nervous system arousals. During Tmax arterial inflow slows and eventually declines, while venous outflow is considerably restricted. The resulting increase in cavernous pressure makes the organ rigid with the penile shaft resistant to buckling, thereby producing an erection capable of achieving vaginal penetration. This Tmax phase normally continues until the end of the REM sleep episode. Tdown is SRE episode’s final phase. Commencing at the end of the Tmax phase, Tdown continues until PCI returns to baseline, or no longer continues to decrease (the Tzero point). Physiologically, Tdown is initiated by increased venous outflow coincident with nervous system alterations accompanying the termination of REM sleep. Sympathetic activation occurs and PCI rapidly declines. SREs, like any episodic, physiological activity, can be characterized in terms of frequency, magnitude, duration, and quality. Frequency is indexed by the number of episodes; magnitude by overall MCI and the average maximum PCI per episode; and duration by total tumescence time, total Tmax phase time, average SRE episode duration, and average Tmax phase duration. SRE pattern (architecture) can be represented by the slope of the Tup, the slope of Tdown, and the
duration of Tmax. Additionally, because SREs are closely correlated with REM sleep, the nature and degree of this relationship can also be expressed numerically (for example, the time from NREM– REM transition until Tmax is reached. For measures with less between-subject variability, dimensional parameters can also be normalized using REM sleep values (for example, total SRE duration as a percentage of REM sleep duration). Such sleep-normalized measures can be compared among individuals. Measuring penile rigidity objectively indexes SRE quality and is the most important single measure for appreciating erectile capacity. Although MCI is normally correlated with rigidity under normal circumstances, it is well documented that some patients with normal MCI have erections that are not firm (Wein et al., 1981). To measure penile buckling resistance objectively, the patient is awakened during an SRE episode and a calibrated force is applied to the tip of the penis, parallel to the shaft. The force is rapidly increased to determine whether the erection can withstand 1000 grams force. If the erection could not withstand 1000 grams, penile rigidity is the force at which the penile shaft bent 30 or more. If no buckling occurs, the value 1000 grams is assigned. To assess erectile quality subjectively, patient and technician percentage-of-full ratings can be used. Effect of aging. SREs have been recorded in young boys, young adults, middle-aged men, and the elderly (Karacan et al., 1975; Reynolds et al., 1989; Schiavi et al., 1990; Ware and Hirshkowitz, 1992). SREs reliably occur in all age groups when subjects are sexually potent, relatively free from major diseases, and are not taking medications known to suppress REM sleep and/ or erections. Over the lifespan there are small but statistically reliable decreases in SRE frequency and duration; however, magnitude and rigidity remain equivalent across age groups. The most consistent and robust finding from the various aging studies is that, in sexually potent men, SREs endure rather than atrophy with aging.
ERECTILE
DYSFUNCTION
ED is the inability to attain or sustain an erection satisfactory for coitus. In the USA, ED afflicts 10–20 million males aged 18 years or greater. Prevalence increases with age. Erectile failure may be due to organic (e.g., vascular disease, hormonal imbalances, or neurological dysfunction) and/or psychological (e.g., anxiety, depression, fear of intimacy) factors. Vascular disease includes penile arterial atherosclerotic disease and venous leaks. These conditions are highly associated with diabetes, hypertension, and cigarette smoking.
SLEEP AND GENITOURINARY SYSTEMS: PHYSIOLOGY AND DISORDERS The last three decades of the 20th century marked several complete revisions in our understanding and treatment of ED. It began with the realization that the vast majority of men with ED had organic rather than psychogenic etiology. In response, invasive surgical treatments underwent rapid development. A variety of prosthetic implants were invented and surgical techniques were created. This development necessitated improved diagnostic techniques. Many surgical urologists wanted assurance that the patient’s ED was organic before performing a procedure that would destroy the normal anatomy. One difficulty with existing diagnostic tests was lack of specificity. These are the events that set the stage for SRE testing in conjunction with polysomnography. SRE testing results are very specific for detecting psychogenic conditions when used in conjunction with a physical exam needed to rule out two to three specific conditions. Thus SRE testing became the “gold standard” presurgical procedure (Figure 22.1). More recently, with the advent of sildenafil (Viagra) and other orally administered medical treatments for ED, the demand for SRE testing to diagnose ED declined dramatically. Currently, SRE testing is mainly used in very difficult cases of ED, as an objective measure in ED research. PAINFUL ERECTIONS
Painful SREs (also known as penile pain syndrome) occur in association with normal SREs. They are associated with intense pain that disrupts sleep and causes the patient tremendous distress (Ferini-Strambi et al.,
A
Hours of sleep
20 10 0 30 20 10 0
1000 g
B
Hours of sleep
30
PCI at CS
PCI at CS
30
PCI at PB
PCI at PB
PCI at CS
Hours of sleep
20 10 0 30 20 10 0
450 g
30 20 10 0 300 g
550 g PCI at PB
SLEEP-RELATED
359
1996a). Erections occurring at other times during wakefulness in sexual situations are not painful. This disorder is mercifully very rare. In its severe form, the patient may have painful erections three to five times nightly, in association with the onset of REM sleep. This can produce profound REM sleep deprivation, hypersomnia, and impaired daytime function. Etiology is unknown; however, an autonomic nervous system disorder is suspected (Ferini-Strambi et al., 1996b). Concomitant vagal cardiac activity reduction and possible hyperactive beta-adrenergic activity led to the use of beta blockers and thissometimes provided relief. An alternative hypothesis is that there is an endothelial dysfunction, which is suggested by painful erections sometimes occurring in association with prostaglandin E1 injections. Other candidate explanations are suggested, including a bulbocavernosus-ischiocavernosus disorder and possible involvement of central dopamine agonists (Calvet, 1999). Amitriptyline is the first-line treatment (Karsenty et al., 2005); however, treating penile pain syndrome is usually very difficult. A wide assortment of pharmacological agents has been tried with varying success, including REM-suppressing antidepressants (e.g., tricyclics and monoamine oxidase inhibitors), beta-blockers, and the atypical antipsychotic clozapine (Steiger and Benkert, 1989). In severe cases, a patient may willingly sacrifice erectile function to attain relief from the painful erections. Chemical castration inhibits overall erectile activity and can be induced with medroxyprogesterone acetate or leuprolide acetate.
30 20 10 0
C
Fig. 22.1. Sleep histograms and penile circumference increase (PCI) in millimeters recorded at the coronal sulcus (CS) and penile base (PB). (A) The sleep-related erectile (SRE) pattern for a man with psychogenic erectile dysfunction. His pattern was normal and penile rigidity withstood >1000 grams of force without buckling. (B) The SRE pattern for a man with borderline erectile function. Some of his SREs appear to be normal while others are diminished. Rigidity during his SRE maximums were 450 and 550 grams. (C) The SRE pattern for a man with organic erectile dysfunction. An abnormal pattern occurred and maximum rigidity was only 300 grams.
360
M. HIRSHKOWITZ AND A. SHARAFKHANEH
Menstrual cycle MENSTRUAL-RELATED
SLEEP DISORDER
In women, hormonal alterations occur in association with the menstrual cycle serving reproductive functions. Egg (ovum) production, release, destruction (if not fertilized), and disposal are accompanied by significant changes in hormonal secretion. Prior to ovulation, menstruation (bleeding) occurs, usually for about 5 days, after which a new egg ripens in the ovary. On approximately day 13 or 14 the new egg is released and pregnancy occurs if it is fertilized. If the egg is not fertilized after ovulation (days 15–28) the uterine wall lining breaks down and is shed during menstruation. The hormonal changes accompanying these processes can alter sleep quantity and quality; however, marked differences occur in response to these variations (Ho, 1972; Billiard et al., 1975). When sleep alteration produces clinically significant distress or interferes with daytime function, menstrual-associated sleep disorder can be diagnosed. Menstrual-associated sleep disorder may present as either insomnia or hypersomnia, depending on its timing within the menstrual cycle. A survey conducted by the National Sleep Foundation found that tenderness and bloating during menstruation provoke insomnia in 50% of women. Headaches, cramps, and mood alterations may also occur. Particular sleep problems are associated with each phase of the menstrual cycle. Specifically, premenstrual insomnia is characterized by difficulty initiating or maintaining sleep the week before menses onset and the problem must recur for three consecutive cycles, or more (Lee et al., 1990; Chuong et al., 1997; Shibui et al., 1999; Moline et al., 2003). Polysomnography reveals decreased sleep efficiency, frequent arousals, prolonged periods of wakefulness, and frequent sleep stage transitions. By contrast, sleep problems occurring later in the cycle (e.g., at day 19–21 when progesterone is at peak levels) are characterized by hypersomnia and polysomnography reveals normal sleep duration and quality. In general, both estrogen and progesterone increase sleep (REM and NREM, respectively). However, multiple sleep latency testing demonstrates increased physiological sleepiness. Other studies have found menstrual-related disturbances in other biological rhythms, including alterations in melatonin, temperature, cortisol, prolactin, and thyroid-stimulating hormone. In susceptible individuals mood alterations may occur (Parry et al., 1989). Both specific interventions to correct the desynchronized rhythms as well as symptomatic treatment may improve mood in these patients (Parry et al., 2006).
MENOPAUSE-RELATED
SLEEP DISORDERS
Menopause has been associated with increased difficulty initiating sleep, maintaining sleep, or both. While some of the sleeplessness can be accounted for by hot flashes, it is known that both estrogen and progesterone affect sleep directly. Progesterone has a sleep-inducing hypnotic property and also is a respiratory stimulant that can decrease apnea in men (Andersen et al., 2006). Epidemiological studies indicate that 3.9% of men and 1.2% of women have clinically significant sleep apnea. However, prevalence in premenopausal women is only 0.6% and only 0.5% in postmenopausal women on hormone replacement therapy. Apnea prevalence was 2.7% for postmenopausal women not on hormone replacement therapy (Bixler et al., 2001). Other sleep disorders associated with menopause include insomnia with depression, sleep-disordered breathing, and fibromyalgia (Eichling and Sahni, 2005). In a study of 102 women (age 44–56 years) reporting disturbed sleep, 53% had sleep apnea, restless legs, or both. The best predictors of polysomnographically derived sleep efficiency were apneas, periodic leg movements, and arousals (P < 0.0001) while the best predictors of Pittsburgh Sleep Quality Index score were anxiety index and the number of hot flashes in the first half of the night (P < 0.001) (Freedman and Roehrs, 2007). Treatments should be targeted for the specific sleep disorder: positive airway pressure therapy for sleep apnea, dopamine agonists for restless-legs syndrome, and sedating antidepressant therapy for insomnia related to mood disorders. If insomnia occurs that is not associated with sleep apnea, sedative-hypnotic medication can be effective. Objective sleep improvement was found in a trial of 410 (age 40–60 years) perimenopausal or early postmenopausal women with insomnia (Soares et al., 2006).
REFERENCES Allen R, Brendler CB (1990). Snap-gauge compared to a full nocturnal penile tumescence study for evaluation of patients with erectile impotence. J Urol 143: 51. Andersen ML, Bittencourt LR, Antunes IB et al. (2006). Effects of progesterone on sleep: a possible pharmacological treatment for sleep-breathing disorders? Curr Med Chem 13: 3575–3582. Aserinsky E (1953). Ocular motility during sleep and its application to the study of rest-activity cycles and dreaming. Unpublished doctoral dissertation. University of Chicago, Chicago. Barry JM, Blank B, Boileau M (1980). Nocturnal penile tumescence monitoring with stamps. Urology 15: 171. Billiard M, Guilleminault C, Dement WC (1975). A menstruation-linked periodic hypersomnia. Kleine–Levin syndrome or new clinical entity. Neurology 25: 436–443.
SLEEP AND GENITOURINARY SYSTEMS: PHYSIOLOGY AND DISORDERS Bixler EO, Vgontzas AN, Lin HM et al. (2001). Prevalence of sleep-disordered breathing in women: effects of gender. Am J Respir Crit Care Med 163: 608–613. Butler RJ, Gasson SL (2005). Enuresis alarm treatment. Scand J Urol Nephrol 39 (5): 349–357. Calvet U (1999). Painful nocturnal erection. Sleep Med Rev 3 (1): 47–57. Chuong CJ, Kim SR, Taskin O et al. (1997). Sleep pattern changes in menstrual cycles of women with premenstrual syndrome: a preliminary study. Am J Obstet Gynecol 177 (3): 554–558. Eichling PS, Sahni J (2005). Menopause related sleep disorders. J Clin Sleep Med 15: 291–300. Ferini-Strambi L, Montorsi F, Zucconi M et al. (1996a). Cardiac autonomic nervous activity in sleep-related painful erections. Sleep 19 (2): 136–138. Ferini-Strambi L, Oldani A, Zucconi M et al. (1996b). Sleeprelated painful erections: clinical and polysomnographic features. J Sleep Res 5 (3): 195–197. Fisher C, Gross J, Zuch J (1965). Cycle of penile erection synchronous with dreaming (REM) sleep: preliminary report. Arch Gen Psychiatry 12: 29–45. Fitzgerald MP, Mulligan M, Parthasarathy S (2006). Nocturic frequency is related to severity of obstructive sleep apnea, improves with continuous positive airways treatment. Am J Obstet Gynecol 194 (5): 1399–1403. Freedman RR, Roehrs TA (2007). Sleep disturbance in menopause. Menopause 14: 826–829. Glazener CM, Evans JH, Peto RE (2004). Treating nocturnal enuresis in children: review of evidence. J Wound Ostomy Continence Nurs 31 (4): 223–234. Glazener CM, Evans JH, Cheuk DK (2005). Complementary and miscellaneous interventions for nocturnal enuresis in children. Cochrane Database Syst Rev 18 (2): 5230. Hirshkowitz M, Karacan I, Arcasoy MO et al. (1989). The prevalence of periodic limb movements during sleep in men with erectile dysfunction. Biol Psychiatry 26: 541. Hirshkowitz M, Karacan I, Arcasoy MO et al. (1990). Prevalence of sleep apnea in men with erectile dysfunction. Urology 36: 232. Ho A (1972). Sex hormones and the sleep of women. In: MH Chase, WC Stern, PL Walter (Eds.), Sleep and Research. Brain Information Service/Brain Research Institute, vol. 1. UCLA, Los Angeles. Karacan I (1965). The effect of exciting presleep events on dreporting and penile erections during sleep. Unpublished doctoral dissertation, Department of Psychiatry, Downstate Medical Center Library, New York University, Brooklyn, NY. Karacan I (1982). Evaluation of nocturnal penile tumescence and impotence. In: C Guilleminault (Ed.), Sleeping and Waking Disorders: Indications and Techniques. Addison-Wesley, Menlo Park, pp. 343–371. Karacan I, Williams RL, Salis PJ (1970). The effect of sexual intercourse on sleep patterns and nocturnal penile erections. Psychophysiology 7: 338. Karacan I, Williams RL, Thornby JI et al. (1975). Sleeprelated penile tumescence as a function of age. Am J Psychiatry 132: 932.
361
Karacan I, Ware JC, Salis PJ et al. (1979). Sexual arousal and activity: effect on subsequent nocturnal penile tumescence patterns. Sleep Res 8: 61. Karsenty G, Werth E, Knapp PA et al. (2005). Sleep-related painful erections. Nat Clin Pract Urol 2 (5): 256–260. Lee KA, Shaver JF, Giblin EC et al. (1990). Sleep patterns related to menstrual cycle phase and premenstrual affective symptoms. Sleep 13 (5): 403–409. Lyon C, Schnall J (2005). What is the best treatment for nocturnal enuresis in children? J Fam Pract 54 (10): 905–906, 909. McCarley RW, Hoffman E (1981). REM sleep dreams and the activation synthesis hypothesis. Am J Psychiatry 138: 904–912. Margel D, Shochat T, Getzler O et al. (2006). Continuous positive airway pressure reduces nocturia in patients with obstructive sleep apnea. Urology 67 (5): 974–977. Moline ML, Broch L, Zak R et al. (2003). Sleep in women across the life cycle from adulthood through menopause. Sleep Med Rev 7 (2): 155–177. National Sleep Foundation poll. Available online at: http:// www.sleepfoundation.org/sites/default/files/Summary_ Of_Findings-FINAL.pdf. Nino-Murcia G, Keenan SA (1987). Enuresis and sleep. In: C Guilleminault (Ed.), Sleep and its Disorders in Children. Raven Press, New York, pp. 253–267. Paick JS, Ku JH, Shin JW et al. (2006). Alpha-blocker monotherapy in the treatment of nocturia in men with lower urinary tract symptoms: a prospective study of response prediction. BJU Int 97 (5): 1017–1023. Parry BL, Mendelson WB, Duncan WC et al. (1989). Longitudinal sleep EEG, temperature, and activity measurements across the menstrual cycle in patients with premenstrual depression and in age-matched controls. Psychiatry Res 30 (3): 285–303. Parry BL, Martinez LF, Maurer EL et al. (2006). Sleep, rhythms and women’s mood. Part I. Menstrual cycle, pregnancy and postpartum. Sleep Med Rev 10 (2): 129–144. Reynolds CF, Thase ME, Jennings JR et al. (1989). Nocturnal penile tumescence in healthy 20- to 59-year olds: a revisit. Sleep 12: 368. Scharf MB, Pravda MF, Jennings SW et al. (1987). Childhood enuresis: a comprehensive treatment program. Psychiatr Clin North Am 10: 655–674. Schiavi RC, Schreiner-Engel P, Mandeli J et al. (1990). Healthy aging and male sexual function. Am J Psychiatry 147: 766–771. Shibui K, Uchiyama M, Okawa M et al. (1999). Diurnal fluctuation of sleep propensity across the menstrual cycle. Psychiatry Clin Neurosci 53 (2): 207–209. Soares CN, Joffe H, Rubens R et al. (2006). Eszopiclone in patients with insomnia during perimenopause and early postmenopause: a randomized controlled trial. Obstet Gynocol 108: 1402–1410. Steiger A, Benkert O (1989). Examination and treatment of sleep-related painful erections – a case report. Arch Sex Behav 18 (3): 263–267. Umlauf MG, Chasens ER (2003). Sleep disordered breathing and nocturnal polyuria: nocturia and enuresis. Sleep Med Rev 7 (5): 403–411.
362
M. HIRSHKOWITZ AND A. SHARAFKHANEH
Ware JC, Hirshkowitz M (1992). Characteristics of penile erections during sleep recorded from normal subjects. J Clin Neurophysiol 9: 78. Ware JC, Hirshkowitz M (1994). Monitoring penile erections during sleep. In: MH Kryger, T Roth, WC Dement (Eds.), Principles and Practice of Sleep Medicine. WB Saunders, Philadelphia, pp. 967–977. Ware JC, Hirshkowitz M, Thornby J et al. (1997). Sleeprelated erections: effects of presleep sexual arousal. J Psychosom Res 42: 547–553.
Weatherall M, Arnold T (2006). Nocturia in adults: draft New Zealand guidelines for its assessment and management in primary care. N Z Med J 119 (1234): U1976. Wein AJ, Fishkin R, Carpiniello VL et al. (1981). Expansion without significant rigidity during nocturnal penile tumescence: a potential source of misinterpretation. J Urol 126: 343–344.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 23
Sleep enuresis TRYGGVE NEVE´US * Uppsala University Children’s Hospital, Uppsala, Sweden
DEFINITIONS AND EPIDEMIOLOGY The term enuresis, or nocturnal enuresis, is applied to any involuntary micturition while asleep in a child aged 5 years or more (Neve´us et al., 2006). If the child has previously experienced an enuresis-free interval of at least 6 months the term secondary enuresis is applicable, otherwise we refer to this as primary enuresis. Enuresis is rightly classified as a parasomnia by the International Sleep Disorder Classification. Wetting during daytime is called daytime incontinence, not diurnal enuresis. Enuresis is extremely common. If a wetting frequency of at least one “wet night” per month is taken into account, the prevalence is probably above 10% among 6-year-olds, around 5% among 10-year-olds and 0.5–1% in teenagers and adults (Jonge, 1969; Hirasing et al., 1997; So¨derstro¨m et al., 2004). Isolated nocturnal enuresis in children is 1.5–2 times more common among boys than girls (Neve´us et al., 1999a). In children with combined day- and nighttime wetting and among adults no such gender differences are found (Hirasing et al., 1997; Neve´us et al., 1999a).
ETIOLOGY AND PATHOGENESIS Heredity Enuresis has long been known to be strongly influenced by hereditary factors (Bakwin, 1971; Ja¨rvelin et al., 1988). Several different genetic loci have been implicated (Eiberg, 1998), but there is no clear correspondence between phenotype (subtype of enuresis) and genotype (von Gontard et al., 1997).
Low arousability The idea that enuretic children are “deep sleepers” is not new (Trousseau, 1870). Many parents report that their bed-wetting children are almost impossible to
awaken from sleep at night (Figure 23.1). This subjectively low arousability has been reported in many epidemiological studies (Wille, 1994; Neve´us et al., 1999a), whereas studies on objective arousal thresholds have been less numerous, and the fact that the standard polysomnogram of enuretic children is not clearly different from that of dry children (Rapoport et al., 1980) has often led to the erroneous conclusion that enuretic children do not sleep more “deeply” than dry children. In fact, they do. In the elegant study by Wolfish et al. (1997), who used acoustic arousal stimuli during polysomnographic registration, it could be quite clearly shown that children with severe enuresis were significantly more difficult to arouse from sleep than controls. Opinions differ regarding the location of the enuretic events within the sleep cycle. Although the voiding may occur during any sleep stage (Mikkelsen and Rapoport, 1980) it seems that the children with severe, therapy-resistant enuresis preferably void during non-REM sleep (Neve´us et al., 1999c).
Nocturnal polyuria The discovery in the 1980s that many enuretic children have nocturnal polyuria ushered in a new and more fruitful phase of enuresis research, which, until then, had been mostly focused on models dealing with psychiatric explanation. It was now shown in a group of bed-wetting children that they lacked the physiological nocturnal peak of vasopressin secretion and had a nocturnal urine production exceeding their functional bladder capacity (Nrgaard et al., 1985). This finding has since been repeated (Hunsballe et al., 1998; Vurgun et al., 1998) and contradicted (La¨ckgren et al., 1997). The possibility has also been put forward that the polyuria is not necessarily always caused by vasopressin deficiency (Vurgun et al., 1998).
*Correspondence to: Tryggve Neve´us, MD PhD, Associate Professor, Consultant in Paediatric Nephrology, Uppsala University Children’s Hospital, 751 85 Uppsala, Sweden. Tel: þ46 18 6110000, Fax: þ46 18 6115853, E-mail:
[email protected]
T. NEVE´US
364
with enuresis go to the toilet more often than dry children, that they void smaller volumes, and that urgency symptoms are more common in this group (Esperanca and Gerrard, 1969; Neve´us et al., 1999a; Yeung et al., 1999). The association between constipation and detrusor overactivity is also relevant here (Yazbeck et al., 1987).
500 Dry children
400 300 200 100 16 14 12 10 8 6 4 2
Enuresis and psychiatry
Enuretic children
?
A
B
C
D
E
F
? = don’t know
C = neither easy nor difficult
A = very easy
D = difficult
B = easy
E = very difficult
F = almost impossible
Fig. 23.1. Subjective arousability of enuretic and dry children. Answers to the question: “How easy or difficult is it to wake you up from sleep at night?” (Adapted from Neve´us et al. (1999c).)
A problem with this hypothesis is the finding that nocturnal polyuria is not exclusive to bed-wetters. Approximately 12% of nonenuretic children produce more urine during the night than during daytime (Mattsson and Lindstro¨m, 1994). Even with these objections taken into consideration it is generally agreed that nocturnal polyuria is common among enuretic children, and that vasopressin deficiency may be causing this polyuria in at least some of them. All bed-wetting children do not, however, have polyuria. And, importantly, the polyuria hypothesis does not explain why the children do not wake up to void.
The old notion about enuresis as a mainly psychiatric disorder has been abandoned today, since the behavior problems among enuretic children that would be expected from models dealing with psychiatric explanation were not found, no differences regarding stressful family events or toilet training were detected, and the prevalence of enuresis has not been found to differ between children with and without psychosocial problems (Couchells et al., 1981; Friman et al., 1998). It is, however, inappropriate to conclude that psychological or psychiatric factors are without any importance in enuresis. Bed-wetting can be a heavy burden for a growing person, and the social and psychological consequences can be grave. Enuretic children suffer from low self-esteem compared with dry children, and this difference disappears when the children become dry (Ha¨gglo¨f et al., 1997). Thus, many of the psychiatric or psychological abnormalities attributed to enuretic children are probably consequences, and not causes, of enuresis. The epidemiological association between attention deficit hyperactivity disorder and enuresis (Duel et al., 2003) may represent a special case; here it can be suspected that the bed-wetting and the psychiatric problems stem from a common neurological disturbance. Although secondary enuresis may sometimes appear in temporal conjunction with significant family events, such as parental divorce or birth of a sibling, these children do not differ in any fundamental way from primary enuretic children.
Detrusor overactivity Given the prominent role of detrusor overactivity (formerly called detrusor instability) in the pathogenesis of daytime incontinence, and the great overlap between the groups of bed-wetting and incontinent children (Ja¨rvelin et al., 1988; Hirasing et al., 1997; Neve´us et al., 1999a), it is not surprising that the detrusor plays a major pathogenetic role in nocturnal enuresis as well. Sleep cystometries have revealed frequent uninhibited nocturnal detrusor contractions in children with nocturnal enuresis, especially those children who do not respond to standard therapy (Yeung et al., 1999). Further support for the detrusor overactivity hypothesis is provided by the finding that children
Pathogenetic heterogeneity It is now clear that enuresis is a clinically and pathogenetically heterogeneous disorder. Different groups of bed-wetting children have different underlying defects and require different treatments to become dry. Nocturnal polyuria, with or without vasopressin deficiency, is characteristic of children with enuresis that responds favorably to antidiuretic treatment (Hunsballe et al., 1998; Neve´us, 1999a). These children usually have no associated daytime bladder dysfunction (Neve´us, 1999a) and wet their beds because nocturnal urine output exceeds the amount of urine that the bladder can accomodate, and they sleep too deeply
SLEEP ENURESIS to wake up when the bladder is full. We have chosen to call this subtype of enuresis diuresis-dependent enuresis. Nonresponders to antidiuretic therapy, on the other hand, can be assumed to suffer from detrusor overactivity (Neve´us, 1999a; Yeung et al., 1999) and often respond favorably to detrusor-relaxant treatment (Neve´us et al., 1999b). Many of these children have daytime symptoms such as urgency and/or incontinence or are constipated (Yazbeck et al., 1987), and they wet their beds because of uninhibited detrusor contractions that fail to awaken the child from sleep. We have used the term detrusor-dependent enuresis for this subgroup. Of course, there are also children who exhibit signs of both diuresis and detrusor dependency, such as those that become dry only with combined detrusorrelaxant and antidiuretic therapy (Neve´us, 2001).
Enuresis due to other diseases There is a small subgroup of enuretic children with heavy snoring and sleep apnea due to enlarged tonsils or nasal polyps, who become dry when the upperairway obstruction has been removed (Weider et al., 1991). The enuresis of these children could be explained by low arousability and nocturnal polyuria (or a combination of the two). Enuresis can be the presenting symptom of diabetes mellitus (Roche et al., 2005), diabetes insipidus, or any kidney disease causing polyuria, but this usually does not present any problems of differential diagnosis. Likewise, urinary tract infections can lead to enuresis via detrusor overactivity, but these children uniformly have other bladder-related symptoms as well.
Suspected underlying brainstem mechanisms The mismatch between genotype and phenotype in enuresis led to the theory that enuresis, regardless of primary pathogenetic mechanism, may be ultimately caused by disturbances in a specific area in the brainstem (Neve´us, 1999b). The sympathetic branch of the autonomous nervous system is crucial for arousal from sleep (Bonnet and Arand, 1997) and urine storage (i.e., detrusor relaxation and urethral contraction) (de Groat and Booth, 1980) and has an antidiuretic effect on the kidneys (Schrier et al., 1972). The parasympathetic system has largely opposite effects and is responsible for bladder emptying (de Groat and Booth, 1980). The locus coeruleus (LC) is a pontine noradrenergic neuron group with pivotal roles both for arousal – as a central actor in the reticular activating system
365
(Foote et al., 1983) – and for the autonomous nervous system – as the major noradrenergic nucleus of the central nervous system (Aston-Jones et al., 2000). Arousal stimuli, such as bladder filling, exert their sleep-disrupting effects via the LC (Koyama et al., 1998). The LC overlaps, anatomically and functionally, with the pontine micturition center – the main brainstem center for bladder control – and the firing of LC neurons themselves has been shown to affect detrusor function directly (Yoshimura et al., 1990). Finally, there are direct and indirect connections between LC and the vasopressin-producing neurons in the hypothalamus (Bowden et al., 1978). Thus, an inborn disturbance of the function of neuron groups in the upper pons may possibly give rise to the various subtypes of enuresis. This theory has been corroborated by the findings that enuretic children firstly, show subtle neurophysiological signs (e.g., deficient prepulse inhibition of startle) of brainstem dysfunction (Ornitz et al., 1999) and secondly, have more nocturnal parasympathetic and less sympathetic activity than controls (Fujiwara et al., 2001; Unalacak et al., 2004).
TREATMENT, THEORETIC CONSIDERATIONS Given the pathogenetic considerations mentioned above it should come as no surprise that successful therapies of enuresis address sleep and urine production or detrusor function and that psychotherapy has not proven to be more effective than placebo. In fact, although a plethora of therapies have been claimed to have effect, only three have, as yet, stood the test of proper randomized, placebo-controlled trials. These are the enuresis alarm, desmopressin, and imipramine, and among those only the enuresis alarm and desmopressin can presently be recommended for routine use. There are, however, other methods, new and old (e.g., urotherapy, anticholinergics, acupuncture, norepinephrine reuptake inhibitors), that show promise and may be of use for specific groups of bed-wetting children.
The enuresis alarm The alarm device consists of a urine detector, placed either in the child’s underclothes or beneath the sheets, connected to an alarm clock that emits a strong wakeup signal. It works by a simple principle: by waking the child from sleep at the moment of enuresis, he or she will gradually learn to recognize the imminent bladder voiding and either suppress the detrusor contraction or wake up and go to the toilet. For the alarm treatment to be successful both child and parents need to be motivated, since the
T. NEVE´US
366
sleep of the whole family will be disrupted and the treatment must be continued for several weeks without interruption. The success rate is reported to be around 60–70% (Monda and Husmann, 1995). Relapse after successful treatment occurs in 5–30% of children (Morgan, 1978; Monda and Husmann, 1995).
Desmopressin Desmopressin is a synthetic vasopressin analog with antidiuretic action that has been used in enuretic children since the late 1970s. Side-effects are rare and treatment is generally considered safe, provided that the patient does not consume large amounts of liquids while taking the drug (Robson and Leung, 1994). Reported success rates have varied between 40 and 80%, but most children relapse after treatment, so the curative effect is low (Monda and Husmann, 1995; Glazener and Evans, 2002).
Anticholinergics, detrusor relaxants Foremost among parasympatholytic substances used in paediatric urological practice is oxybutynin, a drug with both anticholinergic and smooth-muscle relaxant properties that has proven to be effective in the treatment of daytime incontinence caused by detrusor overactivity (Nijman, 2004). Some investigators have successfully treated enuresis with oxybutynin (Persson-Ju¨nemann et al., 1993; Neve´us et al., 1999b). The success rate is greatest in children with proven detrusor overactivity (Kosar et al., 1999). In unselected children with isolated nocturnal enuresis oxybutynin has not been shown to be better than placebo (Lovering et al., 1988). The toxicity of oxybutynin is low but side-effects may limit its usefulness (Jonville et al., 1993). Furthermore, children using oxybutynin may accumulate residual urine and thus run the risk of urinary tract infection. The novel anticholinergic and smooth-muscle relaxant drug tolterodine seems to have the same (limited) clinical efficacy and a lower frequency of side-effects (Raes et al., 2004).
Tricyclic antidepressants Since the early 1960s tricyclic antidepressant drugs, and imipramine in particular, have been used in nocturnal enuresis. Several placebo-controlled studies have shown that roughly 50% of enuretic children are helped by imipramine (Glazener and Evans, 2000). The response rate is similar among children with enuresis resistant to standard therapy (Gepertz and Neve´us, 2004).
The antienuretic effects of imipramine probably reside in central noradrenergic facilitation (Gepertz and Neve´us, 2004). It is interesting to note that desipramine, imipramine’s main active metabolite, binds specifically to the LC (Biegon and Rainbow, 1983). Side-effects are usually minor, but the substance is cardiotoxic in high doses and lethal reactions have been reported when the drug has been overdosed or given to children with severe cardiac arrythmias (Varley, 2000).
Nonpharmacological treatment Constipated children with enuresis often become dry when successfully treated for their constipation (Loening-Baucke, 1997). Urotherapy (e.g., bladder training and other behavioral treatment), the standard first-line treatment of daytime incontinence, has been reported to be successful in enuresis as well (Kruse et al., 1999; Pennesi et al., 2004), which is not surprising, given the overlapping pathogenetic mechanisms behind these conditions, but there is, as yet, a disturbing lack of controlled studies to substantiate these claims. Likewise, there are reports about the beneficial effects of acupuncture (Honjo et al., 2002).
PRACTICAL MANAGEMENT Initial evaluation The primary evaluation of the enuretic child is simple. History and a thorough physical examination will usually suffice to exclude those organic disorders that may present with bed-wetting as a symptom. The history should focus on micturition habits. Daytime incontinence, urgency symptoms, and signs of urinary tract infection should be asked for, as well as symptoms suggesting constipation, such as fecal incontinence. Parents should be asked about the presence of enuresis in the family and about the arousability of the child at night. It is also important to find out whether the child regards the enuresis as a serious problem and if it affects his or her life greatly. A detailed psychiatric evaluation is usually not needed. The physical examination should include inspection of the genitals and a standard neurological examination. Blood samples or other invasive investigations are not needed if the case history and physical examination do not indicate any underlying disease. Ultrasound or other radiological evaluations are not informative. A urine dipstick test for leukocytes, bacteria, and glucose should be taken, especially in cases of secondary enuresis. With this possible exception, primary and secondary enuretic children should be evaluated and treated similarly. If concomitant daytime incontinence is present, measures should be taken to treat this before specific
SLEEP ENURESIS 367 treatment of nocturnal enuresis starts. Urodynamic or go to the toilet often, and/or have current or previous radiological investigations may also be needed in some daytime incontinence as well, and they are often of these children. constipated. The urodynamic and renal status of these children First-line treatment should be evaluated with extra care. They should be asked to complete a home voiding chart for a few If the child is bothered by bed-wetting, usually by the days, so that signs of bladder dysfunction or excessive approximate age of 6 years, it should be treated. Initial urine production can be detected. A noninvasive urotreatment should be the enuresis alarm or desmopresdynamic evaluation with uroflowmetry and measuresin, and our recommendation is to leave this choice ment of residual urine can detect signs of outlet to the child and the family. Children not responding obstruction and suggest the suspicion of detrusor overto the alarm should usually be offered desmopressin, activity. Symptoms and signs of constipation should be and vice versa. The treatment of primary and secondactively sought in these children. This includes a rectal ary enuresis does not differ. examination. The advantages of alarm treatment are that it has a However, invasive urodynamics and further radiolodefinite curative potential and that it is completely harmgic evaluation are still not necessary, provided that the less. It does, however, require a high degree of compliance above-mentioned examinations do not reveal signs of and motivation to be effective. Children whose parents neurological disturbances, renal damage, or bladder show signs of intolerance towards the child’s bed-wetting outlet obstruction. Polysomnographic evaluation is problems are not suitable candidates for alarm treatment. only indicated when frequent sleep apneas are susFamilies using the enuresis alarm should be pected or if the child suffers from severe parasomnias instructed to help the child to awaken and go to the toilet besides enuresis. immediately when the alarm sounds, as very often in the Constipation should always be kept in mind in chilbeginning of the treatment the child does not awaken. dren with therapy-resistant enuresis, especially, but not Furthermore, it is imperative that the treatment be conexclusively, if they also have fecal incontinence or other tinuous; thus, no interruptions during weekends should bowel-related complaints. The appropriate second-line be allowed. Treatment should be continued until either treatment for enuretic children, after constipation has 14 consecutive dry nights have been achieved or more been ruled out or treated, is anticholinergics. Our practhan 6 weeks have passed without signs of effect. Chiltice is to give 5–10 mg oxybutynin or 2–4 mg tolterodine dren relapsing after successful alarm treatment can usuin the evening, starting with half that dosage during the ally easily be treated with a second alarm session. first week. Treatment success is estimated after approxThe advantages of desmopressin are that it is easy to imately 2 months. If response is partial, the addition of administer and that effects appear without delay. The desmopressin in standard dosage may be beneficial. major drawbacks are the low curative potential and the Anticholinergics should not be given if the child has considerable cost. The usual dose is 0.2–0.4 mg orally significant residual urine, due to the risk of urinary tract or 20–40 mg intranasally at bedtime. The one important infections. thing to remember when prescribing desmopressin is to Responders to anticholinergic therapy usually need tell the family that the child should not consume large to continue this medication for 6–12 months. During amounts of liquid on nights when the drug is taken. this time the child should try to develop sound, regular Since the response or nonresponse to this drug will voiding habits and the family should watch out for be evident immediately there is no reason to treat for signs of constipation or urinary tract infection. more than, say, 2 weeks if the child experiences no The child who develops urinary tract infection during beneficial effects of the drug. For children responding anticholinergic treatment should have residual urine to this treatment, the decision to take medication conmeasured and stop treatment at least temporarily until tinuously or just on “important” nights should be left to the infection has been treated and residual urine has the family. If the child chooses to medicate every night disappeared. Constipation during anticholinergic treata 1-week interruption is recommended every 3 months ment is usually heralded by stomach pains, fecal incontiin order to see if the problem has disappeared. nence, or simply a gradually decreased treatment success. Evaluation and treatment of If all the above-mentioned treatments have been tried therapy-resistant cases without success, the cautious use of imipramine might The majority of therapy-resistant children suffer from be warranted. This is, however, a matter for specialist detrusor-dependent enuresis. Many of these children clinics and not for the general pediatrician. If there experience urgency symptoms, void small volumes, is any suspicion of cardiac arrhythmia (palpitations,
368
T. NEVE´US
syncope) in the child or family an electrocardiogram should be performed to rule out long QT syndrome before imipramine is considered. The family should be instructed to keep the medication securely locked. Ordinary dosage is 25–50 mg at bedtime, and the effect is evaluated after 1 month. In case of partial response desmopressin may be added. Children responding to treatment should be instructed to take medicine-free intervals of at least 2 weeks every 3 months or more often, to reduce the risk of tolerance.
REFERENCES Aston-Jones G, Rajkowski J, Cohen J (2000). Locus coeruleus and regulation of behavioral flexibility and attention. Prog Brain Res 126: 165–182. Bakwin H (1971). Enuresis in twins. Am J Dis Child 121: 222–225. Biegon A, Rainbow TC (1983). Localization and characterization of (3H) desmethylimipramine binding sites in rat brain by quantitative autoradiography. J Neurosci 3: 1069–1076. Bonnet MH, Arand DL (1997). Heart rate variability: sleep stage, time of night, and arousal influences. Electroencephalogr Clin Neurophysiol 102 (5): 390–396. Bowden DM, German DC, Poynter WD (1978). An autoradiographic, semistereotaxic mapping of major projections from locus coeruleus and adjacent nuclei in Macaca mulatta. Brain Res 145: 257–276. Couchells SM, Johnson SB, Carter R et al. (1981). Behavioral and environmental characteristics of treated and untreated enuretic children and matched nonenuretic controls. J Pediatr 99: 812–816. de Groat WC, Booth AM (1980). Physiology of the urinary bladder and urethra. Ann Intern Med 92 (Pt 2): 312–315. Duel BP, Steinberg-Epstein R, Hill M et al. (2003). A survey of voiding dysfunction in children with attention deficithyperactivity disorder. J Urol 170 (4 Pt 2): 1521–1524. Eiberg H (1998). Total genome scan analysis in a single extended family for primary nocturnal enuresis: evidence for a new locus (ENUR3) for primary nocturnal enuresis on chromosome 22q11. Eur Urol 33 (Suppl 3): 34–36. Esperanca M, Gerrard JW (1969). Nocturnal enuresis: studies in bladder function in normal children and enuretics. Can Med Assoc J 101: 324–327. Foote SL, Bloom FE, Aston-Jones G (1983). Nucleus locus coeruleus: new evidence of anatomical and physiological specificity. Physiol Rev 63: 844–914. Friman PC, Handwerk ML, Swearer SM et al. (1998). Do children with primary nocturnal enuresis have clinically significant behavior problems? Arch Pediatr Adolesc Med 152 (6): 537–539. Fujiwara J, Kimura S, Tsukayama H et al. (2001). Evaluation of the autonomic nervous system function in children with primary monosymptomatic nocturnal enuresis – power spectrum analysis of heart rate variability using 24-hour Holter electrocardiograms. Scand J Urol Nephrol 35 (5): 350–356.
Gepertz S, Neve´us T (2004). Imipramine for therapy resistant enuresis: a retrospective evaluation. J Urol 171 (6 Pt 2): 2607–2610. Glazener CM, Evans JH (2000). Tricyclic and related drugs for nocturnal enuresis in children. Cochrane Database Syst Rev (2): CD002117. Glazener CM, Evans JH (2002). Desmopressin for nocturnal enuresis. Cochrane Database Syst Rev (3): CD002112. Ha¨gglo¨f B, Andre´n O, Bergstro¨m E et al. (1997). Self-esteem before and after treatment in children with nocturnal enuresis and urinary incontinence. Scand J Urol Nephrol 31 (Suppl 183): 79–82. Hirasing RA, van Leerdam FJ, Bolk-Bennink L et al. (1997). Enuresis nocturna in adults. Scand J Urol Nephrol 31 (6): 533–536. Honjo H, Kawauchi A, Ukimura O et al. (2002). Treatment of monosymptomatic nocturnal enuresis by acupuncture: a preliminary study. Int J Urol 9 (12): 672–676. Hunsballe JM, Hansen TK, Rittig S et al. (1998). The efficacy of DDAVP is related to the circadian rhythm of urine output in patients with persisting nocturnal enuresis. Clin Endocrinology 49 (6): 793–801. Ja¨rvelin MR, Vikeva¨inen-Tervonen L, Moilanen I et al. (1988). Enuresis in seven-year-old children. Acta Paediatr Scand 77: 148–153. Jonge GG (1969). Children with Enuresis (thesis). Van Gorcum, Assen. Jonville AP, Dutertre JP, Barbellion M et al. (1993). Effets indesirables du chlorure d’oxybutynine (Ditropan) en pe´diatrie. Arch Fr Pediatr 50 (1): 27–29. Kosar A, Arikan N, Dincel C (1999). Effectiveness of oxybutynin hydrochloride in the treatment of enuresis nocturna. Scand J Urol Nephrol 33: 115–118. Koyama Y, Imada N, Kayama Y et al. (1998). How does the distention of urinary bladder cause arousal? Psychiatry Clin Neurosci 52 (2): 142–145. Kruse S, Hellstro¨m A-L, Hja¨lma˚s K (1999). Daytime bladder dysfunction in therapy-resistant nocturnal enuresis. A pilot study in urotherapy. Scand J Urol Nephrol 33 (1): 49–52. La¨ckgren G, Neve´us T, Stenberg A (1997). Diurnal plasma vasopressin and urinary output in adolescents with monosymptomatic nocturnal enuresis. Acta Paediatr 86 (4): 385–390. Loening-Baucke V (1997). Urinary incontinence and urinary tract infection and their resolution with treatment of chronic constipation of childhood. Pediatrics 100: 228–232. Lovering JS, Tallett SE, McKendry BI (1988). Oxybutynin efficacy in the treatment of primary enuresis. Pediatrics 82: 104–106. Mattsson S, Lindstro¨m S (1994). Diuresis and voiding pattern in healthy schoolchildren. Br J Urol 76 (6): 783–789. Mikkelsen EJ, Rapoport JL (1980). Enuresis: psychopathology, sleep stage, and drug response. Urol Clin North Am 7: 361–377. Monda JM, Husmann DA (1995). Primary nocturnal enuresis: a comparison among observation, imipramine, desmopressin acetate and bed-wetting alarm systems. J Urol 154 (2 Pt 2): 745–748.
SLEEP ENURESIS Morgan RTT (1978). Relapse and therapeutic response in the conditioning treatment of enuresis: a review of recent findings on intermittent reinforcement, overlearning and stimulus intensity. Behav Res Ther 16: 273–279. Neve´us T (1999a). Osmoregulation and desmopressin pharmacokinetics in enuretic children. Scand J Urol Nephrol 202 (Suppl): 52. Neve´us T (1999b). The Bladder and the Brain. Studies on the Pathogenesis and Treatment of Nocturnal Enuresis (thesis). Department of Women’s and Children’s Health, Uppsala University, Uppsala. Neve´us T (2001). Oxybutynin, desmopressin and enuresis. J Urol 166 (6): 2459–2462. Neve´us T, Hetta J, Cnattingius S et al. (1999a). Depth of sleep and sleep habits among enuretic and incontinent children. Acta Paediatr 88: 748–752. Neve´us T, La¨ckgren G, Tuvemo T et al. (1999b). Desmopressin-resistant enuresis: pathogenetic and therapeutic considerations. J Urol 162: 2136–2140. Neve´us T, Stenberg A, La¨ckgren G et al. (1999c). Sleep of children with enuresis: a polysomnographic study. Pediatrics 106 (6 Pt 1): 1193–1197. Neve´us T, von Gontard A, Hoebeke P et al. (2006). The standardization of terminology of lower urinary tract function in children and adolescents: report from the standardisation committee of the International Children’s Continence Society (ICCS). J Urol 176 (1): 314–324. Nijman RJ (2004). Role of antimuscarinics in the treatment of nonneurogenic daytime urinary incontinence in children. J Urol 63 (3 Suppl 1): 45–50. Nrgaard JP, Pedersen EB, Djurhuus JC (1985). Diurnal antidiuretic hormone levels in enuretics. J Urol 134: 1029–1031. Ornitz EM, Russell AT, Hanna GL et al. (1999). Prepulse inhibition of startle and the neurobiology of primary nocturnal enuresis. Biol Psychiatry 45 (11): 1455–1466. Pennesi M, Pitter M, Bordugo A et al. (2004). Behavioral therapy for primary nocturnal enuresis. J Urol 171 (1): 408–410. Persson-Ju¨nemann CH, Seemann O, Kohrmann KU et al. (1993). Comparison of urodynamic findings and response to oxybutynin in nocturnal enuresis. Eur Urol 24 (1): 92–96. Raes A, Hoebeke P, Segaert I et al. (2004). Retrospective analysis of efficacy and tolerability of tolterodine in children with overactive bladder. Eur Urol 45 (2): 240–244. Rapoport JL, Mikkelsen EJ, Zavaldil A et al. (1980). Childhood enuresis II. Psychopathology, tricyclic concentration in
369
plasma, and antienuretic effect. Arch Gen Psychiatr 37: 1146–1152. Robson HL, Leung AK (1994). Side effects and complications of treatment with desmopressin for enuresis. J Natl Med Assoc 86 (10): 775–778. Roche EF, Menon A, Gill D et al. (2005). Clinical presentation of type 1 diabetes. Pediatr Diabetes 6 (2): 75–78. Schrier RW, Liberman R, Ufferman RC (1972). Mechanism of antidiuretic effect of beta-adrenergic stimulation. J Clin Invest 51: 97. So¨derstro¨m U, Hoelcke M, Alenius L et al. (2004). Urinary and faecal incontinence: a population-based study. Acta Paediatr 93: 386–389. Trousseau A (1870). Nocturnal incontinence of urine. Lectures on Clinical Medicine, vol. 3. New Sydenham Society, London, pp. 475–490. Unalacak M, Aydin M, Ermis B et al. (2004). Assessment of cardiac autonomic regulation in children with monosymptomatic nocturnal enuresis by analysis of heart rate variability. Tohoku J Exp Med 204: 63–69. Varley CK (2000). Sudden death of a child treated with imipramine. Case study. J Child Adolesc Psychopharmachol 10 (4): 321–325. von Gontard A, Hollmann E, Eiberg H et al. (1997). Clinical enuresis phenotypes in familial nocturnal enuresis. Scand J Urol Nephrol 31 (Suppl 183): 8–16. Vurgun N, Yiditodlu MR, Ypcan A et al. (1998). Hypernatriuria and kaliuresis in enuretic children and the diurnal variation. J Urol 159 (4): 1333–1337. Weider DJ, Sateia MJ, West RP (1991). Nocturnal enuresis in children with upper airway obstruction. Otolaryngol Head Neck Surg 105 (3): 427–432. Wille S (1994). Nocturnal enuresis: sleep disturbance and behavioural patterns. Acta Paediatr 83: 772–774. Wolfish NM, Pivik RT, Busby KA (1997). Elevated sleep arousal thresholds in enuretic boys: clinical implications. Acta Paediatr 86: 381–384. Yazbeck S, Schick E, O’Regan S (1987). Relevance of constipation to enuresis, urinary tract infection and reflux. A review. Eur Urol 13 (5): 318–321. Yeung CK, Chiu HN, Sit FK (1999). Bladder dysfunction in children with refractory monosymptomatic primary nocturnal enuresis. J Urol 162 (3 Pt 2): 1049–1055. Yoshimura N, Sasa M, Yoshida O et al. (1990). Mediation of micturition reflex by central norepinephrine from the locus coeruleus in the cat. J Urol 143 (4): 840–843.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 24
Respiratory physiology in sleep and wakefulness ¨ FFER * THORSTEN SCHA Medical Faculty, Ruhr-University Bochum, and Institute of Clinical Physiology, Helios Klinik Hagen-Ambrock, Germany
INTRODUCTION Respiration is part of a transport system that transfers oxygen (O2) from the atmosphere to the cells of the body and removes carbon dioxide (CO2) from the cells into the atmosphere. At the same time respiration plays a major role in the acid–base regulation of the body (Schla¨fke and Koepchen, 1996). For these purposes, the respiratory system is closely linked to the cardiovascular and renal systems. Respiratory physiology includes all the processes of gas exchange and transport between the atmosphere and the body tissues, e.g., pulmonary ventilation, pulmonary O2 and CO2 exchange, blood circulation, gas transport in the blood, O2 and CO2 exchange in the tissues, the consumption of O2, the production of CO2 by oxidative metabolism, and acid–base regulation. There is no clearcut dividing line between respiratory and cardiovascular physiology. In addition, the respiratory system takes over tasks such as speaking, singing, playing a wind instrument, coughing, sneezing, and stabilizing the trunk of the body. In this chapter, we will discuss the different behaviors of the respiratory system during wakefulness and sleep and the influences of different sleep states on respiration. There are only minor changes in blood gases in healthy subjects during sleep; however, most sleep-related breathing disorders result from dysfunction of the respiratory control systems in the central nervous system.
CENTRAL NEURONAL CONTROL OF BREATHING Physiology RESPIRATORY
RHYTHM AND PATTERN GENERATION
The two mechanical phases of ventilation – inhalation and exhalation – are controlled by three neural phases: inspiration, postinspiration, and expiration (Richter
et al., 1992). These three phases can easily be distinguished. During the inspiratory phase, there is an augmenting neural activity necessary to overcome increasing recoil forces of the lungs and the thoracic wall. Laryngeal abductor muscles are also activated to open the larynx. During the subsequent postinspiratory phase inspiratory movements end, but lung volume is held by a continued neural inspiratory activity, which leads to an actively controlled relaxation of inspiratory muscles. This postinspiratory phase is used for vocalization, speaking, singing, and playing wind instruments. Afterwards inspiratory activity stops completely. This is the beginning of the expiratory phase, in which inspiratory neurons are silent, whereas expiratory neurons are activated. During normal breathing, expiration is passive. Energy, stored in the recoil forces of the respiratory apparatus, is released. Intrapulmonary pressure increases and drives air out of the lungs. Our knowledge of the neurophysiological and anatomical properties of the respiratory system is mainly based on the results of animal experiments. Neurophysiologic research resulted in the identification of neurons with respiration-related activity at widespread sites within the brainstem. There is no single neuronal breathing center, but a network of connected neurons, which works as a rhythm generator for the timing of inspiration and expiration, and a pattern generator with highly complex efferent activity to the primary and accessory respiratory muscles and the upper airways, including the nose, pharynx, larynx, and intrathoracic airways. Initially, the central rhythm and the central pattern generators were ascribed to separate networks (Feldman et al., 1990); in the mature mammal, however, these functions seem to be organized by the same network (Richter et al., 1992). Respiratory rhythm generation might be different in neonatal mammals,
*Correspondence to: Prof. Dr. med. Thorsten Scha¨fer, Ruhr-Universita¨t Bochum, Medizinische Fakulta¨t, Geb. MA 0/47, Universita¨tsstraße 150, D-44780 Bochum, Germany. Tel.: þ49 234 32-24889, Fax: þ49 234 32-14250, E-mail:
[email protected]
372
¨ FFER T. SCHA
Pons
PRG
PRG
Baroreceptors Chemoreceptors IX X
Med. oblong.
DRG
VRG
especially in very immature animals at birth, for example, rats in which a respiratory pacemaker cell activation similar to the sinus node of the heart may be functional during early development (Richter et al., 1992), but there are marked modifications with maturation of the brainstem. New synaptic connections between respiratory neurons emerge, whereas gap junctions, which can be seen in the neonate, are not found in the mature brainstem. Respiratory rhythm and pattern generation incorporates several steps, including switching on and off inspiration and expiration controlled by different cell types, transmitters, and membrane channels. Single-cell recordings in the brainstem and the pons identified several types of respiratory-related neurons, which are active during well-defined phases of the respiratory cycle, e.g., early inspiratory, ramp-inspiratory and end-inspiratory cycles (Richter, 1996). Inspiratory neurons are located bilaterally within the ventral respiratory group next to the nucleus ambiguus and more rostrally as the dorsal respiratory group close to the nucleus tractus solitarius. Furthermore, there are inspiratory neurons at the spinal level of C1 and C2. Expiratory neurons are found within the pons (pontine respiratory group) and the caudal brainstem. Respiratory neurons are difficult to identify morphologically, because they are very similar to the surrounding cells of the reticular formation. Respiratory neurons within the ventral respiratory group and the dorsal respiratory group project to the contralateral spinal respiratory motoneurons, which innervate the intercostal muscles and the diaphragm (Figure 24.1). Timing of respiratory efferents. There is precise timing of muscle activation during inspiration, starting at the nostrils, then the upper and lower airways. Milliseconds later respiratory muscles generate intrathoracic subatmospheric pressure necessary to inhale air into the lungs. During expiration, airway resistance increases due to the reduction of the activity of airway dilator muscles. The lung inflation reflex. The lung inflation reflex (Hering–Breuer reflex) controlled by stretch receptors is part of the neuronal control of breathing. During inspiration lung inflation and afferent vagal activity increase whereas during the expiratory phase, afferent activity decreases. Lung inflation causes a reflex inhibition of further inspiration and promotes expiration. On the other hand, the lung deflation reflex during deep expiration stimulates inspiration. These reflexes lead to an optimization of the work of breathing and gas exchange. Breathing slowly, but deeply, markedly increases the work of breathing due to the higher elastic forces that have to be overcome. On the other hand,
Laryngeal aff. Pulmonary aff.
XII
C1 Spinal cord To contralateral spinal motoneurons
Fig. 24.1. Ventral aspect of the brainstem with pons, medulla, and spinal cord. The nuclei of the respiratory neurons in the ventral respiratory group (VRG) in the vicinity of the nucleus ambiguus, the dorsal respiratory group (DRG) close to the solitary tract nucleus (NTS), and the pontine respiratory group (PRG) are marked. The hatched areas on the ventral medullary surface serve the central CO2 chemosensitivity (from animal experiments). VRG and DRG neurons project to contralateral spinal motoneurons. Baro- and chemoreceptor afferents, laryngeal and pulmonary afferents connect to the NTS near the DRG via the glossopharyngeal and vagus nerves.
rapid shallow breathing increases the ineffective dead space ventilation.
TONIC
ACTIVATION OF THE RESPIRATORY NETWORK
The phasic activity of the respiratory network is dependent upon a nonrhythmic, tonic activation by afferents from different sources. This tonic activation is the neuronal substrate of the so-called respiratory drive. Removal of this tonic drive results in a cessation of the respiratory rhythm (See et al., 1983). We distinguish between feedback and nonfeedback drives (Figure 24.2). Nonfeedback respiratory drives change the ventilation independently of blood gases and may therefore cause deviations of blood gases by inducing hyper- or hypoventilation. The following nonfeedback inputs to the respiratory neurons have been tentatively identified (Orem and Kubin, 2005): (1) higher structures of the brain, which are involved in the behavioral control of breathing;
RESPIRATORY PHYSIOLOGY IN SLEEP AND WAKEFULNESS
373
Feedback Hypoxia, hypercapnia, acidosis
Non-feedback
Tonic afferents
Respiratory network
Behaviour (reflexive/voluntary) Reticular formation (sensory afferents) Aminergic and orexinergic brainstem systems
Rhythm + Pattern generator
(PN) |
Motor efferents
Pl E
Upper airway muscles Resp muscles
Fig. 24.2. Schematic drawing of the central respiratory system with feedback and nonfeedback afferents, the neuronal network as the rhythm and pattern generator, and the motor efferents to the respiratory and the airway muscles. PN, phrenic neurogram with the three neural phases of the respiratory rhythm: inspiration (I), postinspiration (PI), and expiration (E).
(2) the reticular formation in the midbrain and the brainstem; (3) the aminergic brainstem neurons; and (4) the hypothalamic orexinergic neurons. Behavioral control of breathing. Besides involuntary, autonomic control of breathing there is a strong behavioral influence on the respiratory system, which not only modifies the activity of the respiratory network but also bypasses the network and connects to spinal respiratory motoneurons directly. Some kinds of behavioral control are reflexive, such as sighing, coughing, sneezing, eructation, and vomiting. Others are voluntary, such as speaking, singing, laughing, playing a wind instrument, holding the breath, or voluntary hyperventilation. Most levels of the central nervous system can contribute to the behavioral control of respiration, depending upon the act. Many of the higher telencephalic structures are involved in emotional and volitional acts. The reticular formation. The respiratory network is embedded in the reticular formation, which receives multiple inputs from afferent sensory systems and is a major part of the brain’s alertness management system. Stimulation of neurons in the reticular formation excites the respiratory network (Hugelin and Cohen,
1963) by shortening the duration of expiration and by increasing the amplitude of the phrenic nerve activity. It also increases laryngeal abductor muscle activity. Preferentially, however, reticular stimulation activates the muscles of the upper airway (Orem and Lydic, 1978). Most sensory afferents influence the reticular activity and thus the respiratory activity by either stimulation or inhibition. Aminergic systems of the brainstem. Serotonergic and norepinephrine-containing neurons of the brainstem are starting points of a widespread system that controls the level of activity in the central nervous system. Serotonin also excites motoneurons, including those innervating the respiratory pump muscles, including the upper airway. Both brainstem and spinal respiratory motoneurons have receptors for serotonin and norepinephrine. Serotonin is responsible for respiratory long-term facilitation, a long-lasting augmentation of respiratory motor output, which persists after initial stimulation of various origins (Terada et al., 2008). Norepinephrine-containing neurons of the locus coeruleus are tonically active and respond to various, especially stressful, stimuli with phasic bursting (Aston-Jones and Bloom, 1981; Aston-Jones et al., 1996).
¨ FFER T. SCHA
374
Hypothalamic orexinergic neurons. Orexinergic (hypocretin-containing) neurons have been identified in the hypothalamus (Peyron et al., 1998), and project to a widespread network of neurons controlling sleep–wake regulation. These neurons can also activate respiratory neurons via medullary and spinal pathways (Young et al., 2005). They densely project to serotonergic raphe neurons, and can elicit the above-mentioned long-term facilitation (Terada et al., 2008).
Influence of wakefulness and sleep on the neural control of breathing GENETIC
DISPOSITION
Several genes have been identified which control breathing frequency during spontaneous ventilation (de Geus et al., 2005). During wakefulness, there was a moderate correlation between respiratory frequencies and the genotype, which markedly increased during sleep. This sleep-related genetic control may be mediated by candidate genes coding for adenosine and 5-hydroxytryptamine (5-HT) receptors, which are also involved in the control of breathing.
THE “WAKEFULNESS
STIMULUS” OF VENTILATION
Behavior. With sleep onset, the influence of nonfeedback respiratory drives is markedly reduced. Most of the behavioral control mechanisms only occur in wakefulness, not in sleep. Cough reflexes after laryngeal or bronchopulmonary stimulation are suppressed during sleep (Sullivan et al., 1979). Vocalization is limited to phases of sleep talking (somniloquy). Thus, at least during nonrapid eye movement (NREM) sleep, the influence of the behavioral control system on respiration is minimal. During rapid eye movement (REM) sleep, however, behavioral controllers may be activated either erratically or by dream contents, which could explain the irregular breathing pattern, the occurrence of short breathing pauses (apneas) and phases of rapid shallow breathing (Figure 24.3). This variable breathing pattern during REM sleep is independent of variations in chemoreceptor (Scha¨fer and Schla¨fke, 1998) or vagal afferent activity, suggesting that the REM sleeprelated activation is of central origin (Orem et al., 2000). Discharge patterns of respiratory neurons correlate with the frequency of ponto-geniculo-occipital waves, which are typical phenomena during phasic REM sleep (Orem, 1980). REM-specific neural activity is positively related to breathing frequencies (Netick et al., 1977). In humans, bursts of REMs during phasic REM sleep are associated with a suppression of tidal volume and an increase in breathing frequency, even under the condition of an increased respiratory drive
NREM-sleep RC AB
REM-sleep RC AB 10 s
Fig. 24.3. Ribcage (RC) and abdominal (AB) breathing movements recorded from a 3-month-old infant: regular, coordinated breathing pattern during nonrapid eye movement (NREM) sleep, irregular and phase-shifted pattern with inspiratory inward motions of the RC and short apneas during rapid eye movement (REM) sleep.
by hypercapnia (Scha¨fer and Schla¨fke, 1998). It has long been assumed that the variability of breathing during REM sleep is related to dream content. Evidence comes from studies in which sleepers are aroused from sleep and the pattern of breathing is related to the reported dream contents. Higher breathing rates, for example, coincided with more vividness, emotions, or physical activities in the dreams (Hobson et al., 1965). Other results are less convincing (Hauri and Van de Castle, 1973). Reticular formation. With sleep onset the activity of the reticular formation decreases. The reticular activity preferentially strengthens upper-airway muscle activity, which is responsible for upper-airway patency. This implies that during transition from wakefulness to sleep, muscles of the upper airway may lose their tonic activation to a greater extent than the inspiratory muscles. This mismatch could lead to an increased collapsibility of the upper airway during sleep onset. The reduction of sensory input reduces the reticular activity of the brainstem. Single-neuron recordings showed that neurons with mostly phasic activity are less affected than those neurons with more tonic activity. Some of these nerve cells are silenced during certain sleep states of NREM sleep, and can experimentally be activated by the application of excitatory neurotransmitters, which induces rhythmic activity. This phenomenon demonstrates that a “subthreshold” respiratory rhythm remains in these cells (Foutz et al., 1987). Aminergic systems. The aminergic systems of the brainstem markedly decrease their activity during sleep. Firing rates of serotonin- and norepinephrinecontaining neurons are maximal during active wakefulness, reduced during NREM sleep, and minimal during
RESPIRATORY PHYSIOLOGY IN SLEEP AND WAKEFULNESS REM sleep (Aston-Jones and Bloom, 1981; Trulson and Trulson, 1982). This coincides with an abolished respiratory long-term facilitation during sleep, which may, at least in part, be responsible for the increased sleep-induced breathing instability (Dempsey et al., 1996). Orexin. Similar to the aminergic systems, the activity of the orexinergic hypothalamic neurons is closely related to wakefulness (Estabrooke et al., 2001; Kuwaki, 2008). Studies in orexin knockout mice imply that the orexin system likely functions as an essential modulator for coordinating circuits controlling autonomic functions and behaviors (Kuwaki et al., 2008). In summary, wakefulness exerts a tonic stimulating effect on respiration. The orexinergic and aminergic systems are the likely candidates for the postulated “wakefulness stimuli” for breathing. Further phasic stimulations by the behavioral control systems and reticular formation are much more frequent during wakefulness than during sleep. REM sleep, however, may trigger the behavioral system intrinsically and thus exerts a drive to breathe independently of the metabolic needs and the feedback regulation of respiration.
FEEDBACK REGULATION OF RESPIRATION
CENTRAL
375
CHEMOSENSITIVITY
Even after experimental elimination of the peripheral chemoreceptors there is still a highly sensitive and very effective CO2- and pH-dependent respiratory drive, in which the ventral medullary surface of the brainstem (Figure 24.1) plays an important role (Schla¨fke, 1981). Minimal changes of the PCO2 or the pH in these superficial layers, in the cerebrospinal fluid, or in the arterial blood cause marked changes in ventilation. Experimental elimination of these areas leads to a loss of the CO2 sensitivity of the respiratory system, followed by a destabilization of blood gas homeostasis, causing hyperventilation during active wakefulness and severe hypoventilation during sleep (Schla¨fke et al., 1999). In animal experiments several brain areas have been identified, where neurons increase their firing rates during an increase of the local PCO2 or a decrease of the local pH depending upon the state of sleep and wakefulness; this coincided with an acceleration or deepening of respiration (Nattie, 2000; Krimsky and Leiter, 2005). This central chemical drive of ventilation, called “central chemosensitivity,” is characterized by a much longer time constant than the peripheral chemoreceptors in the range of minutes, contributing 60–85% of the respiratory drive at rest and showing little adaptation.
Physiology The specific chemical afferents during hypoxia, hypercapnia, and acidosis play an important role in the regulation of breathing. These afferents form closed feedback loops, which lead to a stabilization of oxygen and carbon dioxide partial pressures and the pH in the arterial blood and the cerebrospinal fluid.
PERIPHERAL
CHEMORECEPTORS
The sensors of this feedback loop are located in the peripheral chemoreceptor sites in the carotid and aortic bodies, which respond to hypoxia, hypercapnia, and metabolic acidosis by increasing their firing rate. The afferents from the peripheral chemoreceptors are integrated into the respiratory network via the solitary tract nucleus within the dorsal brainstem. The peripheral chemoreceptors are the only sensor systems of the body which directly drive ventilation during hypoxemia. Their impact on breathing is fast, but they tend to adapt. They contribute 15–40% of the whole respiratory drive during rest (Pan et al., 1998). Denervation of these peripheral sites causes an immediate drop of minute ventilation and an increase in arterial PCO2 by 5–10 mmHg. Ventilation, however, recovers, until the PaCO2 reaches normocapnic values again. The hypoxic respiratory sensitivity remains blunted.
Effect of sleep on the “chemical” regulation of breathing HYPOXIA The hypoxic ventilatory drive is suppressed during sleep to minimal values in REM sleep (Douglas et al., 1982a). This is true for men and women. Women, however, already have a lower hypoxic drive during wakefulness. Therefore, the sleep-related inhibition is significant only during REM sleep (White et al., 1982). According to Tarbichi et al. (2003), the hypoxic ventilatory response during NREM sleep does not differ between men and women.
HYPERCAPNIA The hypercapnic ventilatory response varies during sleep. Rebreathing tests during well-defined sleep states demonstrated a reduction of the CO2 response to 50% in NREM sleep and to 30% in REM sleep compared with the level during wakefulness (Douglas et al., 1982b). Furthermore, there is a circadian rhythm of CO2 sensitivity independent of sleep with minimal hypercapnic responses in the early-morning hours (Raschke and Mo¨ller, 1989; Spengler et al., 2000). In combination with these two findings, a marked
¨ FFER T. SCHA
376
reduction of CO2 sensitivity might be expected during REM sleep in the early morning. This high variability during sleep has been proven by repetitive CO2 challenges throughout the whole night (Scha¨fer, 1998). In this experiment, the mean hypercapnic sensitivity ranged from a maximum of 1.45 0.35 l/min/mmHg to a minimum of 0.31 0.13 l/min/mmHg. The lowest values occurred during the second half of the night, between 3:00 and 6:30 a.m. During REM sleep, the tidal volume response was markedly reduced. The respiratory rate slightly increased, but did not compensate for the reduction in tidal volume (Scha¨fer and Schla¨fke, 2001). Despite reduced chemical drive for ventilation, the average minute ventilation at rest was slightly increased during REM sleep and the mean PCO2 was slightly lower than during NREM sleep. This indicates that additional nonfeedback drives stimulate breathing during REM sleep independently of the blood gas situation. The CO2 response curves were flattened but shifted to the left. The reduced hypercapnic drive becomes apparent only at higher PCO2 values (Figure 24.4). The sleep-related reduction of respiratory motor output in response to elevated CO2 partial pressures is in part attributable to an increased brain blood flow during sleep with consequent relative hypocapnia at the
Slope
THE
APNEA THRESHOLD
Sleep unmasks a highly sensitive hypocapnia-induced apneic threshold (Dempsey et al., 2004), which is blunted during wakefulness by mechanisms like respiratory long-term facilitation and the wakefulness stimuli. During sleep, breathing stops following small transient reductions in PaCO2 below eupnea, and the respiratory rhythm is not restored until the PaCO2 has risen significantly above eupneic levels, which implies a marked hysteresis or inertia of the respiratory control
Apnoea point
*
40
1.5
*
sensor sites of central chemosensitivity (Parisi et al., 1988, 1992). Sleep deprivation also suppresses the chemical drive of respiration. After one night of sleep deprivation in healthy men, the hypoxic ventilatory response was reduced by 29% and the hypercapnic ventilatory response by 24% (White et al., 1983). Studies in patients suffering from obstructive sleep apnea showed that the repetitive hypoxic-hypercapnic events with arousals changed the chemical drive of ventilation. In contrast to healthy subjects, patients showed a 30% increase in chemical drive after one night without therapy. This phenomenon further destabilizes the respiratory rhythm.
20
*
*
P < 0.05
1.0
15 V′ [l/min]
A [Torr]
S [l/min/Torr]
35
30
0.5 25
n.s.
10 Sleep
Deep NREM
Light NREM
REM-sleep
Light WASO
Deep NREM
Light NREM
REM-sleep
REM
n.s.
20 WASO
0.0
Deep 5 Rest
+5 Torr
+10 Torr
PETCO2
Fig. 24.4. CO2 responses of healthy subjects during wakefulness after sleep onset (WASO), light, deep, and rapid eye movement (REM) sleep. Although the slope (S) of the CO2 response curves is markedly reduced during REM sleep, the apnea point (A) is shifted to the left. Therefore, resting ventilation at eucapnia tends to be higher during REM sleep than in other sleep states. n.s., not significant. V, minute ventilation; PETCO2, end-tidal carbon dioxide partial pressure. (Modified from Scha¨fer (1998).)
RESPIRATORY PHYSIOLOGY IN SLEEP AND WAKEFULNESS
377
Tidal volume
PaCO2
Hysteresis /inertia Apnoeic threshold
Fig. 24.5. During sleep, breathing (tidal volume) stops following small transient reductions in arterial CO2 partial pressure (PaCO2) below the apneic threshold. Breathing is not restored until the PaCO2 has risen significantly above eupneic levels, which implies a marked hysteresis or inertia of the respiratory control system.
system (Figure 24.5). This control system inertia favors central apneas and periodic breathing during sleep (Leevers et al., 1993). After sighs and augmented breaths, the lung inflation reflex can suppress the next inspiration and may account for the instability of breathing during sleep (Iber et al., 1995). The smaller the difference between the eucapnic PaCO2 and the PaCO2 at the apneic threshold, the more likely is the occurrence of breathing instabilities. This difference varies inversely with the slope of the ventilatory CO2 response below eupnea and with the ventilatory increase required for a given reduction in PaCO2. The factors inducing periodic breathing in humans (Khoo et al., 1982) and the interaction between arousal and chemical drive in sleep-disordered breathing (Khoo and Berry, 1996) have been mathematically modeled. An enhanced hypercapnic and/or hypoxic respiratory drive and a delayed feedback of the blood gas changes to the respiratory network can induce periodic breathing with central apneas. Patients with idiopathic central sleep apneas showed an exaggerated hypercapnic ventilatory response and hyperventilation with hypocapnia (Xie et al., 1995).
AIRWAY RESISTANCE AND RESPIRATORY MUSCLE TONE
collapsibility of the upper airways. In addition, more than 20 muscles below the pharyngeal mucosa stiffen and widen the upper airway (Fouke et al., 1986). Mainly tonically active muscles (e.g., tensor veli palatini) can be distinguished from mainly phasically active muscles (e.g., genioglossus). The respiratory network controls this phasic activity. During inspiration, the muscle activity continuously increases and thus widens and stiffens the airway to prevent a collapse due to negative intraluminal pressure. In addition to respiratory innervation there are local mechanoreceptor reflexes, which can experimentally be triggered by short negative-pressure pulses within the pharynx and which result in increased tension of specific pharyngeal muscles (Malhotra et al., 2000). The palatopharyngeus (Mortimore and Douglas, 1996) and the genioglossus increase their basic tone during negative-pressure pulses. Superficial anesthesia, however, suppresses this effect markedly (Fogel et al., 2000). Continuous positive airway pressure also suppresses the genioglossus and tensor palatini activities (Mezzanotte et al., 1996). During wakefulness upper-airway muscle activity markedly increases, when the respiratory drive is enhanced, e.g., by hypercapnia (Pillar et al., 2000). This effect, however, is blunted during sleep.
Physiology
State-dependent changes of airway resistance and respiratory muscle tone
The diameter of the upper airway is a result of the interplay of anatomical, functional, mechanical, and neuromuscular components. Some of the anatomical factors can be measured by cephalometry, e.g., position of the upper and lower jaw and the palate, size of the tongue, and thickness of the connective and fatty tissues in the pharynx. The tension of the pharynx is governed by mechanical factors. It is dependent upon the caudal traction of the trachea and decreases with lower functional residual capacity, which increases the
With sleep onset, the upper-airway resistance significantly increases as compared with wakefulness. This happens rapidly and coincides with the occurrence of theta activity in the sleep electroencephalogram (Worsnop et al., 1998). The basal dilator tone decreases (Tangel et al., 1991) and the phasic activity is reduced and less sensitive to enhancements of the respiratory drive (Figure 24.6) (Tangel et al., 1995). This effect favors the occurrence of upper-airway obstructions. After short periods of hyperpnea, the inspiratory
¨ FFER T. SCHA
378 Genioglossus-EMG
Wakefulness
NREM-sleep
REM-sleep
Fig. 24.6. Schematic drawing of the sleep state-related activity of the genioglossus as a pharyngeal dilator muscle. The basal tonic activity and the phasic activity decrease from wakefulness to nonrapid eye movement (NREM) sleep and further to rapid eye movement (REM) sleep, in which the pattern becomes very irregular. EMG, electromyogram.
muscles are activated more strongly and before the upper-airway muscles. Thus, they generate an inspiratory negative pressure, while the upper airways are more collapsible. The muscle atonia during REM sleep also affects the pharyngeal muscles, which further increases the collapsibility of the upper airways. The horizontal position during sleep favors the obstruction of the upper airway because the tongue moves dorsally and reduces the posterior-airway space, and because the traction forces on the trachea decrease due to the smaller functional residual capacity. Even habitual snoring improves in an elevated upper-body position (Verse et al., 2004). The pharynx resembles a Starling resistor in the form of a collapsible tube, which is fixed between the noncollapsible nose and larynx. Its condition is dependent upon the ratio of the intraluminal pressure and the external tissue pressure, the driving pressure difference upstream versus downstream, and the compliance of the tissue. In healthy subjects, the upper airways remain open even during forced inspiration. The so-called critical closing pressure Pcrit is negative at about –14 cm H2O, as proven by the application of negative pressure via a nose mask (Schwartz et al., 1988). Snorers demonstrated a less negative Pcrit. At a Pcrit of –5 cm H2O, the pharynx tends to collapse during inspiration. In patients with obstructive hypopneas without obstructive apneas, the Pcrit is slightly below atmospheric pressure. In patients with obstructive sleep apnea, the Pcrit during sleep is found at positive values, which requires the application of nasal continuous positive airway pressure as the adequate treatment.
MUSCLE
ATONIA DURING
REM
SLEEP
During sleep muscle tone is generally lower than during wakefulness, but minimal during REM sleep. This effect can experimentally be triggered by carbachol
microinjections into a discrete area in the dorsomedial pontine tegmentum (Vanni-Mercier et al., 1989). Carbachol, an acetylcholine agonist, injected into the pons, silences medullary serotonergic cells (Woch et al., 1996) and norepinephrine-containing cells in the locus coeruleus, similar to the physiological events that occur during REM sleep (Kubin and Fenik, 2004). Besides the upper-airway muscles and the tongue, the intercostal and accessory respiratory muscles are affected by this REM sleep-related atonia. The loss of respiratory muscle strength must be compensated by increased efforts of the diaphragm, which is less affected. Thus, patients with impaired abdominal breathing are prone to respiratory insufficiency, especially during REM sleep.
AROUSAL THRESHOLDS Physiology Malfunctions of the respiratory system may lead to an enhancement of alertness, called arousal response. These arousals are observed in response to hypercapnia and hypoxia, bronchial irritation or an exaggerated ventilatory effort, which could be necessary to overcome an increased inspiratory resistance or as a reaction to a complete occlusion of the airway.
State-dependent changes of arousal thresholds HYPOXIA Hypoxia is a poor stimulus to arousal. Healthy subjects often remain asleep with an arterial oxygen saturation below 70% (Berthon-Jones and Sullivan, 1982) during both NREM and REM sleep. However, the arousal sensitivity to hypoxia is further decreased during REM sleep in patients with sleep-disordered breathing (Sullivan and Issa, 1980).
RESPIRATORY PHYSIOLOGY IN SLEEP AND WAKEFULNESS
HYPERCAPNIA Compared with hypoxia, hypercapnia is a more effective arousal stimulus and awakens most healthy subjects after a rise of 15 mmHg above wakefulness levels (Bu¨low, 1963; Douglas et al., 1982b). During deep NREM sleep, men may (Berthon-Jones and Sullivan, 1984) or may not (Douglas et al., 1982b) be less sensitive to hypercapnia than women. Concomitant hypoxia lowers the threshold of hypercapnic arousals (Gothe et al., 1986).
BRONCHIAL
IRRITATION
As mentioned above, sleep suppresses cough and sneezing reflexes, even in patients with chronic bronchitis.
INCREASED
VENTILATORY EFFORT
Airway obstruction, either due to narrowing or closure of the airways or to added resistance, elicits arousal responses in sleeping healthy subjects. Arousal from REM sleep after airway occlusion is far more rapid than from NREM sleep (Issa and Sullivan, 1983). Patients suffering from obstructive sleep apnea syndrome, however, have longer apneas during REM sleep, probably because the complete occlusion of the pharynx prevents the upper-airway receptors from sensing the pressure swings. Arousal responses during sleep often occur at similar levels of respiratory effort, regardless of the blood gas situation. This implies that elevated neuromuscular effort, but not hypoxemia or hypercapnia, is the important event to trigger an arousal response during sleep (Gleeson et al., 1990).
REFERENCES Aston-Jones G, Bloom FE (1981). Activity of norepinephrinecontaining locus coeruleus neurons in behaving rats anticipates fluctuations in the sleep–waking cycle. J Neurosci 1: 876–886. Aston-Jones G, Rajkowski J, Kubiak P et al. (1996). Role of the locus coeruleus in emotional activation. Prog Brain Res 107: 379–402. Berthon-Jones M, Sullivan CE (1982). Ventilatory and arousal responses to hypoxia in sleeping humans. Am Rev Respir Dis 125: 632–639. Berthon-Jones M, Sullivan CE (1984). Ventilation and arousal responses to hypercapnia in normal sleeping humans. J Appl Physiol 57: 59–67. Bu¨low K (1963). Respiration and wakefulness in man. Acta Physiol Scand 59 (Suppl 209): 1–110. de Geus EJ, Posthuma D, Kupper N et al. (2005). A wholegenome scan for 24-hour respiration rate: a major locus at 10q26 influences respiration during sleep. Am J Hum Genet 76: 100–111.
379
Dempsey JA, Smith CA, Harms CA et al. (1996). Sleepinduced breathing instability. University of WisconsinMadison Sleep and Respiration Research Group. Sleep 19: 236–247. Dempsey JA, Smith CA, Przybylowski T et al. (2004). The ventilatory responsiveness to CO(2) below eupnoea as a determinant of ventilatory stability in sleep. J Physiol 560: 1–11. Douglas NJ, White DP, Weil JV et al. (1982a). Hypoxic ventilatory response decreases during sleep in normal men. Am Rev Respir Dis 125: 286–289. Douglas NJ, White DP, Weil JV et al. (1982b). Hypercapnic ventilatory response in sleeping adults. Am Rev Respir Dis 126: 758–762. Estabrooke IV, McCarthy MT, Ko E et al. (2001). Fos expression in orexin neurons varies with behavioral state. J Neurosci 21: 1656–1662. Feldman JL, Smith JC, Ellenberger HH et al. (1990). Neurogenesis of respiratory rhythm and pattern – emerging concepts. Am J Physiol 259: R879–R886. Fogel RB, Malhotra A, Shea SA et al. (2000). Reduced genioglossal activity with upper airway anesthesia in awake patients with OSA. J Appl Physiol 88: 1346–1354. Fouke JM, Teeter JP, Strohl KP (1986). Pressure–volume behavior of the upper airway. J Appl Physiol 61: 912–918. Foutz AS, Boudinot E, Morin-Surun MP et al. (1987). Excitability of “silent” respiratory neurons during sleep– waking states: an iontophoretic study in undrugged chronic cats. Brain Res 404: 10–20. Gleeson K, Zwillich CW, White DP (1990). The influence of increasing ventilatory effort on arousal from sleep. Am Rev Respir Dis 142: 295–300. Gothe B, Cherniack NS, Williams L (1986). Effect of hypoxia on ventilatory and arousal responses to CO2 during NREM sleep with and without flurazepam in young adults. Sleep 9: 24–37. Hauri P, Van de Castle RL (1973). Psychophysiological parallels in dreams. Psychosom Med 35: 297–308. Hobson JA, Goldfrank F, Snyder F (1965). Respiration and mental activity in sleep. J Psychiatr Res 3: 79–90. Hugelin A, Cohen MI (1963). The reticular activating system and respiratory regulation in the cat. Ann N Y Acad Sci 109: 586–603. Iber C, Simon P, Skatrud JB et al. (1995). The Breuer– Hering reflex in humans: effects of pulmonary denervation and hypocapnia. Am J Respir Crit Care Med 152: 217–224. Issa FG, Sullivan CE (1983). Arousal and breathing responses to airway occlusion in healthy sleeping adults. J Appl Physiol 55: 1113–1119. Khoo MCK, Berry RB (1996). Modeling the interaction between arousal and chemical drive in sleep-disordered breathing. Sleep 19: S167–S169. Khoo MCK, Kronauer RE, Strohl KP et al. (1982). Factors inducing periodic breathing in humans: a general model. J Appl Physiol 53: 644–659. Krimsky WR, Leiter JC (2005). Physiology of breathing and respiratory control during sleep. Semin Respir Crit Care Med 26: 5–12.
380
¨ FFER T. SCHA
Kubin L, Fenik V (2004). Pontine cholinergic mechanisms and their impact on respiratory regulation. Respir Physiol Neurobiol 143: 235–249. Kuwaki T (2008). Orexinergic modulation of breathing across vigilance states. Respir Physiol Neurobiol 164: 204–212. Kuwaki T, Zhang W, Nakamura A et al. (2008). Emotional and state-dependent modification of cardiorespiratory function: role of orexinergic neurons. Auton Neurosci. Leevers AM, Simon PM, Xi L et al. (1993). Apnoea following normocapnic mechanical ventilation in awake mammals – a demonstration of control system inertia. J Physiol 472: 749–768. Malhotra A, Pillar G, Fogel RB et al. (2000). Genioglossal but not palatal muscle activity relates closely to pharyngeal pressure. Am J Respir Crit Care Med 162: 1058–1062. Mezzanotte WS, Tangel DJ, White DP (1996). Influence of sleep onset on upper-airway muscle activity in apnea patients versus normal controls. Am J Respir Crit Care Med 153: 1880–1887. Mortimore IL, Douglas NJ (1996). Palatopharyngeous has respiratory activity and responds to negative pressure in sleep apnoeics. Eur Resp J 9: 773–778. Nattie E (2000). Multiple sites for central chemoreception: their roles in response sensitivity and in sleep and wakefulness. Respir Physiol 122: 223–235. Netick A, Orem J, Dement W (1977). Neuronal activity specific to REM sleep and its relationship to breathing. Brain Res 120: 197–207. Orem J (1980). Medullary respiratory neuron activity: relationship to tonic and phasic REM sleep. J Appl Physiol 48: 54–65. Orem J, Kubin L (2005). Respiratory physiology: central neural control. In: MH Kryger, T Roth, WC Dement (Eds.), Principles and Practice of Sleep Medicine. Elsevier Saunders, Philadelphia, USA, pp. 213–223. Orem J, Lydic R (1978). Upper airway function during sleep and wakefulness: experimental studies on normal and anesthetized cats. Sleep 1: 49–68. Orem J, Lovering AT, Dunin-Barkowski W et al. (2000). Endogenous excitatory drive to the respiratory system in rapid eye movement sleep in cats. J Physiol 527: 365–376. Pan LG, Forster HV, Martino P et al. (1998). Important role of carotid afferents in control of breathing. J Appl Physiol 85: 1299–1306. Parisi RA, Neubauer JA, Frank MM et al. (1988). Linkage between brain blood flow and respiratory drive during rapid-eye-movement sleep. J Appl Physiol 64: 1457–1465. Parisi RA, Edelman NH, Santiago TV (1992). Central respiratory carbon dioxide chemosensitivity does not decrease during sleep. Am Rev Respir Dis 145: 832–836. Peyron C, Tighe DK, van den Pol AN et al. (1998). Neurons containing hypocretin (orexin) project to multiple neuronal systems. J Neurosci 18: 9996–10015. Pillar G, Malhotra A, Fogel RB et al. (2000). Upper airway muscle responsiveness to rising Pco(2) during NREM sleep. J Appl Physiol 89: 1275–1282.
Raschke F, Mo¨ller KH (1989). Untersuchungen zur Tagesrhythmik der Chemosensitivita¨t und deren Beitrag zu na¨chtlichen Atmungsregulationssto¨rungen. Pneumologie 43: 568–571. Richter DW (1996). Neural regulation of respiration: rhythmogenesis and afferent control. In: R Greger, U Windhorst (Eds.), Comprehensive Human Physiology. Springer, Berlin, pp. 2079–2095. Richter DW, Ballanyi K, Schwarzacher S (1992). Mechanisms of respiratory rhythm generation. Curr Opin Neurobiol 2: 788–793. Scha¨fer T (1998). Variability of vigilance and ventilation. Studies on the control of respiration during sleep. Resp Physiol 114: 37–48. Scha¨fer T, Schla¨fke ME (1998). Respiratory changes associated with rapid eye movements in normo- and hypercapnia during sleep. J Appl Physiol 85: 2213–2219. Scha¨fer T, Schla¨fke ME (2001). Variability of CO2-sensitivity during sleep. Adv Exp Med Biol 499: 459–463. Schla¨fke ME (1981). Central chemosensitivity: a respiratory drive. Rev Physiol Biochem Pharmacol 90: 172–244. Schla¨fke ME, Koepchen HP (1996). A systems view of respiratory regulation. In: R Greger, U Windhorst (Eds.), Comprehensive Human Physiology – from Cellular Mechansism to Integration. Springer, Berlin, pp. 2097–2127. Schla¨fke ME, Scha¨fer C, Scha¨fer T (1999). Das UndineSyndrom als kongenitales zentrales Hypoventilationssyndrom (CCHS). Somnologie 3: 128–133. Schwartz AR, Smith PL, Wise RA et al. (1988). Induction of upper airway occlusion in sleeping individuals with subatmospheric nasal pressure. J Appl Physiol 64: 535–542. See WR, Schla¨fke ME, Loeschcke HH (1983). Role of chemical afferents in the maintenance of rhythmic respiratory movements. J Appl Physiol 54: 453–459. Spengler CM, Czeisler CA, Shea SA (2000). An endogenous circadian rhythm of respiratory control in humans. J Physiol London 526: 683–694. Sullivan CE, Issa FG (1980). Pathophysiological mechanisms in obstructive sleep apnea. Sleep 3: 235–246. Sullivan CE, Kozar LF, Murphy E et al. (1979). Arousal, ventilatory, and airway responses to bronchopulmonary stimulation in sleeping dogs. J Appl Physiol 47: 17–25. Tangel DJ, Mezzanotte WS, White DP (1991). Influence of sleep on tensor palatini EMG and upper airway resistance in normal men. J Appl Physiol 70: 2574–2581. Tangel DJ, Mezzanotte WS, White DP (1995). Influences of NREM sleep on activity of palatoglossus and levator palatini muscles in normal men. J Appl Physiol 78: 689–695. Tarbichi AG, Rowley JA, Shkoukani MA et al. (2003). Lack of gender difference in ventilatory chemoresponsiveness and post-hypoxic ventilatory decline. Respir Physiol Neurobiol 137: 41–50. Terada J, Nakamura A, Zhang W et al. (2008). Ventilatory long-term facilitation in mice can be observed during both sleep and wake periods and depends on orexin. J Appl Physiol 104: 499–507.
RESPIRATORY PHYSIOLOGY IN SLEEP AND WAKEFULNESS Trulson ME, Trulson VM (1982). Activity of nucleus raphe pallidus neurons across the sleep-waking cycle in freely moving cats. Brain Res 237: 232–237. Vanni-Mercier G, Sakai K, Lin JS et al. (1989). Mapping of cholinoceptive brainstem structures responsible for the generation of paradoxical sleep in the cat. Arch Ital Biol 127: 133–164. Verse T, Pirsig W, Maurer JT et al. (2004). Influence of elevated versus flat upper body position on objective snoring intensity. A case report. Somnologie 8: 151–154. White DP, Douglas NJ, Pickett CK et al. (1982). Hypoxic ventilatory response during sleep in normal premenopausal women. Am Rev Respir Dis 126: 530–533. White DP, Douglas NJ, Pickett CK et al. (1983). Sleep deprivation and the control of ventilation. Am Rev Respir Dis 128: 984–986.
381
Woch G, Davies RO, Pack AI et al. (1996). Behaviour of raphe cells projecting to the dorsomedial medulla during carbachol-induced atonia in the cat. J Physiol 490: 745–758. Worsnop C, Kay A, Pierce R et al. (1998). Activity of respiratory pump and upper airway muscles during sleep onset. J Appl Physiol 85: 908–920. Xie AL, Rutherford R, Rankin F et al. (1995). Hypocapnia and increased ventilatory responsiveness in patients with idiopathic central sleep apnea. Am J Respir Crit Care Med 152: 1950–1955. Young JK, Wu M, Manaye KF et al. (2005). Orexin stimulates breathing via medullary and spinal pathways. J Appl Physiol 98: 1387–1395.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 25
Obstructive sleep apnea: diagnosis, risk factors, and pathophysiology GIORA PILLAR AND PERETZ LAVIE * Sleep Medicine Center, Rambam Hospital and Lloyd Rigler Sleep Apnea Research Laboratory, Ruth and Bruce Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel
OBSTRUCTIVE SLEEPAPNEA: A BRIEF HISTORY The last two decades have seen an increase in public awareness of the importance of sleep and its disorders. This has led to an unprecedented growth in sleep medicine. It has been estimated that some 2 million diagnostic sleep recordings are done annually in the USA alone. Most of this growth is attributed to the emergence of obstructive sleep apnea (OSA) as a major public health problem with a profound impact on quality of life, on safety on the roads and at work, and on the cardiovascular system. Given the vast number of patients diagnosed nightly with breathing disorders in sleep it is difficult to understand why it has taken the medical community so long to awaken to the importance of sleep apnea. Sleepy and obese patients have been recognized in the medical literature since the turn of the 20th century (for detailed history, see Lavie, 2003). The resemblance of these patients to Joe, the picturesque character from Dicken’s 1836 book The Posthumous Papers of the Pickwick Club, was recognized by several physicians, who independently coined the term “pickwickians” to describe these patients. None of these early descriptions, however, linked the symptoms of the pickwickian patients with disturbances in nocturnal sleep. The first laboratory study that documented cases of breathing disorders in sleep was conducted in Ludolf Krehl Clinic in Heidelberg, Germany, by Gerardy et al. in 1960 and by Drachman and Gumnit at the National Institutes of Health, USA, in 1962. In both studies the physiological recordings of pickwickian patients made during sleep demonstrated repeatedly occurring breathing cessations, each terminated by a brief
physiologic arousal. In both reports slowing of the heart rate during the apneas alternating with quickening of the heart rate during the resumption of breathing was noted by the authors. Anticipating modern observations, in both reports, massive weight reduction resulted in great improvement and even disappearance of disordered breathing in sleep and amelioration of daytime sleepiness. These two pioneering publications remained hidden from the general medical community for many years and have been rarely cited in the literature. Jung and Kuhlo (1965) should be credited for bringing the nocturnal events in pickwickian patients to the attention of the medical community. They also conducted sleep laboratory recordings in pickwickian patients and confirmed that these patients suffer from breathing cessations during sleep. Presenting their findings at the Annual Meeting of the European Neurological Society in Oberstdorf in 1964, Kuhl made the original proposal that the frequent interruptions of sleep in pickwickian patients because of the breathing cessations could be responsible for their excessive daytime sleepiness, and not carbon dioxide retention, as had been proposed in all previous publications (Kuhl, 1997). The importance of this presentation was immediately recognized by Henri Gastaut from Marseilles and Elio Lugaresi from Bologna, who shortly after that confirmed Kuhl and Jung’s observations and conclusions and further extended them (Gastaut et al, 1966; Lugaresi et al., 1968). Later, Guilleminault et al. (1973) showed that obesity is not an obligatory condition for the occurrence of apnea during sleep and that apnea also occurred in patients of normal weight, and thus paved the way for a wide recognition of sleep apnea syndrome by the medical community.
*Correspondence to: Peretz Lavie, Ph.D., Lloyd Rigler Sleep Apnea Research Laboratory, Rappaport Building, Efron St 1, Bat Galim, Haifa, 30961, Israel. Tel: 972-544706020, Fax: 972-8343934, E-mail:
[email protected]
384
G. PILLAR AND P. LAVIE
EPIDEMIOLOGY OSA syndrome is very prevalent in the general population. As early as 1983 we estimated that at least 1% of the presumably healthy adult male population have OSA (Lavie, 1983). At that time the syndrome was defined as a sleep laboratory finding of 10 apneas per hour of sleep combined with subjective complaints of excessive daytime sleepiness or disturbed nocturnal sleep. Of note, the importance of hypopneas, that is, partial obstructions of the airways, was not recognized at that time, which probably resulted in an underestimation of the true prevalence of the syndrome. The occurrence of apneas was significantly associated with excessive daytime sleepiness, habitual snoring, frequent headaches, excessive motility in sleep, and hypertension. Others, using similar definitions of the syndrome, reported on similar findings. Based on a study of all patients admitted during 1 year to a hospital in Italy, Franceschi et al. (1982) reported on a prevalence of 1.0% of sleep apnea. Investigating the prevalence of sleep apnea in the general population in the Netherlands, Neven et al. (1998) reported on a prevalence of 0.9%. Higher estimates ranging from 1.3 to 4.7% were reported in studies counting both apneas and hypopneas rather than apneas alone (Bixler et al., 1982; Gislason and Taube, 1987; Cirignotta et al., 1989; Young et al., 1993). The most influential epidemiological study that had a major impact on subsequent recognition of the syndrome and its importance was that of Young et al. (1993). Defining the syndrome as the occurrence of at least 5 apneas or hypopneas per hour of sleep in combination with a complaint of daytime somnolence, they reported that 2% and 4% of middle-aged women and men in the USA, respectively, suffer from OSA. Furthermore, if symptoms were disregarded, 24% of men and 9% of women had at least 5 respiratory events per hour of sleep. Approximately the same rate (Kim et al., 2004), or even slightly higher rates (Schmidt-Nowara et al., 1990; Ong and Clerk, 1998; Udwadia et al., 2004; Villaneuva et al., 2005), were reported for a variety of ethnic groups. It is unclear at this time, however, whether the increased prevalence in specific ethnic groups results from direct genetic causes or from ethnic-related characteristics of body phenotype, such as upper-airway structure or obesity (Villaneuva et al., 2005). Recently, several community-based studies have been performed to learn more about the prevalence and impact of sleep-disordered breathing on general health. In these studies the prevalence of breathing disorders in sleep was investigated irrespective of subjective complaints. In the Sleep Heart Health Study, a very largescale study that longitudinally follows up on the sleep
of community-dwelling adults, it was reported that over 10% of the general population has some degree of sleepdisordered breathing, with daytime somnolence correlated to breathing disorder severity (Gottlieb et al., 1999), most of them undiagnosed (Kapur et al., 2002). The prevalence of breathing disorders in sleep is much higher in specific high-risk populations. Thus, the prevalence of breathing disorders in sleep in the elderly is estimated at around 30% (Ancoli-Israel et al., 1987, 1991), and similar rates were reported for obese patients (Gami et al., 2003; Formiguera and Canton, 2004). Much higher prevalence of 50–98% was reported among the morbidly obese (Valencia-Flores et al., 2000; Resta et al., 2001). Similarly, the prevalence is high in patients with hypothyroidism (Kapur et al., 1998), diabetes (Punjabi et al., 2002; Resnick et al., 2003), gastroesophageal reflux (Gislason et al., 2002), renal failure (Hui et al., 2000, 2002b), acromegaly (Grunstein et al., 1991; Fatti et al., 2001), and women with polycystic ovary syndrome (Fogel et al., 2001b). In populations with cardiovascular disease, the prevalence has been found to be substantially increased, especially in patients with hypertension (Kales et al., 1984; Lavie et al., 1984; Fletcher et al., 1985; Worsnop et al., 1998; Logan et al., 2001), coronary artery disease (Andreas et al., 1996; Schafer et al., 1999), stroke (Hui et al., 2002a; Bassetti, 2005), and heart failure (Javaheri et al., 1998). Thus, OSA is a common disorder in the general population and even more so in specific at-risk populations. Special emphasis should therefore be placed on the recognition of the risk factors of this disorder and understanding its pathophysiology.
DIAGNOSIS The diagnosis of OSA begins with an understanding of the risk factors for this disorder (see below) and the clinical presentation of afflicted patients. The history as related by both the patient and the bed partner is an important source of information. Snoring, witnessed apneas, choking, or gasping during sleep are the most common complaints (Lavie, 1983; Fisher et al., 2002; Caples et al., 2005). Additional symptoms include excessive daytime sleepiness, impaired concentration/cognitive abilities (e.g., memory impairment) (El-Ad and Lavie, 2005), morning headaches, nocturia, sexual impotence (Margel et al., 2004), and possibly depression (Derderian et al., 1988; Pillar and Lavie, 1998). There may be gender-related differences in the presenting symptoms in OSA, with women complaining more of insomnia and men complaining more of excessive daytime sleepiness (Ambrogetti et al., 1991; Lavie and Pillar, 2001), although not all agree on that (Young et al., 1996).
OBSTRUCTIVE SLEEP APNEA: DIAGNOSIS, RISK FACTORS, AND PATHOPHYSIOLOGY The physical exam unfortunately does not add much to the diagnosis, but it can raise suspicion. It may show obesity, an increased neck circumference, a small crowded posterior pharyngeal space (with or without enlarged tonsils), nasal obstruction, lowerextremity edema, and/or systemic hypertension. Using all the information gathered from questionnaires and physical examinations we previously constructed a model to predict sleep apnea severity. We found that the most significant variables were self/spouse report of cessations of breathings and neck circumference, that jointly explained 41% of the variability. The sensitivity of that model in identifying patients with at least 10 respiratory events per hour of sleep was 90%, but its specificity was no more than 20% (Pillar et al., 1994). A later review concluded that using a combination of high-risk symptoms can identify only 30% of patients with at least 10 respiratory events per hour of sleep, and primarily identify patients with very severe disease having more than 40 events per hour (Chesson et al., 1997). Therefore, recording techniques are required to establish the diagnosis of OSA reliably.
Polysomnography (PSG) As stated above, once there is a clinical suspicion of sleep apnea, PSG is recommended, and is the gold standard for the diagnosis of the syndrome. This typically involves monitoring sleep state through the use of the electroencephalogram (EEG), bilateral electrooculogram (EOG), and submental electromyography (EMG). Airflow is monitored via either temperaturesensitive thermistors or a nasal pressure transducer. Respiratory effort is measured using chest and abdominal inductance plethysmography, piezo electrodes, or strain gauges. Other measures often include snoring (microphone or vibration), electrocadiogram, pulse oximetry, body position and anterior tibialis EMG. Whole-night PSG allows for a comprehensive assessment of sleep and respiration with an immediately available technician for detection and correction of technical problems. PSG outcomes provide an index of apnea severity in addition to the sleep quality measures. Apnea severity is provided by two measures: the apnea–hypopnea index (AHI), whch is defined as the total number of respiratory events divided by the hours of sleep, and oxygen desaturations. Generally, in adults AHI < 5, or in some laboratories AHI < 10, are considered normal. The mild apnea range includes 5, 10 < AHI < 20 and minimal oxygen saturation not lower than 85%, while the severe range includes AHI > 40 and/or minimal oxygen saturation lower than 65%. The range in between is considered of moderate severity. Although considered
385
the gold standard, the high cost of in-laboratory wholenight PSG, together with long waiting lists for sleep studies because of the relative scarcity of beds, has led to the commonly used procedure of “split night,” in which diagnosis and treatment trial are performed during the same night (Yamashiro and Kryger, 1995). During the first half of the night the patient sleeps for diagnostic purposes, and if the number of respiratory events reaches a certain threshold (usually 20/hour), the patient is awakened after 2 hours and is instrumented with a nasal continuous positive airway pressure (nCPAP) device for the rest of the night to determine the optimal treatment pressure. While theoretically this approach potentially saves time, there are several inherent limitations that should be recognized. First, frequently the diagnosis based on the first 2 hours of sleep is not accurate enough, particularly in patients having apneas exclusively during REM sleep (Rodway and Sanders, 2003). Second, the time remaining for the treatment trial is too short to allow proper CPAP pressure titration (Rodway and Sanders, 2003). This, in turn, can result in decreased patient satisfaction, decreased confidence in the treatment, and subsequently decreased compliance with treatment (Drake et al., 2003). Thus, this approach should be limited to certain types of patients, keeping in mind that it can potentially increase the portion of patients who remain untreated.
Ambulatory monitoring A different approach, developed in an attempt to beat the cost and long waiting lists for in-lab PSG, is to shift sleep studies from the sleep laboratory to patients’ homes using a variety of ambulatory sleep-monitoring systems. There is a variety of ambulatory devices ranging from a single-channel pulse oximetry monitor, to multichannel recorders that allow a full PSG in the patient’s home (e.g., Watch-PAT, Night-Watch, MESAM 4, Edentrace, and others). The American Academy of Sleep Medicine has classified sleep study systems into four categories: level 1 consists of inlaboratory attended standard PSG. Level 2 consists of unattended home sleep study with comprehensive portable devices incorporating the same channels as the inlab standard PSG. Level 3 comprises unattended devices, which measure at least four cardiorespiratory parameters, and level 4 embraces unattended devices recording one or two parameters (Chesson et al., 2003). While level 2 devices are relatively very accurate, they are complex and cumbersome. Level 4 devices, on the other hand, are frequently not accurate enough. Not included in this classification, however, are novel emerging technologies such as the handmounted Watch-PAT100/200 ambulatory system which
386
G. PILLAR AND P. LAVIE
monitors actigraphy, pulse rate, peripheral arterial tonometry, and oximetry (Bar et al., 2003). This device has been extensively validated for the diagnosis of sleep apnea (Bar et al., 2003; Hedner et al., 2004; Pittman et al., 2004) and detection of arousals from sleep (Pillar et al., 2003), and at the same time it has been shown to be a simple, easy-to-use device with a relatively low failure rate (Margel et al., 2004). It has been shown that the outcome of treatment following diagnosis with this device is very similar to that of full
PSG (Berry et al., 2003). The growing awareness of the clinical importance of sleep apnea and the increased demand for its diagnosis may change the common diagnostic practices in the future.
RISK FACTORS Specific risk factors Table 25.1 summarizes the most important recognized clinical risk factors for OSA.
Table 25.1 Risk factors for sleep apnea syndrome Risk factor
Comments
References
Decreased UAW size
Macroglossia, tonsils/adenoid hypertrophy, increased size of choana/uvula/soft/hard palate/lateral wall tissue, posterior position of the maxilla, inferior displacement of the hyoid bone
Obesity
Predominantly central obesity and increased neck circumference Increased airway length? Hormonal mechanism?
Brown et al., 1987; deBerry-Borowiecki et al., 1988; Hoffstein et al., 1991; Shepard et al., 1991; Morrison et al., 1993; Schwab et al., 1993, 2003; Shelton et al., 1993; Isono et al., 1997a; Jager et al., 1998; Schwab, 1998; Huang et al., 2000; Hsu, 2002; Faber and Grymer, 2003; Kamal, 2004 Wilcox et al., 1994; Brown, 2002; Schafer et al., 2002; Gami et al., 2003 White et al., 1985; Wilhoit and Suratt, 1987; Cistulli et al., 1994; Pillar et al., 1994, 1995, 2000; Millman et al., 1995; Popovic and White, 1995; Lee et al., 1997; Whittle et al., 1999; O’Donnell et al., 2000; Fogel et al., 2001b; Mohsenin, 2001, 2003; Kapsimalis and Kryger, 2002; Malhotra et al., 2002a; Jordan and McEvoy, 2003; Resta et al., 2003; Jordan et al., 2004 White et al., 1985; Ancoli-Israel et al., 1991; Krieger et al., 1997; Ware et al., 2000; Klawe and TafilKlawe, 2003; Malhotra et al., 2006 Redline et al., 1992, 1995; Guilleminault et al., 1995; Mathur and Douglas, 1995; Pillar and Lavie, 1995; Pillar et al., 1997; Desai et al., 2004 Cadieux et al., 1982; Hart et al., 1985; Kittle and Chaudhary, 1988; Main et al., 1988; Grunstein et al., 1991; Lin et al., 1992; Rosenow et al., 1994; Buyse et al., 1997; Kapur et al., 1998; Hira and Sibal, 1999; Hochban et al., 1999; Isono et al., 1999; Fatti et al., 2001; Resnick et al., 2003; Babu et al., 2005 Mendelson et al., 1981; Issa and Sullivan, 1982; Guilleminault et al., 1984; Remmers, 1984; Audenaert et al., 1995 Aldrich, 1990; Guilleminault et al., 1992; Resta et al., 2000; Ayas et al., 2001; Weinberg et al., 2003 Mendelson et al., 1990; Wadhwa et al., 1992; Weitzenblum et al., 1992; Langevin et al., 1993; Hallett et al., 1995; Radwan et al., 1995; Douglas, 1998; Hui et al., 2000; Larsson et al., 2001; Sharma et al., 2002
Male gender
Increased age
Unclear clinical significance in the elderly
Genetic
Multifactorial, two- to fourfold higher risk in first-degree relatives
Endocrine
Hypothyroidism, acromegaly, diabetes
Extrinsic
Alcohol, CNS depressants (hypnotics, narcotics)
Neuromuscular
Myopathies, muscular dystropies, neuromuscular disorders COPD, asthma, renal failure
Other illnesses
UAW, upper airway; CNS, central nervous system; COPD, chronic obstructive pulmonary disease.
OBSTRUCTIVE SLEEP APNEA: DIAGNOSIS, RISK FACTORS, AND PATHOPHYSIOLOGY 387 The most recognized risk factor for OSA is anato1996; Whittle et al., 1999; Schwab et al., 2003), mical narrowing of the upper airways. This has been decreased upper-airway muscle protective force due demonstrated over recent years by a variety of imaging to fatty deposits in the muscle (Ryan and Love, 1996; techniques (Shepard et al., 1991; Schwab, 1998; Faber Whittle et al., 1999; Carrera et al., 2004), and reduced and Grymer, 2003), such as computed tomography upper-airway size secondary to mass effect of the (CT) (Schwab et al., 1993), magnetic resonance imaging large abdomen on the chest wall and trachel traction (MRI) (Shelton et al., 1993; Schwab et al., 2003), acous(Hoffstein et al., 1984; Wheatley and Amis, 1998). This tic reflection technique (Brown et al., 1987; Huang latter mechanism emphasizes the great importance of et al., 2000; Kamal, 2004), endoscopy (Morrison central obesity as compared with peripheral obesity, et al., 1993; Isono et al., 1997a; Hsu, 2002), fluoroscopy since it is the abdomen much more than the thighs that (fluoroscopic MR; Jager et al., 1998), and cephalometaffects upper-airway size (Brown, 2002; Schafer et al., ric X-ray measurements (deBerry-Borowiecki et al., 2002). For these reasons, it has been clearly shown that 1988; Hoffstein et al., 1991). Most of these studies obesity is associated with increased upper-airway colagreed that patients with OSA have an anatomically lapsibility, which sometimes dramatically improves folnarrower airway, manifested in many potential ways, lowing massive weight reduction (Charuzi et al., 1985; such as enlarged tongue and/or soft palate, increased Schwartz et al., 1991; Fogel et al., 2003a). However, lateral-wall fatty tissue, inferior displacement of the obesity definitely cannot solely explain sleephyoid bone, shorter mandible bone, elongated face, disordered breathing since OSA is seen in nonobese inferior displacement of the mandibular body, postepatients and not every obese patient suffers from rior position of the maxilla, increased choanal size or OSA. Thus, obesity should be considered as a very nasal polyps, enlarged or elongated hard and/or soft important risk factor, but not as the single pathological palate, increased uvular size, reduced and/or change factor that causes OSA. in shape of the nasopharyngeal and/or oropharyngeal OSA occurs significantly more in men than women. and/or hypopharyngeal airway area. These narrower The ratio of men to women among OSA patients is as airways can result from congenital facial structure or high as 8:1 in sleep clinic populations (Guilleminault from acquired factors such as obesity and increased et al., 1988), and about 2–3:1 in community-based samfatty tissue around the upper airway. ples (Young et al., 1993; Redline et al., 1994). The reaAn anatomically compromised airway which is notasons for this gender effect in OSA remain poorly ble during wakefulness may worsen during sleep and understood but could result from a combination of reach a point of zero sectional area at the time of various pathophysiological factors, such as differences obstruction. However, since OSA is an exclusively in body fat distribution (or other gender-related uppersleep disorder, the airway does not obstruct during airway anatomy differences), control of ventilation, wakefulness, probably due to a successful compensaphysiology of the pharyngeal airway dilator muscles tory neuromuscular protective mechanism, which may activation, and hormonal differences (White et al., fail during sleep. Thus, sleep apnea results from a 1985; Wilhoit and Suratt, 1987; Cistulli et al., 1994; combination of both anatomical narrowing of the airPillar et al., 1994, 1995, 2000; Millman et al., 1995; ways and dysfunction of protective mechanisms. Popovic and White, 1995; Lee et al., 1997; Whittle Obesity is probably the most important acquired et al., 1999; O’Donnell et al., 2000; Fogel et al., clinical risk factor for the development of OSA in 2001b; Mohsenin, 2001, 2003; Kapsimalis and Kryger, adults. Some 60–90% of adults with OSA are over2002; Malhotra et al., 2002a; Jordan and McEvoy, weight, and the relative risk of sleep apnea from obe2003; Resta et al., 2003; Jordan et al., 2004). sity (body mass index > 29 kg/m2) may be as great The “male” type of obesity is commonly central, as as 10 or more (Wilcox et al., 1994; Brown, 2002; opposed to female peripheral obesity. This implies that, Schafer et al., 2002; Welch et al., 2002; Gami et al., even when controlled for potential confounders such 2003). Numerous studies have shown the development as age and body mass index, men experience an of OSA, or its worsening, with increasing weight, as increase in abdominal size as well as neck circumferopposed to substantial improvement with weight reducence and neck fat, which likely contributes to the male tion (Schwartz et al., 1991; Loube et al., 1994; Wilcox predisposition to OSA (Whittle et al., 1999). Indeed, et al., 1994; Monteforte and Turkelson, 2000; Brown, when upper-airway lumen size was assessed it was 2002; Fisher et al., 2002; Schafer et al., 2002; Gami reported to be somewhat smaller in women (Lee et al., 2003). There are probably several mechanisms et al., 1997; Mohsenin, 2001), although not in all studies responsible for the increased risk of OSA with obesity. (Mohsenin, 2003; Schwab et al., 2003). More imporThese include reduced lumen size due to fatty tissue tantly, men have a longer airway when compared to within the airway or in its lateral walls (Ryan and Love, women, even after correction for body height
388
G. PILLAR AND P. LAVIE
(Malhotra et al., 2002a). Since the collapsibility of a collapsible tube is strongly inversely related to its length, this can be a very dominant mechanistic explanation for the male predominance in OSA. Regardless of the exact anatomical explanation, the compromised anatomy of the male upper airway may result in increased resistance and subsequently OSA (White et al., 1985; Trinder et al., 1997; Mohsenin, 2003). The possible role of central gender-related differences in control of ventilation as contributors to the differences in the prevalence of OSA is unclear (Pillar et al., 2000; Behan et al., 2002; Jordan et al., 2002, 2004). The observation that in women OSA becomes particularly prevalent after menopause (Wilhoit and Suratt, 1987; Resta et al., 2003), and that medroxyprogesterone administration to patients with OSA resulted in substantial improvement (Cistulli et al., 1994; Collop, 1994; Smith and Quinnell, 2004), has suggested the possible role of sex hormones in the control of breathing. Evidence that blood levels of testosterone were correlated with apnea severity in women with polycystic ovary syndrome (Fogel et al., 2001b) supported this notion. Thus, while progesterone has the potential to activate upper-airway-protecting dilator muscle activation, testosterone probably inhibits their activation and may contribute to the gender-related difference in the prevalence of sleep apnea. OSA is probably most intimidating during middle age. The natural history of OSA is not fully known, but it probably begins as several years of just loud snoring, then gradually over a period of several years cessations of breathing and symptoms of excessive sleepiness develop, and thereafter may remain stable or worsen with weight gain (Sforza et al., 1994; Fisher et al., 2002). Others, however, have reported that mild to moderate OSA has a tendency to worsen in the absence of significant weight gain and that upperairway anatomy and clinical variables did not appear to be useful in predicting the progression of the syndrome (Pendlebury et al., 1997). The explanation for this aging increase in the prevalence of OSA remains unknown, although several potential mechanisms have been proposed. Age was reported to correlate with pharyngeal resistance in men but not in women (White et al., 1985). Age was also reported to be associated with a decrement in respiratory effort during an obstruction (Krieger et al., 1997), and in protecting genioglossus muscle activation (Klawe and Tafil-Klawe, 2003). Extensive studies of the underlying anatomical and pathophysiological mechanisms which may lead to increased OSA with age revealed that older people had a poorer responsiveness of pharyngeal dilator muscles to negative pressure stimuli than did younger subjects (Malhotra et al., 2006). In
addition, anatomical changes associated with aging included increased parapharyngeal fat pad size and an increase in pharyngeal airway length in women but not in men. Genetic factors are clearly important as well. We (Pillar and Lavie, 1995), and others (Redline et al., 1992; Guilleminault et al., 1995; Desai et al., 2004), have shown that sleep-disordered breathing clusters in families. The relative risk of OSA may be two- to fourfold greater in first-degree relatives of OSA patients. As much as 40% of the variance in AHI may be accounted for by genetic factors, and these familial factors remain significant after adjustment for body mass index and cephalometric measurements (Redline et al., 1995). Furthermore, we have shown that healthy offspring of OSA patients responded to inspiratory resistive loadings with greater decrease in ventilation than controls (Pillar et al., 1997). Whether this was due to inherited compromised upperairway anatomy or another mechanism (i.e., inherited control of breathing characteristics, or local reflex ones) was unclear. However, we speculated that the decreased tolerance to inspiratory resistive loading might predispose those OSA offspring to develop OSA later on in life.
Other risk factors Several endocrinological pathologies (in addition to the sex hormones discussed above) may also predispose to OSA. These include predominantly hypothyroidism, acromegaly, and diabetes. Hypothyroidism can result in increased body weight, central obesity, and reduced upper-airway muscle strength, which may explain the high prevalence of OSA among hypothyroid patients (Kittle and Chaudhary, 1988; Lin et al., 1992; Kapur et al., 1998; Hira and Sibal, 1999). Furthermore, treating patients with hypothyroidism and OSA with thyroxine may alleviate or even cure their sleep-disordered breathing (Rajagopal et al., 1984; Lin et al., 1992; Hira and Sibal, 1999). Excess of growth hormone which leads to acromegaly is also known to be associated with sleep apnea syndrome (Cadieux et al., 1982; Hart et al., 1985; Main et al., 1988; Grunstein et al., 1991; Rosenow et al., 1994; Buyse et al., 1997; Hochban et al., 1999; Isono et al., 1999; Fatti et al., 2001). The exact mechanism, however, is not fully understood. Studying the collapsibility of passive pharynx in patients with acromegaly, Isono et al. (1999) concluded that anatomic abnormality, especially at the base of the tongue, appears to play a significant role in the development of sleep-disordered breathing in acromegaly. This is partially supported by craniofacial studies (Hochban et al., 1999). On the other hand, sleep apnea commonly normalizes with treatment of acromegaly, even before local anatomical changes at
OBSTRUCTIVE SLEEP APNEA: DIAGNOSIS, RISK FACTORS, AND PATHOPHYSIOLOGY the upper-airway level are noticeable (Cadieux et al., 1982; Hart et al., 1985; Leibowitz et al., 1994; Buyse et al., 1997). Furthermore, it appears that central sleep apnea is also very common in acromegaly, which raises the possibility that altered respiratory control is involved in producing sleep apnea in acromegaly (Grunstein et al., 1991). Another important pathology which closely relates to OSA is diabetes, although the exact relationships between the conditions are rather complicated. On the one hand, OSA can result in diabetes by increasing insulin resistance, which improves with nCPAP therapy (Babu et al., 2005). On the other hand, diabetes can result in changes in the central ventilatory control system that can lead to periodic breathing (Resnick et al., 2003). Furthermore, the association between sleep apnea and diabetes is strongly affected by many confounders, most importantly, obesity, and therefore the clear net effect of sleep apnea and diabetes on each other is not that obvious (Sanders and Givelber, 2003). Nevertheless, diabetes is common in OSA and OSA is common in diabetes, regardless of the exact mechanism linking them together. The risk of sleep apnea also increases with the use of substances and medications which weaken upperairway dilator muscle activation. These include alcohol (Issa and Sullivan, 1982; Remmers, 1984), central nervous system depressants such as benzodiazepines (Mendelson et al., 1981; Guilleminault et al., 1984), and barbiturates (Audenaert et al., 1995). Similarly, neuromuscular diseases such as myopathies, muscular dystrophies, spinal cord injuries, and other neuromuscular disorders (Aldrich, 1990; Guilleminault et al., 1992; Short et al., 1992; Resta et al., 2000; Ayas et al., 2001; Weinberg et al., 2003), can change the balance between collapsing and stabilizing forces of the airways and can result in increased upper-airway collapsibility and consequently OSA. Finally, there are some specific diseases that, when they coexist with sleep apnea, exacerbate its severity. The most important of these are chronic obstructive pulmonary disease (COPD), asthma, and renal failure. Sleep has effects on breathing, including changes in respiratory control, airway resistance, and muscular contractility. These sleep-related modifications in the respiratory system do not induce adverse effects in healthy subjects, but may cause problems in patients with COPD. Hypoventilation causes the most important gas exchange alteration during sleep in COPD patients, leading to hypercapnia and hypoxemia, especially during rapid eye movement (REM) sleep. Blood gas alterations lead to increased arousals, sleep disruption, and pulmonary hypertension (Fanfulla et al., 2004). Similarly, nocturnal worsening of asthma, which
389
can result from sleep or circadian effects, is a common manifestation of this disease that indicates increased disease severity. Potential mechanisms which associate COPD/asthma and sleep apnea include decreased ventilatory responsiveness to hypercapnia, reduced respiratory muscle output, and marked increases in upper-airway resistance (potentially secondary to allergy, inflammation, and congestion). Thus, in some cases of COPD/asthma, OSA coexists (overlap syndrome), and is usually of greater severity (Weitzenblum et al., 1992; Radwan et al., 1995; Douglas, 1998; Larsson et al., 2001; Sharma et al., 2002). It is well established that sleep apnea is more common in patients with renal failure (Mendelson et al., 1990; Wadhwa et al., 1992; Langevin et al., 1993; Hallett et al., 1995; Hui et al., 2000). The exact mechanism is still not fully understood, but can potentially be affected by edema, which may be seen in patients with renal failure. In addition, abnormalities in respiratory control mechanisms from chronic hypocarbia, metabolic acidosis, and uremic toxins have been blamed for this association in patients with chronic renal failure. Hypertension may play a role as well. Interestingly, although apnea severity did not change much following dialysis (Mendelson et al., 1990), OSA was almost completely resolved after kidney transplantation (Langevin et al., 1993). The association between OSA and renal failure is further complicated by reports of improved renal function following treatment with CPAP to the respiratory disorder (Krieger et al., 1988; Zhang et al., 1997). In this context, several factors associated with OSA can contribute to progressive renal dysfunction in these patients. These include predominantly hypertension, hypoxemia, and increased sympathetic nerve activity. Thus, although the exact relationships between these two diseases need to be better understood, renal failure is considered a potential risk factor for sleep apnea and some researchers and clinicians even proposed that patients with chronic renal failure should be screened for sleep apnea.
PATHOPHYSIOLOGY The pathogenesis of OSA has been the subject of intense research activity in recent years. Research has focused on the neurochemical and physiological changes that occur at sleep onset leading to the loss of muscle activity and diminished reflex pharyngeal control and a loss of the neuromuscular compensation present during wakefulness, resulting in pharyngeal collapse. Characteristics of the central respiratory centers (ventilatory control instability) and arousal threshold may play a role as well.
390
G. PILLAR AND P. LAVIE
Pharyngeal anatomy As discussed above, the majority of the evidence supporting an anatomic abnormality in adult OSA patients is derived from imaging and endoscopic studies. Haponik et al. (1983) originally reported a substantially smaller minimal pharyngeal cross-sectional airway area in sleep apnea patients compared to controls when imaged during wakefulness, although the groups were not controlled for weight. Since this original report, several authors, using a variety of imaging techniques (CT, MRI, acoustic reflection, cephalometrics), have demonstrated a small pharyngeal airway in sleep apnea patients, with the smallest airway luminal size generally occurring at the level of the velopharynx (behind the soft palate) in both patients and controls (Abbey et al., 1989; Hoffstein et al., 1991; Schwab et al., 1993, 2003; Jager et al., 1998; Morrell et al., 1998; Schwab, 1998; Whittle et al., 1999; Ciscar et al., 2001; Ikeda et al., 2001; Sanner et al., 2002; Macey et al., 2003). However, these studies suffer from two important limitations. First, they have focused, for the most part, on airway luminal size with little attention to airway soft-tissue structures and characteristics. Second, during wakefulness, airway luminal size does not reflect pure anatomy, but rather the interaction between anatomy and muscle activation, as stated above. Therefore, the information available on the determinants of upper-airway anatomy is somewhat limited. The most convincing evidence supporting functional abnormality in OSA patients comes from Isono et al. (1997a, b). These authors measured the critical pressure (Pcrit) required to close (completely collapse) the upper airway of humans undergoing general anesthesia with complete neuromuscular paralysis. Under the condition of absent neuromuscular activity, the authors observed a positive Pcrit in OSA patients, meaning that the airway was collapsed at atmospheric pressure and required positive pressure to reopen (Isono et al., 1997b). Normal controls, on the other hand, had patent airways at atmospheric pressure and required suction (negative pressure) to collapse the pharynx. This observation strongly supports the existence of a biomechanical abnormality of the upper airway in sleep apnea patients. In addition, the authors showed a strong correlation between Pcrit and the oxygen desaturation index, indicating a clear relationship between airway anatomy and apnea severity. Endoscopic evaluation also demonstrated a larger cross-sectional area of the velopharynx in controls compared to apneics, again suggesting deficient anatomy in the apnea patients (Isono et al., 1997b). One possible limitation of this otherwise unique and persuasive study is the potential development of atelectasis and reduced lung volume
under conditions of anesthesia and hyperoxia. Lung volume can have a substantial influence on upper-airway size, especially in apneics (Hoffstein et al., 1984). In addition to airway size, airway shape may also be an important determinant of upper-airway collapsibility. Several studies have reported an oval shape of the pharyngeal airway in individuals with OSA when compared to controls (i.e., a relatively high anteroposterior/lateral luminal airway dimension) (Horner et al., 1989; Rodenstein et al., 1990). Leiter (1996) has also suggested a reduced ability of muscles to dilate the pharynx when it is oval in shape. Whether it represents an important component of apnea pathogenesis, or is simply a marker of fat deposition in the fat pads lateral to the airway, remains to be elucidated. Finally, the soft tissues surrounding the upper airway may have an independent role. Using sophisticated analyses of soft-tissue variables, sleep apnea patients were shown to have increased thickness of the lateral pharyngeal walls, independent of fat pad thickness (at the level of the minimum axial airway lumen) (Schwab et al., 1993; Schwab, 1998, 2005; Whittle et al., 1999; Ciscar et al., 2001). This finding is helpful in explaining the reduced lateral diameter of the airway lumen in apneics as compared to weight-matched controls. No important skeletal differences were observed, implicating soft tissues as the major anatomic difference between apneics and nonapneic controls. Schwab et al. (1993) and Schwab (1998) have argued therefore that lateral wall thickening and ultimately collapse are important components in the pathogenesis of OSA in adults. The measurement of an upper airway Pcrit during sleep (not anesthesia) is increasingly appreciated as a useful measure of an individual’s propensity or vulnerability to pharyngeal collapse (Issa and Sullivan, 1984a, b; Smith et al., 1988; Schwartz et al., 1989; Jordan et al., 2005). Indeed, OSA patients often require positive pressure to maintain airway patency during sleep (i.e., positive Pcrit, needed for nCPAP therapy during sleep). Patients with mild disease or simple snoring tend to have a slightly negative Pcrit whereas normal controls have a substantially negative Pcrit (–10 to – 15 cmH2O) (Schwartz et al., 1988, 1989; Sforza et al., 1999). These Pcrit measurements, which reflect both anatomy and neuromuscular activity, also support an upper-airway anatomic abnormality among patients with OSA (Schwartz et al., 1988, 1989; Smith et al., 1988; Gleadhill et al., 1991; Sforza et al., 1999).
Role of pharyngeal muscles Three groups of muscles have been investigated in the context of pathogenesis of sleep apnea: (1) the muscles influencing hyoid bone position (geniohyoid,
OBSTRUCTIVE SLEEP APNEA: DIAGNOSIS, RISK FACTORS, AND PATHOPHYSIOLOGY sternohyoid); (2) the muscle of the tongue (genioglossus); and (3) the muscles of the palate (tensor palatini, levator palatini). The activity of many of these muscles is increased during inspiration, thus stiffening and dilating the upper airway and by that counteracting the collapsing influence of negative airway pressure (van Lunteren and Strohl, 1986). These are referred to as inspiratory dilator phasic upper-airway muscles. The genioglossus is the best-studied such muscle. The activity of the genioglossus is substantially reduced (although not eliminated) during expiration when pressure inside the airway becomes positive and there is less tendency for collapse. Other muscles, such as the tensor palatini, do not consistently demonstrate inspiratory phasic activity but instead maintain a relatively constant level of activity throughout the respiratory cycle (Tangel et al., 1991). These are called tonic or postural muscles, and are also thought to play a role in the maintenance of airway patency. These two types of pharyngeal muscles are likely controlled by groups of neurons within the brainstem that have different firing patterns relative to the respiratory cycle. The activity of the pharyngeal dilator muscles can be influenced during wakefulness by a number of physiological stimuli. Chemical stimulation (rising PaCO2 or falling PaO2) can substantially augment the activity of these muscles (Onal et al., 1981a, b). Perhaps more importantly, negative pressure in the pharynx (which would tend to collapse the airway) markedly activates these muscles which in turn counteract this collapsing influence (Fogel et al., 2000; Malhotra et al., 2000, 2001a, 2002b; Pillar et al., 2001a; Berry et al., 2003). This response to negative pressure is likely driven by topical, pressure, or stretch-sensitive receptors, as it can be substantially attenuated by the application of topical anesthesia (Fogel et al., 2000). It is this receptor mechanism that is likely activated in an individual with an anatomically small airway in response to greater negative pressure, airway stretch, or collapse itself. In patients with sleep apnea who have an anatomically small airway, this negative-pressure reflex is substantially activated during wakefulness, leading to augmented dilator muscle activity as a neuromuscular compensatory mechanism to protect the airways. The genioglossus muscle in sleep apnea patients functions at nearly 40% of its maximum capacity during wakefulness, while in control subjects the muscle functions at only about 12% of maximum (Mezzanotte et al., 1992). That negative pressure drives this augmented muscle activity is suggested by the observation that nCPAP can reduce the level of activity in the genioglossus muscle of sleep apnea patients to near-normal levels (Mezzanotte et al., 1992). Thus, were it not for this increased activity of the pharyngeal dilator
391
muscles, the airway of the sleep apnea patient would substantially narrow or collapse, even during wakefulness. Therefore, the individual’s propensity for upperairway collapse during sleep depends on two variables: (1) predisposing anatomy; and (2) the level of pharyngeal dilator muscle activity. The effect of sleep on upper-airway muscle activity probably plays an important role in the pathophysiology of OSA. The activity of tonic pharyngeal muscles such as the tensor palatini is markedly reduced during NREM sleep (to 20–30% of awake values) while phasic muscles generally maintain waking levels of activity (Tangel et al., 1992). This fall in tonic muscle activity conceivably contributes to the observed increments in airflow resistance commonly seen in normal individuals with the transition from wakefulness to sleep. Phasic muscle activity, on the other hand, remains stable or even slightly increases in normal subjects in sleep in comparison with wakefulness (Tangel et al., 1992; Wheatley et al., 1993a, b). However, the protective reflex activation of these muscles which can be observed during wakefulness is markedly diminished during sleep. This reflex-driven augmentation of dilator muscle activity compensates for deficient anatomy in apnea patients during wakefulness. During sleep, there is a marked attenuation or loss of this reflex mechanism, even in normal subjects. Using a model of passive negative pressure ventilation, a tight relationship between varying intrapharyngeal negative pressures and genioglossal muscle activation during wakefulness has been shown both in controls and in sleep apnea patients (Fogel et al., 2001a). Using the same model, it has been found that the stable relationship between negative epiglottic pressure and genioglossal EMG was markedly reduced during sleep while ventilated with negative pressure (Fogel et al., 2003b), or with inspiratory resistive loading (Malhotra et al., 2001b). This was associated with a markedly higher pharyngeal airflow resistance during sleep. At the transition from wakefulness to sleep there was also a greater reduction in peak genioglossal EMG. Thus, while the negative pressure reflex is able to maintain genioglossal EMG during wakefulness, this reflex is unable to do so during sleep. Furthermore, it has been shown that the strong dependency of the dilator muscle activation on CO2 that is seen during wakefulness is substantially diminished during either stage 2 or slowwave sleep (Pillar et al., 2001b). Thus, the loss of the negative pressure reflex protecting mechanism with the reduced dependency of dilator muscle activation on negative pressure and rising CO2 leads to falling dilator muscle activity and airway collapse (Wheatley et al., 1993a, b; Malhotra et al., 2001a, 2002b; Pillar et al., 2001b; Fogel et al., 2003c).
392
G. PILLAR AND P. LAVIE
The finding that the protective genioglossal activation is almost completely lost during REM sleep may help understand why apnea worsens during REM in most OSA patients (Shea et al., 1999). Interestingly, it has been shown that a fall in genioglossal EMG was seen during sleep onset followed by subsequent muscle recruitment in the third to fifth breaths following the transition from alpha to theta EEG activities. It has been suggested that the initial sleep-onset reduction in upper-airway muscle activity is due to loss of a wakefulness stimulus, rather than to loss of responsiveness to negative pressure, and that this wakefulness stimulus may be greater in the OSA patient than in healthy controls (Fogel et al., 2005). This finding emphasizes the potential role of the arousal/awakening stimuli and the potential importance of other central nervous mechanisms in the patophysiology of sleep apnea.
Ventilatory control instability (loop gain) and arousal effects It has been argued that an intrinsic instability of the ventilatory control mechanisms leads to variable activity in the diaphragm and the pharyngeal muscles, resulting in airway collapse (Onal et al., 1986). Others have suggested that a “mismatch” in the timing of activation of the diaphragm and pharyngeal muscles renders the pharyngeal airway susceptible to collapse during sleep. Thus, if the diaphragm is activated before the upper-airway muscles, then negative pressure would develop in the pharynx at a time when the airway was relatively unprotected. Such alterations in the timing of the pharyngeal muscles relative to the diaphragm have been demonstrated in apneics in one study but it is unclear if this is a primary abnormality (Hudgel and Harasick, 1990). Younes et al. (2001) studied 32 patients with OSA (12 severe) during sleep while their upper airway was stabilized with continuous positive airway pressure. Susceptibility to periodic breathing was assessed by gradually increasing controller gain, using proportional assisted ventilation. Nine of 12 patients with severe OSA developed periodic breathing, with recurrent central apneas, compared with only 6 of the 20 patients in the mild/moderate group. The authors concluded that the chemical control system is less stable in patients with severe OSA than in patients with milder OSA, and speculated that this may contribute to the severity of OSA (Younes et al., 2001). In a later study, loop gain magnitudes were found to be similar in 6 OSA and 5 normal subjects, but the chemoreflex loop impulse response in the OSA patients exhibited faster and more oscillatory dynamics, implying unstable upper-airway mechanics and an underdamped chemoreflex control system (Asyali
et al., 2002). This may be another important factor that promotes the occurrence of periodic obstructive apneas during sleep, although studies failed to relate the higher susceptibility to OSA seen in men or with increasing age to this ventilatory control instability mechanism (Browne et al., 2003; Wellman et al., 2003; Jordan et al., 2005). However, in vulnerable patients with collapsible airway (closing pressure near atmospheric pressure), loop gain may have a substantial impact on apnea severity (Wellman et al., 2004). Once the patient with apnea falls asleep and the cycle of repetitive airway obstruction begins, recurrent hypoxemia and hypercapnia develop. The rate at which these chemical disturbances evolve is related to a number of factors, including: (1) the PaO2 and PaCO2 at which the apnea starts; (2) the individual oxygen stores, which relate to lung volume; and (3) whether there is continued effort during the apnea (Bradley et al., 1985). The severity of hypoxemia and hypercapnia is also dependent on apnea length. Termination of the apnea generally requires a transient arousal from sleep, thus activating the upper-airway muscles and reestablishing airway patency. Without such an arousal profound hypoxemia and hypercapnia would likely ensue. The possible mechanisms leading to arousal include direct stimulation of peripheral and central chemoreceptors by rising PaCO2 and falling PaO2, afferent central nervous system input from the lung, chest wall, or upper-airway receptors resulting from the increasing ventilatory effort that develops over the course of an apnea, or direct stimulation of the reticular activating system by respiratory neurons activated during the apnea (Gleeson et al., 1989, 1990). Regardless of the exact route by which apneas are terminated, arousal remains an important mechanism that prevents asphyxia, but at the same time arousals may increase the severity of the sleepdisordered breathing by promoting greater ventilatory instability (Younes, 2004). In summary, the principal abnormality in OSA is an anatomically small pharyngeal airway. During wakefulness the individual is able to compensate for the deficient anatomy, by increasing the activity of upper-airway muscles which maintain airway patency. However, with sleep onset, this compensation is lost and airway collapse occurs. The physiological consequences of apnea are a rise in PaCO2, a fall in PaO2, and increasing ventilatory effort against an occluded airway. Ultimately, transient arousal from sleep occurs, which reestablishes the airway and ventilation. The individual subsequently returns to sleep and the cycle begins again, to be repeated frequently over the course of the night. Figure 25.1 summarizes the balance of forces which result in upper-airway patency or collapse. Inspiratory negative pressure, anatomically
OBSTRUCTIVE SLEEP APNEA: DIAGNOSIS, RISK FACTORS, AND PATHOPHYSIOLOGY
393
Promotion of airway patency
Promotion of airway collapse Negative pressure on inspiration
Pharyngeal dilator muscle contraction (genioglossus)
Extraluminal positive pressure Fat deposition Small mandible Lung volume (longitudinal traction)
Fig. 25.1. The balance of forces. Inspiratory negative pressure, anatomically narrow airway, and extraluminal positive pressure tend to promote pharyngeal collapse. Upper-airway dilator muscle and increased lung volume tend to maintain pharyngeal patency. (Reproduced from Malhotra and White (2002), with permission.)
narrow airway, and extraluminal positive pressure tend to promote pharyngeal collapse. Upper-airway dilator muscle and increased lung volume tend to maintain pharyngeal patency (Malhotra and White, 2002).
SUMMARY OSA syndrome is a disorder characterized by repetitive episodes of upper-airway obstruction that occur during sleep, usually associated with a reduction in blood oxygen saturation and characteristic complaints such as excessive daytime sleepiness and chronic fatigue. The diagnosis is typically confirmed by overnight PSG or ambulatory monitoring, during which sleep is recorded while breathing, respiratory effort, oxygen saturation, and the electrocardiogram are simultaneously monitored. Upper-airway obstruction can be complete, in which case there is no airflow (obstructive apnea), or partial, during which there is a substantial reduction in, but not a complete cessation of airflow (obstructive hypopnea). The severity of the syndrome is indexed by the AHI – the average number of apneas plus hypopneas per hour of sleep. OSA is a prevalent syndrome, affecting 4% and 2% of adult men and women, respectively, and its prevalence is considerably higher in specific patient groups. The prevalence of disordered breathing in sleep regardless of symptoms is sixfold higher than that of OSA. The most important risk factors for OSA are decreased upper-airway size, obesity, male gender, age, certain diseases, and substances that affect upper-airway tone. Genetic factors also appear to play a role, as the syndrome was shown to cluster in families. Extensive research has shown that the
principal abnormality in OSA is a biomechanical one. While during wakefulness sleep apnea patients are able to compensate for their deficient airways anatomy by increasing the activity of upper-airway muscles which maintain airway patency, during sleep this compensation is lost and airway collapse occurs. The physiological consequences of apnea are a rise in PaCO2, a fall in PaO2, and increasing ventilatory effort against an occluded airway. Ultimately, transient arousal from sleep occurs, which reestablishes the airway and ventilation.
REFERENCES Abbey NC, Block AJ, Green D et al. (1989). Measurement of pharyngeal volume by digitized magnetic resonance imaging. Effect of nasal continuous positive airway pressure. Am Rev Respir Dis 140: 717–723. Aldrich MS (1990). Neurologic aspects of sleep apnea and related respiratory disturbances. Otolaryngol Clin North Am 23: 761–769. Ambrogetti A, Olson LG, Saunders NA (1991). Differences in the symptoms of men and women with obstructive sleep apnoea. Aust N Z J Med 21: 863–866. Ancoli-Israel S, Kripke DF, Mason W (1987). Characteristics of obstructive and central sleep apnea in the elderly: an interim report. Biol Psychiatry 22: 741–750. Ancoli-Israel S, Kripke DF, Klauber MR et al. (1991). Sleepdisordered breathing in community-dwelling elderly. Sleep 14: 486–495. Andreas S, Schulz R, Werner GS et al. (1996). Prevalence of obstructive sleep apnoea in patients with coronary artery disease. Coron Artery Dis 7: 541–545. Asyali MH, Berry RB, Khoo MC (2002). Assessment of closed-loop ventilatory stability in obstructive sleep apnea. IEEE Trans Biomed Eng 49: 206–216.
394
G. PILLAR AND P. LAVIE
Audenaert SM, Montgomery CL, Thompson DE et al. (1995). A prospective study of rectal methohexital: efficacy and side effects in 648 cases. Anesth Analg 81: 957–961. Ayas NT, Epstein LJ, Lieberman SL et al. (2001). Predictors of loud snoring in persons with spinal cord injury. J Spinal Cord Med 24: 30–34. Babu AR, Herdegen J, Fogelfeld L et al. (2005). Type 2 diabetes, glycemic control, and continuous positive airway pressure in obstructive sleep apnea. Arch Intern Med 165: 447–452. Bar A, Pillar G, Dvir I et al. (2003). Evaluation of a portable device based on peripheral arterial tone for unattended home sleep studies. Chest 123: 695–703. Bassetti CL (2005). Sleep and stroke. Semin Neurol 25: 29–32. Behan M, Zabka AG, Mitchell GS (2002). Age and gender effects on serotonin-dependent plasticity in respiratory motor control. Respir Physiol Neurobiol 131: 65–77. Berry RB, White DP, Roper J et al. (2003). Awake negative pressure reflex response of the genioglossus in OSA patients and normal subjects. J Appl Physiol 94: 1875–1882. Bixler EO, Kales A, Soldatos CR et al. (1982). Sleep apneic activity in a normal population. Res Commun Chem Pathol Pharmacol 36: 141–152. Bradley TD, Martinez D, Rutherford R et al. (1985). Physiological determinants of nocturnal arterial oxygenation in patients with obstructive sleep apnea. J Appl Physiol 59: 1364–1368. Brown LK (2002). A waist is a terrible thing to mind: central obesity, the metabolic syndrome, and sleep apnea hypopnea syndrome. Chest 122: 774–778. Brown IB, McClean PA, Boucher R et al. (1987). Changes in pharyngeal cross-sectional area with posture and application of continuous positive airway pressure in patients with obstructive sleep apnea. Am Rev Respir Dis 136: 628–632. Browne HA, Adams L, Simonds AK et al. (2003). Ageing does not influence the sleep-related decrease in the hypercapnic ventilatory response. Eur Respir J 21: 523–529. Buyse B, Michiels E, Bouillon R et al. (1997). Relief of sleep apnoea after treatment of acromegaly: report of three cases and review of the literature. Eur Respir J 10: 1401–1404. Cadieux RJ, Kales A, Santen RJ et al. (1982). Endoscopic findings in sleep apnea associated with acromegaly. J Clin Endocrinol Metab 55: 18–22. Caples SM, Gami AS, Somers VK (2005). Obstructive sleep apnea. Ann Intern Med 142: 187–197. Carrera M, Barbe F, Sauleda J et al. (2004). Effects of obesity upon genioglossus structure and function in obstructive sleep apnoea. Eur Respir J 23: 425–429. Charuzi I, Ovnat A, Peiser J et al. (1985). The effect of surgical weight reduction on sleep quality in obesity-related sleep apnea syndrome. Surgery 97: 535–538. Chesson AL Jr., Ferber RA, Fry JM et al. (1997). The indications for polysomnography and related procedures. Sleep 20: 423–487.
Chesson AL Jr., Berry RB, Pack A (2003). Practice parameters for the use of portable monitoring devices in the investigation of suspected obstructive sleep apnea in adults. Sleep 26: 907–913. Cirignotta F, D’Alessandro R, Partinen M et al. (1989). Prevalence of every night snoring and obstructive sleep apnoeas among 30–69-year-old men in Bologna, Italy. Acta Neurol Scand 79: 366–372. Ciscar MA, Juan G, Martinez V et al. (2001). Magnetic resonance imaging of the pharynx in OSA patients and healthy subjects. Eur Respir J 17: 79–86. Cistulli PA, Barnes DJ, Grunstein RR et al. (1994). Effect of short-term hormone replacement in the treatment of obstructive sleep apnoea in postmenopausal women. Thorax 49: 699–702. Collop NA (1994). Medroxyprogesterone acetate and ethanolinduced exacerbation of obstructive sleep apnea. Chest 106: 792–799. deBerry-Borowiecki B, Kukwa A, Blanks RH (1988). Cephalometric analysis for diagnosis and treatment of obstructive sleep apnea. Laryngoscope 98: 226–234. Derderian SS, Bridenbaugh RH, Rajagopal KR (1988). Neuropsychologic symptoms in obstructive sleep apnea improve after treatment with nasal continuous positive airway pressure. Chest 94: 1023–1027. Desai AV, Cherkas LF, Spector TD et al. (2004). Genetic influences in self-reported symptoms of obstructive sleep apnoea and restless legs: a twin study. Twin Res 7: 589–595. Douglas NJ (1998). Sleep in patients with chronic obstructive pulmonary disease. Clin Chest Med 19: 115–125. Drachman DB, Gumnit RJ (1962). Periodic alteration of consciousness in the ‘pickwickian’ syndrome. Arch Neurol 6: 63–69. Drake CL, Day R, Hudgel D et al. (2003). Sleep during titration predicts continuous positive airway pressure compliance. Sleep 26: 308–311. El-Ad B, Lavie P (2005). Effect of sleep apnea on cognition and mood. Int Rev Psychiatry 17: 277–282. Faber CE, Grymer L (2003). Available techniques for objective assessment of upper airway narrowing in snoring and sleep apnea. Sleep Breath 7: 77–86. Fanfulla F, Cascone L, Taurino AE (2004). Sleep disordered breathing in patients with chronic obstructive pulmonary disease. Minerva Med 95: 307–321. Fatti LM, Scacchi M, Pincelli AI et al. (2001). Prevalence and pathogenesis of sleep apnea and lung disease in acromegaly. Pituitary 4: 259–262. Fisher D, Pillar G, Malhotra A et al. (2002). Long-term follow-up of untreated patients with sleep apnoea syndrome. Respir Med 96: 337–343. Fletcher EC, DeBehnke RD, Lovoi MS et al. (1985). Undiagnosed sleep apnea in patients with essential hypertension. Ann Intern Med 103: 190–195. Fogel RB, Malhotra A, Shea SA et al. (2000). Reduced genioglossal activity with upper airway anesthesia in awake patients with OSA. J Appl Physiol 88: 1346–1354. Fogel RB, Malhotra A, Pillar G et al. (2001a). Genioglossal activation in patients with obstructive sleep apnea versus
OBSTRUCTIVE SLEEP APNEA: DIAGNOSIS, RISK FACTORS, AND PATHOPHYSIOLOGY control subjects. Mechanisms of muscle control. Am J Respir Crit Care Med 164: 2025–2030. Fogel RB, Malhotra A, Pillar G et al. (2001b). Increased prevalence of obstructive sleep apnea syndrome in obese women with polycystic ovary syndrome. J Clin Endocrinol Metab 86: 1175–1180. Fogel RB, Malhotra A, Dalagiorgou G et al. (2003a). Anatomic and physiologic predictors of apnea severity in morbidly obese subjects. Sleep 26: 150–155. Fogel RB, Trinder J, Malhotra A et al. (2003b). Within-breath control of genioglossal muscle activation in humans: effect of sleep–wake state. J Physiol 550: 899–910. Fogel RB, White DP, Pierce RJ et al. (2003c). Control of upper airway muscle activity in younger versus older men during sleep onset. J Physiol 553: 533–544. Fogel RB, Trinder J, White DP et al. (2005). The effect of sleep onset on upper airway muscle activity in patients with sleep apnoea versus controls. J Physiol 564: 549–562. Formiguera X, Canton A (2004). Obesity: epidemiology and clinical aspects. Best Pract Res Clin Gastroenterol 18: 1125–1146. Franceschi M, Zamproni P, Crippa D et al. (1982). Excessive daytime sleepiness: a 1-year study in an unselected inpatient population. Sleep 5: 239–247. Gami AS, Caples SM, Somers VK (2003). Obesity and obstructive sleep apnea. Endocrinol Metab Clin North Am 32: 869–894. Gastaut H, Tassinari CA, Duron B (1966). Polygraphic study of the episodic diurnal and nocturnal (hypnic and respiratory) manifestations of the Pickwick syndrome. Brain Res 1: 167–186. Gerardy W, Herberg D, Kuhn HM (1960). Vergleichende Untersuchungen der Lungenfunktion und des Elektroencephalogramms bi zwei Patienten mit PickwickianSyndrom. Z Klin Med 156: 362–380. Gislason T, Taube A (1987). Prevalence of sleep apnea syndrome – estimation by two stage sampling. Ups J Med Sci 92: 193–203. Gislason T, Janson C, Vermeire P et al. (2002). Respiratory symptoms and nocturnal gastroesophageal reflux: a population-based study of young adults in three European countries. Chest 121: 158–163. Gleadhill IC, Schwartz AR, Schubert N et al. (1991). Upper airway collapsibility in snorers and in patients with obstructive hypopnea and apnea. Am Rev Respir Dis 143: 1300–1303. Gleeson K, Zwillich CW, White DP (1989). Chemosensitivity and the ventilatory response to airflow obstruction during sleep. J Appl Physiol 67: 1630–1637. Gleeson K, Zwillich CW, White DP (1990). The influence of increasing ventilatory effort on arousal from sleep. Am Rev Respir Dis 142: 295–300. Gottlieb DJ, Whitney CW, Bonekat WH et al. (1999). Relation of sleepiness to respiratory disturbance index: the Sleep Heart Health Study. Am J Respir Crit Care Med 159: 502–507. Grunstein RR, Ho KY, Sullivan CE (1991). Sleep apnea in acromegaly. Ann Intern Med 115: 527–532.
395
Guilleminault C, Eldridge FL, Dement WC (1973). Insomnia with sleep apnea: a new syndrome. Science 181: 856–858. Guilleminault C, Silvestri R, Mondini S et al. (1984). Aging and sleep apnea: action of benzodiazepine, acetazolamide, alcohol, and sleep deprivation in a healthy elderly group. J Gerontol 39: 655–661. Guilleminault C, Quera-Salva MA, Partinen M et al. (1988). Women and the obstructive sleep apnea syndrome. Chest 93: 104–109. Guilleminault C, Stoohs R, Quera-Salva MA (1992). Sleeprelated obstructive and nonobstructive apneas and neurologic disorders. Neurology 42: 53–60. Guilleminault C, Partinen M, Hollman K et al. (1995). Familial aggregates in obstructive sleep apnea syndrome. Chest 107: 1545–1551. Hallett M, Burden S, Stewart D et al. (1995). Sleep apnea in end-stage renal disease patients on hemodialysis and continuous ambulatory peritoneal dialysis. ASAIO J 41: M435–M441. Haponik EF, Smith PL, Bohlman ME et al. (1983). Computerized tomography in obstructive sleep apnea. Correlation of airway size with physiology during sleep and wakefulness. Am Rev Respir Dis 127: 221–226. Hart TB, Radow SK, Blackard WG et al. (1985). Sleep apnea in active acromegaly. Arch Intern Med 145: 865–866. Hedner J, Pillar G, Pittman SD et al. (2004). A novel adaptive wrist actigraphy algorithm for sleep–wake assessment in sleep apnea patients. Sleep 27: 1560–1566. Hira HS, Sibal L (1999). Sleep apnea syndrome among patients with hypothyroidism. J Assoc Physicians India 47: 615–618. Hochban W, Ehlenz K, Conradt R et al. (1999). Obstructive sleep apnoea in acromegaly: the role of craniofacial changes. Eur Respir J 14: 196–202. Hoffstein V, Zamel N, Phillipson EA (1984). Lung volume dependence of pharyngeal cross-sectional area in patients with obstructive sleep apnea. Am Rev Respir Dis 130: 175–178. Hoffstein V, Weiser W, Haney R (1991). Roentgenographic dimensions of the upper airway in snoring patients with and without obstructive sleep apnea. Chest 100: 81–85. Horner RL, Shea SA, McIvor J et al. (1989). Pharyngeal size and shape during wakefulness and sleep in patients with obstructive sleep apnoea. Q J Med 72: 719–735. Hsu PP (2002). A new method of evaluation of upper airway in patients with obstructive sleep apnoea – computerassisted quantitative videoendoscopic analysis. Ann Acad Med Singapore 31: 393–398. Huang J, Itai N, Hoshiba T et al. (2000). A new nasal acoustic reflection technique to estimate pharyngeal crosssectional area during sleep. J Appl Physiol 88: 1457–1466. Hudgel DW, Harasick T (1990). Fluctuation in timing of upper airway and chest wall inspiratory muscle activity in obstructive sleep apnea. J Appl Physiol 69: 443–450. Hui DS, Wong TY, Ko FW et al. (2000). Prevalence of sleep disturbances in Chinese patients with end-stage renal failure on continuous ambulatory peritoneal dialysis. Am J Kidney Dis 36: 783–788.
396
G. PILLAR AND P. LAVIE
Hui DS, Choy DK, Wong LK et al. (2002a). Prevalence of sleep-disordered breathing and continuous positive airway pressure compliance: results in Chinese patients with first-ever ischemic stroke. Chest 122: 852–860. Hui DS, Wong TY, Li TS et al. (2002b). Prevalence of sleep disturbances in Chinese patients with end stage renal failure on maintenance hemodialysis. Med Sci Monit 8: CR331–CR336. Ikeda K, Ogura M, Oshima T et al. (2001). Quantitative assessment of the pharyngeal airway by dynamic magnetic resonance imaging in obstructive sleep apnea syndrome. Ann Otol Rhinol Laryngol 110: 183–189. Isono S, Feroah TR, Hajduk EA et al. (1997a). Interaction of cross-sectional area, driving pressure, and airflow of passive velopharynx. J Appl Physiol 83: 851–859. Isono S, Remmers JE, Tanaka A et al. (1997b). Anatomy of pharynx in patients with obstructive sleep apnea and in normal subjects. J Appl Physiol 82: 1319–1326. Isono S, Saeki N, Tanaka A et al. (1999). Collapsibility of passive pharynx in patients with acromegaly. Am J Respir Crit Care Med 160: 64–68. Issa FG, Sullivan CE (1982). Alcohol, snoring and sleep apnea. J Neurol Neurosurg Psychiatry 45: 353–359. Issa FG, Sullivan CE (1984a). Upper airway closing pressures in obstructive sleep apnea. J Appl Physiol 57: 520–527. Issa FG, Sullivan CE (1984b). Upper airway closing pressures in snorers. J Appl Physiol 57: 528–535. Jager L, Gunther E, Gauger J et al. (1998). Fluoroscopic MR of the pharynx in patients with obstructive sleep apnea. AJNR Am J Neuroradiol 19: 1205–1214. Javaheri S, Parker TJ, Liming JD et al. (1998). Sleep apnea in 81 ambulatory male patients with stable heart failure. Types and their prevalences, consequences, and presentations. Circulation 97: 2154–2159. Jordan AS, McEvoy RD (2003). Gender differences in sleep apnea: epidemiology, clinical presentation and pathogenic mechanisms. Sleep Med Rev 7: 377–389. Jordan AS, Catcheside PG, O’Donoghue FJ et al. (2002). Long-term facilitation of ventilation is not present during wakefulness in healthy men or women. J Appl Physiol 93: 2129–2136. Jordan AS, McEvoy RD, Edwards JK et al. (2004). The influence of gender and upper airway resistance on the ventilatory response to arousal in obstructive sleep apnoea in humans. J Physiol 558: 993–1004. Jordan AS, Wellman A, Edwards JK et al. (2005). Respiratory control stability and upper airway collapsibility in men and women with obstructive sleep apnea. J Appl Physiol 99: 2020–2027. Jung R, Kuhlo W (1965). Neurophysiological studies of abnormal night sleep and the Pickwickian syndrome. In: K Akert, C Bally, JP Schade´ (Eds.), Sleep Mechanisms. Elsevier, Amsterdam, pp. 140–159. Kales A, Bixler EO, Cadieux RJ et al. (1984). Sleep apnoea in a hypertensive population. Lancet 2: 1005–1008. Kamal I (2004). Acoustic pharyngometry patterns of snoring and obstructive sleep apnea patients. Otolaryngol Head Neck Surg 130: 58–66.
Kapsimalis F, Kryger MH (2002). Gender and obstructive sleep apnea syndrome, part 2: mechanisms. Sleep 25: 499–506. Kapur VK, Koepsell TD, deMaine J et al. (1998). Association of hypothyroidism and obstructive sleep apnea. Am J Respir Crit Care Med 158: 1379–1383. Kapur V, Strohl KP, Redline S et al. (2002). Underdiagnosis of sleep apnea syndrome in U.S. communities. Sleep Breath 6: 49–54. Kim J, In K, You S et al. (2004). Prevalence of sleepdisordered breathing in middle-aged Korean men and women. Am J Respir Crit Care Med 170: 1108–1113. Kittle WM, Chaudhary BA (1988). Sleep apnea and hypothyroidism. South Med J 81: 1421–1425. Klawe JJ, Tafil-Klawe M (2003). Age-related response of the genioglossus muscle EMG-activity to hypoxia in humans. J Physiol Pharmacol 54 (Suppl 1): 14–19. Krieger J, Imbs JL, Schmidt M et al. (1988). Renal function in patients with obstructive sleep apnea. Effects of nasal continuous positive airway pressure. Arch Intern Med 148: 1337–1340. Krieger J, Sforza E, Boudewijns A et al. (1997). Respiratory effort during obstructive sleep apnea: role of age and sleep state. Chest 112: 875–884. Kuhl W (1997). History of clinical research on sleep apnea syndrome. The early days of polysomnography. Respiration 64 (Suppl 1): 5–10. Langevin B, Fouque D, Leger P et al. (1993). Sleep apnea syndrome and end-stage renal disease. Cure after renal transplantation. Chest 103: 1330–1335. Larsson LG, Lindberg A, Franklin KA et al. (2001). Symptoms related to obstructive sleep apnoea are common in subjects with asthma, chronic bronchitis and rhinitis in a general population. Respir Med 95: 423–429. Lavie P (1983). Incidence of sleep apnea in a presumably healthy working population: a significant relationship with excessive daytime sleepiness. Sleep 6: 312–318. Lavie P (2003). Restless Nights. Understanding Snoring and Sleep Apnea. Yale, New Haven. Lavie P, Pillar G (2001). Gender and age differences in symptoms’ profile in sleep apnea syndrome: a possible cause of gender bias in diagnosis. Somnologie 3: 93–96. Lavie P, Ben-Yosef R, Rubin AE (1984). Prevalence of sleep apnea syndrome among patients with essential hypertension. Am Heart J 108: 373–376. Lee JJ, Ramirez SG, Will MJ (1997). Gender and racial variations in cephalometric analysis. Otolaryngol Head Neck Surg 117: 326–329. Leibowitz G, Shapiro MS, Salameh M et al. (1994). Improvement of sleep apnoea due to acromegaly during shortterm treatment with octreotide. J Intern Med 236: 231–235. Leiter JC (1996). Upper airway shape: is it important in the pathogenesis of obstructive sleep apnea? Am J Respir Crit Care Med 153: 894–898. Lin CC, Tsan KW, Chen PJ (1992). The relationship between sleep apnea syndrome and hypothyroidism. Chest 102: 1663–1667.
OBSTRUCTIVE SLEEP APNEA: DIAGNOSIS, RISK FACTORS, AND PATHOPHYSIOLOGY Logan AG, Perlikowski SM, Mente A et al. (2001). High prevalence of unrecognized sleep apnoea in drug-resistant hypertension. J Hypertens 19: 2271–2277. Loube DI, Loube AA, Mitler MM (1994). Weight loss for obstructive sleep apnea: the optimal therapy for obese patients. J Am Diet Assoc 94: 1291–1295. Lugaresi E, Coccagna G, Petrella A et al. (1968). [The disorder of sleep and respiration in the Pickwick syndrome (in Italian)]. Sist Nerv 20: 38–50. Macey PM, Macey KE, Henderson LA et al. (2003). Functional magnetic resonance imaging responses to expiratory loading in obstructive sleep apnea. Respir Physiol Neurobiol 138: 275–290. Main G, Borsey DQ, Newton RW (1988). Successful reversal of sleep apnoea syndrome following treatment for acromegaly, confirmed by polygraphic studies. Postgrad Med J 64: 945–946. Malhotra A, White DP (2002). Obstructive sleep apnoea. Lancet 360: 237–245. Malhotra A, Fogel RB, Edwards JK et al. (2000). Local mechanisms drive genioglossus activation in obstructive sleep apnea. Am J Respir Crit Care Med 161: 1746–1749. Malhotra A, Pillar G, Fogel R et al. (2001a). Upper-airway collapsibility: measurements and sleep effects. Chest 120: 156–161. Malhotra A, Pillar G, Fogel RB et al. (2001b). Genioglossal but not palatal muscle activity relates closely to pharyngeal pressure. Am J Respir Crit Care Med 162: 1058–1062. Malhotra A, Huang Y, Fogel RB et al. (2002a). The male predisposition to pharyngeal collapse: importance of airway length. Am J Respir Crit Care Med 166: 1388–1395. Malhotra A, Pillar G, Fogel RB et al. (2002b). Pharyngeal pressure and flow effects on genioglossus activation in normal subjects. Am J Respir Crit Care Med 165: 71–77. Malhotra A, Huang Y, Fogel R et al. (2006). Aging influences on pharyngeal anatomy and physiology: the predisposition to pharyngeal collapse. Am J Med 119: 72e9–72e14. Margel D, Cohen M, Livne PM et al. (2004). Severe, but not mild, obstructive sleep apnea syndrome is associated with erectile dysfunction. Urology 63: 545–549. Mathur R, Douglas NJ (1995). Family studies in patients with the sleep apnea–hypopnea syndrome. Ann Intern Med 122: 174–178. Mendelson WB, Garnett D, Gillin JC (1981). Flurazepaminduced sleep apnea syndrome in a patient with insomnia and mild sleep-related respiratory changes. J Nerv Ment Dis 169: 261–264. Mendelson WB, Wadhwa NK, Greenberg HE et al. (1990). Effects of hemodialysis on sleep apnea syndrome in end-stage renal disease. Clin Nephrol 33: 247–251. Mezzanotte WS, Tangel DJ, White DP (1992). Mechanisms of control of alae nasi muscle activity. J Appl Physiol 72: 925–933. Millman RP, Carlisle CC, McGarvey ST et al. (1995). Body fat distribution and sleep apnea severity in women. Chest 107: 362–366.
397
Mohsenin V (2001). Gender differences in the expression of sleep-disordered breathing: role of upper airway dimensions. Chest 120: 1442–1447. Mohsenin V (2003). Effects of gender on upper airway collapsibility and severity of obstructive sleep apnea. Sleep Med 4: 523–529. Monteforte MJ, Turkelson CM (2000). Bariatric surgery for morbid obesity. Obes Surg 10: 391–401. Morrell MJ, Arabi Y, Zahn B et al. (1998). Progressive retropalatal narrowing preceding obstructive apnea. Am J Respir Crit Care Med 158: 1974–1981. Morrison DL, Launois SH, Isono S et al. (1993). Pharyngeal narrowing and closing pressures in patients with obstructive sleep apnea. Am Rev Respir Dis 148: 606–611. Neven AK, Middelkoop HA, Kemp B et al. (1998). The prevalence of clinically significant sleep apnoea syndrome in The Netherlands. Thorax 53: 638–642. O’Donnell CP, Schwartz AR, Smith PL (2000). Upper airway collapsibility: the importance of gender and adiposity. Am J Respir Crit Care Med 162: 1606–1607. Onal E, Lopata M, O’Connor TD (1981a). Diaphragmatic and genioglossal electromyogram responses to CO2 rebreathing in humans. J Appl Physiol 50: 1052–1055. Onal E, Lopata M, O’Connor TD (1981b). Diaphragmatic and genioglossal electromyogram responses to isocapnic hypoxia in humans. Am Rev Respir Dis 124: 215–217. Onal E, Burrows DL, Hart RH et al. (1986). Induction of periodic breathing during sleep causes upper airway obstruction in humans. J Appl Physiol 61: 1438–1443. Ong KC, Clerk AA (1998). Comparison of the severity of sleep-disordered breathing in Asian and Caucasian patients seen at a sleep disorders center. Respir Med 92: 843–848. Pendlebury ST, Pepin JL, Veale D et al. (1997). Natural evolution of moderate sleep apnoea syndrome: significant progression over a mean of 17 months. Thorax 52: 872–878. Pillar G, Lavie P (1995). Assessment of the role of inheritance in sleep apnea syndrome. Am J Respir Crit Care Med 151: 688–691. Pillar G, Lavie P (1998). Psychiatric symptoms in sleep apnea syndrome: effects of gender and respiratory disturbance index. Chest 114: 697–703. Pillar G, Peled N, Katz N et al. (1994). Predictive value of specific risk factors, symptoms and signs, in diagnosing obstructive sleep apnoea and its severity. J Sleep Res 3: 241–244. Pillar G, Schnall R, Peled N et al. (1995). Healthy men have a greater upper airway collapsibility than healthy women. Sleep 18: 172. Pillar G, Schnall RP, Peled N et al. (1997). Impaired respiratory response to resistive loading during sleep in healthy offspring of patients with obstructive sleep apnea. Am J Respir Crit Care Med 155: 1602–1608. Pillar G, Malhotra A, Fogel R et al. (2000). Airway mechanics and ventilation in response to resistive loading during sleep: influence of gender. Am J Respir Crit Care Med 162: 1627–1632.
398
G. PILLAR AND P. LAVIE
Pillar G, Fogel RB, Malhotra A et al. (2001a). Genioglossal inspiratory activation: central respiratory vs mechanoreceptive influences. Respir Physiol 127: 23–38. Pillar G, Malhotra A, Fogel RB et al. (2001b). Upper airway muscle responsiveness to rising PCO(2) during NREM sleep. J Appl Physiol 89: 1275–1282. Pillar G, Bar A, Betito M et al. (2003). An automatic ambulatory device for detection of AASM defined arousals from sleep: the WP100. Sleep Med 4: 207–212. Pittman SD, Ayas NT, MacDonald MM et al. (2004). Using a wrist-worn device based on peripheral arterial tonometry to diagnose obstructive sleep apnea: in-laboratory and ambulatory validation. Sleep 27: 923–933. Popovic RM, White DP (1995). Influence of gender on waking genioglossal electromyogram and upper airway resistance. Am J Respir Crit Care Med 152: 725–731. Punjabi NM, Sorkin JD, Katzel LI et al. (2002). Sleepdisordered breathing and insulin resistance in middle-aged and overweight men. Am J Respir Crit Care Med 165: 677–682. Radwan L, Maszczyk Z, Koziorowski A et al. (1995). Control of breathing in obstructive sleep apnoea and in patients with the overlap syndrome. Eur Respir J 8: 542–545. Rajagopal KR, Abbrecht PH, Derderian SS et al. (1984). Obstructive sleep apnea in hypothyroidism. Ann Intern Med 101: 491–494. Redline S, Tosteson T, Tishler PV et al. (1992). Studies in the genetics of obstructive sleep apnea. Familial aggregation of symptoms associated with sleep-related breathing disturbances. [published erratum appears in Am Rev Respir Dis 1992; 145(4 Pt 1):979]. Am Rev Respir Dis 145 440–444. Redline S, Kump K, Tishler PV et al. (1994). Gender differences in sleep disordered breathing in a community-based sample. Am J Respir Crit Care Med 149: 722–726. Redline S, Tishler PV, Tosteson TD et al. (1995). The familial aggregation of obstructive sleep apnea. Am J Respir Crit Care Med 151: 682–687. Remmers JE (1984). Obstructive sleep apnea. A common disorder exacerbated by alcohol. Am Rev Respir Dis 130: 153–155. Resnick HE, Redline S, Shahar E et al. (2003). Diabetes and sleep disturbances: findings from the Sleep Heart Health Study. Diabetes Care 26: 702–709. Resta O, Foschino-Barbaro MP, Bonfitto P et al. (2000). Prevalence and mechanisms of diurnal hypercapnia in a sample of morbidly obese subjects with obstructive sleep apnoea. Respir Med 94: 240–246. Resta O, Foschino-Barbaro MP, Legari G et al. (2001). Sleep-related breathing disorders, loud snoring and excessive daytime sleepiness in obese subjects. Int J Obes Relat Metab Disord 25: 669–675. Resta O, Caratozzolo G, Pannacciulli N et al. (2003). Gender, age and menopause effects on the prevalence and the characteristics of obstructive sleep apnea in obesity. Eur J Clin Invest 33: 1084–1089. Rodenstein DO, Dooms G, Thomas Y et al. (1990). Pharyngeal shape and dimensions in healthy subjects, snorers, and patients with obstructive sleep apnoea. Thorax 45: 722–727.
Rodway GW, Sanders MH (2003). The efficacy of splitnight sleep studies. Sleep Med Rev 7: 391–401. Rosenow F, Reuter S, Szelies B et al. (1994). Sleep apnoea in acromegaly – prevalence, pathogenesis and therapy. Report on two cases. Presse Med 23: 1203–1208. Ryan CF, Love LL (1996). Mechanical properties of the velopharynx in obese patients with obstructive sleep apnea. Am J Respir Crit Care Med 154: 806–812. Sanders MH, Givelber R (2003). Sleep disordered breathing may not be an independent risk factor for diabetes, but diabetes may contribute to the occurrence of periodic breathing in sleep. Sleep Med 4: 349–350. Sanner BM, Heise M, Knoben B et al. (2002). MRI of the pharynx and treatment efficacy of a mandibular advancement device in obstructive sleep apnoea syndrome. Eur Respir J 20: 143–150. Schafer H, Koehler U, Ewig S et al. (1999). Obstructive sleep apnea as a risk marker in coronary artery disease. Cardiology 92: 79–84. Schafer H, Pauleit D, Sudhop T et al. (2002). Body fat distribution, serum leptin, and cardiovascular risk factors in men with obstructive sleep apnea. Chest 122: 829–839. Schmidt-Nowara WW, Coultas DB, Wiggins C et al. (1990). Snoring in a Hispanic-American population. Risk factors and association with hypertension and other morbidity. Arch Intern Med 150: 597–601. Schwab RJ (1998). Upper airway imaging. Clin Chest Med 19: 33–54. Schwab RJ (2005). Genetic determinants of upper airway structures that predispose to obstructive sleep apnea. Respir Physiol Neurobiol 147: 289–298. Schwab RJ, Gefter WB, Hoffman EA et al. (1993). Dynamic upper airway imaging during awake respiration in normal subjects and patients with sleep disordered breathing. Am Rev Respir Dis 148: 1385–1400. Schwab RJ, Pasirstein M, Pierson R et al. (2003). Identification of upper airway anatomic risk factors for obstructive sleep apnea with volumetric magnetic resonance imaging. Am J Respir Crit Care Med 168: 522–530. Schwartz AR, Smith PL, Wise RA et al. (1988). Induction of upper airway occlusion in sleeping individuals with subatmospheric nasal pressure. J Appl Physiol 64: 535–542. Schwartz AR, Smith PL, Wise RA et al. (1989). Effect of positive nasal pressure on upper airway pressure–flow relationships. J Appl Physiol 66: 1626–1634. Schwartz AR, Gold AR, Schubert N et al. (1991). Effect of weight loss on upper airway collapsibility in obstructive sleep apnea. Am Rev Respir Dis 144: 494–498. Sforza E, Addati G, Cirignotta F et al. (1994). Natural evolution of sleep apnoea syndrome: a five year longitudinal study. Eur Respir J 7: 1765–1770. Sforza E, Petiau C, Weiss T et al. (1999). Pharyngeal critical pressure in patients with obstructive sleep apnea syndrome. Clinical implications. Am J Respir Crit Care Med 159: 149–157. Sharma SK, Reddy TS, Mohan A et al. (2002). Sleep disordered breathing in chronic obstructive pulmonary disease. Indian J Chest Dis Allied Sci 44: 99–105.
OBSTRUCTIVE SLEEP APNEA: DIAGNOSIS, RISK FACTORS, AND PATHOPHYSIOLOGY Shea SA, Edwards JK, White DP (1999). Effect of wakesleep transitions and rapid eye movement sleep on pharyngeal muscle response to negative pressure in humans. J Physiol 520 (Pt 3): 897–908. Shelton KE, Gay SB, Hollowell DE et al. (1993). Mandible enclosure of upper airway and weight in obstructive sleep apnea. Am Rev Respir Dis 148: 195–200. Shepard JWJr., Gefter WB, Guilleminault C et al. (1991). Evaluation of the upper airway in patients with obstructive sleep apnea. Sleep 14: 361–371. Short DJ, Stradling JR, Williams SJ (1992). Prevalence of sleep apnoea in patients over 40 years of age with spinal cord lesions. J Neurol Neurosurg Psychiatry 55: 1032–1036. Smith IE, Quinnell TG (2004). Pharmacotherapies for obstructive sleep apnoea: where are we now? Drugs 64: 1385–1399. Smith PL, Wise RA, Gold AR et al. (1988). Upper airway pressure–flow relationships in obstructive sleep apnea. J Appl Physiol 64: 789–795. Tangel DJ, Mezzanotte WS, White DP (1991). Influence of sleep on tensor palatini EMG and upper airway resistance in normal men. J Appl Physiol 70: 2574–2581. Tangel DJ, Mezzanotte WS, Sandberg EJ et al. (1992). Influences of NREM sleep on the activity of tonic vs. Inspiratory phasic muscles in normal men. J Appl Physiol 73: 1058–1066. Trinder J, Kay A, Kleiman J et al. (1997). Gender differences in airway resistance during sleep. J Appl Physiol 83: 1986–1997. Udwadia ZF, Doshi AV, Lonkar SG et al. (2004). Prevalence of sleep-disordered breathing and sleep apnea in middle-aged urban Indian men. Am J Respir Crit Care Med 169: 168–173. Valencia-Flores M, Orea A, Castano VA et al. (2000). Prevalence of sleep apnea and electrocardiographic disturbances in morbidly obese patients. Obes Res 8: 262–269. van Lunteren E, Strohl KP (1986). The muscles of the upper airways. Clin Chest Med 7: 171–188. Villaneuva AT, Buchanan PR, Yee BJ et al. (2005). Ethnicity and obstructive sleep apnoea. Sleep Med Rev. Wadhwa NK, Seliger M, Greenberg HE et al. (1992). Sleep related respiratory disorders in end-stage renal disease patients on peritoneal dialysis. Perit Dial Int 12: 51–56. Ware JC, McBrayer RH, Scott JA (2000). Influence of sex and age on duration and frequency of sleep apnea events. Sleep 23: 165–170. Weinberg J, Klefbeck B, Borg J et al. (2003). Polysomnography in chronic neuromuscular disease. Respiration 70: 349–354. Weitzenblum E, Krieger J, Oswald M et al. (1992). Chronic obstructive pulmonary disease and sleep apnea syndrome. Sleep 15: S33–S35. Welch KC, Foster GD, Ritter CT et al. (2002). A novel volumetric magnetic resonance imaging paradigm to study upper airway anatomy. Sleep 25: 532–542.
399
Wellman A, Malhotra A, Fogel RB et al. (2003). Respiratory system loop gain in normal men and women measured with proportional-assist ventilation. J Appl Physiol 94: 205–212. Wellman A, Jordan AS, Malhotra A et al. (2004). Ventilatory control and airway anatomy in obstructive sleep apnea. Am J Respir Crit Care Med 170: 1225–1232. Wheatley JR, Amis TC (1998). Mechanical properties of the upper airway. Curr Opin Pulm Med 4: 363–369. Wheatley JR, Mezzanotte WS, Tangel DJ et al. (1993a). Influence of sleep on genioglossus muscle activation by negative pressure in normal men. Am Rev Respir Dis 148: 597–605. Wheatley JR, Tangel DJ, Mezzanotte WS et al. (1993b). Influence of sleep on response to negative airway pressure of tensor palatini muscle and retropalatal airway. J Appl Physiol 75: 2117–2124. White DP, Lombard RM, Cadieux RJ et al. (1985). Pharyngeal resistance in normal humans: influence of gender, age, and obesity. J Appl Physiol 58: 365–371. Whittle AT, Marshall I, Mortimore IL et al. (1999). Neck soft tissue and fat distribution: comparison between normal men and women by magnetic resonance imaging. Thorax 54: 323–328. Wilcox I, Collins FL, Grunstein RR et al. (1994). Relationship between chemosensitivity, obesity and blood pressure in obstructive sleep apnoea. Blood Press 3: 47–54. Wilhoit SC, Suratt PM (1987). Obstructive sleep apnea in premenopausal women. A comparison with men and with postmenopausal women. Chest 91: 654–658. Worsnop CJ, Naughton MT, Barter CE et al. (1998). The prevalence of obstructive sleep apnea in hypertensives. Am J Respir Crit Care Med 157: 111–115. Yamashiro Y, Kryger MH (1995). CPAP titration for sleep apnea using a split-night protocol. Chest 107: 62–66. Younes M (2004). Role of arousals in the pathogenesis of obstructive sleep apnea. Am J Respir Crit Care Med 169: 623–633. Younes M, Ostrowski M, Thompson W et al. (2001). Chemical control stability in patients with obstructive sleep apnea. Am J Respir Crit Care Med 163: 1181–1190. Young T, Palta M, Dempsey J et al. (1993). The occurrence of sleep-disordered breathing among middle-aged adults. N Engl J Med 32: 1230–1235. Young T, Hutton R, Finn L et al. (1996). The gender bias in sleep apnea diagnosis. Are women missed because they have different symptoms? Arch Intern Med 156: 2445–2451. Zhang L, Huang X, Li X et al. (1997). Alterations in renal function in patients with obstructive sleep apnea syndrome and effects of continuous positive airway pressure. Chin Med J (Engl) 110: 915–918.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 26
Upper-airway resistance syndrome CHRISTIAN GUILLEMINAULT * AND VIRGINIA DE LOS REYES Stanford University Sleep Medicine Program, Stanford, CA, USA
INTRODUCTION Upper-airway resistance syndrome (UARS) was first recognized in children in 1982 (Guilleminault et al., 1982). The term UARS, however, was not used until adult cases were reported in 1993 (Guilleminault et al., 1993). The description of UARS brought the attention of clinicians to a group of patients that was left undiagnosed and untreated despite severe impairment. The authors indicated that they had to identify this clinical entity as many had been denied proper treatment based on subjects’ symptoms and polysomnographic (PSG) features that differ from those of obstructive sleep apnea syndrome (OSAS). However, controversies exist regarding UARS. Some have rejected it as a distinct clinical entity or even doubted its existence (Douglas, 2000). In the past few years, however, there has been greater acceptance of this entity, and review articles have been published on UARS in general (Exar and Collop, 1999) and in children (Guilleminault and Khramtsov, 2001). Since the first description of a polygraphic pattern called obstructive sleep apnea in the pickwickian syndrome in 1965 (Gastaut et al., 1965; Jung and Kuhlo, 1965), sleep medicine has undergone an evolution. UARS was introduced as part of the efforts to describe a generally unrecognized patient population that is nonobese and whose clinical features do not match those reported with OSAS. Unfortunately, many sleep-breathing abnormalities are still ignored due to the belief that sleepdisordered breathing is synonymous with OSAS and that patients must be overweight or clearly obese. Such limited views have already led to the underdiagnosis and undertreatment of OSAS in women, “the forgotten gender” (Guilleminault et al., 1995). With the use of new techniques, such as the esophageal catheter for esophageal pressure (Pes) measurement (Flemale et al.,
1988) and nasal cannula/pressure transducer (Norman et al., 1997), it has become more convenient to identify subtle changes in breathing patterns during sleep. In the past few years, UARS has been linked to many somatic, psychiatric, or psychosomatic conditions, including parasomnias, attention deficit disorder (ADD) or attention deficit hyperactivity disorder (ADHD), fibromyalgia, as well as chronic insomnia. It has been shown that the consequences of the syndrome on the autonomic nervous system are different compared to those linked to OSAS. Some considered UARS as part of a spectrum that includes benign snoring, UARS, obstructive hypopnea, obstructive sleep apnea (OSA), and hypoventilation. However, despite the fact that some patients may present such progression, it is too simple to link all these entities together. The first issue is whether to believe that there is a “benign” chronic snoring. Our studies support that chronic snoring is not “benign” and is part of UARS. The American Academy of Pediatrics recognized such possibility when it recommended exploring chronic snoring in all children (American Academy of Pediatrics, 2002), but such a recommendation has never been made in adults. The second issue is whether to consider that UARS is systematically associated with chronic snoring, as even the initial description of the syndrome indicated that snoring was absent in about one-third of reported patients (Guilleminault et al., 1993). Finally, the progressive evolution from UARS is questionable. The only longitudinal study performed on about 100 UARS subjects seen again without treatment about 5 years later reported that fewer than 10% had such evolution (Guilleminault et al., 2006b). In these cases, it was associated with clear weight gain, leading to fatty infiltration of both neck and abdomen, with secondary restrictive chest bellows impairment; this was particularly obvious during rapid eye movement (REM) sleep and became worse by
*Correspondence to: Christian Guilleminault, M.D., Biol.D., Stanford University Sleep Disorders Program, 401 Quarry Road, suite 3301, Stanford, CA, 94305, USA. Tel: 1 650 723 6601, Fax: 1 650 725 8910, E-mail:
[email protected]
402
C. GUILLEMINAULT AND V. DE LOS REYES
physiologic development of the REM sleep-related muscle atonia that eliminates usage of respiratory accessory muscles. Our understanding of OSAS and its underlying lesions has improved in recent years, and the two syndromes can be understood as related to the presence of either normal or impaired capability to respond to specific upper-airway airflow challenges during sleep.
EPIDEMIOLOGY There is no investigation of UARS in the general population. In children, it has been reported that 9–12% of children are chronic snorers (Guilleminault et al., 2005a). Chronic snoring without OSA in children has been shown to be associated with different health problems, mostly behavioral, such as hyperactivity, inattention, poor school performance, anxiety, or depressive effects. Unfortunately, most chronic snorers have not been studied with PSG. When studied, however, absence of apnea–hypopnea and presence of increased respiratory effort, indicative of UARS, and documented by Pes, were shown during sleep. In children, prevalence of OSAS has been calculated at between 4 and 5%, compared to the reports of chronic snoring, at 9–12% (Guilleminault et al., 2005a).
CLINICAL SYMPTOMS Although some of the symptoms in UARS overlap with those in OSAS, studies have found some important differences (Guilleminault and Bassiri, 2005). Chronic insomnia tends to be much more common in patients with UARS than those with OSAS. Many UARS patients report maintenance insomnia characterized by frequent nocturnal awakenings and difficulty falling back to sleep, but sleep-onset insomnia is also present, and is thought to be caused by “conditioning” as a consequence of frequent sleep disruptions (Guilleminault et al., 2002a). Adult patients with UARS are also more likely to complain of fatigue rather than sleepiness. They may have difficulty getting up in the morning and may shift their sleep schedule, evolving toward a delayed sleep phase disorder. Other presentations include parasomnias with sleepwalking and sleep terrors (Guilleminault et al., 2006a), myalgia, depression, and anxiety. Gold and colleagues (2003) emphasized that UARS patients have complaints related more to functional somatic syndromes, such as headaches, sleep-onset insomnia, and irritable bowel syndrome. Not infrequently, UARS is misinterpreted as chronic fatigue syndrome, fibromyalgia, or psychiatric disorders such as ADD/ADHD (Lewin and Pinto, 2004) or depressive disorders. A clinical case report of UARS has also presented symptomatology mimicking nocturnal
asthma (Guerrero et al., 2001). Symptoms related to chronic nasal allergies are often seen. The clinical interview reveals the presence of lightheadedness with abrupt positional changes, sometime more pronounced on awakenings, and subjects may have learned early to avoid “jumping out of bed” and having a two-step approach when getting up. History of fainting mostly during teenage years may also be elicited. Between one-fifth and one-fourth will report the presence of cold hands and/or cold feet and sometimes other mild signs associated with vagal hyperactivity such as orthostatic hypotension and cold extremities. The other reported health problems are related to the most common cause of UARS, i.e., small maxilla and/ or mandible manifested as impaction of wisdom teeth with need for removal between 15 and 25 years, history of orthodontic treatment often with teeth removal, usage of dental retainer or other dental device during childhood, or presence of bruxism. A history of chronic nasal allergies sometimes associated with chronic sinus infection or a history of repetitive upper-airway infection or earaches may occur during the first years of life.
PHYSICAL EXAMINATION Clinical examination will show low blood pressure in about one-fourth of subjects, often associated with moderate worsening with orthostatic maneuvers (Guilleminault et al., 2001a, 2004). Indications of anatomic narrowing of the upper airway have to be evaluated: 1.
2.
3.
4.
evaluation of nose: asymmetrical external valve, collapse of internal valve at inspiration, narrow and long nose, enlargement of inferior nasal turbinates due to allergy, presence of deviated septum evaluation of maxilla: high and narrow hard palate, presence of overlapping teeth, short intermolar distance evaluation of mandible: retroposition indicated by important (>2.2 mm) overjet, presence of indentation on lateral sides of tongue, presence of scars related to lateral biting of cheek evaluation of face: elongation of lower anterior third of face, steep mandibular plane, narrow and elongated chin.
Soft tissues should also be evaluated with determination of tonsil size using standard scales and placement of the tongue in relation to the uvula, using the Mallampati scale (Mallampati et al., 1985). Cephalometric X-rays may confirm this information. Although the clinical evaluation allows one to suspect UARS and its potential relationship to anatomical factors impacting the upper airway, the diagnosis can only be confirmed by PSG.
UPPER-AIRWAY RESISTANCE SYNDROME
Polysomnography PSG reveals an apnea–hypopnea index (AHI) < 5, oxygen saturation > 92%, and presence of respiratory effort-related arousals (RERAs) as well as other nonapnea/hypopnea respiratory events. Although inductive respiratory plethysmography (Loube et al., 1999), pneumotachograph, and most commonly nasal cannula/pressure transducer have been tried to measure subtle respiratory alterations (Ayap et al., 2000; Epstein et al., 2000; Virkula et al., 2002), measurement of Pes remains the gold standard for detecting respiratory abnormalities. The use of a pediatric feeding catheter instead of an esophageal balloon has improved tolerance of the procedure in both adults (Epstein et al., 2000) and children (Serebrisky et al., 2002). The nasal cannula/pressure transducer is more sensitive than thermistors in picking up respiratory changes and has been used to detect RERAs. In addition to the nasal cannula/pressure transducer system, respiratory channels, mouth thermistor (mandatory to recognize mouth breathing with nasal obstruction), thoracic and abdominal piezoelectric bands or inductive respiratory plethysmography, neck microphone and Pes are important to allow proper diagnosis. Calibration of different channels, particularly Pes, before the beginning and at the end of monitoring, is mandatory. The other PSG channels all have to be present in these cases, particularly several electroencephalogram (EEG) leads that will allow monitoring not only C3–A2 and C4–A1 but also frontal and occipital derivations, that will help in the investigation of the presence of American Sleep Disorders Association (1992) arousals of 3 seconds’ or more duration as well as the calculation of cyclic alternating pattern (CAP) during non-REM (NREM) sleep. Analysis of PSG will not only recognize apnea and hypopnea as classically defined, but will also determine the presence of flow limitation based on the analysis of the nasal cannula curve. Flow limitation will appear as flattening of the normal bell-shaped curve of normal breath with a drop in the amplitude of the curve by 2–29% compared to the normal breaths immediately preceding (Figures 26.1–26.3). The nasal cannula/ pressure transducer is more sensitive than thermistors in picking up respiratory changes and detecting RERAs. However, sensitivity comparable with Pes measurement has not been demonstrated. Three abnormal forms of Pes tracings have been described (Black et al., 2000; Guilleminault et al., 2001b). First, Pes crescendo is a progressively increased negative peak inspiratory pressure in each breath which terminates with an alpha-wave EEG arousal or a burst of delta wave. This is not associated with a drop in oxygen saturation of 3%, as used for definition of hypopnea. The second form is a sustained
403
continuous respiratory effort, wherein the Pes tracing shows a relatively stable and persistent negative peak inspiratory pressure, which is more than the baseline and nonobstructed breaths. This lasts longer than four breaths. The third form is Pes reversal, wherein there is an abrupt drop in respiratory effort indicated by a less negative peak inspiratory pressure after a sequence of increased respiratory efforts independent of the EEG pattern seen. This indicates the end of an abnormal breathing sequence, independent of the EEG pattern. The disadvantage of Pes measurement is the need to insert a small catheter from the patient’s nostril down to the esophagus. Despite validations of good tolerability and a low complication rate in adults and children, Pes measurement is not widely applied, due to patients’ fear of discomfort and sleep technologists’ hesitancy, except in centers where the technique has been well adapted, or in academic and research settings. We have applied a new algorithm using intercostal EMG signals to pick up the respiratory variations. The results are quite promising (Stoohs et al., 2004). Another technique using pulse wave signals was developed in Japan and patented in the USA for commercial development (Nanba et al., 2002). It is expected that, in the near future, new techniques will be available for measuring even more subtle changes in respiratory efforts without the need of a Pes catheter placement.
POLYSOMNOGRAPHIC FINDINGS EEG ANALYSIS
AND POWER
SPECTRAL
The typical PSG findings for UARS include AHI < 5, minimum oxygen saturation > 92%, an increase in alpha rhythm, and a relative increase in delta sleep, which persists in the latter cycles of sleep. Recent studies also confirm that UARS patients may have more alpha EEG frequency time (Guilleminault et al., 2001c; Poyares et al., 2002) and more RERAs (Poyares et al., 2002) during sleep than patients with obstructive sleep apnea-hypopnea syndrome (OSAHS). Scoring of CAPs is another novel approach evaluating quality of sleep in UARS. A higher frequency of CAPs is noted in UARS compared to age- and gender-matched controls (Guilleminault et al., 2005a; Lopes and Guilleminault, 2005). The comparison of the sleep EEG of UARS, OSAHS, and normal control subjects, using power spectrum analysis, shows a higher amount of theta and alpha powers (i.e., 7–9 Hz bandwidth) during NREM sleep, and more delta powers during REM sleep compared with OSAHS and normal subjects (Guilleminault et al., 2001c). The new analytic approach design by Chervin et al. (2004) that quantifies the so-called respiratory cycle-related electroencephalographic changes breath by breath, and correlates delta, theta, and alpha EEG
404
C. GUILLEMINAULT AND V. DE LOS REYES
Patient Name: 100029 Example, 1 Subject Code: X Study Date: 02/17/2006 -37.5
(C3) - (A2) +37.5
(C4) - (A1) (O1) - (A2) (Fp1) - (A2) Chin EMG (LOC) - (A2) (ROC) - (A1)
PULSE
[EKG-L - EKG-R]
68.0
LAT RAT SaO2
+100.0 +90.0 96.0+80.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 95.0 95.0 95.0 96.0 96.0 96.0 96.0 +70.0
Min 96.0
Mic Nasal Oral Chest Abdomen 23:33:49
23:34:04
23:34:19
23:34:34
23:34:49
23:35:04
23:35:19
23:35:34
Fig. 26.1. Example of flow limitation in a patient with upper-airway resistance syndrome during slow-wave sleep. From top to bottom the following channels were recorded: channel 1–4 electroencephalogram (EEG) (C3/A2, C4/A1, O1/A1, Fp1/A2); channel 5: chin electromyogram (EMG), channels 6 and 7: left and right electro-oculogram (LOC and ROC), channel 8: electrocardiogram (EKG), channels 9 and 10: leg EMG, channel 11: pulse oximetry, channel 12: neck microphone, channel 13: nasal cannula/pressure transducer, channel 14: oral thermistor, channels 15 and 16 thoracic and abdominal movements. Bottom: time during the night. During this 120 seconds’ monitoring during slow-wave sleep, the presence of flow limitation can be seen without apnea, hypopnea, snoring, or oxygen saturation drop. The flow limitation is seen on the nasal cannula channel. Presence of cyclic alternating pattern can also be seen when looking at the EEG leads.
powers with respiratory cycle variations, may allow the detection of more subtle sleep EEG changes related to abnormal respiratory efforts.
PATHOPHYSIOLOGY Difference between OSAS and UARS The idea that OSAS involves the presence of a local neuropathy at the pharyngeal region was first proposed by Swedish investigators and is based on neurophysiologic, electron microscopic, and clinical investigations (Edstrom et al., 1992; Friberg et al., 1997, 1998a, b). The presence or absence of these neurogenic lesions is the basis for the existence of the two syndromes. Data obtained by Friberg et al. (1997, 1998a, b) provided evidence of local neurogenic lesions of the
upper airway in OSAS and these lesions are associated with slowing of impulse conduction (MacKenzie et al., 1977). Their data are in accordance with those shown by Woodson et al. (1991), Series et al. (1996), Kimoff et al. (2001), and Guilleminault et al. (2002a). Friberg (1999) compared the findings observed in the “vibration-induced white finger” syndrome with those noted in clinical neurophysiologic and histologic tests in OSAS patients. The clinical and histologic findings secondary to long-term use of low-frequency hand-held vibrating tools include decreased sensitivity to vibration and temperature, hypertrophied muscle cells, and a demyelinating neuropathy in the peripheral nerves. There is marked loss of nerve fibers and myelin sheaths and relatively smaller axons without myelin. Similar findings have been reported with
UPPER-AIRWAY RESISTANCE SYNDROME
405
Patient Name: 100029 Example, 1 Subject Code: X Study Date: 02/17/2006 -37.5
(C3) - (A2) +37.5
(C4) - (A1) (O1) - (A2) (Fp1) - (A2) Chin EMG (LOC) - (A2) (ROC) - (A1)
PULSE 70.0
[EKG-L - EKG-R] LAT RAT SaO2
+100.0 +90.0 96.0+80.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0
Min 96.0
+70.0
Mic Nasal Oral Chest Abdomen 03:02:19
03:02:29
03:02:39
03:02:49
03:02:59
03:03:09
Fig. 26.2. Example of flow limitation during stage 2 nonrapid eye movement sleep in a patient with upper-airway resistance syndrome. Montage is the same as for Figure 26.1. Note the presence of flow limitation during 30 seconds of recording, well shown on the nasal cannula channel: the normal upper round shape of each breath has been replaced by a flattening of the curve, indicative of the flow limitation.
clinical testing and with the Swedish group’s histologic studies in the oropharyngeal region (Friberg, 1999). Heavy snoring produces low-frequency vibration, and these similarities support the hypothesis that a vibration trauma may be involved in the development of lesions (Nguyen et al., 2005). Furthermore, human receptors located in the upper airway respond to oscillations similar to snoring simply by increasing the EMG activity in the genioglossus and other respiratory muscles. Nguyen et al. (2005) used an endoscopic sensory testing technique (Aviv et al., 1993, 1999) in OSAS and an air pulse stimulator in control patients. Using such a technique, no difference in sensory thresholds was seen in patients and matched controls when air pulse was delivered on the lips, but clear differences were seen at the oropharyngeal and laryngeal levels, more particularly at the level of the aryepiglottic eminence, indicating that OSAS patients have lesions not only in the oral-pharyngeal but also laryngeal regions,
with disturbance of an aryepiglottic reflex due to sensory lesions. The importance of the sensory lesions in the larynx correlates with the AHI (Nguyen et al., 2005). In OSAS the presence of local sensory lesions does not allow passage of information concerning airflow to induce motor response. An investigation performed by Affifi et al. (2003) also supports this conclusion. Simultaneous investigation of auditory evoked responses and respiratoryrelated evoked potentials were performed in OSAS and controls during wakefulness and sleep. An abnormal evoked response to inspiratory occlusion stimuli during NREM sleep was demonstrated in OSAS patients compared to matched normal controls. However, normal responses in the same OSAS subjects occurred with auditory stimulation. This study therefore supports the presence of a sleep-specific dampening of cortical processing of inspiratory effort-related information but presence of otherwise normal stimuli response. In summary, OSAS patients have local
406
C. GUILLEMINAULT AND V. DE LOS REYES
Patient Name: 100029 Example, 1 Subject Code: X Study Date: 02/17/2006 -37.5
(C3) - (A2) +37.5
(C4) - (A1) (O1) - (A2) (Fp1) - (A2) Chin EMG (LOC) - (A2) (ROC) - (A1)
PULSE
[EKG-L - EKG-R]
69.0
LAT RAT SaO2
+100.0 +90.0 96.0+80.0 96.0 96.0 96.0 96.0 96.0 96.0 95.0 95.0 95.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 96.0 95.0 95.0 95.0 95.0 95.0 95.0 96.0 96.0 96.0 96.0 96.0
Min 96.0
+70.0
Mic Nasal Oral Chest Abdomen 01:50:19
01:50:29
01:50:39
01:50:49
01:50:59
01:51:09
Fig. 26.3. Example of flow limitation during stage 2 nonrapid eye movement sleep in a patient with upper-airway resistance syndrome. Montage is the same as for Figure 26.1 and duration of recording is 60 seconds. Note the presence of flow limitation on the nasal cannula channel and the associated snoring on the microphone channel.
neurogenic lesions in the pharynx and upper larynx that interfere with normal control of upper-airway patency and lead to slow modulations of airway patency. Apneas and hypopneas occur due to the abnormal balance between intrathoracic effort and upper-airway muscle contractions created by local sensory pathway impairment. UARS patients do not present these local sensory destructions, or at least not in a sufficient amount to impair reflexes adjusting the upper-airway patency continuously during sleep. The studies supporting the absence of local neurogenic lesions in UARS are more limited: one study compared the responses between age- and gender-matched OSAS and UARS patients and normal controls, involving 20 subjects per group (Guilleminault et al., 2002a). The results showed similar two-point discrimination responses between UARS and controls while OSAS had abnormal responses. This study matched the results obtained by Dematteis et al. (2005) in patients with low AHI scores (5–10 events/hour).
The pathophysiological difference between OSAS and UARS is conceptualized as follows. The blunting or elimination of sensory input from the upper airway in OSA does not allow an appropriate adjustment of upper-airway muscle tone to many challenges and this leads to a too narrow upper airway at onset of inspiration, causing airway collapse. In UARS, however, the absence of neurogenic lesions in the upper airways and the persistence of sensory input lead to a faster arousal and changes despite the presence of a narrow airway related to anatomical changes at a point with variable location, from the external valve of the nose to the base of the tongue (Guilleminault et al., 1993; Bao and Guilleminault, 2004). The presence or absence of an important decrease in the size of the airway in relation to the importance of the local neurogenic lesions will lead to variable changes in blood gases and the need to call upon other stimuli to reopen a collapsing airway. Drops in oxygen saturation (SaO2) and arousal responses related to these blood gases changes will have a direct impact on the
UPPER-AIRWAY RESISTANCE SYNDROME autonomic nervous system. UARS and OSAS will lead to different autonomic nervous system stimulations. Investigation of UARS patients with low blood pressure (Guilleminault et al., 2001a; Guilleminault et al., 2004) and studies of heart rate variability using fast Fourier transformation (Guilleminault et al., 2005c) have shown that UARS subjects present an active vagal tone compared to sympathetic tone during sleep. In contrast, hyperactivity of the sympathetic tone has been well shown in OSAS patients. This sympathetic hyperactivity, initially during sleep but quickly seen during wakefulness, has been well demonstrated in OSAS using different techniques, but the most demonstrative is the continuous recording of muscle nerve sympathetic activity in the leg. This technique shows an abnormal resetting of sympathetic tone, with hyperactivity as the first sign in the development of lesions of the vascular endothelium and of hypertension. In UARS, the inhibition of sympathetic tone during sleep is related to the abnormal inspiratory effort associated with increased airway resistance. The liberation of the vagal tone left alone as the autonomic regulator during sleep is responsible for the observation of mild orthostatism and vagal dominance during sleep and sometimes during wakefulness. The absence of a clear SaO2 drop in UARS also eliminates one of the important stimuli of the sympathetic tone activity during sleep, as seen in OSAS. In summary, UARS patients have upper-airway reflexes intact during wakefulness and sleep, while they are impaired in OSAS. Furthermore, in OSAS, the presence of repetitive SaO2 drops excite sympathetic tone during sleep, leading to progressive sympathetic tone resetting and hyperactivity, a response not present in UARS.
TREATMENT In the original description of UARS by Guilleminault et al. (1993), patients were treated successfully with nasal continuous positive airway pressure (CPAP). Since then, other therapeutic alternatives have been used. CPAP is still widely tried as the first-line therapy. It is often used as a therapeutic trial to demonstrate improvement of symptoms (Guilleminault et al., 2002b). Studies have demonstrated that adding cognitive behavioral therapy to CPAP treatment is beneficial for patients with chronic insomnia or psychosomatic symptoms secondary to UARS (Guilleminault et al., 2002b; Krakow et al., 2004). On the other hand, in a randomized study conducted on postmenopausal women with UARS and chronic insomnia, radiofrequency reduction of nasal turbinates, or turbinectomy,
407
or a trial of CPAP showed better relief in daytime fatigue than behavioral treatment alone at 6 months (Guilleminault et al., 2002b). Oral appliances can also achieve satisfactory outcomes in UARS (Yoshida, 2002). Septoplasty and radiofrequency reduction of enlarged inferior nasal turbinates can be successful in treating UARS. Anatomical abnormalities also often involve soft tissues in the soft palate and the maxilla and mandible skeletal structures. If the primary cause of the abnormal breathing, such as crowded airway and narrowed jaws, is not corrected, patients will be left with the complaint of worsening “functional” symptoms, which potentially may lead to the development of local polyneuropathy. The classic surgical procedures have often been considered too aggressive for treatment of UARS. Treatment must address the cause of the syndrome and avoid progression of untreated anomalies. Uvuloflap (Powell et al., 1996) and distraction osteogenesis (Guilleminault and Li, 2004) have been helpful in the management of UARS. Orthodontic approaches, such as rapid maxillary distraction, which are conveniently performed in children and teenagers, are not directly applicable in adults. This is due to complete ossification of the maxilla and mandible. In adults, midline incisions of the maxilla and mandible are necessary prior to the placement of internal jaw distractors. Distraction osteogenesis applied to sleep-disordered breathing patients showed promising clinical improvement (Pirelli et al., 2004). This combined surgical and orthodontic treatment is much less invasive than the traditional jaw advancement surgery. However, patients are required to wear braces for an extended time after jaw expansion for orthodontic purposes. In summary, the treatment of UARS may be more demanding than OSAS, as patients usually tolerate nasal CPAP less and become quickly noncompliant. Treatment of the underlying causes of the upperairway anatomical problems is the usual approach that may consist of aggressive treatment of nasal allergies, usage of palatal soft-tissue surgery, orthognatic surgery, or the use of dental devices.
REFERENCES Affifi L, Guilleminault C, Colrain I (2003). Sleep and respiratory stimulus specific dampening of cortical responsiveness in OSAS Respir. Physiol Neurobiol 136: 221–234. American Academy of Pediatrics (2002). Clinical practice guideline: diagnosis and management of childhood obstructive sleep apnea syndrome. Pediatrics 109: 704–712. American Sleep Disorders Association Atlas Task Force (1992). EEG arousals: scoring rules and examples. A preliminary report from the Sleep Disorders Atlas Task
408
C. GUILLEMINAULT AND V. DE LOS REYES
Force of the American Sleep Disorders Association. Sleep 15: 173–184. Aviv JE, Martin JH, Keen MS et al. (1993). Air-pulse quantification of supra-glottic and pharyngeal sensation: a new technique. Ann Otol Rhinol Laryngol 102: 777–780. Aviv JE, Martin JH, Keen MS et al. (1999). Laryngopharyngeal sensory discrimination testing and the laryngeal adductor reflex. Ann Otol Rhinol Laryngol 108: 725–730. Ayap I, Norman RG, Krieger AC et al. (2000). Non-invasive detection of respiratory effort-related arousals (RERAs) by a nasal cannula/pressure transducer system. Sleep 23: 763–771. Bao G, Guilleminault C (2004). The upper airway resistance syndrome – one decade later. Curr Opin Pulm Med 10: 461–467. Black J, Guilleminault C, Colrain I et al. (2000). Upper airway resistance syndrome: central EEG power and changes in breathing effort. Am J Respir Crit Care Med 162: 406–411. Chervin RD, Burns JW, Subotic NS et al. (2004). Correlates of respiratory cycle-related EEG changes in children with sleep-disordered breathing. Sleep 27: 116–121. Dematteis M, Le´vy P, Pe´pin J-L (2005). A simple procedure for measuring pharyngeal sensation: a contribution to sleep apnoea diagnosis. Thorax 60: 418–426. Douglas NJ (2000). Upper airway resistance syndrome is not a distinct syndrome. Am J Respir Crit Care Med 161: 1413–1416. Edstrom L, Larsson H, Larsson L (1992). Neurogenic efforts on the palatopharyngeal muscle in patients with obstructive sleep apnea: a muscle biopsy study. J Neurol Neurosurg Psych 55: 916–920. Epstein MD, Chicoine SA, Hanumara RC (2000). Detection of upper airway resistance syndrome using a nasal cannula/pressure transducer. Chest 117: 1073–1077. Exar EN, Collop NA (1999). The upper airway resistance syndrome. Chest 115: 1127–1139. Flemale A, Gillard C, Dierckx JP (1988). Comparison of central venous, oesophageal and mouth occlusion pressure with water-filled catheters for estimating pleural pressure changes in healthy adults. Eur Respir J 1: 51–57. Friberg D (1999). Heavy snorer’s disease: a progressive local neuropathy. Acta Otolaryngol 119: 925–933. Friberg D, Gazelius B, Holfelt T et al. (1997). Abnormal afferent nerve endings in the soft palatal mucosa of sleep apneics and habitual snorers. Regul Pept 71: 29–36. Friberg D, Ansved T, Borg K et al. (1998a). Histological indications of a progressive snorer’s disease in an upperairway muscle. Am J Resp Crit Care Med 157: 586–593. Friberg D, Gazelius B, Linblad LE et al. (1998b). Habitual snorers and sleep apneics have abnormal vascular reaction of the soft palatal mucosa or afferent nerve stimulation. Laryngoscope 108: 431–436. Gastaut H, Tassinari CA, Duron B (1965). Polygraphic study of diurnal and nocturnal (hypnic and respiratory) episodic manifestations of Pickwick syndrome. Rev Neurol (Paris) 112: 568–579.
Gold AR, Dipalo F, Gold MS et al. (2003). The symptoms and signs of upper airway resistance syndrome: a link to the functional somatic syndromes. Chest 123: 87–95. Guerrero M, Lepler L, Kristo D (2001). The upper airway resistance syndrome masquerading as nocturnal asthma and successfully treated with an oral appliance. Sleep Breath 5: 93–96. Guilleminault C, Bassiri A (2005). Clinical features and evaluation of obstructive sleep apnea–hypopnea syndrome and the upper airway resistance syndrome. In: MH Kryger, TH Roth, WC Dement (Eds.), Principles and Practice of Sleep Medicine. 4th edn. WB Saunders, Philadelphia, pp. 1043–1052. Guilleminault C, Khramtsov A (2001). Upper airway resistance syndrome in children: a clinical review. Semin Pediatr Neurol 8: 207–215. Guilleminault C, Li KK (2004). Maxillomandibular expansion for the treatment of sleep-disordered breathing: preliminary result. Laryngoscope 114: 893–896. Guilleminault C, Winkle R, Korobkin R et al. (1982). Children and nocturnal snoring: evaluation of the effects of sleep related respiratory resistive load and daytime functioning. Eur I Pediatr 139: 165–171. Guilleminault C, Stoohs R, Clerk A et al. (1993). A cause of daytime sleepiness: the upper airway resistance syndrome. Chest 104: 781–787. Guilleminault C, Stoohs R, Kim YD et al. (1995). Upper airway sleep disordered breathing in women. Ann Intern Med 122: 493–501. Guilleminault C, Faul JL, Stoohs R (2001a). Sleepdisordered breathing and hypotension. Am J Respir Crit Care Med 164: 1242–1247. Guilleminault C, Poyares D, Palombini L et al. (2001b). Variability of respiratory effort in relationship with sleep stages in normal controls and upper airway resistance syndrome patients. Sleep Med 2: 397–406. Guilleminault C, Kim YD, Chowdhuri S et al. (2001c). Sleep and daytime sleepiness in upper airway resistance syndrome compared to obstructive sleep apnea syndrome. Eur Respir J 17: 1–10. Guilleminault C, Li K, Chen NH et al. (2002a). Two-point palatal discrimination in patients with upper airway resistance syndrome, obstructive sleep apnea syndrome, and normal control subjects. Chest 122: 866–870. Guilleminault C, Palombini L, Poyares D et al. (2002b). Chronic insomnia, post-menopausal women, and SDB. Part 2: Comparison of non-drug treatment trials in normal breathing and UARS post-menopausal women complaining of insomnia. J Psychosomat Res 53: 617–623. Guilleminault C, Khramtsov A, Stoohs RA et al. (2004). Abnormal blood pressure in pre-pubertal children with sleep-disordered breathing. Pediatr Res 55: 76–84. Guilleminault C, Lee JH, Chan A (2005a). Pediatric obstructive sleep apnea syndrome. Arch Pediatr Adolesc Med 159: 775–785. Guilleminault C, Poyares D, Rosa A et al. (2005c). Heart rate variability, sympathetic and vagal balance, and EEG
UPPER-AIRWAY RESISTANCE SYNDROME arousal in upper airway resistance and mild OSA. Sleep Med 6: 451–457. Guilleminault C, Kirisoglu C, Rosa A da et al. (2006a). Sleepwalking, a disorder of NREM sleep instability. Sleep Med 7: 163–170. Guilleminault C, Kirisoglu C, Poyares A et al. (2006b). Upper airway resistance syndrome: an outcome study on a retrospective cohort. J Psychiatr Res 40 (3): 273–279. Jung R, Kuhlo W (1965). Neurophysiological studies of abnormal night sleep and the pickwickian syndrome. Prog Brain Res 18: 140–159. Kimoff JR, Sforza E, Champagne V et al. (2001). Upper airway sensation in snoring and obstructive sleep apnea. Am J Respir Crit Care Med 164: 250–255. Krakow B, Melendrez D, Lee SA et al. (2004). Refractory insomnia and sleep-disordered breathing: a pilot study. Sleep Breath 8: 15–29. Lewin DS, Pinto MD (2004). Sleep disorders and ADHD: shared and common phenotypes. Sleep 27: 188–189. Lopes MC, Guilleminault C (2005). Cyclic alternating pattern in adults with upper airway resistance syndrome. Sleep 28 (S1): A184. Loube DI, Andrada T, Howard RS (1999). Accuracy of respiratory inductive plethysmography for the diagnosis of upper airway resistance syndrome. Chest 115: 1333–1337. MacKenzie RA, Skuse NF, Lethelean AF (1977). A microelectrode study of peripheral neuropathy in man. Part 2. Response to conditioning stimuli. J Neurosci 34: 175–179. Mallampati SR, Gatt SP, Gugino LD et al. (1985). A clinical sign to predict difficult tracheal intubation: a prospective study. Can Anaesth Soc J 32: 429–434. Nanba S, Ohsaki R, Shiomi T (2002). Apparatus and method for electronically predicting pleural pressure from pulse wave signals. United States Patent Application US2002/ 0143261 A1.
409
Nguyen ATD, Jobin V, Payne R et al. (2005). Laryngeal and velo-pharyngeal sensory impairment in obstructive sleep apnea. Sleep 28: 585–593. Norman RG, Ahmed MM, Walslebel JA et al. (1997). Detection of respiratory events during NPSG: nasal cannula/ pressure sensor versus thermistor. Sleep 20: 1175–1184. Pirelli P, Saponara M, Guilleminault C (2004). Rapid maxillary expansion in children with obstructive sleep apnea syndrome. Sleep 27: 761–766. Powell N, Riley R, Guilleminault C et al. (1996). A reversible uvulopalatal flap for snoring and sleep apnea syndrome. Sleep 19: 593–599. Poyares D, Guilleminault C, Rosa A et al. (2002). Arousal, EEG spectral power and pulse transit time in UARS and mild OSAS subjects. Clin Neurophysiol 113: 1598–1606. Serebrisky D, Cordero R, Mandeli J et al. (2002). Assessment of inspiratory flow limitation in children with sleep-disordered breathing by a nasal cannula pressure transducer system. Pediatric Pulmonol 33: 380–387. Series F, Simoneau JA, St.Pierre S et al. (1996). Characteristics of the genioglossus and musculus uvulae in sleep apnea–hypopnea syndrome and in snorers. Am J Resp Crit Care Med 153: 1870–1874. Stoohs RA, Blum HC, Knaak L et al. (2004). Non-invasive estimation of esophageal pressure based on intercostals EMG monitoring. IEEE IMB 3867–3869. Virkkula P, Silvola J, Maasilta P et al. (2002). Esophageal pressure monitoring in detection of sleep-disordered breathing. Laryngoscope 112: 1264–1270. Woodson BT, Garancia J, Toohill RJ (1991). Histopathologic changes in snoring and obstructive sleep apnea syndrome. Laryngoscope 101: 1318–1332. Yoshida K (2002). Oral device therapy for the upper airway resistance syndrome patient. J Prosthet Dent 87: 427–430.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 27
Central sleep apnea ALLAN I. PACK * Division of Sleep Medicine and Center for Sleep and Respiratory Neurobiology, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
Central sleep apnea is much less common than obstructive sleep apnea. It occurs when there is absent neural output to both the respiratory pump muscles, e.g., the diaphragm, and the upper-airway muscles. This chapter describes current knowledge about the different conditions in which central apnea occurs.
DEFINITION A central apneic event is said to be present when there is cessation of respiratory effort for > 10 seconds. It can be difficult to determine when an individual event is central or obstructive. The gold standard method is esophageal pressure monitoring, but this is not routinely performed in most clinical sleep laboratories. Rather, inferences are made from assessment of chest and abdominal motion. For an event to be central, there should be absent motion in both the chest and abdomen signals. In an obstructive event, one classically sees paradoxical motion during the event, i.e., the chest is moving out while the abdomen is moving in (or vice versa). Assessment by this methodology is not totally reliable, however, since misclassification can occur when results from this approach are compared to esophageal pressure monitoring (for review, see American Academy of Sleep Medicine, 1999). Thus, esophageal pressure monitoring is needed if one wishes to be certain that the events are central. In one of the more common types of central sleep apnea – Cheyne–Stokes respiration – it is the total pattern of respiration with waxing and waning of ventilation that defines the abnormality (see below).
HYPERCAPNIC CENTRAL SLEEPAPNEA AND SLEEP HYPOVENTILATION SYNDROME Central sleep apnea syndromes can be divided into those where the subject is hypercapnic and those in which a major pathogenetic mechanism is hypocapnia (for review, see Eckert et al. (2007)). Hypercapnic central sleep apnea can occur in a number of neurological disorders. The most classic form is congenital sleeprelated hypoventilation, also called Ondine’s curse. Individuals with this can ventilate normally during wakefulness but have marked hypoventilation, including episodes of apnea, during sleep. They have absent ventilatory responses to carbon dioxide. We now know that in the majority of cases there is a typical mutation in the POX2B gene (Amiel et al., 2003). This mutation usually arises de novo and the typical mutation is a polyalanine repeat with 25–33 repeats in exon 3 (Amiel et al., 2003; Weese-Mayer et al., 2003) (for review, see Weese-Mayer et al., 2005). Patients with this entity typically present early in life. Rarer cases have been described who present as adults (Antic et al., 2006). Such cases have fewer polyalanine repeats in the gene than those patients who present in the early years of life (Antic et al., 2006). Other neurological disorders that can lead to hypoventilation and central apnea during sleep include Shy–Drager syndrome (dysautononia), brainstem lesions, e.g., syringomyelia, and lesions of the spinal cord. The criteria for sleep hypoventilation syndrome were laid out as part of the “Chicago criteria” (American Academy of Sleep Medicine, 1999). It is not necessary to have frank apnea to make this diagnosis.
*Correspondence to: Allan I. Pack, M.B.Ch.B., Ph.D., Center for Sleep and Respiratory Neurobiology, Translational Research Laboratories, 125 South 31st Street, Suite 2100, Philadelphia, PA 19104-3403 USA. Tel: (215) 746-4806, Fax: (215) 746-4814, E-mail: pack@mail. med.upenn.edu
412
A.I. PACK
The diagnostic criteria are that an individual must fulfill A and B in the list below. A. One or more of the following: ● cor pulmonale ● pulmonary hypertension ● excessive sleepiness – not explained by other factors ● erythrocytosis ● awake PCO2 > 45 mmHg B. Overnight monitoring demonstrates one or more of the following: ● an increase in PCO2 during sleep >10 mmHg ● oxygen desaturation (sustained) not explained by events. In developing these criteria, the authors argued that we should move away from discussing specific syndromes such as obesity hypoventilation since there are often in the same individual different factors that contribute to the sleep-related hypoventilation, e.g., obesity and some degree of chronic obstructive pulmonary disease. This suggestion does not seem, however, to have had a major effect since current literature still reports findings in obesity hypoventilation. The various contributing factors to sleep-related hypoventilation are given in Table 27.1.
HYPOCAPNIC CENTRAL APNEA The other type of central sleep apnea is hypocapnic (normocapnic) sleep apnea. There are three major causes: (1) idiopathic central sleep apnea; (2) central apnea at high altitude; and (3) Cheyne–Stokes respiration. Certain aspects of their pathogenesis are common to all types, i.e., the permissive role of hypocapnia. One of the most profound changes in ventilatory control with sleep is the emergence of a CO2dependent apnea threshold (Figure 27.1). In a seminal study, Skatrud and Dempsey (1983) showed that awake PCO2 could be reduced by passive hyperventilation to low levels and rhythmic respiration continues. There Table 27.1 Sleep hypoventilation syndromes Predisposing factors Morbid obesity (body mass index >35 kg/m2) Chest wall restrictive disorders Neuromuscular disease Brainstem or high cord lesions Idiopathic central hypoventilation Obstructive lung disease Hypothyroidism Medications that suppress ventilatory drive
CO2-dependent apnea threshold in sleep Apnea threshold awake
Apnea threshold sleep
W
10
20
30
S
40
50
PaCO2 W = wakefulness S = NREM sleep
Fig. 27.1. Schematic demonstrating the concept of the CO2dependent apnea threshold during sleep. During wakefulness (W) the arterial PCO2 can be reduced as low as 20 mmHg and rhythmic respiration will continue. There is a strong wakefulness drive to ventilation that is not coupled to the chemical stimuli (CO2, O2). In nonrapid eye movement (NREM) sleep (S), arterial PCO2 rises, primarily due to increased upper-airway resistance as a result of reduction of activity in upper-airway dilator muscles. During NREM sleep, reduction in arterial PCO2 to just below the normal level in wakefulness results in central apnea. The emergence of the CO2-dependent apnea threshold during sleep is a major part of the mechanism for central apnea, and why hypocapnia is permissive of central apneas during sleep.
is a powerful wakefulness stimulus to respiration that is not dependent on chemical drive. With sleep onset, PCO2 rises, primarily due to an increase in upperairway resistance secondary to reduction of neural output to upper-airway dilator muscles. Passive hyperventilation of subjects in nonrapid eye movement (NREM) sleep reveals that reducing PCO2 to just below the original wake level results in apnea. Thus, during NREM sleep there is a CO2-dependent apnea threshold and hence hypocapnia that brings subjects closer to this threshold is permissive of central apnea during sleep. The emergence of this threshold is produced by loss of the wakefulness drive for respiration. The other aspect that is common to the pathogenesis of hypocapnic central apnea is unstable operation of the chemical feedback system for ventilation (Khoo et al., 1982, 1991). Control systems are unstable if they are hyperresponsive and there is a delay between the plant (the lung) and the feedback sensors (in this case, the peripheral and central chemoreceptors). Responsiveness of the system is determined by the overall loop gain, i.e., the product of the feedback gain – change in ventilation for a given increment in PCO2 – and the plant or feedforward gain – change in PCO2 for a given increase in ventilation. Unstable operation of the control
CENTRAL SLEEP APNEA system, coupled with the CO2-dependent apnea threshold, underlies the central apneas that occur at high altitude and in patients with congestive heart failure (CHF) with Cheyne–Stokes respiration. At high altitude the major destabilizing factor is the enhanced ventilatory response due to hypoxia, mediated by the peripheral chemoreceptors. Thus, the cycle time of oscillations in ventilation at high altitude is shorter (15–30 seconds) than that occurring in Cheyne–Stokes in CHF (60–90 seconds). Given this description, it is surprising that acetazolamide, a diuretic that produces a metabolic acidosis and hence is a ventilatory stimulant, is used to treat central apnea with beneficial effects. The basis of its effectiveness has been shown in animal studies (Nakayama et al., 2002). With acetazolamide, PCO2 falls but the CO2-dependent apnea threshold falls more, so that the difference between the eupneic PCO2 and the PCO2 at which apnea occurs is larger, i.e., it is more difficult to reach the PCO2 at which apnea occurs. Effectiveness of acetazolamide in reducing central apneas has been shown in subjects at high altitude (White et al., 1982; DeBacker et al., 1995) and in patients with CHF and Cheyne–Stokes respiration (Javaheri, 2006).
Idiopathic central apnea This is a relatively uncommon condition, and most of the literature on this entity comes from the Toronto group of Dr. Douglas Bradley. These subjects breathe normally awake and they develop repetitive central apneas during sleep. To make the diagnosis, such subjects need to have apneas > 5/hour, with >85% being central (Bradley et al., 1986). Like classic Cheyne– Stokes respiration (see below), when arousals occur, they do not occur at the end of the apnea as in obstructive events, but rather at the peak of the ventilatory phase of their cyclical oscillation in ventilation. This results in sleep fragmentation, and hence subjects with idiopathic central apnea can be excessively sleepy. Such subjects have lower PCO2 during wakefulness, of the order of 35 mmHg, and an increased ventilatory response to CO2. The basis for this is unknown. The apneas in such patients can be abolished by giving the subjects small amounts of CO2 to breathe during sleep, of the order of an FICO2 of 2.0%, thereby demonstrating the permissive role of hypocapnia (Xie et al., 1997). This is currently, however, not used as a routine therapy.
Central sleep apnea at altitude In individuals going to altitude, central sleep apnea will occur. As with idiopathic central apnea, the PCO2 is low and central apneas can be frequent in NREM sleep.
413
Table 27.2 Typical results during sleep at altitude (5050 meters)
Subject
Central apnea index
Mean sleep SaO2 (%)
PaCO2 (mmHg)
1 2 3 4 5 6
141.8 25.3 20.9 129.9 30 40.5
76 76 77 69 51 68
25.3 25.1 25.2 31.4 31.6 28.6
(Data from Burgess et al. (2004).)
Typical results during NREM sleep at high altitude are shown in Table 27.2 (Burgess et al., 2004). Acetazolamide improves the degree of respiratory disturbance during sleep (White et al., 1982; DeBacker et al., 1995).
Cheyne–Stokes respiration The most common type of central sleep apnea seen clinically is Cheyne–Stokes respiration. This was originally described in the early part of the 19th century by two Irish physicians in Dublin (Cheyne, 1818; Stokes, 1854). It occurs in patients with stroke and in those with CHF. The latter is more studied. In stroke, there is no relationship between either the severity of the stroke or its location and the presence of Cheyne– Stokes respiration (Bassetti et al., 1997). Cheyne–Stokes is recognized from its classic pattern, with the repetitive waxing and waning of ventilation with central apneas at the nadir of ventilation. Arousals, when they occur, arise at the peak of the ventilatory phase (Figure 27.2). Cheyne–Stokes is said to be present when the following are seen (American Academy of Sleep Medicine, 1999): (1) at least three consecutive cycles of a cyclical crescendo–decrescendo change in the breathing cycle, typically lasting 60 seconds; (2) at least one of the following: five or more central apneas or hypopneas/ hour of sleep and/or cyclical crescendo–decrescendo duration of at least 10 minutes. To assess severity of the respiratory disturbance, one can count either the number of central apneas, thereby permitting evaluation of the central apnea index, or the percentage of sleep during which the Cheyne–Stokes pattern is present. Recent excitement about treating Cheyne–Stokes in CHF comes from earlier observations (for review, see Pepin et al. (2006). First, studies suggested that in patients with stable CHF and systolic dysfunction (left ventricular ejection fraction < 45%), central apnea with Cheyne–Stokes respiration was extremely common,
414
A.I. PACK
Untreated Cheyne-Stokes EMG Arousals
Awakening
EOG EEG Ribcage Apneas Abdomen Airflow SaO2 95% 85% 60 sec
Hypoxia
Fig. 27.2. Major features of Cheyne–Stokes respiration. There is a cyclical pattern of respiration with waxing and waning of ventilation (see airflow recording). At the nadir of ventilation, central apneas may occur. With this cyclical pattern there is oscillation in arterial blood gas values: see trace of oxygen saturation (bottom trace). The cycle time of these ventilatory oscillations is 60–90 seconds. If arousal occurs, it typically coincides with the peak of the ventilatory effect and not at the termination of apnea, i.e., in contrast to the timing of the arousal in the case of obstructive sleep apnea. EMG, electromyogram; electrooculogram; EEG, electroencephalogram.
occurring in 40% of all such patients (Javaheri et al., 1998). But such numbers were generated before the recent changes in medical management of such patients, in particular the now widespread use of beta-blockers as a result of large clinical trials (Bristow et al., 1996; Colucci et al., 1996; Packer et al., 2001). Beta-blockers blunt the increase in the ventilatory response to hypoxia produced by norepinephrine (Heistad et al., 1972), hence stabilizing the overall ventilatory control system in such patients and making Cheyne–Stokes respiration less likely. Patients with CHF and similar degree of systolic dysfunction have less central apnea and oxygen desaturation when on beta-blockers than those who are not (Kohnlein and Welte, 2007; Tamura et al., 2007). Treatment of such patients with beta-blockers over a period of months decreases the central apnea index (Tamura et al., 2007). Thus, the current prevalence of Cheyne–Stokes respiration in this population of patients is likely to be lower than previously reported. Given these pathogenetic arguments, and the findings about the use of beta-blockers, it is surprising that a recent study of patients with CHF, the majority of whom were on beta-blockers (85%), still reports a very high prevalence of sleep-disordered breathing (76%): 40% of these patients had central sleep apnea (Oldenburg et al., 2007). This prevalence study needs to be replicated in other heart failure populations.
Risk factors for Cheyne–Stokes respiration in this patient group include hypocapnia (Sin et al., 1999) (for identified risk factors, see Table 27.3). The role of hypocapnia as a risk factor was also demonstrated by Javaheri et al (1998) and, as in idiopathic central apnea, Cheyne–Stokes respiration can be abolished by inhaling small amounts of CO2 (around an FICO2 of 2.0% in the inspirate) (Lorenzi-Filho et al., 1999). The strong association of atrial fibrillation and the presence of Cheyne–Stokes respiration (Table 27.3) has also been shown in idiopathic central apnea syndrome. Patients with idiopathic central apnea have a higher prevalence of atrial fibrillation than either controls or patients with obstructive sleep apnea (Leung et al., 2005). Table 27.3 Risk factors for central sleep apnea in congestive heart failure
Gender: male Age: > 60 years Atrial fibrillation Hypocapnia (PaCO2 <38 mmHg)
Odds ratio
Confidence interval
3.5 2.37 4.13 4.33
1.39–8.84 1.35–4.15 1.53–11.14 2.50–7.52
(Data from Sin et al. (1999).)
CENTRAL SLEEP APNEA 415 Thus, atrial fibrillation and central apnea may share some (This difference was only significant when 2 subjects common pathogenetic mechanisms. in the CPAP arm of the study, who did not use the Cheyne–Stokes respiration in CHF is associated therapy, were dropped from the analysis.) with adverse consequences. Such patients may be These smaller studies led to an ambitious multicenexcessively sleepy due to sleep fragmentation. They ter study that was conducted in Canada, the Continuhave increased sympathetic activity with higher levels ous Positive Airway Pressure for patients with central of norepinephrine (Naughton et al., 1995a). Most sleep apnea and heart failure (CANPAP) study. Results importantly, studies indicate that CHF patients with of a planned interim analysis were, however, disapCheyne–Stokes respiration have poorer cardiac outpointing (Bradley et al., 2005) leading the Data Safety comes, i.e., increased mortality, as compared to those Monitoring Board to propose that the study be stopped without (Lanfranchi et al., 1999). This led to the notion on grounds of futility. that actively treating Cheyne–Stokes respiration in In the CANPAP study, patients with CHF and patients with CHF would improve cardiac outcomes. Cheyne–Stokes with an AHI > 15 episodes/hour were randomized into CPAP (n ¼ 128) or normal medical management (n ¼ 130) (Bradley et al., 2005). CPAP Treatment of Cheyne–Stokes respiration in reduced the AHI significantly (P < 0.001) but subjects patients with congestive heart failure still had substantial respiratory disturbance and central Different modalities have been used to treat Cheyne– apneas during sleep (mean AHI pre-CPAP ¼ 40 epiStokes respiration in patients with CHF. First is the sodes/hour; post-CPAP ¼ 19 episodes/hour). Over the use of oxygen. This reduces the peripheral chemosensi5-year follow-up, the total number of deaths and cartivity and hence tends to stabilize ventilation. In diac transplants, the primary composite end-point in patients with Cheyne–Stokes respiration oxygen the trial, was not different between the CPAP treatreduces the overall respiratory disturbance index but ment group and the control group (32 such events in does not normalize it (Hanly et al., 1989; Franklin each group). However, there were significantly more et al., 1997; Javaheri et al., 1999; Krachman et al., events, i.e., deaths or need for transplant, early in the 1999). Oxygen also improves exercise capacity in such trial in the CPAP treatment group (P ¼ 0.02). This difpatients (Andreas et al., 1996). ference was significant until 18 months after the start Theophylline has also been shown to reduce central of the study. By year 5 of follow-up, the number of apneas in such patients (Javaheri et al., 1996) but conevents had equalized, although the number of subjects cerns about theophylline increasing ectopy have limited who were followed for 5 years was small. its use for this indication. A case report indicates the Part of the issue with this trial is that patients in the value of theophylline in the acute setting in CPAP group were only partially treated. CPAP only patients with severe Cheyne–Stokes respiration (Pesek produced about a 50% fall in respiratory events during et al., 1999). sleep, resulting in the average respiratory disturbance Continuous positive airway pressure (CPAP) has during sleep on active treatment still being in the range also been used. For this indication, CPAP pressure is of moderate sleep apnea severity (19 episodes/hour). not titrated in a sleep laboratory as it is for obstructive Moreover, the average compliance with CPAP was low, sleep apnea. Rather, patients are started on a low level being on average 4.3 hours during the first 3 months of of CPAP, e.g., 5.0 cm H2O, and the pressure is therapy and 3.6 hours at 1 year and beyond. increased slowly over days with the goal of reaching That the negative result in this important study is the maximally tolerated pressure or to 10.0 cm H2O. related to inadequate therapy is supported by addiPatients with CHF and Cheyne–Stokes may have partional analyses of the data. When analysis is restricted oxysmal nocturnal dyspnea, waking up during sleep to those whose respiratory disturbance on CPAP was in the ventilatory phase of the Cheyne–Stokes cycle, reduced to less than 15 episodes/hour (n ¼ 57), there and therefore have difficulty tolerating CPAP. was significant improvement in left ventricular ejection An initial small study in this area (Naughton et al., fraction and reduced rates of death and need for trans1995b) showed that, compared to normal medical manplant as compared to either control subjects (no CPAP) agement (n ¼ 15), CPAP (n ¼ 14) reduced the apnea– or to those on CPAP who still had an AHI > 15 epihypopnea index (AHI) and improved left ventricular sodes/hour on therapy (n ¼ 43) (Arzt et al., 2007). Nevejection fraction and symptoms of heart failure over a ertheless, given that this was not the primary analysis 3-month period. Using a similar design, CPAP (n ¼ 12) plan for the study, one has to conclude that data are was also shown to improve transplant-free survival currently insufficient to recommend use of CPAP for time over a 3.5-year period compared to medical the treatment of Cheyne–Stokes respiration in patients management (n ¼ 15; P ¼ 0.017) (Sin et al., 2000). with CHF (Olson and Somers, 2007).
416
A.I. PACK Normal effort
Pressure cm H2O
Cessation of spontaneous effort
Resumption of normal effort
15 9 5 0
Respiratory airflow
Fig. 27.3. Schematic illustrating the action of the auto-CS system, now called an adaptive servo-ventilator. There is a fixed expiratory pressure, in this case at 5.0 cm H2O. This is the lowest line in the top tracing of pressure. The inspiratory pressure (lines above this on the top tracing) is adjustable and is set by the device depending on the ongoing level of ventilation. In this example, at the beginning of the traces (left side), ventilation is relatively normal and inspiratory pressure is set at 9.0 cm H2O. In contrast, when breathing declines (the middle portion of the trace), inspiratory pressure is raised to 15.0 cm H2O to maintain ventilation. The resulting pattern of airflow is shown in the bottom trace.
60
40 Events/hr
There is, moreover, another positive airway pressure therapy now available for the treatment of Cheyne– Stokes respiration. It was originally called auto-CS but is now called adaptive servo-ventilation. It is ingenious (for schematic of action, see Figure 27.3). With this device, a fixed expiratory pressure (E) is established. The inspiratory pressure (I), however, varies from breath to breath, essentially varying the level of pressure support. The subject’s ventilation is servocontrolled by the machine with a high-gain integral controller with a time constant of 3 minutes. Thus, during the hypoventilatory phase of the Cheyne–Stokes cycle, the I pressure is set high to assist ventilation while during the height of the ventilation it is set low. Thus, the device essentially counteracts the effects of Cheyne–Stokes respiration and removes respiratory events during sleep in such patients on the first night of use. The superior efficacy of this device over CPAP or standard bilevel therapy or oxygen, at least on a single night of therapy, was demonstrated by Teschler et al. (2001) (Figure 27.4). It is to be emphasized, however, that application of CPAP to these patients is not based on a single-night titration but rather slow increases in pressure over a period of days or weeks. Given this superior efficacy, it is unfortunate that the adaptive servo-ventilator was not used as part of the CANPAP study. While there are small studies indicating benefit of therapy with this modality in these patients, there is currently no large randomized trial. Thus, although intriguing, the current evidence is insufficient to recommend this form of therapy in patients with CHF who have Cheyne–Stokes respiration. An important caveat about these studies is that separation of sleep-disordered breathing into pure
20
0 vs control: vs ASV:
Control
Oxygen
CPAP
Bilevel
ASV
P<0.001 P<0.001 P<0.001 P<0.001 P<0.001 P<0.001 P<0.001 P=0.02
Fig. 27.4. Results comparing the central apnea index in a group of patients with congestive heart failure and Cheyne–Stokes respiration with different treatment modalities for a single night. The data with no treatment are shown on the left (labeled control) and that with oxygen, continuous positive airways pressure (CPAP), bilevel pressure with fixed expiratory and inspiratory pressure, and with the adaptive servo-ventilator (ASV) are shown. The P-values for various statistical comparisons are shown below. On a single night of application the adaptive servo-ventilator is the most efficacious and essentially abolishes sleep-disordered breathing. (Reproduced from Teschler et al. (2001). with permission.)
Cheyne–Stokes respiration and obstructive sleep apnea is somewhat artificial. Cyclical neural output affects not only the diaphragm but also the activity of upperairway dilator muscles. Thus, both Cheyne–Stokes respiration and obstructive apneas are often seen in the
CENTRAL SLEEP APNEA same patient during the course of a single night. The fraction of episodes that are central and those that are obstructive may vary from night to night in these patients (Tkacova et al., 2006). From a therapeutic point of view the best current approach to patients with CHF who demonstrate Cheyne–Stokes respiration during sleep is to consider this as a marker of inadequate medical therapy of their heart failure. The degree of Cheyne–Stokes respiration can be improved by, for example, aggressive diuresis or by institution of beta-blockers. There is an association in individual subjects with the amount of Cheyne– Stokes respiration within a night and the measured pulmonary wedge pressure (Solin et al., 1999). Thus, the finding of Cheyne–Stokes respiration in patients with CHF merits referral to a specialized heart failure program for optimization of medical management. Cheyne–Stokes may, however, persist in some patients even after optimizing medical management of their heart failure. There are, as outlined above, a number of distinct treatment options. Given our current state of knowledge, a reasonable initial strategy for persistent Cheyne–Stokes after optimization of medical therapy is use of nocturnal oxygen.
COMPLEX SLEEP APNEA While the adaptive servo-ventilator was originally developed for treatment of Cheyne–Stokes respiration, particularly those with CHF, a new potential indication for this unique form of positive airway pressure has emerged – complex sleep apnea. The concept of complex sleep apnea is that, in patients with obstructive sleep apnea who are being titrated with CPAP for therapy, there is emergence of central sleep apnea and a ventilatory pattern that is similar to Cheyne–Stokes respiration (Morgenthaler et al., 2006). The pathogenesis of this is unknown. It remains a controversial entity. Some would argue that it is an artifact of less than optimal CPAP titration with excessive positive airway pressure being employed. The entity was originally described based on retrospective analysis of sleep studies in over 200 patients investigated at the Mayo Clinic (Morgenthaler et al., 2006). All studies were split-night studies. Surprisingly, the prevalence of complex sleep apnea was found to be high, i.e., 15%, with obstructive sleep apnea being 84% and pure central sleep apnea being 0.4%. To date, prevalence studies of complex sleep apnea have not been reported from other sleep centers and this finding needs to be replicated. There are already studies reporting treatment of this new entity, albeit in very small samples of patients. As in other types of central sleep apnea described above,
417
the addition of CO2 to the inspirate can abolish central apneas in patients with complex sleep apnea (Thomas et al., 2005). In 9 patients with complex sleep apnea, the adaptive servo-ventilator described above also essentially abolished all sleep-disordered breathing (Morgenthaler et al., 2007). Further studies on this entity are needed.
CONCLUSION Central sleep apnea is much less common than obstructive sleep apnea. The state-dependent CO2 apnea threshold plays a permissive role and hence hypocapnia is an important risk factor for the occurrence of central apnea in subjects at high altitude and in patients with CHF. While a number of different treatment modalities have been employed for the management of specific types of central apnea, the current data do not lead to a clear picture of what strategies to employ in particular patients. There was early enthusiasm that use of CPAP in patients with CHF with Cheyne–Stokes respiration would produce improved cardiac outcomes. It is, therefore, disappointing that the largest randomized trial done to date in the field of sleep-disordered breathing, the CANPAP study, evaluating the effect of CPAP on a cardiac composite end-point (total death, plus need for cardiac transplantation) in patients with CHF and Cheyne–Stokes respiration was negative (Bradley et al., 2005). There are new treatment modalities, in particular the adaptive servo-ventilator, but currently studies using this device are small, and there is a need for larger randomized trials before the role of this new therapy can be established. Currently the indications for its use are unclear. There is, finally, the possibility that a new type of sleep-disordered breathing, complex sleep apnea, has been identified. It is too early to determine whether this new entity will stand the test of time and further investigation is needed. Thus, central apnea is an area much in need of more studies, with a larger number of patients, using randomized designs. The history of this field is a cautionary tale, and indicates the problem of drawing definitive conclusions from studies with small numbers of patients.
REFERENCES American Academy of Sleep Medicine (1999). Sleep-related breathing disorders in adults: recommendations for syndrome definition and measurement techniques in clinical research. The Report of an American Academy of Sleep Medicine Task Force. Sleep 22 (5): 667–689. Amiel J, Laudier B, Attie-Bitach T et al. (2003). Polyalanine expansion and frameshift mutations of the paired-like
418
A.I. PACK
homeobox gene PHOX2B in congenital central hypoventilation syndrome. Nat Genet 33 (4): 459–461. Andreas S, Clemens C, Sandholzer H et al. (1996). Improvement of exercise capacity with treatment of Cheyne–Stokes respiration in patients with congestive heart failure. J Am Coll Cardiol 27 (6): 1486–1490. Antic NA, Malow BA, Lange N et al. (2006). PHOX2B mutation-confirmed congenital central hypoventilation syndrome: presentation in adulthood. Am J Respir Crit Care Med 174 (8): 923–927. Arzt M, Floras JS, Logan AG et al. (2007). Suppression of central sleep apnea by continuous positive airway pressure and transplant-free survival in heart failure: a post hoc analysis of the Canadian Continuous Positive Airway Pressure for Patients with Central Sleep Apnea and Heart Failure Trial (CANPAP). Circulation 115 (25): 3173–3180. Bassetti C, Aldrich MS, Quint D et al. (1997). Sleep-disordered breathing in patients with acute supra- and infratentorial strokes. A prospective study of 39 patients. Stroke 28 (9): 1765–1772. Bradley TD, McNicholas WT, Rutherford R et al. (1986). Clinical and physiologic heterogeneity of the central sleep apnea syndrome. Am Rev Respir Dis 134 (2): 217–221. Bradley TD, Logan AG, Kimoff RJ et al. (2005). Continuous positive airway pressure for central sleep apnea and heart failure. N Engl J Med 353 (19): 2025–2033. Bristow MR, Gilbert EM, Abraham WT et al. (1996). Carvedilol produces dose-related improvements in left ventricular function and survival in subjects with chronic heart failure. MOCHA Investigators. Circulation 94 (11): 2807–2816. Burgess KR, Johnson PL, Edwards N (2004). Central and obstructive sleep apnoea during ascent to high altitude. Respirology 9 (2): 222–229. Cheyne J (1818). A case of apoplexy in which the fleshy part of the heart converted into fat. Dublin Hospital Report. Colucci WS, Packer M, Bristow MR et al. (1996). Carvedilol inhibits clinical progression in patients with mild symptoms of heart failure. US Carvedilol Heart Failure Study Group [see comment]. Circulation 94 (11): 2800–2806. DeBacker WA, Verbraecken J, Willemen M et al. (1995). Central apnea index decreases after prolonged treatment with acetazolamide. Am J Respir Crit Care Med 151 (1): 87–91. Eckert DJ, Jordan AS, Merchia P et al. (2007). Central sleep apnea: pathophysiology and treatment. Chest 131 (2): 595–607. Franklin KA, Eriksson P, Sahlin C et al. (1997). Reversal of central sleep apnea with oxygen. Chest 111 (1): 163–169. Hanly PJ, Millar TW, Steljes DG et al. (1989). The effect of oxygen on respiration and sleep in patients with congestive heart failure. Ann Intern Med 111 (10): 777–782. Heistad DD, Wheeler RC, Mark AL et al. (1972). Effects of adrenergic stimulation on ventilation in man. J Clin Invest 51 (6): 1469–1475. Javaheri S (2006). Acetazolamide improves central sleep apnea in heart failure: a double-blind, prospective study. Am J Respir Crit Care Med 173 (2): 234–237.
Javaheri S, Parker TJ, Wexler L et al. (1996). Effect of theophylline on sleep-disordered breathing in heart failure. N Engl J Med 335 (8): 562–567. Javaheri S, Parker TJ, Liming JD et al. (1998). Sleep apnea in 81 ambulatory male patients with stable heart failure. Types and their prevalences, consequences, and presentations. Circulation 97 (21): 2154–2159. Javaheri S, Ahmed M, Parker TJ et al. (1999). Effects of nasal O2 on sleep-related disordered breathing in ambulatory patients with stable heart failure. Sleep 22 (8): 1101–1106. Khoo MC, Kronauer RE, Strohl KP et al. (1982). Factors inducing periodic breathing in humans: a general model. J Appl Physiol 53 (3): 644–659. Khoo MC, Gottschalk A, Pack AI (1991). Sleep-induced periodic breathing and apnea: a theoretical study. J Appl Physiol 70 (5): 2014–2024. Kohnlein T, Welte T (2007). Does beta-blocker treatment influence central sleep apnoea? Respir Med 101 (4): 850–853. Krachman SL, D’Alonzo GE, Berger TJ et al. (1999). Comparison of oxygen therapy with nasal continuous positive airway pressure on Cheyne–Stokes respiration during sleep in congestive heart failure. Chest 116 (6): 1550–1557. Lanfranchi PA, Braghiroli A, Bosimini E et al. (1999). Prognostic value of nocturnal Cheyne–Stokes respiration in chronic heart failure. Circulation 99 (11): 1435–1440. Leung RS, Huber MA, Rogge T et al. (2005). Association between atrial fibrillation and central sleep apnea. Sleep 28 (12): 1543–1546. Lorenzi-Filho G, Rankin F, Bies I et al. (1999). Effects of inhaled carbon dioxide and oxygen on Cheyne–Stokes respiration in patients with heart failure. Am J Respir Crit Care Med 159 (5 Pt 1): 1490–1498. Morgenthaler TI, Kagramanov V, Hanak V et al. (2006). Complex sleep apnea syndrome: is it a unique clinical syndrome? Sleep 29 (9): 1203–1209. Morgenthaler TI, Gay PC, Gordon N et al. (2007). Adaptive servoventilation versus noninvasive positive pressure ventilation for central, mixed, and complex sleep apnea syndromes. Sleep 30 (4): 468–475. Nakayama H, Smith CA, Rodman JR et al. (2002). Effect of ventilatory drive on carbon dioxide sensitivity below eupnea during sleep. Am J Respir Crit Care Med 165 (9): 1251–1260. Naughton MT, Benard DC, Liu PP et al. (1995a). Effects of nasal CPAP on sympathetic activity in patients with heart failure and central sleep apnea. Am J Respir Crit Care Med 152 (2): 473–479. Naughton MT, Liu PP, Bernard DC et al. (1995b). Treatment of congestive heart failure and Cheyne–Stokes respiration during sleep by continuous positive airway pressure. Am J Respir Crit Care Med 151 (1): 92–97. Oldenburg O, Lamp B, Faber L et al. (2007). Sleepdisordered breathing in patients with symptomatic heart failure: a contemporary study of prevalence in and characteristics of 700 patients. Eur J Heart Fail 9 (3): 251–257. Olson LJ, Somers VK (2007). Treating central sleep apnea in heart failure: outcomes revisited. Circulation 115 (25): 3140–3142.
CENTRAL SLEEP APNEA Packer M, Coats AJ, Fowler MB et al. (2001). Effect of carvedilol on survival in severe chronic heart failure. N Engl J Med 344 (22): 1651–1658. Pepin JL, Chouri-Pontarollo N, Tamisier R et al. (2006). Cheyne–Stokes respiration with central sleep apnoea in chronic heart failure: proposals for a diagnostic and therapeutic strategy. Sleep Med Rev 10 (1): 33–47. Pesek CA, Cooley R, Narkiewicz K et al. (1999). Theophylline therapy for near-fatal Cheyne–Stokes respiration. A case report [see comment]. Ann Intern Med 130 (5): 427–430. Sin DD, Fitzgerald F, Parker JD et al. (1999). Risk factors for central and obstructive sleep apnea in 450 men and women with congestive heart failure. Am J Respir Crit Care Med 160 (4): 1101–1106. Sin DD, Logan AG, Fitzgerald FS et al. (2000). Effects of continuous positive airway pressure on cardiovascular outcomes in heart failure patients with and without Cheyne–Stokes respiration. Circulation 102 (1): 61–66. Skatrud JB, Dempsey JA (1983). Interaction of sleep state and chemical stimuli in sustaining rhythmic ventilation. J Appl Physiol 55 (3): 813–822. Solin P, Bergin P, Richardson M et al. (1999). Influence of pulmonary capillary wedge pressure on central apnea in heart failure. Circulation 99 (12): 1574–1579. Stokes W (1854). The Diseases of the Heart and Aorta. Hodges & Smith, Dublin, Ireland. Tamura A, Kawano Y, Naono S et al. (2007). Relationship between beta-blocker treatment and the severity of
419
central sleep apnea in chronic heart failure. Chest 131 (1): 130–135. Teschler H, Dohring J, Wang YM et al. (2001). Adaptive pressure support servo-ventilation: a novel treatment for Cheyne–Stokes respiration in heart failure. Am J Respir Crit Care Med 164 (4): 614–619. Thomas RJ, Daly RW, Weiss JW (2005). Low-concentration carbon dioxide is an effective adjunct to positive airway pressure in the treatment of refractory mixed central and obstructive sleep-disordered breathing. Sleep 28 (1): 69–77. Tkacova R, Wang H, Bradley TD (2006). Night-to-night alterations in sleep apnea type in patients with heart failure. J Sleep Res 15 (3): 321–328. Weese-Mayer DE, Berry-Kravis EM, Zhou L et al. (2003). Idiopathic congenital central hypoventilation syndrome: analysis of genes pertinent to early autonomic nervous system embryologic development and identification of mutations in PHOX2b. Am J Med Genet A 123 (3): 267–278. Weese-Mayer DE, Berry-Kravis EM, Marazita ML (2005). In pursuit (and discovery) of a genetic basis for congenital central hypoventilation syndrome. Respir Physiol Neurobiol 149 (1–3): 73–82. White DP, Zwillich CW, Pickett CK et al. (1982). Central sleep apnea. Improvement with acetazolamide therapy. Arch Intern Med 142 (10): 1816–1819. Xie A, Rankin F, Rutherford R et al. (1997). Effects of inhaled CO2 and added dead space on idiopathic central sleep apnea. J Appl Physiol 82 (3): 918–926.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 28
Positive-pressure treatment of obstructive sleep apnea syndrome 1
PETER R. BUCHANAN 1 * AND RONALD R. GRUNSTEIN 2 Woolcock Institute of Medical Research, University of Sydney, Department of Respiratory Medicine, Liverpool Hospital and Sleep Medicine Consultative Service, St. Vincent’s Clinic, Sydney, Australia
2
Woolcock Institute of Medical Research, University of Sydney and Sleep Investigation Unit, Department of Respiratory and Sleep Medicine, Royal Prince Alfred Hospital and Sleep Medicine Consultative Service, St. Vincent’s Clinic, Sydney, Australia
INTRODUCTION Continuous positive airway pressure (CPAP), usually nasally applied, is the established treatment of first choice for moderate to severe obstructive sleep apnea syndrome (OSAS). Studies have provided information on different aspects of usage and compliance, as well as efficacy, of CPAP therapy. In this chapter, these data are summarized with emphasis on the practical use of CPAP therapy in clinical management of OSAS patients. Nasal CPAP therapy for sleep apnea was first described in 1981 (Sullivan et al., 1981), but there was initial skepticism of its efficacy and concern regarding its potential adverse effects on breathing (Krieger et al., 1983; Wagner et al., 1983). However, there was also early recognition of the importance of having a treatment that could essentially prevent disordered breathing during sleep in contrast to partial or variable response to surgery (Bradley and Phillipson, 1983). By 1985, over 100 patients were using this therapy on a regular basis (Grunstein et al., 1986). Subsequently, technical improvements took place in design of masks and pressure delivery systems when CPAP was commercialized. Over the past 20 years, the evidence base supporting the use of CPAP has improved in both quantity and quality, driven at least in part by the demands of government funding authorities and health maintenance organizations and the availability of industry sponsorship with the increasing commercial success of companies selling CPAP equipment (Grunstein, 1995).
Nevertheless, there are problems designing studies to assess and validate a mechanical device such as CPAP, compared with those required for medications. Performing true double-blind randomized controlled trials (RCTs) of CPAP treatment or variants are problematic. “Sham CPAP,” by its nature, will have less efficacy on unavoidably observable variables such as snoring or apnea with consequent difficulties to truly “blind” study participants. It is also quite difficult to blind effectively a CPAP therapist or doctor involved in such studies compared with pharmaceutical trials involving placebo medications. Also, the advent of automatically titrating CPAP devices has had major implications for the delivery of health care to patients with sleep apnea and for the traditional sleep laboratory–patient relationship. Currently nasal CPAP is the gold standard treatment for moderate to severe OSAS but many patients do not use it, or use it irregularly. Comparative, intention-totreat trials in all degrees of OSAS severity are needed to delineate treatment pathways in this condition. Currently, studies focusing on comparative treatments and ways in which there is better effectiveness of CPAP are forming the next phase in the historical development of this treatment modality. Although there is tremendous interest and active research in potential pharmacotherapy for OSAS, the absence of any currently available viable pharmacological therapy for sleep apnea (Grunstein et al., 2001; Abad and Guilleminault, 2006; Buchanan and Grunstein, 2006) suggests that CPAP will remain the appropriate gold standard for the foreseeable future.
*Correspondence to: Peter R. Buchanan, Sleep and Circadian Group, Woolcock Institute of Medical Research, University of Sydney, PO Box M77, Missenden Rd, Camperdown NSW 2050 Australia. Tel: þ612 9114 0439, Fax: þ612 9114 0010, E-mail: pbuchanan@med. usyd.edu.au
422
P.R. BUCHANAN AND R.R. GRUNSTEIN
CONTINUOUS POSITIVE AIRWAY PRESSURE Mode of action The concept of CPAP in managing respiratory failure is a relatively old development (Gregory et al., 1971). However, the original experiments using CPAP in sleep apnea followed from the notion that closure of the oropharynx in OSA results from an imbalance of the forces (Remmers et al., 1978) that normally keep the upper airway open. In the first description of CPAP use for treatment of OSAS in 1981 (Sullivan et al., 1981), it was suggested that nasal CPAP acts as a pneumatic splint to prevent collapse of the pharyngeal airway, by elevating the pressure in the oropharyngeal airway and reversing the transmural pressure gradient across the pharyngeal airway (Figure 28.1). This notion has been subsequently confirmed by a number of studies which either demonstrate the “pneumatic splint” effect by endoscopic or other imaging or show that CPAP does not increase upper-airway muscle activity by reflex mechanisms (Strohl and Redline, 1986). Detailed magnetic resonance imaging (MRI) has confirmed that CPAP increases airway volume and airway area, and reduces lateral pharyngeal wall thickness and upper-airway edema secondary to chronic vibration and occlusion of the airway (Schwab et al., 1996). The apparatus providing the pressure at the nasal airway must have the capacity to maintain any given pressure during inspiration (Figure 28.2). The simplest CPAP systems involve an air blower with sufficient pressure–flow characteristics to provide CPAP via a fixed resistive leak in the system (typically adjacent to the mask).
Fig. 28.1. Mechanism of upper-airway occlusion and its prevention by nasal continuous positive airway pressure (CPAP). When the patient is awake (A), muscle tone prevents collapse of the upper airway during inspiration. During sleep, the tongue and soft palate are sucked against the posterior oropharyngeal wall (B). CPAP with low pressure provides a pneumatic splint and keeps the upper airway open (C). (Adapted from Sullivan et al. (1981).)
Fig. 28.2. Nasal continous positive airway pressure. (Courtesy of A Dawes.)
CPAP and central apnea Regardless of the mechanism, nasal CPAP has been documented to be effective in eliminating both mixed and obstructive apneas (Issa and Sullivan, 1986b). Some central apneas, particularly those observed in patients with predominantly obstructive events, are also eliminated by nasal CPAP (Issa and Sullivan, 1986b) (Figure 28.3). Clearly, some central apneas are associated with increased upper-airway resistance and it could be argued that it is better to consider apnea classification as being CPAP-responsive or CPAPnonresponsive. CPAP may also be effective in central apneas associated with cardiac failure. Sometimes in patients with obstructive sleep apnea (OSA), central sleep apnea (CSA) may appear to be induced during CPAP titration studies, but mostly these CSAs will have resolved after 3 months of CPAP usage (Dernaika et al., 2007). In some instances, CPAP alone will not control severe mixed CSA and OSA and adjunctive entrainment of low concentrations of carbon dioxide, with CPAP, may further reduce sleep respiratory disturbance in such individuals (Thomas et al., 2005). In small studies adaptive servoventilation has been shown to benefit patients with complicated sleep apnea who have not responded to CPAP therapy (Allam et al., 2007; Morgenthaler et al., 2007).
PRACTICAL ASPECTS OF TREATMENT Originally, most patients commenced CPAP under supervision, usually in a hospital-based sleep laboratory. The purposes of this supervision include ensuring that the patient was appropriately educated about the therapy, to select the best interface (mask) for the
POSITIVE-PRESSURE TREATMENT OF OBSTRUCTIVE SLEEP APNEA SYNDROME
423
Fig. 28.3. Polygraphic records demonstrating prevention of central sleep apnea by continuous positive airway pressure (CPAP) applied through the nose. (A) Note the presence of central apnea at a nasal CPAP of 2 cm H2O. (B) Elevation of nasal CPAP to 6.6 cm H2O changes the apnea from a central to a mixed type. Further increase of nasal CPAP to 10 cm H2O (not shown) leads to a change in the apnea pattern from a mixed to an obstructive apnea. (C) Loud, continuous snoring occurs when the nasal CPAP is elevated to 11.5 cm H2O. (D) Finally, at a nasal CPAP of 14.5 cm H2O, the patient breathes with an open airway. EEG, electroencephalogram; EMGd, diaphragm electromyogram; IN, inspiration; Pn, nasal pressure; SaO2, arterial oxyhemoglobin saturation (scale, 100% to 75%); time scale is in seconds. Patient is in the supine position. (Adapted from Issa and Sullivan (1986b).)
individual and determine the adequacy of CPAP across the night, and to evaluate immediate acceptance or problems with the therapy. Economic pressures within health systems, however, have challenged this approach. Alternative nonlaboratory-based approaches to initiating CPAP are being applied in numerous health systems. For example, in 2004 throughout New Zealand nearly all (> 90% in some centers) CPAP initiation was implemented via either in-lab split-night or home autotitrating CPAP (A Neill, personal communication). Similarly, in the UK full in-lab CPAP titration studies are not routinely undertaken in many centers. Economic drivers have been of major importance in the adoption of these practices in these and other health services. As part of the drive toward economic rationalization, health authorities expect some evidence base for clinical CPAP titration strategies. Some such evidence has now accumulated but not all research points in the same direction. Irrespective of the location or method of CPAP titration, there is a clear demand for proper patient assessment (e.g., does the patient have awake respiratory failure or marked hypoxemia in sleep?), which, in turn, requires specific physician training and experience. Until recently there was no evidence for the safety and efficacy of CPAP titration outside a medically supervised process (Zozula and Rosen, 2001). Current evidence supports the use of trained technologists to provide patient education, technical aspects of titration, and follow-up. However, data from small patient groups have challenged the notion of close medical supervision and clearly this should be a continuing major research focus (Fitzpatrick et al., 2003; Hukins, 2004, 2005).
The first night Sleeping with a nose mask and feeling the pressure sensation of CPAP, although not necessarily uncomfortable, are certainly novel experiences for the patient. Physician explanation, video programs, and mask acclimatization sessions prior to commencing CPAP are routine in many centers. Although the benefits of these techniques have not been fully scientifically evaluated, it would seem obvious that patient education about CPAP will reduce anxiety and improve acceptance. Current evidence provides some support for the benefit of more intensive patient education in CPAP usage (Zozula and Rosen, 2001; Brin et al., 2005). On the first night of treatment, it is important to ensure that the CPAP level which is identified to be most therapeutically effective is sufficient not only to prevent apnea and oxyhemoglobin desaturation but also to prevent respiratory-related arousals in all sleep stages and in all postures of sleep (Figure 28.4). Thus, simple apnea prevention is not the sole endpoint of CPAP titration. It is important to ensure that the airflow–CPAP pressure tracing is normal and not “chopped off,” so as to avoid residual partial airway obstruction (Figure 28.5) (Grunstein, 1995). It is important to correct this flow limitation as it may indicate residual upper-airway obstruction, potentially causing arousal (Montserrat et al., 1995). Studies have emphasized the importance of proper airflow measurement in CPAP titration using pressure–flow transducers rather than thermistors or other more indirect airflow measures (Hosselet et al., 1998). Proper airflow measurement could help determine the optimal CPAP level
424
P.R. BUCHANAN AND R.R. GRUNSTEIN
Fig. 28.4. All-night recordings of arterial hemoglobin saturation in one of the earliest patients to use home continuous positive airway pressure (CPAP). Light gray bar, nonrapid eye movement sleep; dark gray bar, rapid eye movement sleep; open bar, awake. (A) Control night. (Adapted from Sullivan et al. (1981).) (B) CPAP trial night. A CPAP of 7 cm H2O was applied at arrow A and continued for the rest of the night. (Adapted from Sullivan et al. (1981).)
by providing insights regarding the etiology of arousals, whether they are related to respiratory events (respiratory-related arousals) and if increasing pressure has a beneficial effect on sleep continuity. Although acute (one-night) studies suggest that flow limitation correction may be the preferred endpoint of CPAP titration, long-term data are sparse (Meurice et al., 1998). Pursuing normalization of the respiratory disturbance index may not be the only or optimal goal in CPAP titration strategies in some OSA patients who exhibit a cyclic alternating pattern non-REM stage respiratory instability and relative nonresponsiviness to CPAP (Thomas et al., 2004). Prediction equations for starting pressures may enhance the success of
titration studies (Rowley et al., 2005) and also potentially offer the option of an effective outpatient titration setting for CPAP-providing health services (Masa et al., 2004; Stradling et al., 2004a, b; West et al., 2006). Heated humidification appears not to offer any advantages during nasal CPAP titration studies (Duong et al., 2005). When the correct CPAP level is reached and the airway is open, sleep should no longer be fragmented by repetitive arousals but there is often rebound slowwave and rapid eye movement (REM) sleep (Issa and Sullivan, 1986a). This rebound phase of recovery from severe sleep fragmentation lasts about a week; the duration and intensity of these rebound sleep episodes decrease quickly after the first night of treatment
POSITIVE-PRESSURE TREATMENT OF OBSTRUCTIVE SLEEP APNEA SYNDROME
425
Fig. 28.5. Two-minute tracing of rapid eye movement sleep in a patient exhibiting persisting upper-airway flow limitation. The second part of the flow tracing demonstrates “chopped-off” airflow. EOG, electrooculogram; EEG, electroencephalogram; SaO2, arterial oxyhemoglobin saturation.
(Issa and Sullivan, 1986a). Although the improvement in basic aspects of sleep architecture is usually immediate and can be used as a sign of an effective CPAP level, following the time course of more detailed analysis of sleep pattern reorganization beyond the first night of treatment under the influence of CPAP therapy suggests a novel adjunct to conventional CPAP titration (Parrino et al., 2005b). Continued frequent arousals may indicate that a critical level of upper-airway resistance persists, especially if associated with flow limitation. Continued snoring is another sign of inadequate CPAP pressure. There are data demonstrating that hysteresis exists in the CPAP–upper-airway resistance relationship. In other words, to eliminate inspiratory flow limitation, higher pressures are required during upward titration of CPAP compared with downward titration from higher pressures (Condos et al., 1994). This means that an OSAS patient may normalize breathing during sleep at a lower CPAP level if manual or automatic titration involves both upward titration until airflow is sinusoidal in shape, and downward titration until obstructed events recur. This may be an important concept in patients with complications of CPAP due to higher CPAP levels (such as mask or mouth leak) or a problem if an autotitrating CPAP does not allow for this “up and down” titration approach. Considering the length of time CPAP has been used to treat patients with sleep apnea, there are surprisingly few published data on the variability in CPAP pressure with posture or sleep stage. Some evidence exists for higher pressure requirements with the supine posture (Pevernagie and Shepard, 1992) and REM sleep (Marrone et al., 2002). It appears that a CPAP level accurately set on one night is generally effective on
subsequent nights (Jokic et al., 1998). Early work and clinical experience suggested this was the case, but the use of auto-CPAP technology in the home has provided the research methodology to support this view (Willson et al., 1996). Clinically, in patients who respond immediately to CPAP but then report continued daytime sleepiness on home treatment, it may be appropriate to increase CPAP pressure empirically, assuming that the laboratory study underestimated the pressure requirement. However, this has not been specifically studied. There is also a range of factors which may have an impact on the therapeutic efficacy of a given CPAP pressure in the home. Weight gain may lead to a need for a higher CPAP setting (Miljeteig and Hoffstein, 1993). Heavy, but not moderate, alcohol consumption may affect CPAP pressure, presumably owing to the effect of alcohol in depressing upper-airway neuromuscular tone (Berry et al., 1991). Nasal congestion or a different posture in the home may also lead to different pressure requirements but this has not been well researched.
Treatment of decompensated patients with cardiorespiratory failure Patients with carbon dioxide retention, heart failure, and extreme nocturnal hypoxemia (i.e., SaO2 50% or less) require close supervision when commencing CPAP. Such patients may have confusion at night from delirium (due to their blood gas derangement) that may be exacerbated by someone trying to attach a mask to their face. The nurse or technician needs to provide close attention in case the patient tries to pull off the mask repeatedly throughout the night. After the first
426
P.R. BUCHANAN AND R.R. GRUNSTEIN
few nights, these patients typically settle down and sleep with the CPAP unit without the need for intensive nursing. The previous choice of therapy for these patients was endotracheal intubation or urgent tracheostomy. Intubation may still be the appropriate option; however, in trained hands, nasally applied CPAP or noninvasive ventilation (see Chapter 30) will readily control the breathing disturbance during sleep. Many of these patients have both upper-airway obstruction and hypoventilation and nasal CPAP may not be adequate to normalize gas exchange (Becker et al., 1999). Increasingly, the clinical approach in these patients is to employ bilevel positive airway pressure (PAP) therapy. Auto-CPAP approaches are inappropriate in such patients. Hospitalization would be the most reasonable approach in the management of patients with severe CO2 retention due to a hypoventilation syndrome and/ or chronic lung disease, until studies showing the safety of ambulatory approaches are available.
The split-night study It has been suggested that CPAP can be initiated on the same night the diagnosis is established (Sanders et al., 1993; McArdle et al., 2000; Deutsch et al., 2006; Kapur and Sullivan, 2006). However, in these studies, patient selection was not randomized or split-night studies tended to be performed in patients with more severe disease without comorbidities who had been waiting a shorter time for their CPAP titration. Others have identified a subset of patients for whom a split-night study provided insufficient time for CPAP titration to achieve a satisfactory prescription (Hoffstein and Mateika, 1994). Patients with milder degrees of sleepdisordered breathing (apnea–hypopnea index (AHI) < 20) in whom the titration is initiated later in the night (because prolonged monitoring was required to establish a diagnosis) were more likely to have unsuccessful split-night titrations. CPAP can potentially be titrated during the day (Rosenthal et al., 1998): in this study, both daytime and nocturnal CPAP titration studies yielded sufficient amounts of REM and non-REM (NREM) sleep to help determine CPAP settings. The diurnal and nocturnal CPAP titrations resulted in comparable therapeutic pressures, resolution of sleepdisordered breathing, and 1-week compliance. Split-night or day studies may appear attractive from a short-term economic point of view but data in larger numbers of unselected patients are required before this approach is routinely accepted. It is possible but speculative at this stage, depending on outcome studies, that a combination of split-night titration and subsequent home autotitration may be an adequate strategy.
Initiation of CPAP in the home setting There may be theoretical economic advantages of starting CPAP at home and avoiding a formal inlaboratory polysomnographic (PSG) CPAP titration, but outcome studies showing true cost utility are not available. Current reviews and guidelines do not advocate home commencement of CPAP, particularly using autotitrating devices (Littner et al., 2002). This is a controversial area as it implies a major change in practice in sleep centers. One study has observed poorer CPAP compliance in patients assessed only with respiratory monitoring (Krieger et al., 1998), another study has shown poorer compliance outcomes with patients having initial unattended CPAP PSG at home (Means et al., 2004), but equivalence of outcomes between in-laboratory and home-based studies has also been reported (White and Gibb, 1998; Hukins, 2004; West et al., 2006). Other workers have found reasonable utility with unattended in-hospital CPAP titration in patients with mild to moderate disease but not severe obstructive sleep apnea–hypopnea syndrome (OSAHS) (Juhasz et al., 1996). Some studies have suggested that equations can be determined which would allow an empirical CPAP level to be set, potentially preventing the need for any investigation of CPAP efficacy (Hoffstein and Mateika, 1994; West et al., 2006). Data from a small group of patients support this empirical method of home CPAP titration instead of laboratory initiation (Fitzpatrick et al., 2003), and a further multicenter 3-month trial involving 360 CPAP-naive OSAS patients has shown equivalence of outcomes (AHI, subjective daytime sleepiness, compliance, dropout rates) whether CPAP was titrated in-laboratory, by auto-CPAP, or by using a prediction formula (Masa et al., 2004). A 6-month assessment of outcomes has shown equivalence for three methods of CPAP initiation, including auto-CPAP throughout, fixed pressure from algorithm, or after 1 week of auto-CPAP to determine therapeutic (“95th centile”) CPAP level, which was then applied in fixed-pressure mode for the duration of the study (West et al., 2006). Thus, although longer-term outcome data are lacking, there is a growing body of evidence supporting effective alternatives to in-laboratory CPAP titration in selected groups of OSAS patients.
AUTOTITRATING CONTINUOUS POSITIVE AIRWAY PRESSURE The aim of auto-CPAP devices are to detect and then prevent (virtually) simultaneously and automatically upper-airway obstruction using the lowest possible CPAP level across the night (Berthon-Jones, 1993). If pressure requirements vary with changes in upper-airway
POSITIVE-PRESSURE TREATMENT OF OBSTRUCTIVE SLEEP APNEA SYNDROME 427 resistance (nasal obstruction, alcohol, or sedative use), (Hukins, 2004). Autotitrating CPAP appeared to have then an auto-CPAP machine would, in theory, adjust no advantage at 6 months over simpler methods of to these changes, unlike a fixed-pressure machine. Ecotitration (1 week auto-CPAP followed by fixed-pressure nomic benefits could also potentially accrue if autoCPAP, or fixed CPAP based on algorithm determinaCPAP reduced technician time, eliminated in-hospital tion) in terms of sleepiness, blood pressure, or qualityPSG for CPAP titration, or reduced clinic visits of of-life outcomes (West et al., 2006). patients with CPAP compliance problems. Compliance with treatment and symptom improvement were similar at 3 months among 93 OSAS patients whether titrated to CPAP by conventional Accuracy of auto-CPAP therapeutic manual in-lab night titration, or manual or autopressure determination daytime titration after sleep deprivation, though Generally, research studies have shown that autotitratpressure selected with auto-CPAP was significantly ing CPAP provides similar pressure values to fixedhigher (Lloberes et al., 2004). In patients with high pressure CPAP in selected patients. However, there is within-night variability in pressure requirements, the often great variability in study methodology (Littner use of auto-CPAP compared with fixed-pressure et al., 2002; Roux and Hilbert, 2003) with some patients CPAP did not confer compliance advantage and both initially undergoing in-laboratory manual titration methods were equivalent in terms of AHI reduction; before home use of auto-CPAP. For in-laboratory studhowever, mean Epworth Sleepiness Scale score ies comparing technician- and auto-CPAP-determined was slightly and significantly lower on auto-CPAP pressures, it is important that the technician and (Noseda et al., 2004). machine are trying to achieve the same titration outA small study of CPAP preference, i.e., fixed versus comes. Also, it may be inappropriate to depend on a auto, suggested better compliance to auto-CPAP in the flow signal provided by the auto-CPAP device itself auto-preferring group but the study was not able to and, for research and comparative purposes, indepenidentify factors that predicted in advance those who dent verification should be obtained. Finally, data would prefer auto-CPAP (Marrone et al., 2004). obtained in the sleep laboratory with technician superAnother small study found no difference between vision cannot be extrapolated to home; with unattended fixed and auto-CPAP in outcomes of symptom and CPAP titration correction of a leak or mask adjustment AHI reduction, and was associated with similar freis not possible. One study has suggested imperfect titraquency of side-effects and compliance, though at the tion of therapeutic CPAP pressure in at least 10% of end of the study more preferred fixed than auto-CPAP CPAP-naive patients (Marrone et al., 2005). (Hussain et al., 2004). In a study of 68 patients determined to have a very high pretest probability of moderate to severe OSA, ambulatory autotitrating CPAP, as Do autotitrating CPAP devices improve compared with standard in-laboratory diagnostic and compliance and outcomes? titration PSG, was found to be equivalent at 3 months One of the main reasons for developing auto-CPAP in terms of outcomes of measured AHI on CPAP, subwas to decrease average CPAP pressure levels and jective daytime sleepiness, and sleep apnea quality-ofimprove compliance. However, a meta-analysis of life index, and modestly better in measured CPAP randomized trials comparing autotitrating CPAP with adherence (Mulgrew et al., 2007b). fixed-pressure CPAP concluded that there were no difThus, autotitrating CPAP does not appear to ferences in hours of use and other outcomes despite a improve compliance dramatically, nor make for submean decrease in overnight CPAP pressure of 2 cm stantial outcome advantages. There is no evidence that H2O (Ayas et al., 2004). the availability of auto-CPAP has led to a major Many studies have shown equivalence, or nearly so, increase in hours of CPAP use by patients or increased of conventional CPAP and auto-CPAP in measured acceptance of this therapy in patients refusing fixedoutcomes. Both fixed and auto-CPAP produce similar pressure CPAP. Given the current costs of auto-CPAP benefits on improving respiratory function during devices, there is no rationale, at this stage, for their sleep, nocturnal sleep architecture, and subjective dayuse as the standard initial home device replacing time sleepiness after 1 month of therapy (Resta et al., cheaper fixed-pressure CPAP (Ayas et al., 2004; West 2004). Overall compliance, Epworth Sleepiness Scale et al., 2006). Even if the CPAP level required to treat and SF-36 were similar between fixed and auto-CPAP sleep apnea decreases over time in compliant patients, in patients treated for 2 months, but auto-CPAP delivsuch changes in pressure are usually small. It is not ered lower pressures, fewer leaks, and enhanced comclear what the advantage of lowering pressure would pliance in subjects experiencing any side-effects be in patients who are, presumably, successfully
428
P.R. BUCHANAN AND R.R. GRUNSTEIN
established on therapy. Autotitrating CPAP may have a role in replacing in-hospital titration of CPAP but this needs to be further tested in large studies measuring cost–utility and looking at a wide range of unselected patients and a comparison with empirical home treatment (White and Gibb, 1998; Kuna, 2003; Ayas et al., 2004).
Table 28.1 Side-effects of nasal continuous positive airway pressure Type of problem
Side-effect
Nasal
Rhinorrhea Nasal congestion, oronasal dryness Epistaxis Skin abrasion/rash Conjunctivitis from air leak Chest discomfort Aerophagy Sinus discomfort Claustrophobia Difficulty exhaling Pneumothorax (very rare) Pneumoencephaly (very rare) Cerebrospinal fluid leak/ meningitis (very rare)
Problems with autotitrating CPAP Potential problems with auto-CPAP include overcompensation for mask or mouth leaks with a possibility of unnecessarily high pressures. This, in turn, could lead to a worsening air leak. Other potential problems include undertreatment due to slow responses to airway obstruction or even the presence of central apnea or hypoventilation, which may not be detected if flow limitation is the only endpoint used by the device’s diagnostic algorithm. Auto-CPAP does not appear to correct easily the flow limitation caused by acute nasal congestion or may have problems treating patients where central apneas appear after adequate correction of obstructive events. Other work has shown mask leaks to be a significant problem in auto-CPAP, as well as manual titration (Littner et al., 2002). They may lead to overshoots in CPAP level compromising sleep structure (Marrone et al., 2002). Finally, it is important to recognize that data from studies investigating one type of autotitrating machine cannot be extrapolated to other autotitrating devices (Littner et al., 2002). In a small study of three different auto-CPAP devices using AHI < 5/hour as an indication of optimal treatment there was a considerable difference in the efficacy of the various devices. An acceptable treatment AHI of < 5/hour was achieved in 10/12 patients for two devices but in only 6/12 for the third device (Stammnitz et al., 2004).
PROBLEMS AND SIDE-EFFECTS Side-effects reported by the patient are usually, but not exclusively, related to pressure or airflow or the mask– nose interface (Table 28.1). Side-effects are important for CPAP usage; patients who complain of side-effects use CPAP less frequently than those without sideeffects (Engleman et al., 1996). A nonspecific sense of claustrophobia may be reported by patients but this often involves mask/interface problems, nasal congestion, or exhalation difficulties, discussed below. Claustrophobic tendencies scored from a 15-item scale and measured pre-CPAP initiation in OSA subjects correlated with poorer outcomes at 3 months with respect to mask-on CPAP adherence, and this preemptive screening approach offers the opportunity to target such patients for early interventions to improve adherence (Chasens et al., 2005). Dangerous complications
Mask Flow-related
Noise Partner intolerance Inconvenience
of nasal CPAP therapy are extremely rare and represent isolated case reports in the literature, including pulmonary barotrauma, pneumocephalus, increased intraocular pressure, tympanic membrane rupture, cerebrospinal fluid leak and meningitis (Kuzniar et al., 2005), massive epistaxis, and subcutaneous emphysema after facial trauma (Strollo et al., 1998). It is clear that caution should be used when implementing CPAP therapy after neuro- or facial surgery. Irritating side-effects such as aerophagy and musculoskeletal chest discomfort (presumably related to increased lung volumes) have also been reported (Strollo et al., 1998).
Nasal congestion Nasal congestion is a common side-effect of CPAP therapy (Strollo et al., 1998). Although most patients experience initial self-limiting nasal congestion, at least 10% complain of persistent nasal stuffiness to some degree after 6 months of therapy (Pepin et al., 1995). There appear to be many reasons for nasal symptoms. CPAP may provoke pressure-sensitive mucosal receptors, leading to vasodilation and mucus production. In some patients, it may unmask allergic rhinitis by restoring the nasal route of breathing after years of mouth breathing. In others, fixed nasal obstruction with polyps or a deviated septum may produce symptoms. Mouth leaks also cause increased nasal resistance (Richards et al., 1996).
POSITIVE-PRESSURE TREATMENT OF OBSTRUCTIVE SLEEP APNEA SYNDROME 429 Histologic changes of nasal mucosa vary between However, nasal prongs may cause irritation in the untreated OSAS patients and those treated with CPAP, nares and long-term use data are needed. Newer interand further vary according to the duration of CPAP faces are constantly being developed to address mask treatment; rhinitic symptoms can be correlated with problems but, for some patients, particularly younger these changes (Schrodter et al., 2004). On the other patients with mild disease, perceived esthetic problems hand, in a small study of OSAS patients treated for 6 with CPAP, regardless of interface, preclude this treatmonths with nonhumidified CPAP, measures of nasal ment modality. resistance, mucociliary clearance, and ciliary beat freAn infrequent but difficult problem is the patient quency did not change over time (Bossi et al., 2004). who has no upper front teeth. The upper teeth provide Treatment of nasal congestion will depend on the the rigid structure against which the lower part of the exact cause. Mouth leak producing increased nasal mask can be pulled. If there is no dentition, the mask flow may be minimized by ensuring that the correct simply rolls around the top gums into the mouth, with CPAP pressure is used. Sometimes, it may be necessary loss of an adequate seal. The problem may be rectified to use chin straps. However, these are often uncomby providing a denture (Bucca et al., 1999) or possibly fortable and acclimatization to this device is often an oronasal mask. necessary. Nasal congestion can be treated with antihistamines, topical steroids, or topical saline sprays, and The pressure level and airflow humidification of the circuit will improve nasal dryAlthough frequently mentioned as a problem, there is ness. Heated, rather than cold, passover humidification no convincing evidence that the CPAP level impairs is necessary to treat nasal congestion (Richards et al., compliance (see autotitrating CPAP, above). Some 1996; Martins De Araujo et al., 2000; Mador et al., patients may complain of initial increased resistance to 2005). Intranasal ipratropium bromide can be helpful exhalation or the sensation of too much pressure in in abating CPAP-induced rhinorrhea. the nose. For these patients, a CPAP unit with a pressure Patients with persistent symptoms of nasal congestion ramp may be worth considering; most modern CPAP or those with obvious nasal obstruction should have nasomachines have this as a patient-selectable and modifipharyngoscopy performed and may require corrective able feature. The ramp allows the pressure to increase surgery for an obstructive lesion such as polyps, marked to the optimal CPAP pressure gradually over a set time mucosal thickening, or deviated septum. There is some interval (usually 5–30 minutes). No studies have been limited evidence of benefit (Friedman et al., 2000). Oral performed to show that a ramp feature improves accepmasks may also be of value in managing a few patients tance or compliance with CPAP; however, interestingly, with nasal side-effects (Beecroft et al., 2003). a case of “ramp abuse” has been reported where continuous patient application of the ramp function led to The interface undertreatment of sleep apnea (Pressman et al., 1995). Initially, masks were custom-made but in the mid-1980s Alternatively, a bilevel PAP system, in which inspiratory new forms of plastic self-sealing masks became more and expiratory PAP can be adjusted independently, may convenient to use. Mask technology has improved be used, as this approach lowers mean airway pressure greatly, and this is important as mask comfort remains and resistance to expiration. Again, it is not clear a pivotal influence on CPAP acceptance and compliwhether these approaches will improve compliance. ance. Poorly fitting masks permit air leakage and a drop Limited data indicated that use of bilevel devices in pressure, leading to persistent OSA and sleep fragdoes not affect positive pressure usage in OSAHS mentation. The leak is usually the source of considerable patients (Reeves-Hoche et al., 1995). More recently, discomfort; if it is directed toward the eye, it may cause CPAP with reduced expiratory pressure has been marconjunctivitis (Stauffer et al., 1984). A potential problem keted (for example, C-Flex, Respironics), with no eviwith a poorly fitting mask is the development of dence in one study for increased patient compliance bruising or even ulceration of the bridge of the nose. using this modality at 1 month compared to convenThere are few studies comparing different mask tional CPAP (Gay et al., 2003), but with some complitypes despite the constant availability of new designs. ance and other modest advantage in another study at Anecdotally, the newer generation of mask types is 3-month follow-up (Aloia et al., 2005b). Interim reports associated with fewer mask fit problems. Nevertheless, of further studies of this device suggest equivalence or certain patients become claustrophobic when using marginally better outcomes compared to conventional nasal CPAP with any mask. Changing the interface CPAP (Aloia et al., 2005a; Duntley et al., 2005; prescription from a nasal mask to less confining Rosenthal et al., 2005a, b; Ruyak et al., 2005; Nilius nasal prongs or “pillows” may correct that problem. et al., 2006; Mulgrew et al., 2007a).
430 P.R. BUCHANAN AND R.R. GRUNSTEIN Patients occasionally find the air generated by the this treatment modality. In addition to compliance, varCPAP unit too warm or too cold. If moving the machine ious other terms, such as acceptance, adherence, and from the floor to a bedside table, heating the bedroom, others, have been used in studies to do with patient or placing tubing under the blankets does not correct the use (or not) of recommended CPAP treatment. These problem, incorporating a heated humidifier into the cirterms need standardized definitions and use to allow cuit may help. Bed partners may also experience cold air valid across-studies interpretation of results (Grunstein, on their bodies from the expiratory port of the device. 2005). True efficacy studies have yet to be performed, Another complaint, also usually from the bed partner, as they would need to measure total sleep time over a is that the CPAP machine generates too much noise. set period and compare this with CPAP usage and the Removing the machine from the bedside or placing it number of respiratory events not prevented by CPAP. in a closet may remedy the problem. Extra tubing may Nevertheless, when one looks at all the CPAP usage data be needed and it is important to recheck pressures if currently available, compliance with CPAP devices comnonstandard tubing is used. Noise or a changing level pares favorably with medication use in various other of noise may be a problem in some auto-CPAP devices medical conditions. due to the nature of their motors. Several specific factors can potentially affect CPAP uptake and compliance, including machine cost, the COMPARISON WITH OTHER technical advances in equipment, and prescriber motiTREATMENTS vation. Current machines are quieter compared to those of past years, with a ramp facility to increase One of the great advantages of nasal CPAP is that it is the pressure slowly over the first period of sleep, and immediately and demonstrably effective in relieving there are more comfortable masks. Many earlier CPAP OSAHS (Sullivan et al., 1981; Lojander et al., 1996). usage studies have used equipment that has been Although that effect is often obvious clinically on the replaced by newer devices (for example, the C-Flex CPAP titration night, this beneficial effect of reducing CPAP device – see above) and compliance data need or normalizing the respiratory disturbance index has to be continually updated to verify whether these techbeen convincingly demonstrated in follow-up PSG studnical changes do influence CPAP use or are purely ies between 2 weeks and 3 months after CPAP initiation, cosmetic marketing ploys. This situation is analogous in contrast to other treatments, including sham CPAP, to clinical trials of new medications within the other placebo, oral appliances, conservative managesame drug class, for example, comparative studies of ment, and positional therapy (Henke et al., 2001; beta-blockers. Monasterio et al., 2001; Becker et al., 2003; Barnes If a CPAP mask is taken off the face, there is a et al., 2004). Another advantage is that it can be offered detectable drop in pressure and this can be detected on a trial basis and withdrawn if not tolerated, in conon devices with data storage capability. So, if patients trast to surgical options. This is particularly important simply switch on their machine and leave the mask on in milder cases of OSAHS, or where the contribution the floor, then there would be a major discrepancy of OSAHS to the patient’s symptomatology is unclear. between “machine-on” time and “mask-on-face” time. A few studies have attempted to compare CPAP A simultaneous study of CPAP use and pressure delivwith other treatments for OSAHS using formal protoery at the mask revealed a reasonable correlation cols. The conclusion of most of these studies is that between claimed usage and measured compliance CPAP is the appropriate therapy for patients with mod(Kribbs et al., 1993b). erate to severe sleep apnea (Grunstein et al., 1989; Mean CPAP use of less than 4 hours per night proRauscher et al., 1991; Hers et al., 1997; Van Dongen duces a demonstrable reduction in sleepiness (Engleman et al., 2004). This view is also supported by an American et al., 1994). Another study showed that one night off Academy of Sleep Medicine Standards of Practice CPAP in compliant CPAP users led to a recurrence in Committee Task Force review of the use of PAP treatdaytime sleepiness (Kribbs et al., 1993a). A dose– ment in adults with sleep-disordererd beathing (Gay response relationship between benefits and hours of et al., 2006). nightly CPAP use has been demonstrated (Weaver et al., 2007). At this stage all criteria set for CPAP usage COMPLIANCE or nonusage or compliance or noncompliance (Kribbs et al., 1993b; Engleman et al., 1994) are essentially General issues arbitrary. It is widely acknowledged that CPAP is effective treatHowever, it is clear that even partial-night CPAP ment for OSA but just as readily recognized that there use can lead to measurable clinical improvement. Some are significant limitations to patients’ effective use of sleep apnea patients use CPAP for only part of the
POSITIVE-PRESSURE TREATMENT OF OBSTRUCTIVE SLEEP APNEA SYNDROME night because they derive a satisfactory degree of symptomatic benefit from that limited application (Hers et al., 1997). This possibly reflects interindividual variation in function with sleep loss or fragmentation, with some patients needing to obtain less sleep to function at a reasonable level during wakefulness (Van Dongen et al., 2004). However, given the evidence that shortened sleep hours are associated with significant performance deficit, patients need to be warned about the risk of persisting problems with alertness with limited hours’ use of CPAP. Newergeneration CPAP devices that allow monitoring of more precise patterns of use and efficacy will give us insight into the minimal duration of CPAP use that is needed to maintain normal daytime neurobehavioral function and, possibly, to modify the vascular consequences of sleep apnea.
Uptake and purchase We do not know how many people with moderate to severe OSA avoid initial consultation with a sleep physician, or seek primary referral to surgeons or dentists, because they will not entertain even the possibility of using CPAP. The percentage of patients who refuse CPAP after an in-hospital trial is variable, ranging from 58% to 80% (Meurice et al., 1994). CPAP purchase rates after PSG CPAP titration are over 50%, based on a calculation comparing new CPAP machine sales provided by manufacturers with national insurance data on multiple sleep study frequency (Grunstein, 1997). In other words, over 50% of patients completing a sleep laboratory trial end up purchasing a CPAP machine or having one purchased for them by the health system.
Use of CPAP long-term Covert objective monitoring of CPAP has demonstrated that compliance with nasal CPAP is substantially less than in studies where compliance is reported on the basis of subjective patient data (Kribbs et al., 1993b), with only 46% of patients having used nasal CPAP 4 hours for 70% of the observed nights. Compliance at 1 month predicted compliance at 3 months (Kribbs et al., 1993b; Weaver et al., 1997). Other studies have generally confirmed this degree of usage. Published CPAP follow-up cohorts are biased by the same factors that affect clinical trials of pharmaceuticals. Patient populations are often highly selected for lack of comorbidity, intellectual capacity, geographical access and health consciousness – all factors that may affect compliance in the real world. More large “open” studies from a variety of sleep clinics (McArdle et al., 1999) would provide better information on true CPAP compliance.
431
Attempts to improve CPAP compliance have involved refinements of devices, including the use of auto-CPAP, and adjunctive supportive measures. Patients’ adherence to a flexible (i.e., differential inspiratory versus expiratory pressure) PAP device (C-Flex) at 3-month follow-up was higher compared to patients using standard CPAP, but clinical outcomes of treatment did not differ; patients using C-Flex showed a trend toward improved self-efficacy (Aloia et al., 2005b). Video education at outset may enhance CPAP usage and clinic attendance at 1 month postinitiation (Jean Wiese et al., 2005). Various behavioral interventions, for example based on cognitive behavioral therapy, may improve CPAP usage (Aloia et al., 2004; Richards et al., 2007). A Cochrane review of interventions to improve CPAP compliance did not report a clearcut advantage of increased hours of use in favor of auto-CPAP over fixed CPAP in pooled data of unselected patients though, where measured, patient preference was for auto-CPAP; two of six studies of educational/psychological interventions demonstrated improved hours of use (Haniffa et al., 2004).
Baseline indicators influencing CPAP usage Identification of claustrophobia prior to initiating CPAP using a Fear and Avoidance Scale predicted lower CPAP adherence at 3 months (Chasens et al., 2005). Remedial measures to address such identified claustrophobia logically might improve compliance in those subjects. Along similar lines, reporting “initial problems” after the first night of CPAP (using autotitration) was the most powerful predictor of lower hours of CPAP “on time” at 1-month follow-up, with “recent life events” and “living alone” but not pretreatment measures of anxiety or depression also being somewhat predictive (Lewis et al., 2004). Contrariwise, in another study low CPAP compliance predicted high anxiety scores, and low CPAP compliance and excessive daytime sleepiness predicted high depression scores in a questionnaire-based study of OSA patients (Kjelsberg et al., 2005). Progressing from diagnosis to titration to purchase of CPAP in a health care system requiring copayment for CPAP is dependent on measures of subjective sleepiness and severity of OSA by respiratory disturbance index, as well as on higher socioeconomic status, and support from bed partner, referring physician, and sleep lab staff (Brin et al., 2005). Predominant nose breathing rather than mouth breathing at outset predicted better adherence with CPAP at 1-year follow-up in moderate to severe OSA (Bachour and Maasilta, 2004).
432
P.R. BUCHANAN AND R.R. GRUNSTEIN
Several other studies have confirmed that the severity of symptoms has a major role in maintaining usage of CPAP; that is, that patients with good objective usage or reported adherence are sleepier at baseline (Kribbs et al., 1993b; Strollo et al., 1998; McArdle et al., 1999; Barbe et al., 2001; Patel et al., 2003). Although multiple sleep latency test (MSLT)-measured daytime sleepiness improves following CPAP (Engleman et al., 1994), baseline MSLT scores do not appear to predict CPAP compliance and it is controversial whether the amount of improvement in MSLT scores will predict compliance in contrast to MSLT results at baseline (Kribbs et al., 1993b; Barbe et al., 2001). It is possible that in sleep apnea the maintenance of wakefulness test (MWT) may be a better predictor of CPAP use, but this is untested. Sleep fragmentation measured by a electroencephalographic neural network analysis or movement events on video recordings are reasonably correlated with CPAP compliance (Bennett et al., 1998). Improved compliance has also been linked to the degree of improvement in sleep efficiency and quality between diagnostic and treatment studies (Drake et al., 2003). Other factors that may be related to reduced usage include previous palatal surgery and fewer years of education. Surprisingly, considering the potential discomfort and mask leak, having a higher CPAP pressure level has been not been a negative influence on compliance (Remmers et al., 1978; Strollo et al., 1998; Zozula and Rosen, 2001; Fitzpatrick et al., 2003). In fact, it may be associated with better compliance, though these data could be confounded by more marked symptoms in patients requiring higher pressures (McArdle et al., 1999).
et al., 1993b). This figure equates to 2.7 hours use per night but was essentially an arbitrary figure based on the authors’ expert clinical opinion (Kribbs et al., 1993b). Some have adopted a policy of reclaiming loaned CPAP machines if use is less than 2 hours per night (McArdle et al., 1999). Sometimes patients will use CPAP effectively but only for part of their total sleep time. This may represent CPAP failure depending on the endpoint of therapy (Grote et al., 2000; Stepnowsky and Moore, 2003). Clearly, it is important to identify the cause of CPAP failure. Some of the commonest side-effects and potential solutions have been mentioned. Ear, nose, and throat assessment may be appropriate in looking for any structural reasons to explain CPAP failure. It is important also to consider if there has been a misdiagnosis or if there are coexisting causes of sleepiness from other causes (Stepnowsky and Moore, 2003). Residual sleepiness in CPAP-treated subjects should be subjected to rigorous review including, if necessary, the use of esophageal pressure balloons to detect subtle episodes of upper-airway obstruction, and a proportion of such patients will be shown to have been undertreated rather than having failed treatment. Some attempts to overcome true CPAP treatment failures have involved the use of other than CPAP devices, such as bilevel PAP, but supporting evidence is limited (Gay et al., 2006).
Role of physician or technologist motivation/support
Over the past decade, there have been a number of RCTs that have demonstrated the effectiveness of CPAP in improving neurobehavioral outcomes such as daytime sleepiness, or blood pressure, in patients with moderate to severe OSA (Pepperell et al., 2002; White et al., 2002; Patel et al., 2003). Different parameters of sleep patterns improve over a defined time scale but mostly within 1 month of establishing CPAP in severe OSA patients (Parrino et al., 2005a). Depression symptoms associated with untreated OSA may ameliorate with successful institution of CPAP therapy (Schwartz et al., 2005). However, the evidence for benefits is less clear in patients with more severe disease not reporting sleepiness (Barbe et al., 2001) or in patients with mild disease (Barnes et al., 2002). Researchers have employed either an oral placebo or sham/subtherapeutic CPAP as control arms in RCTs examining the effects of CPAP. There is no “perfect placebo” for CPAP and each approach has limitations and obvious difficulties in blinding. Even a patient on
It would seem obvious that the greater positive reinforcement given to patients, the more likely the patient will use CPAP as prescribed. Various studies have shown the value of patient education, although it is unclear as to the quantum of education and support that is necessary to improve compliance (Hoy et al., 1999; Zozula and Rosen, 2001; Fitzpatrick et al., 2003; Brin et al., 2005).
MANAGEMENT OF CPAP FAILURE What constitutes CPAP failure? This is a subjective issue and practice varies from center to center in the absence of hard data addressing the diverse health consequences of varying “exposures” of sleep apnea. CPAP failure has been defined as the “use of CPAP for less than 4 hours per night on 70% of the nights and/or lack of symptomatic improvement” (Kribbs
HEALTH OUTCOMES AND NASAL CONTINUOUS POSITIVE AIRWAY PRESSURE
POSITIVE-PRESSURE TREATMENT OF OBSTRUCTIVE SLEEP APNEA SYNDROME sham CPAP will be made aware of persisting snoring by a partner. However, existing studies have clearly defined a role for CPAP in moderate to severe symptomatic OSA. The treatment of the asymptomatic patient with milder disease remains controversial (Barnes et al., 2002). One study compared (humidified) CPAP to sham CPAP in mild OSAS and showed improvement in subjective sleepiness and a trend to improved objective wakefulness in the treatment group along with improvement of PSG indices of OSA, but other outcomes (mood, quality of life, psychomotor vigilance task reaction times) were similar in the two groups, as were compliance and treatment preference (Marshall et al., 2005). A meta-analysis of RCTs in mild to moderate OSA suggests quite modest benefit from CPAP treatment on both subjective and objective measures of daytime sleepiness (Marshall et al., 2006).
CPAP AND CARDIOVASCULAR OUTCOMES Prospective, well-designed population-based studies have confirmed significant adverse cardio- and cerebrovascular and overall mortality outcomes in untreated OSA (Marshall et al., 2008; Young et al., 2008). The present evidence for a significant protective or ameliorating effect of CPAP against adverse cardiovascular outcomes in OSA is mixed, especially with treatment of mild OSA. In a large observational cohort study, there was an increased risk of stroke and death which persisted after allowing for other risk factors, including hypertension; however, CPAP use did not appear to provide protection against adverse outcomes in this study (Yaggi et al., 2005). In contrast, in case-control studies, there is some evidence of cardiovascular benefit from nasal CPAP therapy in severe sleep apnea. Long-term CPAP therapy seemed to provide a protective benefit against death from established cardiovascular disease, though there was no difference in the development of new cases of hypertension, cardiac disorder, or stroke between CPAP-treated and untreated groups (Doherty et al., 2005). In a large Spanish study patients with untreated severe OSAS had a higher incidence of both fatal and nonfatal cardiovascular events than untreated patients with mild to moderate OSAS, simple snorers, healthy subjects, and patients treated with CPAP (Marin et al., 2005). CPAP also appears to provide a protective benefit against new vascular events after stroke or transient ischemic attack in moderate to severe OSA subjects (Martinez-Garcia et al., 2005). A recent CPAP study suggests protective cardiovascular outcome benefits across the spectrum of OSA severity (Buchner et al., 2007). These results point
433
toward a possible protective benefit of CPAP against these adverse cardiovascular outcomes but more welldesigned RCTs are needed to demonstrate this benefit convincingly. Cardiovascular-protective benefits of CPAP have been demonstrated mainly against hypertension. Short-term improvements in hypertension control have been shown in a randomized parallel trial of CPAP-treated OSA patients when compared to subtherapeutic CPAP, and cardiovascular risk benefits imputed therefrom (Pepperell et al., 2002). In a small study of nonrandomized OSA subjects measures of muscle sympathetic traffic were improved over time with CPAP treatment, although blood pressure did not change (Narkiewicz et al., 1999). However, recent data question the ability of CPAP to decrease blood pressure over longer time periods, particularly in nonsleepy patients (Robinson et al., 2006). Although acute (auto-)CPAP use did not alter systolic or diastolic blood pressure, or heart rate, from diagnostic (pretreatment) values in 12 OSAS patients, CPAP treatment was associated with a stabilizing effect by reducing nighttime but not daytime variability of parameters (Dursunoglu et al., 2005). Nearly half of a group of moderate to severe OSAS patients experienced severe, mainly nocturnal cardiac arrhythmia documented by use of an insertable loop recorder (but largely not documented by Holter monitor), and long-term CPAP treatment was associated with marked reduction of arrhythmia (Simantirakis et al., 2004). Preeclamptic women exhibited sleep-induced decrements of heart rate, stroke volume, and cardiac output, and further increased total peripheral resistance (compared to wake); these changes were minimized and reduced, respectively, in subjects treated with CPAP (Blyton et al., 2004). There is an apparent link between untreated OSA and right-to-left cardiac shunt via a patent foramen ovale, and a case report documents reversal of wake right-to-left shunt with institution of CPAP therapy (Pinet and Orehek, 2005). In summary, although there is tantalizing evidence from small physiological studies of potential cardiovascular benefit from treating OSA patients with CPAP, and epidemiological evidence of significant cardiovascular and mortality risk from OSA, there is a continuing lack of and need for large randomized studies to support the idea that we provide cardiovascular benefit to our OSA patients on CPAP, beyond merely reducing the level of respiratory disturbances.
CPAP AND CARDIAC FAILURE Sleep apnea is common in patients with cardiac failure (Javaheri et al., 1998). A number of studies have reported the presence of central sleep apnea (CSA) in
434
P.R. BUCHANAN AND R.R. GRUNSTEIN
patients with ventricular dysfunction. Central apnea appears to be an adverse prognostic factor in such patients (Bradley and Floras, 2003b). OSAS is also prevalent in patients with cardiac failure (Bradley and Floras, 2003a). It has been suggested that OSAS may cause or exacerbate ventricular dysfunction by a number of mechanisms. These include increasing left ventricular afterload through the combined effects of elevations in systemic blood pressure and the generation of exaggerated negative intrathoracic pressure, and by activating the sympathetic nervous system through the influence of hypoxia and arousals from sleep (Bradley and Floras, 2003a). Use of nasal CPAP in OSAS in cardiac failure patients for 1 month (Kaneko et al., 2003) and 3 months (Mansfield et al., 2004) leads to improvement in left ventricular function. A number of studies, including some with a randomized controlled design, have demonstrated improvement in various endpoints, including reduced mitral regurgitant fraction, atrial natriuretic factor secretion, inspiratory muscle strength, reduced left ventricular afterload, increasing PCO2 toward normal, and norepinephrine concentrations, with CPAP treatment in patients with cardiac failure and central apnea (Bradley and Floras, 2003b). However, results of the Canadian Continuous Positive Airway Pressure for patients with central sleep apnea and heart failure (CANPAP) trial (Bradley et al., 2005), although confirming small physiological changes with active treatment, showed no advantage on survival or transplant-free interval in such patients treated with CPAP (Bradley et al., 2005). Subsequent post hoc subgroup analysis demonstrated improved left ventricular function and tranplant-free survival in patients if CPAP suppressed CSA effectively soon after CPAP initiation (Arzt et al., 2007). It is also possible that changes in effective cardiac failue therapy over time may have influenced the essentially negative results of the CANPAP trial (Bradley et al., 2005), and there has been commentary with regard to the other possible limitations of that study (Somers, 2005).
SUMMARY PAP is the treatment of first choice for OSA of moderate or greater severity in adults. Applied via a facial interface it is a very effective and safe method of preventing the upper-airway obstructions characteristic of OSA. There remain issues of imperfect patient acceptance and compliance with continuous PAP, and uncertainties regarding the role of CPAP in mild OSA, and the desired cardiovascular benefits of CPAP. Techniques of diagnosing OSA and initiating CPAP in a timely and economic manner continue to evolve.
ACKNOWLEDGMENTS RRG was supported by a Practitioner Fellowship from the National Health and Medical Research Council of Australia. PRB was supported by a Translational Research Fellowship of the Woolcock Institute of Medical Research Centre for Clinical and Research Excellence of the NHMRC of Australia. Thanks to A Dawes for Figure 28.2.
REFERENCES Abad VC, Guilleminault C (2006). Pharmacological management of sleep apnoea. Expert Opin Pharmacother 7: 11–23. Allam JS, Olson EJ, Gay PC et al. (2007). Efficacy of adaptive servoventilation in treatment of complex and central sleep apnea syndromes. Chest 132: 1839–1846. Aloia MS, Arnedt JT, Riggs RL et al. (2004). Clinical management of poor adherence to CPAP: motivational enhancement. Behav Sleep Med 2: 205–222. Aloia M, Arnedt J, Zimmerman M et al. (2005a). Combined therapy to improve adherence to CPAP. Sleep 28: A192. Aloia MS, Stanchina M, Arnedt JT et al. (2005b). Treatment adherence and outcomes in flexible vs standard continuous positive airway pressure therapy. Chest 127: 2085–2093. Arzt M, Floras JS, Logan AG et al. (2007). Suppression of central sleep apnea by continuous positive airway pressure and transplant-free survival in heart failure: a post hoc analysis of the Canadian Continuous Positive Airway Pressure for patients with central sleep apnea and heart failure trial (CANPAP). Circulation 115: 3173–3180. Ayas NT, Patel SR, Malhotra A et al. (2004). Auto-titrating versus standard continuous positive airway pressure for the treatment of obstructive sleep apnea: results of a meta-analysis. Sleep 27: 249–253. Bachour A, Maasilta P (2004). Mouth breathing compromises adherence to nasal continuous positive airway pressure therapy. Chest 126: 1248–1254. Barbe F, Mayoralas LR, Duran J et al. (2001). Treatment with continuous positive airway pressure is not effective in patients with sleep apnea but no daytime sleepiness. A randomized, controlled trial. Ann Intern Med 134: 1015–1023. Barnes M, Houston D, Worsnop CJ et al. (2002). A randomized controlled trial of continuous positive airway pressure in mild obstructive sleep apnea. Am J Respir Crit Care Med 165: 773–780. Barnes M, Mcevoy RD, Banks S et al. (2004). Efficacy of positive airway pressure and oral appliance in mild to moderate obstructive sleep apnea. Am J Respir Crit Care Med 170: 656–664. Becker HF, Piper AJ, Flynn WE et al. (1999). Breathing during sleep in patients with nocturnal desaturation. Am J Respir Crit Care Med 159: 112–118. Becker HF, Jerrentrup A, Ploch T et al. (2003). Effect of nasal continuous positive airway pressure treatment on
POSITIVE-PRESSURE TREATMENT OF OBSTRUCTIVE SLEEP APNEA SYNDROME blood pressure in patients with obstructive sleep apnea. Circulation 107: 68–73. Beecroft J, Zanon S, Lukic D et al. (2003). Oral continuous positive airway pressure for sleep apnea: effectiveness, patient preference, and adherence. Chest 124: 2200–2208. Bennett LS, Langford BA, Stradling JR et al. (1998). Sleep fragmentation indices as predictors of daytime sleepiness and nCPAP response in obstructive sleep apnea. Am J Respir Crit Care Med 158: 778–786. Berry RB, Desa MM, Light RW (1991). Effect of ethanol on the efficacy of nasal continuous positive airway pressure as a treatment for obstructive sleep apnea. Chest 99: 339–343. Berthon-Jones M (1993). Feasibility of a self-setting CPAP machine. Sleep 16: S120–S121; discussion S121–S123. Blyton DM, Sullivan CE, Edwards N (2004). Reduced nocturnal cardiac output associated with preeclampsia is minimized with the use of nocturnal nasal CPAP. Sleep 27: 79–84. Bossi R, Piatti G, Roma E et al. (2004). Effects of long-term nasal continuous positive airway pressure therapy on morphology, function, and mucociliary clearance of nasal epithelium in patients with obstructive sleep apnea syndrome. Laryngoscope 114: 1431–1434. Bradley TD, Floras JS (2003a). Sleep apnea and heart failure. Part I: obstructive sleep apnea. Circulation 107: 1671–1678. Bradley TD, Floras JS (2003b). Sleep apnea and heart failure. Part II: central sleep apnea. Circulation 107: 1822–1826. Bradley D, Phillipson EA (1983). The treatment of obstructive sleep apnea. Separating the wheat from the chaff. Am Rev Respir Dis 128: 583–586. Bradley TD, Logan AG, Kimoff RJ et al. (2005). Continuous positive airway pressure for central sleep apnea and heart failure. N Engl J Med 353: 2025–2033. Brin YS, Reuveni H, Greenberg S et al. (2005). Determinants affecting initiation of continuous positive airway pressure treatment. Isr Med Assoc J 7: 13–18. Bucca C, Carossa S, Pivetti S et al. (1999). Edentulism and worsening of obstructive sleep apnoea. Lancet 353: 121–122. Buchanan PR, Grunstein RR (2006). Neuropharmacology of obstructive sleep apnea and central apnea. In: Clinical Pharmacology of Sleep, Birkhauser Verlag, Switzerland. Buchner NJ, Sanner BM, Borgel J et al. (2007). Continuous positive airway pressure treatment of mild to moderate obstructive sleep apnea reduces cardiovascular risk. Am J Respir Crit Care Med 176: 1274–1280. Chasens ER, Pack AI, Maislin G et al. (2005). Claustrophobia and adherence to CPAP treatment. West J Nurs Res 27: 307–321. Condos R, Norman RG, Krishnasamy I et al. (1994). Flow limitation as a noninvasive assessment of residual upper-airway resistance during continuous positive airway pressure therapy of obstructive sleep apnea. Am J Respir Crit Care Med 150: 475–480. Dernaika T, Tawk M, Nazir S et al. (2007). The significance and outcome of continuous positive airway pressurerelated central sleep apnea during split-night sleep studies. Chest 132: 81–87.
435
Deutsch PA, Simmons MS, Wallace JM (2006). Costeffectiveness of split-night polysomnography and home studies in the evaluation of obstructive sleep apnea syndrome. J Clin Sleep Med 2: 145–153. Doherty LS, Kiely JL, Swan V et al. (2005). Long-term effects of nasal continuous positive airway pressure therapy on cardiovascular outcomes in sleep apnea syndrome. Chest 127: 2076–2084. Drake CL, Day R, Hudgel D et al. (2003). Sleep during titration predicts continuous positive airway pressure compliance. Sleep 26: 308–311. Duntley S, Morrissey A, Doerr C et al. (2005). Flexible CPAP with expiratory pressure relief: an in-laboratory, polysomnographic comparison with conventional CPAP. Sleep 28: A182. Duong M, Jayaram L, Camfferman D et al. (2005). Use of heated humidification during nasal CPAP titration in obstructive sleep apnoea syndrome. Eur Respir J 26: 679–685. Dursunoglu N, Dursunoglu D, Cuhadaroglu C et al. (2005). Acute effects of automated continuous positive airway pressure on blood pressure in patients with sleep apnea and hypertension. Respiration 72: 150–155. Engleman HM, Martin SE, Deary IJ et al. (1994). Effect of continuous positive airway pressure treatment on daytime function in sleep apnoea/hypopnoea syndrome. Lancet 343: 572–575. Engleman HM, Asgari-Jirhandeh N, Mcleod AL et al. (1996). Self-reported use of CPAP and benefits of CPAP therapy: a patient survey. Chest 109: 1470–1476. Fitzpatrick MF, Alloway CE, Wakeford TM et al. (2003). Can patients with obstructive sleep apnea titrate their own continuous positive airway pressure? Am J Respir Crit Care Med 167: 716–722. Friedman M, Tanyeri H, Lim JW et al. (2000). Effect of improved nasal breathing on obstructive sleep apnea. Otolaryngol Head Neck Surg 122: 71–74. Gay PC, Herold DL, Olson EJ (2003). A randomized, double-blind clinical trial comparing continuous positive airway pressure with a novel bilevel pressure system for treatment of obstructive sleep apnea syndrome. Sleep 26: 864–869. Gay P, Weaver T, Loube D et al. (2006). Evaluation of positive airway pressure treatment for sleep related breathing disorders in adults. A review by the Positive Airway Pressue Task Force of the Standards of Practice Committee of the American Academy of Sleep Medicine. Sleep 29: 381–401. Gregory GA, Kitterman JA, Phibbs RH et al. (1971). Treatment of the idiopathic respiratory-distress syndrome with continuous positive airway pressure. N Engl J Med 284: 1333–1340. Grote L, Hedner J, Grunstein R et al. (2000). Therapy with nCPAP: incomplete elimination of sleep related breathing disorder. Eur Respir J 16: 921–927. Grunstein RR (1995). Sleep-related breathing disorders. 5. Nasal continuous positive airway pressure treatment for obstructive sleep apnoea. Thorax 50: 1106–1113.
436
P.R. BUCHANAN AND R.R. GRUNSTEIN
Grunstein R (1997). Investigation and treatment of sleep apnea in Australia 1991–95. Am J Respir Crit Care Med 155: A133. Grunstein R (2005). Continuous positive airway pressure treatment for obstructive sleep apnea-hypopnea syndrome. In: Principles and Practice of Sleep Medicine, 4th edn. Elsevier Saunders, Philadelphia. Grunstein RR, Dodd MJ, Costas L et al. (1986). Home nasal CPAP for sleep apnea – acceptance of home therapy and its usefulness. Aust N Z J Med 16: 635. Grunstein RR, Handelsman DJ, Lawrence SJ et al. (1989). Neuroendocrine dysfunction in sleep apnea: reversal by continuous positive airways pressure therapy. J Clin Endocrinol Metab 68: 352–358. Grunstein RR, Hedner J, Grote L (2001). Treatment options for sleep apnoea. Drugs 61: 237–251. Haniffa M, Lasserson TJ, Smith I (2004). Interventions to improve compliance with continuous positive airway pressure for obstructive sleep apnoea. Cochrane Database Syst Rev CD003531. Henke KG, Grady JJ, Kuna ST (2001). Effect of nasal continuous positive airway pressure on neuropsychological function in sleep apnea-hypopnea syndrome. A randomized, placebo-controlled trial. Am J Respir Crit Care Med 163: 911–917. Hers V, Liistro G, Dury M et al. (1997). Residual effect of nCPAP applied for part of the night in patients with obstructive sleep apnoea. Eur Respir J 10: 973–976. Hoffstein V, Mateika S (1994). Predicting nasal continuous positive airway pressure. Am J Respir Crit Care Med 150: 486–488. Hosselet JJ, Norman RG, Ayappa I et al. (1998). Detection of flow limitation with a nasal cannula/pressure transducer system. Am J Respir Crit Care Med 157: 1461–1467. Hoy CJ, Vennelle M, Kingshott RN et al. (1999). Can intensive support improve continuous positive airway pressure use in patients with the sleep apnea/hypopnea syndrome? Am J Respir Crit Care Med 159: 1096–1100. Hukins C (2004). Comparative study of autotitrating and fixed-pressure CPAP in the home: a randomized, singleblind crossover trial. Sleep 27: 1512–1517. Hukins CA (2005). Arbitrary-pressure continuous positive airway pressure for obstructive sleep apnea syndrome. Am J Respir Crit Care Med 171: 500–505. Hussain SF, Love L, Burt H et al. (2004). A randomized trial of auto-titrating CPAP and fixed CPAP in the treatment of obstructive sleep apnea-hypopnea. Respir Med 98: 330–333. Issa FG, Sullivan CE (1986a). The immediate effects of nasal continuous positive airway pressure treatment on sleep pattern in patients with obstructive sleep apnea syndrome. Electroencephalogr Clin Neurophysiol 63: 10–17. Issa FG, Sullivan CE (1986b). Reversal of central sleep apnea using nasal CPAP. Chest 90: 165–171. Javaheri S, Parker TJ, Liming JD et al. (1998). Sleep apnea in 81 ambulatory male patients with stable heart failure. Types and their prevalences, consequences, and presentations. Circulation 97: 2154–2159.
Jean Wiese H, Boethel C, Phillips B et al. (2005). CPAP compliance: video education may help! Sleep Med 6: 171–174. Jokic R, Klimaszewski A, Sridhar G et al. (1998). Continuous positive airway pressure requirement during the first month of treatment in patients with severe obstructive sleep apnea. Chest 114: 1061–1069. Juhasz J, Schillen J, Urbigkeit A et al. (1996). Unattended continuous positive airway pressure titration. Clinical relevance and cardiorespiratory hazards of the method. Am J Respir Crit Care Med 154: 359–365. Kaneko Y, Floras JS, Usui K et al. (2003). Cardiovascular effects of continuous positive airway pressure in patients with heart failure and obstructive sleep apnea. N Engl J Med 348: 1233–1241. Kapur VK, Sullivan SD (2006). More isn’t always better: cost-effectiveness analysis and the case for using a splitnight protocol. J Clin Sleep Med 2: 154–155. Kjelsberg FN, Ruud EA, Stavem K (2005). Predictors of symptoms of anxiety and depression in obstructive sleep apnea. Sleep Med 6: 341–346. Kribbs NB, Pack AI, Kline LR et al. (1993a). Effects of one night without nasal CPAP treatment on sleep and sleepiness in patients with obstructive sleep apnea. Am Rev Respir Dis 147: 1162–1168. Kribbs NB, Pack AI, Kline LR et al. (1993b). Objective measurement of patterns of nasal CPAP use by patients with obstructive sleep apnea. Am Rev Respir Dis 147: 887–895. Krieger J, Weitzenblum E, Monassier JP et al. (1983). Dangerous hypoxaemia during continuous positive airway pressure treatment of obstructive sleep apnoea. Lancet 2: 1429–1430. Krieger J, Sforza E, Petiau C et al. (1998). Simplified diagnostic procedure for obstructive sleep apnoea syndrome: lower subsequent compliance with CPAP. Eur Respir J 12: 776–779. Kuna ST (2003). Can continuous positive airway pressure be self-titrated? Am J Respir Crit Care Med 167: 674–675. Kuzniar TJ, Gruber B, Mutlu GM (2005). Cerebrospinal fluid leak and meningitis associated with nasal continuous positive airway pressure therapy. Chest 128: 1882–1884. Lewis KE, Seale L, Bartle IE et al. (2004). Early predictors of CPAP use for the treatment of obstructive sleep apnea. Sleep 27: 134–138. Littner M, Hirshkowitz M, Davila D et al. (2002). Practice parameters for the use of auto-titrating continuous positive airway pressure devices for titrating pressures and treating adult patients with obstructive sleep apnea syndrome. An American Academy of Sleep Medicine report. Sleep 25: 143–147. Lloberes P, Rodriguez B, Roca A et al. (2004). Comparison of conventional nighttime with automatic or manual daytime CPAP titration in unselected sleep apnea patients: study of the usefulness of daytime titration studies. Respir Med 98: 619–625. Lojander J, Maasilta P, Partinen M et al. (1996). NasalCPAP, surgery, and conservative management for
POSITIVE-PRESSURE TREATMENT OF OBSTRUCTIVE SLEEP APNEA SYNDROME treatment of obstructive sleep apnea syndrome. A randomized study. Chest 110: 114–119. Mador MJ, Krauza M, Pervez A et al. (2005). Effect of heated humidification on compliance and quality of life in patients with sleep apnea using nasal continuous positive airway pressure. Chest 128: 2151–2158. Mansfield DR, Gollogly NC, Kaye DM et al. (2004). Controlled trial of continuous positive airway pressure in obstructive sleep apnea and heart failure. Am J Respir Crit Care Med 169: 361–366. Marin JM, Carrizo SJ, Vicente E et al. (2005). Long-term cardiovascular outcomes in men with obstructive sleep apnoea-hypopnoea with or without treatment with continuous positive airway pressure: an observational study. Lancet 365: 1046–1053. Marrone O, Insalaco G, Bonsignore MR et al. (2002). Sleep structure correlates of continuous positive airway pressure variations during application of an autotitrating continuous positive airway pressure machine in patients with obstructive sleep apnea syndrome. Chest 121: 759–767. Marrone O, Resta O, Salvaggio A et al. (2004). Preference for fixed or automatic CPAP in patients with obstructive sleep apnea syndrome. Sleep Med 5: 247–251. Marrone O, Insalaco G, Salvaggio A et al. (2005). Role of different nocturnal monitorings in the evaluation of CPAP titration by autoCPAP devices. Respir Med 99: 313–320. Marshall NS, Neill AM, Campbell AJ et al. (2005). Randomised controlled crossover trial of humidified continuous positive airway pressure in mild obstructive sleep apnoea. Thorax 60: 427–432. Marshall NS, Barnes M, Travier N et al. (2006). Continuous positive airway pressure reduces daytime sleepiness in mild-moderate obstructive sleep apnoea: meta-analysis. Thorax thx.2005.050583. Marshall N, Wong K, Liu P et al. (2008). Sleep apnea as an independent risk factor for all-cause mortality: the Busselton Health Study. Sleep 31: 1079–1085. Martinez-Garcia MA, Galiano-Blancart R, Roman-Sanchez P et al. (2005). Continuous positive airway pressure treatment in sleep apnea prevents new vascular events after ischemic stroke. Chest 128: 2123–2129. Martins De Araujo MT, Vieira SB, Vasquez EC et al. (2000). Heated humidification or face mask to prevent upper airway dryness during continuous positive airway pressure therapy. Chest 117: 142–147. Masa JF, Jimenez A, Duran J et al. (2004). Alternative methods of titrating continuous positive airway pressure: a large multicenter study. Am J Respir Crit Care Med 170: 1218–1224. McArdle N, Devereux G, Heidarnejad H et al. (1999). Longterm use of CPAP therapy for sleep apnea/hypopnea syndrome. Am J Respir Crit Care Med 159: 1108–1114. McArdle N, Grove A, Devereux G et al. (2000). Split-night versus full-night studies for sleep apnoea/hypopnoea syndrome. Eur Respir J 15: 670–675. Means MK, Edinger JD, Husain AM (2004). CPAP compliance in sleep apnea patients with and without laboratory CPAP titration. Sleep Breath 8: 7–14.
437
Meurice JC, Dore P, Paquereau J et al. (1994). Predictive factors of long-term compliance with nasal continuous positive airway pressure treatment in sleep apnea syndrome. Chest 105: 429–433. Meurice JC, Paquereau J, Denjean A et al. (1998). Influence of correction of flow limitation on continuous positive airway pressure efficiency in sleep apnoea/hypopnoea syndrome. Eur Respir J 11: 1121–1127. Miljeteig H, Hoffstein V (1993). Determinants of continuous positive airway pressure level for treatment of obstructive sleep apnea. Am Rev Respir Dis 147: 1526–1530. Monasterio C, Vidal S, Duran J et al. (2001). Effectiveness of continuous positive airway pressure in mild sleep apnea-hypopnea syndrome. Am J Respir Crit Care Med 164: 939–943. Montserrat JM, Ballester E, Olivi H et al. (1995). Timecourse of stepwise CPAP titration. Behavior of respiratory and neurological variables. Am J Respir Crit Care Med 152: 1854–1859. Morgenthaler TI, Gay PC, Gordon N et al. (2007). Adaptive servoventilation versus noninvasive positive pressure ventilation for central, mixed, and complex sleep apnea syndromes. Sleep 30: 468–475. Mulgrew AT, Cheema R, Fleetham J et al. (2007a). Efficacy and patient satisfaction with autoadjusting CPAP with variable expiratory pressure vs standard CPAP: a twonight randomized crossover trial. Sleep Breath 11: 31–37. Mulgrew AT, Fox N, Ayas NT et al. (2007b). Diagnosis and initial management of obstructive sleep apnea without polysomnography: a randomized validation study. Ann Intern Med 146: 157–166. Narkiewicz K, Kato M, Phillips BG et al. (1999). Nocturnal continuous positive airway pressure decreases daytime sympathetic traffic in obstructive sleep apnea. Circulation 100: 2332–2335. Nilius G, Happel A, Domanski U et al. (2006). Pressurerelief continuous positive airway pressure vs constant continuous positive airway pressure: a comparison of efficacy and compliance. Chest 130: 1018–1024. Noseda A, Kempenaers C, Kerkhofs M et al. (2004). Constant vs auto-continuous positive airway pressure in patients with sleep apnea hypopnea syndrome and a high variability in pressure requirement. Chest 126: 31–37. Parrino L, Thomas RJ, Smerieri A et al. (2005a). Reorganization of sleep patterns in severe OSAS under prolonged CPAP treatment. Clin Neurophysiol 116: 2228–2239. Parrino L, Thomas RJ, Smerieri A et al. (2005b). Reorganization of sleep patterns in severe OSAS under prolonged CPAP treatment. Clin Neurophysiol 116: 2228. Patel SR, White DP, Malhotra A et al. (2003). Continuous positive airway pressure therapy for treating sleepiness in a diverse population with obstructive sleep apnea: results of a meta-analysis. Arch Intern Med 163: 565–571. Pepin JL, Leger P, Veale D et al. (1995). Side effects of nasal continuous positive airway pressure in sleep apnea syndrome. Study of 193 patients in two French sleep centers. Chest 107: 375–381.
438
P.R. BUCHANAN AND R.R. GRUNSTEIN
Pepperell JC, Ramdassingh-Dow S, Crosthwaite N et al. (2002). Ambulatory blood pressure after therapeutic and subtherapeutic nasal continuous positive airway pressure for obstructive sleep apnoea: a randomised parallel trial. Lancet 359: 204–210. Pevernagie DA, Shepard JW (1992). Relations between sleep stage, posture and effective nasal CPAP levels in OSA. Sleep 15: 162–167. Pinet C, Orehek J (2005). CPAP suppression of awake rightto-left shunting through patent foramen ovale in a patient with obstructive sleep apnoea. Thorax 60: 880–881. Pressman MR, Peterson DD, Meyer TJ et al. (1995). Ramp abuse. A novel form of patient noncompliance to administration of nasal continuous positive airway pressure for treatment of obstructive sleep apnea. Am J Respir Crit Care Med 151: 1632–1634. Rauscher H, Popp W, Wanke T et al. (1991). Acceptance of CPAP therapy for sleep apnea. Chest 100: 1019–1023. Reeves-Hoche MK, Hudgel DW, Meck R et al. (1995). Continuous versus bilevel positive airway pressure for obstructive sleep apnea. Am J Respir Crit Care Med 151: 443–449. Remmers JE, Degroot WJ, Sauerland EK et al. (1978). Pathogenesis of upper airway occlusion during sleep. J Appl Physiol 44: 931–938. Resta O, Carratu P, Depalo A et al. (2004). Effects of fixed compared to automatic CPAP on sleep in obstructive sleep apnoea syndrome. Monaldi Arch Chest Dis 61: 153–156. Richards GN, Cistulli PA, Ungar RG et al. (1996). Mouth leak with nasal continuous positive airway pressure increases nasal airway resistance. Am J Respir Crit Care Med 154: 182–186. Richards D, Bartlett DJ, Wong K et al. (2007). Increased adherence to CPAP with a group cognitive behavioral treatment intervention: a randomized trial. Sleep 30: 635–640. Robinson GV, Smith DM, Langford BA et al. (2006). CPAP does not reduce blood pressure in non-sleepy hypertensive OSA patients. Eur Respir J 27 6: 1229–1235. Rosenthal L, Nykamp K, Guido P et al. (1998). Daytime CPAP titration: a viable alternative for patients with severe obstructive sleep apnea. Chest 114: 1056–1060. Rosenthal L, Hansbrough J, Zachek M et al. (2005a). International multi-center long-term study of treatment satisfaction and compliance in OSA: CPAP with expiratory pressure relief versus conventional CPAP. Sleep 28: A180. Rosenthal L, Hansbrough J, Zachek M et al. (2005b). International multi-center CPAP study of split-night titration and expiratory pressure relief – long-term effect on compliance and subjective satisfaction. Sleep 28: A210. Roux FJ, Hilbert J (2003). Continuous positive airway pressure: new generations. Clin Chest Med 24: 315–342. Rowley J, Tarbichi A, Badr M (2005). The use of a predicted CPAP equation improves CPAP titration success. Sleep and Breathing 9: 26–32.
Ruyak P, Stanchina M, Arnedt J et al. (2005). The efficacy of C-Flex at improving treatment adherence in obstructive sleep apnea (OSA). Sleep 28: A170. Sanders MH, Kern NB, Costantino JP et al. (1993). Adequacy of prescribing positive airway pressure therapy by mask for sleep apnea on the basis of a partial-night trial. Am Rev Respir Dis 147: 1169–1174. Schrodter S, Biermann E, Halata Z (2004). Histologic evaluation of nasal epithelium of the middle turbinate in untreated OSAS patients and during nCPAP therapy. Rhinology 42: 153–157. Schwab RJ, Pack AI, Gupta KB et al. (1996). Upper airway and soft tissue structural changes induced by CPAP in normal subjects. Am J Respir Crit Care Med 154: 1106–1116. Schwartz DJ, Kohler WC, Karatinos G (2005). Symptoms of depression in individuals with obstructive sleep apnea may be amenable to treatment with continuous positive airway pressure. Chest 128: 1304–1309. Simantirakis EN, Schiza SI, Marketou ME et al. (2004). Severe bradyarrhythmias in patients with sleep apnoea: the effect of continuous positive airway pressure treatment: a long-term evaluation using an insertable loop recorder. Eur Heart J 25: 1070–1076. Somers VK (2005). Sleep – a new cardiovascular frontier. N Engl J Med 353: 2070–2073. Stammnitz A, Jerrentrup A, Penzel T et al. (2004). Automatic CPAP titration with different self-setting devices in patients with obstructive sleep apnoea. Eur Respir J 24: 273–278. Stauffer JL, Fayter N, Maclurg BJ (1984). Conjunctivitis from nasal CPAP apparatus. Chest 86: 802. Stepnowsky CJ JR, Moore PJ (2003). Nasal CPAP treatment for obstructive sleep apnea: developing a new perspective on dosing strategies and compliance. J Psychosom Res 54: 599–605. Stradling JR, Hardinge M, Paxton J et al. (2004a). Relative accuracy of algorithm-based prescription of nasal CPAP in OSA. Respir Med 98: 152–154. Stradling JR, Hardinge M, Smith DM (2004b). A novel, simplified approach to starting nasal CPAP therapy in OSA. Respir Med 98: 155–158. Strohl KP, Redline S (1986). Nasal CPAP therapy, upper airway muscle activation, and obstructive sleep apnea. Am Rev Respir Dis 134: 555–558. Strollo PJJR, Sanders MH et al. (1998). Positive pressure therapy. Clin Chest Med 19: 55–68. Sullivan CE, Issa FG, Berthon-Jones M et al. (1981). Reversal of obstructive sleep apnoea by continuous positive airway pressure applied through the nares. Lancet 1: 862–865. Thomas RJ, Terzano MG, Parrino L et al. (2004). Obstructive sleep-disordered breathing with a dominant cyclic alternating pattern – a recognizable polysomnographic variant with practical clinical implications. Sleep 27: 229–234. Thomas RJ, Daly RW, Weiss JW (2005). Low-concentration carbon dioxide is an effective adjunct to positive airway pressure in the treatment of refractory mixed central and obstructive sleep-disordered breathing. Sleep 28: 69–77.
POSITIVE-PRESSURE TREATMENT OF OBSTRUCTIVE SLEEP APNEA SYNDROME Van Dongen HP, Maislin G, Dinges DF (2004). Dealing with inter-individual differences in the temporal dynamics of fatigue and performance: importance and techniques. Aviat Space Environ Med 75: A147–A154. Wagner DR, Pollak CP, Weitzman ED (1983). Nocturnal nasalairway pressure for sleep apnea. N Engl J Med 308: 461–462. Weaver TE, Kribbs NB, Pack AI et al. (1997). Night-to-night variability in CPAP use over the first three months of treatment. Sleep 20: 278–283. Weaver TE, Maislin G, Dinges DF et al. (2007). Relationship between hours of CPAP use and achieving normal levels of sleepiness and daily functioning. Sleep 30: 711–719. West SD, Jones DR, Stradling JR (2006). Comparison of three ways to determine and deliver pressure during nasal CPAP therapy for obstructive sleep apnoea. Thorax 61: 226–231. White DP, Gibb TJ (1998). Evaluation of the Healthdyne nightwatch system to titrate CPAP in the home. Sleep 21: 198–204.
439
White J, Cates C, Wright J (2002). Continuous positive airways pressure for obstructive sleep apnoea. Cochrane Database Syst Rev CD001106. Willson G, Grunstein R, Doyle J et al. (1996). Domiciliary use of autoset nasal continuous positive airway pressure (n CPAP): feasibility, efficacy and night to night variability. Sleep Res 25: 210. Yaggi HK, Concato J, Kernan WN et al. (2005). Obstructive sleep apnea as a risk factor for stroke and death. N Engl J Med 353: 2034–2041. Young T, Finn L, Peppard P et al. (2008). Sleep-disordered breathing and mortality: eighteen-year follow-up of the Wisconsin Sleep Cohort. Sleep 31: 1071–1078. Zozula R, Rosen R (2001). Compliance with continuous positive airway pressure therapy: assessing and improving treatment outcomes. Curr Opin Pulm Med 7: 391–398.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 29
Medical and surgical treatment of obstructive sleep apnea syndrome, including dental appliances JOHN A. FLEETHAM* Department of Medicine, University of British Columbia, Vancouver, Canada
INTRODUCTION This chapter provides an overview of the management of the obstructive sleep apnea syndrome (OSAS) by behavioral and pharmacologic treatment, dental appliances (DA), and upper-airway surgery. This treatment approach does not include nasal continuous positive airway pressure (CPAP), which is covered in Chapter 28. Where possible, recommendations are based on data from randomized controlled clinical trials. However, many of the proposed treatments for OSAS are not supported by such rigorous forms of evidence and so, to a considerable extent, treatment recommendations are based on data from uncontrolled studies, case series, consensus guidelines, and practice parameters (Fleetham et al., 2006). The treatment approach to OSAS should be individualized to each patient based on a careful risk–benefit analysis that takes into account age, severity of symptoms, presence of associated comorbidities or safety-critical occupation, etiology of upper-airway obstruction, overnight sleep monitoring findings, the local expertise in terms of specialized treatments, and the ability to provide long-term follow-up. The primary goal of treatment for OSAS is symptom improvement, so the need to establish effective treatment is more important in patients with marked daytime symptoms. Some treatments, such as CPAP, can be established in a more timely fashion compared to others, such as DA and corrective upper-airway surgery. This is an important factor when the patient has a comorbidity or condition or a safety-critical occupation. Relevant comorbidites and conditions are ischemic heart disease, cerebrovascular disease, congestive heart failure, refractory systemic hypertension, obstructive/restrictive lung
disease, pulmonary hypertension, hypercapnic respiratory failure, and pregnancy. Safety-critical occupations include patients working with machinery or employed in hazardous occupations and include truck, taxi, and bus drivers; railway engineers, airline pilots, air traffic controllers, aircraft mechanics, ship captains, and pilots. Car drivers who admit to have fallen asleep while driving within the last 2 years also require expedited treatment. The indications for treatment of asymptomatic patients with OSAS are less clear. Treatment may be considered in asymptomatic patients with significant comorbid illness, who work in a safety-critical occupation, or who have an apnea–hypopnea index (AHI) > 30 events/hour. Certain physical factors limit the use of some treatments. Severe nasal obstruction may preclude nasal CPAP or DA therapy and may need to be addressed before these treatments are considered. Most DAs require adequate dentition for their effective use. Temporomandibular joint dysfunction may prevent the use of a DA. The presence of large tonsils should prompt referral to an otolaryngologist for consideration of tonsillectomy. Corrective upper-airway surgery may not be a suitable option for patients who use their voice professionally. All patients should be encouraged to adopt lifestyle modifications; however, this should not delay the initiation of additional treatment if indicated. In addition, patients should be counselled about the interaction between some of these risk factors, which include obesity and cigarette smoking, and the long-term cardiovascular consequences of OSAS. Treatment adherence should be assessed within 2–4 weeks of initiation of treatment. Patients initiated on treatment
*Correspondence to: John A. Fleetham, Professor of Medicine, The Lung Centre, 7th Floor, 2775 Laurel Street, Vancouver, BC V5Z 1M9 Canada. Tel: (604)875-5653, Fax: (604)875-5587, E-mail:
[email protected]
442
J.A. FLEETHAM
should be seen in follow-up within 3 months to assess their symptomatic response to and adherence with treatment. Long-term follow-up by either a primary care provider or sleep disorders specialist should be arranged in a similar fashion to other chronic diseases such as diabetes or hypertension. Patient education about the nature, complications, and treatment of OSAS by a trained health care professional (respiratory therapist, nurse, or polysomnographic technologist) is an important component of all treatment strategies.
LIFESTYLE MODIFICATION There were no randomized trial data upon which to base a recommendation that lifestyle modifications improve OSAS in a systematic review (Shneerson and Wright, 2006). Nevertheless, common sense dictates the importance of identifying and attempting to correct lifestyle issues that may contribute to the development of OSAS.
Weight loss Obesity, particularly upper-body obesity (Bliwise et al., 1987; Rajala et al., 1991; Stradling and Crosby, 1991; Grunstein et al., 1993; Schwartz et al., 2008), is a major risk factor for the development of OSAS. Upper-body obesity causes upper-arway narrowing and predisposes to upper-airway obstruction during sleep. Obesity also interacts with other risk factors such as abnormal craniofacial structure (Browman et al., 1984), causing OSAS with relatively mild obesity (Harman et al., 1982). The majority of patients with OSAS are overweight or obese (Kales et al., 1985). Obesity may be a more important risk factor for OSAS in younger adults (Tischler et al., 2003). Most studies of weight loss in the treatment of OSAS have methodological limitations, including lack of randomization, confounding factors, lack of control patients, and inadequate long-term follow-up (Strobel and Rosen, 1996). A variety of cross-sectional studies have demonstrated that changes in body weight are frequently associated with marked changes in the severity of OSAS (Peiser et al., 1984; Young et al., 2002). Dietary weight reduction was associated with significant improvements in OSAS in two controlled trials with limited numbers of patients (Smith et al., 1985; Schwartz et al., 1991). The relationship between the degree of obesity and the severity of OSAS is nonlinear (Rajala et al., 1991; Peppard et al., 2000) and the degree of improvement in OSAS severity with weight loss is unpredictable, and varies considerably between individuals. This makes it difficult to recommend a specific weight loss goal for individual patients. Weight loss may lower the effective nasal CPAP
pressure required to control OSAS and thereby potentially improve CPAP adherence. Some patients are motivated by the prospect that weight loss may allow them eventually to be free of nasal CPAP therapy. Finally, the potentially favorable impact of weight loss on comorbid conditions such as systemic hypertension, diabetes, and dyslipidemia, and their interactions with OSAS in the premature development of vascular disease should be impressed upon the patient (Browman et al., 1984). Weight loss should be encouraged in all overweight patients with OSAS; however, attempts to lose weight should not delay the initiation of additional treatment if indicated. Similar to other patient populations, successful dietary weight loss is infrequent and when acheived is often not sustained in the long term. In contrast to dietary weight loss, bariatric surgery using either a restrictive and/or malabsoptive procedures can result in a more impressive and sustained weight loss (Mun et al., 2001). In a meta-analysis of bariatric surgery for the management of obesity and OSAS (Buchwald et al., 2004), the mean percentage of excess weight loss was 70% for patients who underwent biliopancreatic diversion or duodenal switch, 68% with gastroplasty, 62% with gastric bypass, and 48% with gastric banding. The weight loss is commonly sustained and one of the commonest bariatric surgical procedures, Roux-en-Y gastric bypass, achieved a weight loss of > 50% excess body weight over a period of at least 14 years (Pories et al., 1995). Thirty-day operative mortality is 0.1–1.1% depending on the type of bariatric surgery performed. Bariatric surgery also has a morbidity and there are potential medical risks associated with recurring weight loss and weight gain. The weight loss which occurs following bariatric surgery is associated with marked reductions in AHI in some patients, along with improvements in oxygenation, sleep architecture, blood pressure, self-reported daytime alertness, multiple sleep latency scores, and upper-airway collapsibility. OSAS was resolved or improved in 83.6% of patients (Buchwald et al., 2004). Patients who are morbidly obese with a body mass index of at least 35 kg/m2, who fail a supervised weight control program, and whose OSAS cannot be successfully managed by other methods should be considered for bariatric surgery (Mun et al., 2001).
Avoidance of alcohol and respiratorydepressant medications Alcohol consumption is not different between patients with OSAS and control subjects (Jalleh et al., 1992); however, alcohol selectively suppresses upper-airway dilator muscle activity, while leaving the diaphragm virtually unaffected (Bonora et al., 1984; Krol et al., 1984).
MEDICAL AND SURGICAL TREATMENT OF This effect increases upper-airway inspiratory resistance during sleep and predisposes to the development of both snoring and OSAS. Moderate amounts of alcohol increases the AHI in normal subjects and patients with OSAS (Issa and Sullivan, 1982; Mitler et al., 1988). Patients who are unwilling to avoid alcohol completely should be advised not to drink within 3–4 hours of retiring to bed (Serima et al., 1982). Similar effects to alcohol may be seen with other respiratory depressants such as benzodiazepines, narcotics, and barbiturates. Benzodiazepines can cause or exacerbate OSAS (Mendelson et al., 1981; Dolly and Block, 1982); however, benzodiazepine antagonists have no beneficial effect on OSAS severity. Opiates and barbiturates similarly increase OSAS severity and opiates may also increase central apneas (Keifer et al., 1992; Takhar and Bishop, 2000). However, higher CPAP pressure is not required after alcohol or sedative use (Berry et al., 1991; Teschler et al., 1996). All patients should be informed of the potential for alcohol, sedatives, and narcotic medication to exacerbate OSAS.
Smoking cessation Cigarette smoking may be a risk factor for the development of snoring and OSAS. Several epidemiological studies have demonstrated a high prevalence of current smoking among individuals with snoring and OSAS (Bloom et al., 1988; Wetter et al., 1994; Teculescu et al., 2001; Casasola et al., 2002). The mechanism of this causative interaction may be related to upperairway narrowing secondary to mucosal inflammation caused by cigarette smoke exposure. However, there is some dispute as to whether smoking is an independent risk factor for OSAS (Hoffstein, 2002) and there is even one study which suggests that smoking may be protective against developing OSAS (Newman et al., 2001). Patients with OSAS who are current cigarette smokers should be counseled to stop. They should also be warned about the increased risk of weight gain which commonly follows stopping smoking.
Positional therapy Upper-airway collapsibility during sleep in adult patients with OSAS (Smith et al., 1982), is lower in the lateral compared with the supine position (Penzel et al., 2001). OSAS is more severe in the supine than in the lateral position in adult patients, although the effect of posture becomes less important as the body mass index increases (Cartwright et al., 1991; Itasaka et al., 2000; Akita et al., 2003). In contrast, the supine sleeping position may protect against OSAS in children (Fernandes et al., 2002; Cuhadaroglu et al., 2003). In a
OBSTRUCTIVE SLEEP APNEA SYNDROME 443 retrospective study of 574 adult patients with OSAS, 56% had positional apnea as defined by a supine AHI 2 times higher than lateral AHI (Oksenberg et al., 1997). These patients were younger, less obese, had less severe OSAS, and were less sleepy. OSAS severity is greater in the supine compared with the lateral sleep position (Oksenberg et al., 2000). Positional therapy involves avoidance of sleep in the supine position, and is achieved by body belts or specially designed pillows. Several studies have demonstrated improvement in OSAS severity in adults with avoidance of the supine position (Braver et al., 1995; Bahamman et al., 1999; Nakano et al., 2003) and elevation of the head (Skinner et al., 2004b; Zuberi et al., 2004). The effect of promoting the lateral sleep position for 1 month on systemic blood pressure was studied in 13 patients with OSAS, 6 of whom were hypertensive (Berger et al., 1997). Mean 24-hour awake and sleeping blood pressure decreased significantly and the reduction in systolic blood pressure was greater in the hypertensive patients compared with the normotensive patients. There is only one 2-week prospective randomized single-blind crossover study comparing CPAP and positional therapy for treatment of positional OSAS (Jokic et al., 1999). Positional treatment was highly effective in reducing supine sleep. AHI was lower and minimum oxygen was higher with nasal CPAP, positional therapy and CPAP had similar effects on quality of life, sleep architecture, alertness, mood, and cognitive performance, but the majority of patients preferred CPAP over positional therapy. Neck flexion and hyperextension are both associated with increased upper-airway resistance as compared with the neutral position (Kushida et al., 1999; Isono et al., 2004), suggesting that neck position may play a role in causing the upper-airway occlusion in OSAS. Studies that have used devices to stabilize head and neck position during sleep have shown little or no therapeutic benefit (Kushida et al., 2001; Skinner et al., 2004b). While positional therapy is effective in the short term, its long-term practicality and efficacy are unclear. There have been no long-term studies of positional therapy in the treatment of OSAS. Patients with positional OSAS tend to require a slightly lower CPAP pressure requirement than those without positional OSAS (Pevernagie and Shepard, 1992), and the optimal CPAP pressure is lower in the lateral than the supine position (Penzel et al., 2001; Isono et al., 2002). Positional therapy may also be used as an adjunct to CPAP or DA therapy for OSAS. The value of positional therapy as a long-term treatment for OSAS has not been established. Monitoring of adherence with positional treatment may also prove difficult. Positional treatment should be
444 J.A. FLEETHAM considered for patients with mild positional OSAS, deviated nasal septum or nasal polyposis may warrant and as an adjunct to facilitate effective treatment referral to an otorhinolaryngologist for consideration with CPAP or DA. of polypectomy, submucosal resection, turbinectomy, or septoplasty.
Sleep hygiene Sleep deprivation reduces chemical drives to breathe (Guilleminault and Rosekind, 1981; Cooper and Phillips, 1982; White et al., 1983), and selectively decreases upper-airway muscle activity (Leiter et al., 1985). Sleep deprivation increases the AHI in patients with mild OSAS (Guilleminault and Rosekind, 1981; Leiter et al., 1985). Sleep fragmentation increases upper-airway collapsibility to a greater extent than sleep deprivation (Series et al., 1994). Consequently, sleep fragmentation and deprivation as a result of poor sleep hygiene, OSAS, or another sleep disorder such as periodic limb movement disorder may exacerbate OSAS. There are no randomized controlled trials in this area but it is always appropriate to encourage patients to adopt measures to improve sleep hygiene, including avoidance of caffeine and other stimulants, adoption of a regular sleep–wake schedule, environmental measures to promote a comfortable undisturbed sleep, and avoidance of daytime napping.
Relief of nasal obstruction Chronic nasal obstruction secondary to anatomic abnormalities or nasal irritation is common in patients with OSAS, and can both contribute to the cause of OSAS and affect its management (Berkani et al., 1998; Lofaso et al., 2000; Young et al., 2001). Nasal obstruction can increase upstream inspiratory resistance, promoting more negative upper-airway intraluminal pressure and predisposing to upper-airway obstruction during sleep. Mouth opening (Meurice et al., 1996) and oral breathing (McNicholas et al., 1982; Lavie et al., 1983; Suratt et al., 1986; Fitzpatrick et al., 2003) predispose to the development of OSAS. Nasal obstruction has been shown to increase AHI and to cause sleep fragmentation (Lavie et al., 1981; Olsen et al., 1981; Taasen et al., 1981; McNicholas et al., 1982). Patients with OSAS and nasal obstruction do more mouth breathing during sleep (McLean et al., 2005). However, relief of nasal obstruction with decongestants or intranasal corticosteroids is rarely an effective treatment for OSAS (Kerr et al., 1992; Friedman et al., 2000; McLean et al., 2005). Relief of nasal obstruction should not be viewed as a primary treatment for OSAS, but as an adjunct to facilitate effective treatment with CPAP or DA. Patients with chronic nasal obstruction secondary to allergic rhinitis may benefit from treatment with intranasal corticosteroids. Selected patients with a grossly
PHARMACOTHERAPY Drugs as the primary treatment for OSAS A wide variety of drugs have been evaluated for the treatment of OSAS. Proposed mechanisms of action include increased respiratory drive (medroxyprogesterone, acetazolamide, theophylline, doxapram, naloxone, nicotine, carbon dioxide); rapid eye movement (REM) sleep suppression (protriptyline, clonidine, selective serotonin reuptake inhibitors); decreased sympathetic tone and baroreceptor activity (metoprolol, alazapril); stabilization of ventilation (sabeluzole); and selective activation of upper-airway dilator muscles (strychnine, paroxetine, trazodone and L-tryptophan). Two reviews have concluded that there is no evidence to support the use of pharmacologic therapy as a first-line treatment for OSAS. They also highlighted the paucity of well-designed randomized controlled trials in this area (Hudgel and Thanakitcharu, 1998; Smith et al., 2002). In a randomized double-blind placebo-controlled crossover study in 10 male patients with OSAS, 4 of whom were hypercapnic, Cook et al. (1989) found that medroxyprogesterone 150 mg/day had no effect on AHI or total sleep time. Whyte et al. (1988) compared acetazolamide, protriptyline, and placebo in 8 men and 2 women with OSAS (AHI > 15/hour) using a randomized doubleblind crossover design. Acetazolamide 250 mg qid for 14 days significantly reduced the AHI but not daytime sleepiness. Long-term use was limited by intolerable side-effects, particularly paresthesiae. Protriptyline had no beneficial effect on AHI or symptoms. In two other randomized double-blind crossover studies, protriptyline showed improvements in daytime sleepiness, but no change in AHI compared with placebo (Brownell et al., 1982; Stepanski et al., 1988). Mulloy and McNicholas (1992) studied the effect of theophylline in 12 men with OSAS in a randomized double-blind placebo-controlled crossover study. The AHI decreased significantly, but sleep quality deteriorated. Randomized, blinded, placebo-controlled crossover studies of theophylline, buspirone, sabeluzole, and clonidine have failed to demonstrate any benefit of these agents in OSAS. Several small pilot studies have demonstrated short-term beneficial effects of hormone replacement therapy in postmenopausal women with OSAS (Keefe et al., 1999; Manber et al., 2003; Wesstrom et al., 2005), but this has not been a consistent finding (Cistulli et al., 1994). There is currently insufficient long-term prospective evidence to
MEDICAL AND SURGICAL TREATMENT OF OBSTRUCTIVE SLEEP APNEA SYNDROME
445
support the use of hormone replacement therapy as a treatment for OSAS in postmenopausal women. Similarly, surface tension-reducing agents applied topically to the upper airway have very modest effect on OSAS severity (Jokic et al., 1988; Kirkness et al., 2003). In summary, pharmacological agents are not effective therapies for OSAS. The future development of novel pharmacological approaches to OSAS awaits a greater understanding of the central neuronal mechanisms and the various neurotransmitters involved in the modulation of motor output to the upper-airway muscles (Horner, 1996, 2000).
devices include neck collars (Hensley and Read, 1976; Skinner et al., 2004a), nasal valve dilators (Pevernagie et al., 2000; Schonhofer et al., 2000), nasopharyngeal tubes (Nahmias and Karetzky, 1988), electrical stimulation of upper-airway dilator muscles (Schwartz et al., 2001), transtracheal air insufflation (Schneider et al., 2000), and atrial pacing (Garrigue et al., 2002). The Clinical Practice Review Committee of the American Academy of Sleep Medicine has concluded that there were insufficient data upon which to base standards of practice recommendations for any of these nonprescription treatments for OSAS (Meoli et al., 2003).
Drugs as an adjunct to treatment of sleep apnea
DENTAL APPLIANCES
Modafinil is an awake-promoting agent used to treat daytime fatigue and sleepiness caused by a variety of conditions (Black and Hirshkowitz, 2005). Two randomized double-blind placebo-controlled trials of modafinil in patients with OSAS who had residual sleepiness despite nasal CPAP therapy showed significant improvement in alertness (Kingshott et al., 2001) and subjective and objective daytime sleepiness (Pack et al., 2001). Similarly, in a pilot study, the tumor necrosis factor-alpha antagonist, etanercept, reduced daytime sleepiness in untreated patients with OSAS (Vgontzas et al., 2004). Awake-promoting agents may be a useful adjunct in the treatment of patients who remain sleepy despite adequate sleep hygiene, and who comply with effective treatment for OSAS.
DAs are now widely used for the treatment of snoring and mild to moderate OSAS, both as primary therapy and as an alternative for patients who are unwilling or unable to tolerate CPAP. DAs are an appealing treatment option for patients as they are small and simple to use. There is a variety of synonyms for DAs. In addition to dental, they may be called oral, intraoral, or mandibular; and instead of appliance, they may be called a device, splint, or prosthesis. DA therapy for OSAS remains underutilized despite several recent reviews (Ferguson et al., 2006; Fleetham, 2007; Hoffstein, 2007; Chan et al., 2008) and recommendations from both the Cochrane Collaboration (Lim et al., 2006) and American Academy of Sleep Medicine (Kushida et al., 2006).
Appliance type OXYGEN OSAS is usually associated with arterial oxygen desaturation during the night, which may contribute to the development of cognitive impairment, pulmonary hypertension, and cardiac arrhythmias. Supplemental nocturnal oxygen is an accepted treatment for patients with chronic obstructive pulmonary disease with sleep hypoxemia. Supplemental oxygen improves arterial oxygen desaturation during the night in patients with OSAS. However, it has no impact on daytime sleepiness and increases apnea duration while reducing apnea frequency only slightly (Martin et al., 1982; Gold et al., 1986). Supplemental oxygen should not be used as a primary treatment for OSAS but is indicated as an adjunct therapy for patients with OSAS on CPAP who have persistent arterial oxygen desaturation at the highest tolerated pressures.
MISCELLANEOUS DEVICES There is a variety of pilot studies of miscellaneous devices in the treatment of OSAS but none have been evaluated by randomized controlled trials. These
There are currently a large number of different DAs available for the treatment of OSAS. DAs increase the size of the upper airway by advancing either the mandible or the tongue (George, 1987; Bernstein and Reidy, 1988; Bonham et al., 1988; Clark et al., 1993). There are other minor design differences in the DA currently available that may also have an impact on their success and treatment adherence. Mandibular advancement DAs are most widely used and utilize traditional dental techniques to attach the DA to one or both dental arches (Figure 29.1). Construction usually requires dental impressions, bite registration, and fabrication by a dental laboratory. Some DAs are available in a prefabricated form and are sometimes referred to as “boil and bite” (Schmidt Nowara et al., 1991). These can either be fitted by patients themselves or molded to the patient’s teeth in an office setting. Some DAs restrict mouth opening by means of clasps, whereas others allow relatively unhindered movement. More recently, DAs have been developed with an adjustable hinge that allows progressive advancement of the mandible after initial construction until the
446
J.A. FLEETHAM
Fig. 29.1. Lateral view of a fabricated adjustable mandibular advancement oral appliance, Klearway. (Courtesy of Dr. A Lowe.)
optimal mandibular position is achieved (Figure 29.2). The amount of anterior–posterior mandibular movement and the speed with which this can be changed vary considerably between patients. DAs sometimes include tubes or openings for oral breathing or pressure relief. Several DAs feature a posterior extension of the maxillary component to modify the position of the soft palate or tongue. Mandibular advancement DAs require at least 8 teeth in each of the maxillary and mandibular arches. Furthermore, patients should be able to advance their mandible by at least 5 mm
Fig. 29.2. The screw mechanism from the adjustable oral appliance Klearway that connects the mandibular and maxillary components and enables progressive advancement of the mandible. (Courtesy of Dr. A Lowe.)
without discomfort. Temporomandibular joint disease, bruxism, and advanced periodontal disease are all relative contraindications to mandibular advancement DA treatment. The other major type of DA available is the tongue retainer that keeps the tongue in an anterior position during sleep by means of negative pressure in a soft plastic bulb. It fits over both the mandibular and maxillary arches and has a flange which fits between the lips and teeth, keeping the appliance anterior in the mouth. This appliance was one of the first to be developed and is available in both a fabricated and prefabricated form (Cartwright and Samelson, 1982; Cartwright et al., 1988). It can be used in edentulous patients and is the DA of choice for patients with no teeth, limited anterior–posterior mandibular movement, or a large tongue. A combined medical and dental approach to DA treatment is important. DA therapy should be supervised by both medical and dental specialists with a major interest in the management of sleep-disordered breathing. Patients should not have major periodontal disease and all dental restorations should be completed prior to DA therapy.
Mechanism of action The majority of DAs are designed to maintain the mandible and/or tongue in a protruded posture, thereby preventing upper-airway obstruction during sleep. Proposed mechanisms of action of DA include increased upper-airway size, decreased upper-airway collapsibility, activation of upper-airway dilator muscles, and stabilization of mandibular posture. Several different upper-airway imaging techniques have been used to assess changes in upper-airway size and function with DA in patients with OSAS. These imaging techniques include cephalometry, computed tomography, magnetic resonance imaging, and videoendoscopy. Voluntary mandibular and tongue protrusion has been shown to increase upper-airway size and alter upper-airway shape, particularly in the velopharynx in subjects with and without OSAS (Ryan et al., 1999). Several studies have demonstrated an increase in the anteroposterior diameter of the upper airway following DA insertion (Lowe et al., 1990; Johnson et al., 1992; Eveloff et al., 1994). This increase was predominantly in the oropharynx and hypopharynx, but some studies have also suggested an effect on the velopharynx (Ng et al., 2003). Almost all of these upper-airway imaging studies have been performed during wakefulness and it is unknown whether the same changes occur during sleep. Mandibular advancement DAs have been shown to increase upper-airway muscle tone, which may also contribute to increased upper-airway patency.
MEDICAL AND SURGICAL TREATMENT OF OBSTRUCTIVE SLEEP APNEA SYNDROME
Efficacy The effectiveness of DA therapy can be influenced by the patient’s body mass index, the severity of OSAS, the presence of positional OSAS, and the degree of mandibular advancement obtained with the DA. Until recently, the majority of the data concerning the efficacy of DA in the treatment of OSAS were from uncontrolled case series studies which were subject to study design issues such as regression to the mean, and selection and reporting bias. There is increasing evidence that DAs improve daytime sleepiness, systemic hypertension, and indices of sleep-disordered breathing. A variety of prospective randomized trials have been performed to evaluate the efficacy, side-effects, compliance, and preference of DA treatment in patients with OSAS. There are at least six randomized controlled trials comparing DA to an inactive control (Mehta et al., 2001; Gotsopoulos et al., 2002, 2004; Naismith et al., 2005; Lim et al., 2006) that demonstrate that DAs improve daytime sleepiness, systemic hypertension, and indices of sleep-disordered breathing in patients with OSAS. Additional well designed, largescale randomized controlled trials comparing active and control DA are required to determine which groups of patients are most likely to benefit from DA treatment, how these patients can be identified, how much benefit can be achieved and with what cost, side-effects, and complications. At least nine randomized controlled trials have compared the efficacy and side-effects of DA and CPAP (Lim et al., 2006). Although both CPAP and DA led to improvements in daytime sleepiness, health status, and AHI, the magnitude of improvement in AHI was significantly more with CPAP. Furthermore, it takes longer to obtain optimal treatment with a DA than CPAP, which can be a major issue in patients with excessive daytime sleepiness. More patients were unwilling or unable to use a DA than CPAP. However, patients who responded to both treatments preferred the use of a DA over CPAP. All of the randomized controlled trials have been shortterm studies over 3–6 months, but there are now several nonrandomized studies establishing long-term efficacy over 4–5 years (Marklund et al., 2001; Walker-Engstro¨m et al., 2002). DA design has been proposed as an important determinant of treatment success, and there have been at least five prospective comparative studies evaluating different DA designs (Lawton et al., 2005; Lim et al., 2006). There were varying degrees of improvement in indices of sleep-disordered breathing and side-effects with different DAs. These differences may be related to the degree of vertical opening and mandibular
447
advancement achieved with each DA. Finally, one longitudinal parallel group study compared the effectiveness of DA with uvulopalatopharyngoplasty (UPPP) in patients with mild to moderate OSAS over 4 years, which suggests that a DA was more effective than UPPP in improving indices of sleep-disordered breathing (Walker-Engstro¨m et al., 2002). However, the significance of this finding is questionable, as there is no definitive evidence of the effectiveness of this type of corrective upper-airway surgery. DA therapy may also be indicated as an adjuvant to nasal CPAP when the patient is away from home or electrical power (Smith and Stradling, 2002). DAs have also been used as combination therapy in patients who have had an unsuccessful response to UPPP (Millman et al., 1998).
Predictors of success A variety of predictors of DA treatment success have been proposed (Marklund et al., 2004; Horiuchi et al., 2005; Ng et al., 2006). It has been suggested that younger, less obese patients with OSAS that occurs predominantly in the supine position may be more likely to obtain a successful response with a DA. Treatment success may be inversely related to pretreatment severity, but this relationship may just be a function of the definition of treatment success. Several upper-airway skeletal and soft-tissue measurements made from pretreatment lateral cephalometry have been shown to be associated with treatment success. These include a more micrognathic or retrognathic mandible, and small soft palate and tongue. Upper-airway fluoroscopy has also been proposed as a technique to guide successful DA therapy. A hypopharyngeal site of obstruction may be associated with a better treatment outcome. However, there is considerable overlap between good and poor treatment responses with all these variables (Otsuka et al., 2006). The utility of any treatment recommendation based on clinical features, OSAS severity, or upper-airway anatomy requires prospective validation.
Treatment adherence Self-reported treatment adherence data for up to 5 years are available for DA therapy. Self-reported treatment adherence has been reported as high as 96% patients using DA for >75% nights, and 80% patients used DA >75% of each night (Ferguson et al., 1996). Treatment adherence varies between DA type and appears better with mandibular advancement than tongue-retaining DA. Adherence rates appear to decrease with duration of use and have been reported as 60% at 1 year and 48% at 2 years. Previous
448 J.A. FLEETHAM experience with nasal CPAP suggests that self-reported to patients with mild symptomatic OSAS and those treatment adherence tends to overestimate actual use. patients who are unwilling or unable to comply with Attempts to develop a covert DA compliance monitor CPAP therapy. The American Academy of Sleep Medhave been fraught with technological difficulties and, icine (Kushida et al., 2006) reviewed similar data to the at present, limited objective DA compliance data are Cochrane Collaboration and recommended that DAs available. were indicated for use in patients with mild to moderate OSAS who prefer them to CPAP, or who do not respond to, or are not appropriate candidates for, or Side-effects and complications who fail treatment with CPAP. They recommended Side-effects are common but generally minor. ExcesCPAP therapy whenever possible for patients with sive salivation, mouth dryness, morning-after occlusal severe OSAS. DAs can increase OSAS severity so it changes, and discomfort in the gums, teeth, or jaw is important to perform follow-up sleep monitoring are common side-effects in the first weeks of DA therto verify the efficacy of DA therapy. Patients treated apy, but usually resolve with time (De Almeida et al., with DAs require long-term dental follow-up to moni2005, 2006). More persistent and severe side-effects, tor patient adherence, evaluate DA deterioration or which include tooth movement, occlusal alteration, maladjustment and to evaluate the health of the oral temporomandibular joint dysfunction, and dental structures and integrity of the occlusion. crown damage, appear uncommon (Marklund, 2006). Small occlusal changes may be found in 14% of UPPER-AIRWAY SURGERY patients after 5 years of DA treatment (Pantin and Tennant, 1999; Ringqvist et al., 2003). The clinical sigUpper-airway surgery is the treatment of choice in the nificance of these occlusal changes is uncertain. DA fewer than 1% of patients with OSAS who have a speadjustment can decrease side-effects by reducing prescific anatomic upper-airway lesion such as adenotonsilsure on the anterior teeth and excessive mandibular lar enlargement, antrochoanal polyp, or tumor advancement. Side-effects vary between type of DA, (Rojeweski et al., 1984; Sher, 1990). Tracheostomy was with tongue pain occurring in tongue retention DA the primary treatment for severe OSAS prior to the and gagging associated with DAs that have a maxillary introduction of CPAP (Motta et al., 1978; Guilleminault component to modify soft-palate position. et al., 1981). The long-term morbidity associated with
Cost The cost of DA therapy varies depending on the type of DA used and the extent and expertise of the dental supervision. Consensus opinion indicates that a prefabricated DA can range from $45 to $100 and custommade DAs range from $100 to over $600 (Ferguson et al., 2006). DAs usually remain effective for at least 5 years, but they can break and require either repair or replacement. Dentist service fees vary greatly, between $200 and $2500, depending on the time spent caring for the patient and geographic economic factors. Costs can equal or exceed those associated with nasal CPAP therapy. There is increasing evidence that both DAs and nasal CPAP are cost-effective treatments for OSAS (Ayas et al., 2006; Sadatsafavi et al., 2009).
Treatment recommendations A Cochrane systematic review (Lim et al., 2006) has concluded that there was increasing evidence that DAs improve subjective daytime sleepiness and sleepdisordered breathing compared with control appliances. However, it recommended that, until there was more definitive evidence on the effectiveness of DA compared to CPAP, DA therapy should be restricted
tracheostomy led to the development of a variety of other upper-airway surgical procedures for the treatment of OSAS. The goal of these procedures is to remove the site of upper-airway obstruction by either increasing upper-airway size or decreasing upper-airway collapsibility. The procedures achieve this by: (1) resection of redundant soft tissue (nasal surgery, UPPP, laser-assisted uvulopalatoplasty, midline glossectomy); (2) induction of scar tissue formation (cautery or radiofrequency ablation of soft palate, tongue, or epiglottis); or (3) displacement of bony and ligamentous attachments of upper-airway soft-tissue structures (maxillary and mandibular osteotomies, tongue and hyoid suspensions). There are two detailed reviews of the literature on surgery for OSAS (Ryan, 2005; Sundaram et al., 2006). They identified only a few randomized or quasirandomized trials comparing upper-airway surgery with conservative management or other treatments for OSAS. Consequently, any recommendations regarding the role of upper-airway surgery in the treatment of OSAS must take into account the weakness of the existing data. CPAP should be used to treat patients preoperatively and to protect against postoperative upper-airway obstruction. Long-term follow-up is strongly recommended because the long-term efficacy of upper-airway surgery has not been well established.
MEDICAL AND SURGICAL TREATMENT OF OBSTRUCTIVE SLEEP APNEA SYNDROME 449 infection were reported in the UPPP group. Another Tonsillectomy study evaluated the short-term and long-term response Adenotonsillar hypertrophy is a common cause of to UPPP or UPPP plus tonsillectomy (Verse et al., OSAS in children. Adenotonsillectomy is curative in 2000). Snoring was improved in the majority of patients 75–100% of children with OSAS (Schechter, 2002). at long-term follow-up. The oxygen desaturation index Adenotonsillar hypertrophy is occasionally the primary was improved in some patients at short-term followcause of OSAS in adults. Eight of 9 patients had a up. UPPP in combination with tonsillectomy was more reduction in AHI of 50% or to < 20/hour postopereffective than UPPP alone. UPPP can result in an atively in a prospective study of tonsillectomy in adult increase in OSAS severity (Sher et al., 1996) and subjecpatients (Verse et al., 2000). The presence of large tontive outcomes do not always match objective outcomes. sils in a patient with OSAS should prompt referral to One study found the majority of patients reported an otolarygologist for consideration of tonsillectomy. reduced snoring and improved sleep despite lack of improvement in the AHI, and snoring intensity followUvulopalatopharyngoplasty ing UPPP surgery (Miljeteig et al., 1994). Consequently, UPPP is a procedure introduced in the early 1980s it is important to perform follow-up sleep monitoring (Fujita et al., 1981) which has been widely used for to verify there has been an objective improvement in the treatment of OSAS. This procedure attempts to OSAS severity. enlarge the retropalatal airway by excising the tonsils UPPP may be more effective in patients with retroalong with portions of the anterior and posterior tonsilpalatal obstruction than in patients who also have a retlar pillars, and the free margin of the soft palate rolingual obstruction (Sher et al., 1996). Five percent of including the uvula, while preserving the function of patients with OSAS and retrolingual obstruction the proximal palatal musculature. Sher and associates obtained a good response to UPPP compared with (1996) performed a meta-analysis of 37 reports pub52% of patients with a retropalatal obstruction. The lished between 1966 and 1995 on UPPP for the treatgood responders had a lower mean AHI compared ment of OSAS. UPPP resulted in a mean 38% with the poor responders. Langin and coworkers reduction in AHI. A higher AHI was associated with (1998) performed cephalometry and upper-airway coma lesser improvement post-UPPP. A good response to puted tomography scans on 20 patients before and UPPP, as defined by a 50% decrease in AHI and a after UPPP. Thirty-five percent had a good response postoperative apnea index < 10/hour and AHI < 20/ to UPPP and these patients had an increase in retropahour, was obtained in 41% of patients. There is one latal oropharynx post-UPPP, whereas poor responders randomized controlled trial comparing UPPP with condid not. The post-UPPP velopharynx was larger in good servative management (Lojander et al., 1996). Daytime responders compared with poor responders. The sleepiness was improved in the surgical group but there change in the size of the narrowest segment of the orowas no difference in oxygen desaturation index pharynx correlated with the change in the AHI, sugbetween the two groups at 12 months. The surgical gesting that failure to increase velopharynx size may complication rate was 22%. Complications included be one of the causes of a failure to achieve a good infection, tracheostomy, and dysphagia. One patient response with UPPP. had a myocardial infarction and one patient had a tranThere is limited long-term follow-up on UPPP. In a sient ischemic attack following surgery. study of 50 patients following UPPP for OSAS, the One randomized trial compared UPPP to lateral good response progressively decreased from 60% at pharyngoplasty (Cahali et al., 2004). Daytime sleepi6 months to 30% at 21 months during the long-term ness was improved in both groups, but AHI was only follow-up which was associated with significant weight significantly reduced in the lateral pharyngoplasty gain (Larsson et al., 1994). Complication rates are diffigroup. Nasal regurgitation was noted with equal frecult to determine from the literature. Postoperative quency in both groups. There is another randomized pain is common but self-limited. Velopharyngeal insuftrial of UPPP versus laser-assisted uvulopalatoplasty ficiency may occur in up to 40% of patients (Zohar (LAUP) for the treatment of snoring in patients with et al., 1991). Velopharygeal stenosis has also been palatal flutter (Osman et al., 2000). Eighty percent of reported and may explain the worsening of OSAS in patients had a subjective improvement in their snoring some patients post-UPPP. Postoperative upper-airway and the objective snoring index was also significantly obstruction has been reported in 10% of patients, and reduced with both procedures. Some of the LAUP some deaths have occurred (Esclamado et al., 1989). patients had a higher snoring index after surgery. No UPPP may interfere with the patient’s ability to tolerate postoperative complications were reported in the LAUP CPAP therapy. Patients with a prior UPPP develop a group, but bleeding, velopharyngeal insufficiency, and mouth leak at a lower CPAP pressure than patients
450
J.A. FLEETHAM
with OSAS without prior UPPP (Mortimore et al., 1996). Furthermore, patients with prior UPPP have a lower adherence with CPAP than patients with OSAS without a UPPP (Janson et al., 2000). UPPP may be considered in selected patients with OSAS who have failed CPAP and/or DA treatment. Patients being offered UPPP should be informed about the limited efficacy, potential complications, and risk of subsequent difficulty with CPAP treatment.
Laser-assisted uvulopalatoplasty LAUP is a modified UPPP procedure with less radical resection of palatal tissue. LAUP is performed with a carbon dioxide laser as either a one-stage or multistage office procedure under local anesthesia (Dickson and Mintz, 1996). Although it was originally introduced for the treatment of snoring (Kamami, 1990), more recently it has been used to treat patients with OSAS (Ryan, 2005). Two meta-analyses (Verse and Pirsig, 2000; Littner et al., 2001) reviewed over 70 articles published between 1980 and 2000. These meta-analyses revealed a small reduction in AHI post-LAUP. Applying similar criteria to those outlined earlier for UPPP, good response rates of between 27 and 41% were reported with LAUP. In all, 20–30% of patients were objectively worse post-LAUP, which may be caused by palatal fibrosis and subsequent upper-airway narrowing (Finkelstein et al., 1997; Berger et al., 2003). Subsequently, in the only randomized controlled trial to date, 45 patients with mild OSAS were assigned to either LAUP or no treatment (Ferguson et al., 2003). AHI was reduced by a mean 21% in the LAUP-treated group compared with no change in the control group. Less than 25% of the LAUP-treated patients had a good response in terms of a reduction in AHI to less than 10/hour with an associated symptomatic improvement. There was no difference in the change in subjective sleepiness between the two treatment groups. Both snoring severity and frequency based on visual analog scales were reduced in the LAUP group. There was no difference between the two treatment groups in change of quality-of-life scores. Despite this limited efficacy, approximately 50% of patients were satisfied with LAUP. Reported adverse effects include postoperative pain, nasal regurgitation, dysphagia infection, change in vocal quality and a sensation of dry throat. The development of postoperative upper-airway edema and narrowing has raised concerns about the advisability of performing LAUP as an outpatient procedure in patients with OSAS (Terris et al., 1996). The long-term results of LAUP have not been defined, but there are some data to suggest that short-term improvements are not maintained over time (Berger
et al., 2003). Practice parameters issued by the American Academy of Sleep Medicine advise that LAUP is not recommended for the treatment of OSAS (Littner et al., 2001).
Other palatal procedures A variety of other surgical procedures which either stiffen or ablate palatal tissue have been described for the treatment of both snoring and OSAS. These include laser palatoplasty (Ellis et al., 1993), laser cautery-assisted palatal stiffening (Wassmuth et al., 2000), and temperature-controlled radiofrequency tissue ablation (TCRFTA) of the tongue and soft palate (Stuck et al., 2004). A randomized controlled trial comparing TCRFTA with sham placebo surgery and nasal CPAP therapy has been performed in patients with mild to moderate OSAS (Woodson et al., 2003). There were no differences in outcomes between TCRFTA and CPAP. TCRFTA increased airway volume, reduced AHI, and improved quality of life. Compared with sham surgery, TCRFTA does not reduce the AHI sufficiently to be recommended as a treatment for OSAS.
Nasal surgery There are no randomized controlled trials of nasal surgery as a treatment for OSAS. It is rarely an effective treatment for OSAS (Verse et al., 2002). There was an improvement in OSAS following nasal surgery in a subgroup of patients without a narrow upper airway (Series et al., 1992), which suggests that the failure of nasal surgery to improve OSAS may be related to the persistent upper-airway narrowing. Relief of nasal obstruction may reduce snoring (Fairbanks, 1984; Hoffstein et al., 1993; Todorova et al., 1998; Pevernagie et al., 2000; Schonhofer et al., 2000) and may help to facilite CPAP treatment (Friedman et al., 2000; Powell et al., 2001). Nasal surgery is not indicated as a primary treatment for OSAS, but may play a role in improving CPAP adherence.
Maxillary and mandibular surgery A variety of maxillary and mandibular surgical procedures have been developed to relieve upper-airway obstruction distal to the velopharynx, in the retroglossal oropharynx and hypopharynx (Won et al., 2008). Inferior sagittal mandibular osteotomy with genioglossus advancement, hyoid myotomy, and hyothyroidopexy, total subapical mandibular osteotomy, bilateral sagittal split mandibular osteotomy, and LeFort 1 maxillary osteotomy are performed in various combinations and are designed to advance the ventral wall of the pharynx. There are no randomized controlled
MEDICAL AND SURGICAL TREATMENT OF OBSTRUCTIVE SLEEP APNEA SYNDROME studies of this type of surgery for OSAS. The literature is difficult to interpret because of the different surgical procedures, the adjunct procedures used (e.g., hyoid suspension, septoplasty, UPPP), the selection of patients with different skeletal types, confounding variables such as postoperative weight loss, and varying definitions of a good response. A total of 306 patients with OSAS were treated in a two-phase surgical approach (Riley et al., 1993). Stage I procedures included UPPP for retropalatal narrowing, and inferior sagittal mandibular osteotomy with genioglossus advancement, hyoid myotomy, and suspension for retroglossal obstruction. Patients who failed to respond adequately to the stage I procedure were offered the stage II procedure, consisting of maxillomandibular advancement. Good response rates to stage I surgical procedures ranged between 23 and 67%. Stage II procedures yielded good response rates between 75 and 100%, whether as primary treatment or following stage I surgery (Waite et al., 1989; Riley et al., 1993; Hochban et al., 1994, 1997; Prinsell, 1999; Bettega et al., 2000). Maxillomandibular advancement has been proposed as the primary surgical treatment without a staged approach. Limited long-term follow-up suggests that good response rates of 80% persist for at least 2 years (Conradt et al., 1997). A combined surgical and dental approach is important to ensure satisfactory dental occlusion postoperatively. Complications of stage I surgery include anesthesia of the lower lip in the majority of patients, and postoperative upper-airway obstruction. Anesthesia of the cheek, lower lip, and chin are common after stage II procedures and a change in facial appearance is to be anticipated. Maxillomandibular surgery may be effective in carefully selected patients with OSAS who have failed CPAP and/or DA treatment.
Tongue base surgery Glossoplasty, laser midline glossectomy, lingualplasty, and tongue base suspension have all been developed to remove excess lingual tissue and increase retrolingual oropharyngeal size in patients with snoring or OSAS. A randomized trial compared tongue advancement done by a mandibular osteotomy in conjunction with UPPP to tongue suspension with UPPP (Thomas et al., 2003). AHI was not reported, but there were significant improvements in subjective daytime sleepiness in both treatment groups. There are insufficient data to recommend tongue base surgery as a treatment for OSAS. Most forms of upper-airway surgery have not been proven to have benefit for the treatment of OSAS in controlled clinical trials. New or unproven procedures should be considered experimental and rigorously tested
451
in research studies prior to widespread implementation in clinical practice.
Tracheostomy Tracheostomy was commonly performed for severe OSAS prior to the introduction of CPAP (Weitzman et al., 1980; Conway et al., 1981; Guilleminault et al., 1981). It is the only surgical procedure that consistently relieves OSAS by bypassing the recurrent upper-airway obstruction during sleep. Central apneas and hyponeas may occur after tracheostomy, but usually resolve within 6 months (Guilleminault and Cummiskey, 1982). Tracheostomy is associated with long-term morbidity related to granulation tissue and the cosmetic effect with its associated psychosocial morbidity (Weitzman et al., 1980). There are no randomized studies of tracheostomy for the treatment of OSAS. Tracheostomy should only be considered in carefully selected patients with OSAS when all other treatments fail.
REFERENCES Akita Y, Kawakatsu K, Hattori C et al. (2003). Posture of patients with sleep apnea during sleep. Acta Otolaryngol Suppl 41–45. Ayas NT, FitzGerald JM, Fleetham JA et al. (2006). Costeffectiveness of continuous positive airway pressure for moderate to severe obstructive sleep apnea hypopnea. Arch Intern Med 166: 977–984. Bahammam AS, Tate R, Manfreda J et al. (1999). Upper airway resistance syndrome: effect of nasal dilation, sleep stage, and sleep position. Sleep 22: 592–598. Berger M, Oksenberg A, Silverberg DS et al. (1997). Avoiding the supine position during sleep lowers 24 h blood pressure in obstructive sleep apnea (OSA) patients. J Human Hypertens 11: 657–664. Berger G, Stein G, Ophir D et al. (2003). Is there a better way to do laser-assisted uvulopalatoplasty? Arch Otolaryngol Head Neck Surg 129: 447–453. Berkani M, Lofaso F, Chouaid C et al. (1998). CPAP titration by an auto-CPAP device based on snoring detection: a clinical trial and economic considerations. Eur Respir J 12: 759–763. Bernstein AK, Reidy RM (1988). The effects of mandibular repositioning on obstructive sleep apnea. Cranio 6: 179–181. Berry RB, Desa MM, Light RW (1991). Effect of ethanol on the efficacy of nasal continuous positive airway pressure as a treatment for obstructive sleep apnea. Chest 99: 339–343. Bettega CT, Pepin J-L, Veale D et al. (2000). Obstructive sleep apnea syndrome: fifty-one consecutive patients treated by maxillofacial surgery. Am J Respir Crit Care Med 162: 641–649. Black JE, Hirshkowitz M (2005). Modafinil for treatment of residual excessive sleepiness in nasal continuous positive airway pressure-treated obstructive sleep apnea/hypopnea syndrome. Sleep 28: 464–471.
452
J.A. FLEETHAM
Bliwise D, Feldman D, Bliwise N et al. (1987). Risk factors for sleep disordered breathing in heterogeneous geriatric populations. J Am Geriatr Soc 35: 132–141. Bloom JW, Kaltenhorn WT, Quan SF et al. (1988). Risk factors in a general population for snoring: importance of cigarette smoking and obesity. Chest 93: 678–683. Bonham PE, Currier GF, Orr WC et al. (1988). The effect of a modified functional appliance on obstructive sleep apnea. Am J Orthod Dentofacial Orthop 94: 384–392. Bonora M, Shields GI, Knuth SL et al. (1984). Selective depression by ethanol of upper airway respiratory motor activity in cats. Am Rev Respir Dis 130: 156–161. Braver HM, Block AJ, Perri MG (1995). Treatment for snoring. Combined weight loss, sleeping on side, and nasal spray. Chest 107: 1283–1288. Browman CP, Sampson MG, Yolles SF et al. (1984). Obstructive sleep apnea and body weight. Chest 85: 435–436. Brownell LG, West P, Sweatman P et al. (1982). Protriptyline in obstructive sleep apnea: a double blind trial. N Engl J Med 307: 1037–1042. Buchwald H, Avidor Y, Braunwald E et al. (2004). Bariatric surgery: a systematic review and meta-analysis. JAMA 292: 1724–1737. Cahali MB, Formigoni GG, Gebrim EM et al. (2004). Lateral pharyngoplasty versus uvulopalatopharyngoplasty: a clinical, polysomnographic and computed tomography measurement comparison. Sleep 27: 942–950. Cartwright RD, Samelson CF (1982). The effects of a nonsurgical treatment for obstructive sleep apnea. The tongue-retaining device. JAMA 248: 705–709. Cartwright R, Stefoski D, Caldarelli D et al. (1988). Toward a treatment logic for sleep apnea: the place of the tongue retaining device. Behav Res Ther 26: 121–126. Cartwright RD, Diaz F, Lloyd S (1991). The effects of sleep posture and sleep stage on apnea frequency. Sleep 14: 351–353. Casasola GG, Alvarez-Sala JL, Marques JA et al. (2002). Cigarette smoking behavior and respiratory alterations during sleep in a healthy population. Sleep Breath 6: 19–24. Chan AS, Lee RW, Cistulli PA (2008). Non-positive airway pressure modalities: mandibular advancement devices/ positional therapy. Proc Am Thorac Soc 5 (2): 173–176. Cistulli PA, Barnes DJ, Grunstein RR et al. (1994). Effect of short-term hormone replacement in the treatment of obstructive sleep apnoea in postmenopausal women. Thorax 49: 699–702. Clark GT, Arand D, Chung E et al. (1993). Effect of anterior mandibular positioning on obstructive sleep apnea. Am Rev Respir Dis 147: 624–629. Conradt R, Hochban W Brandenburg U et al. (1997). Longterm follow-up after surgical treatment of obstructive sleep apnoea by maxillomandibular advancement. Eur Respir J 10: 123–128. Conway WA, Victor LD, Magilligan DJ Jr et al. (1981). Adverse effects of tracheostomy for sleep apnea. JAMA 246: 347–350.
Cook WR, Benich JJ, Wooten SA (1989). Indices of severity of obstructive sleep apnea syndrome do not change during medroxyprogesterone acetate therapy. Chest 96: 262–266. Cooper KR, Phillips BA (1982). Effect of short-term sleep loss on breathing. J Appl Physiol 53: 855–858. Cuhadaroglu C, Keles N, Erdamar B et al. (2003). Body position and obstructive sleep apnea syndrome. Pediatr Pulmonol 36: 335–338. De Almeida FR, Lowe AA, Tsuiki S et al. (2005). Long term compliance and side-effects of oral appliances used for the treatment of snoring and obstructive sleep apnea syndrome. J Clin Sleep Med 1: 143–152. De Almeida FR, Lowe AA, Otsuka R et al. (2006). Longterm sequelae of oral appliance therapy in obstructive sleep apnea patients: Part 2. Study-model analysis. Am J Orthod Dentofacial Orthop 129: 205–213. Dickson RI, Mintz DR (1996). One-stage laser assisted uvulopalatoplasty. J Otolaryngol 25: 155–161. Dolly FR, Block AJ (1982). Effect of flurazepam on sleepdisordered breathing and nocturnal desaturation in asymptomatic subjects. Am J Med 73: 239–243. Ellis PD, Williams JEF, Shneerson JM (1993). Surgical relief of snoring due to palatal flutter: a preliminary report. Ann R Coll Surg 75: 286–290. Esclamado RM, Glenn MG, McCulloch TM et al. (1989). Perioperative complications and risk factors in the surgical treatment of obstructive sleep apnea syndrome. Laryngoscope 99: 1125–1129. Eveloff SE, Rosenberg CL, Carlisle CC et al. (1994). Efficacy of a Herbst mandibular advancement device in obstructive sleep apnea. Am J Respir Crit Care Med 149: 905–909. Fairbanks DN (1984). Snoring: surgical vs. nonsurgical management. Laryngoscope 94: 1188–1192. Ferguson KA, Ono T, Lowe AA et al. (1996). A randomized crossover study of an oral appliance vs. nasal-continuous positive airway pressure in the treatment of mild-moderate obstructive sleep apnea. Chest 109: 1269–1275. Ferguson KA, Heighway K, Ruby RR (2003). A randomized trial of laser-assisted uvulopalatoplasty in the treatment of mild obstructive sleep apnea. Am J Respir Crit Care Med 167: 15–19. Ferguson KA, Cartwright R, Rogers R et al. (2006). Oral appliances for snoring and sleep apnea: a review. Sleep 29: 244–262. Fernandes DO, Prado LB, Li X, X R et al. (2002). Body position and obstructive sleep apnea in children. Sleep 25: 66–71. Finkelstein Y, Shapiro-Feinberg M, Stein G et al. (1997). Uvulopalatopharyngoplasty vs laser-assisted uvulopalatoplasty. Arch Otolaryngol Head Neck Surg 123: 265–276. Fitzpatrick MF, McLean H, Urton AM et al. (2003). Effect of nasal or oral breathing route on upper airway resistance during sleep. Eur Respir J 22: 827–832. Fleetham JA (2007). Sleep apnea: oral appliances. In: GJ Laurent, SD Shapiro (Eds.), Encyclopedia of Respiratory Medicine. Vol. 4. Elsevier, Oxford, pp. 67–70.
MEDICAL AND SURGICAL TREATMENT OF OBSTRUCTIVE SLEEP APNEA SYNDROME Fleetham J, Ayas N, Bradley D et al. (2006). Canadian Thoracic Society guidelines: diagnosis and treatment of sleep disordered breathing in adults. Can Respir J 13 (7): 38l7–392. Friedman M, Tanyeri H, Lim JW et al. (2000). Effect of improved nasal breathing on obstructive sleep apnea. Otolaryngol Head Neck Surg 122: 71–74. Fujita S, Conway W, Zorick F et al. (1981). Surgical correction of anatomic abnormalities in obstructive sleep apnea syndrome: uvulopalatopharyngoplasty. Otolaryngol Head Neck Surg 89: 923–934. Garrigue C, Bordier P, Jais P et al. (2002). Benefit of atrial pacing in sleep apnea syndrome. N Engl J Med 346: 404–412. George PT (1987). A modified functional appliance for treatment of obstructive sleep apnea. J Clin Orthod 21: 171–175. Gold AR, Schwartz AR, Bleecker ER et al. (1986). The effect of chronic nocturnal oxygen administration upon sleep apnea. Am Rev Respir Dis 134: 925–929. Gotsopoulos H, Chen C, Qian J et al. (2002). Oral appliance therapy improves symptoms in obstructive sleep apnoea syndrome. a randomised controlled trial. Am J Resp Crit Care Med 166: 743–748. Gotsopoulos H, Kelly JJ, Cistulli PA (2004). Oral appliance therapy reduces blood pressure in obstructive sleep apnea: a randomized, controlled trial. Sleep 27: 934–941. Grunstein R, Wilcox I, Yang T et al. (1993). Snoring and sleep apnea in men: association with central obesity and hypertension. Int J Obesity 17: 533–540. Guilleminault C, Cummiskey J (1982). Progressive improvement of apnea index and ventilatory response to CO2 after tracheostomy in obstructive sleep apnea syndrome. Am Rev Respir Dis 126: 14–20. Guilleminault C, Rosekind M (1981). The arousal threshold: sleep deprivation, sleep fragmentation, and obstructive sleep apnea syndrome. Bull Eur Physiopathol Respir 17: 341–349. Guilleminault HC, Simmons FB, Motta J et al. (1981). Obstructive sleep apnea syndrome and tracheostomy: longterm follow-up experience. Arch Intern Med 141: 985–988. Harman EM, Wynne JW, Block AJ (1982). The effect of weight loss on sleep disordered breathing and oxygen desaturation in morbidly obese men. Chest 82: 291–294. Hensley MJ, Read DJ (1976). Intermittent obstruction of the upper airway during sleep causing profound hypoxemia: a neglected mechanism exacerbating chronic respiratory failure Aust N Z J Med 6: 481–486. Hochban W, Brandenburg U, Peter JH (1994). Surgical treatment of obstructive sleep apnea by maxillomandibular advancement. Sleep 17: 624–629. Hochban W, Conradt V, Brandenburg J et al. (1997). Surgical maxillofacial treatment of obstructive sleep apnea. Plast Reconstr Surg 99: 619–628. Hoffstein V (2002). Relationship between smoking and sleep apnea in clinic population. Sleep 25: 519–524. Hoffstein V (2007). Review of oral appliances for treatment of sleep-disordered breathing. Sleep Breath 11: 1–22. Hoffstein V, Mateika S, Metes A (1993). Effect of nasal dilation on snoring and apneas during different stages of sleep. Sleep 16: 360–365.
453
Horiuchi A, Suzuki M, Ookubo M et al. (2005). Measurement techniques predicting the effectiveness of an oral appliance for obstructive sleep apnea hypopnea syndrome. Angle Orthod 75: 1003–1011. Horner RL (1996). Motor control of the pharyngeal musculature and implications for the pathogenesis of obstructive sleep apnea. Sleep 19: 827–853. Horner RL (2000). Is there a rationale in modulating brainstem neurons in obstructive sleep apnea and is it clinically relevant? 23: S179–S181. Hudgel DW, Thanakitcharu S (1998). Pharmacologic treatment of sleep-disordered breathing. Am J Respir Crit Care Med 158: 691–699. Isono S, Tanaka A, Nishino T (2002). Lateral position decreases collapsibility of the passive pharynx in patients with obstructive sleep apnea. Anesthesiology 97: 780–785. Isono S, Tanaka A, Tagaito Y et al. (2004). Influences of head positions and bite opening on collapsibility of the passive pharynx. J Appl Physiol 97: 339–346. Issa FG, Sullivan CE (1982). Alcohol, snoring and sleep apnoea. J Neurol Neurosurg Psychiatry 45: 353–359. Itasaka Y, Miyazaki S, Ishikawa K et al. (2000). The influence of sleep position and obesity on sleep apnea. Psychiatry Clin Neurosci 54: 340–341. Jalleh R, Fitzpatrick MF, Mathur R et al. (1992). Do patients with the sleep apnea/hypopnea syndrome drink more alcohol? Sleep 15: 319–321. Janson C, Noges E, Svedberg-Randt S et al. (2000). What characterizes patients who are unable to tolerate continuous positive airway pressure (CPAP) treatment? Respir Med 94: 145–149. Johnson LM, Arnett GW, Tamborello JA et al. (1992). Airway changes in relationship to mandibular posturing. Otolaryngol Head Neck Surg 106: 143–148. Jokic R, Klimaszewski A, Mink J et al. (1988). Surface tension forces in sleep apnea: the role of a soft tissue lubricant: a randomized double-blind, placebo-controlled trial. Am J Respir Crit Care Med 157: 1522–1525. Jokic R, Klimaszewski A, Crossley M et al. (1999). Positional treatment vs continuous positive airway pressure in patients with positional obstructive sleep apnea syndrome. Chest 115: 771–781. Kales A, Cadieux RJ, Bixler EO et al. (1985). Severe obstructive sleep apnea–I: Onset, clinical course, and characteristics. J Chronic Dis 38: 419–425. Kamami YV (1990). Laser CO2 for snoring: preliminary results. Acta Otorhinolaryngol Belg 44: 451–456. Keefe DL, Watson R, Naftolin F (1999). Hormone replacement therapy may alleviate sleep apnea in menopausal women: a pilot study. Menopause 6: 196–200. Keifer JC, Baghdoyan HA, Lydic R (1992). Sleep disruption and increased apneas after pontine microinjection of morphine. Anesthesiology 77: 973–982. Kerr P, Millar T, Buckle P et al. (1992). The importance of nasal resistance in obstructive sleep apnea syndrome. J Otolaryngol 21: 189–195. Kingshott RN, Vennelle M, Coleman EL et al. (2001). Randomized, double-blind, placebo-controlled crossover trial
454
J.A. FLEETHAM
of modafinil in the treatment of residual excessive daytime sleepiness in the sleep apnea/hypopnea syndrome. Am J Respir Crit Care Med 163: 918–923. Kirkness JP, Madronio M, Stavrinou R et al. (2003). Relationship between surface tension of upper airway lining liquid and upper airway collapsibility during sleep in obstructive sleep apnea hypopnea syndrome. J Appl Physiol 95: 1761–1766. Krol RC, Knuth SL, Bartlett D Jr (1984). Selective reduction of genioglossal muscle activity by alcohol in normal human subjects. Am Rev Respir Dis 129: 247–250. Kushida CA, Rao S, Guilleminault C et al. (1999). Cervical positional effects on snoring and apneas. Sleep Res Online 2: 7–10. Kushida CA, Sherrill CM, Hong SC et al. (2001). Cervical positioning for reduction of sleep-disordered breathing in mild-to-moderate OSAS. Sleep Breath 5: 71–78. Kushida CA, Morgenthaler TI, Littner MR et al. (2006). Practice parameters for the treatment of snoring and obstructive sleep apnea with oral appliances: an update for 2005. Sleep 29: 240–243. Langin T, Pepin J-L, Pendlebury S et al. (1998). Upper airway changes in snorers and mild sleep apnea sufferers after uvulopalatopharyngoplasty (UPPP). Chest 113: 1595–1603. Larsson LH, Carlsson-Nordlander B, Svanborg E (1994). Four-year follow-up after uvulopalatopharyngoplasty in 50 unselected patients with obstructive sleep apnea syndrome. Laryngoscope 104: 1362–1368. Lavie P, Gertner R, Zomer J et al. (1981). Breathing disorders in sleep associated with “microarousals” in patients with allergic rhinitis. Acta Otolaryngol 92: 529–533. Lavie P, Fischel N, Zomer J et al. (1983). The effects of partial and complete mechanical obstruction of the nasal passages on sleep structure and breathing in sleep. Acta Otolaryngol 95: 161–166. Lawton HM, Battagel JM, Kotecha B (2005). A comparison of the Twin Block and Herbst mandibular advancement splints in the treatment of patients with obstructive sleep apnoea: a prospective study. Eur J Orthod 27: 82–90. Leiter JC, Knuth SL, Bartlett D (1985). The effect of sleep deprivation on activity of the genioglossus muscle. Am Rev Respir Dis 132: 1242–1245. Lim J, Lasserson TJ, Fleetham J et al. (2006). Oral appliances for obstructive sleep apnea. Cochrane Database Syst Rev 1. CD004435. Littner M, Kushida CA, Hartse K et al. (2001). Practice parameters for the use of laser-assisted uvulopalatoplasty: an update for 2000. Sleep 24: 603–619. Lofaso F, Coste A, d’Ortho MP et al. (2000). Nasal obstruction as a risk factor for sleep apnoea syndrome. Eur Respir J 16: 639–643. Lojander J, Maasilta P, Partinen M et al. (1996). NasalCPAP, surgery, and conservative management for treatment of obstructive sleep apnea syndrome. A randomized study. Chest 110: 114–119. Lowe A, Fleetham J, Ryan F et al. (1990). Effects of a mandibular repositioning appliance used in the treatment of
obstructive sleep apnea on tongue muscle activity. In: FG Issa, PM Suratt, JE Remmers (Eds.), Seep and Respiration. Wiley-Liss, New York, pp. 395–405. McLean HA, Urton AM, Driver HS et al. (2005). Effect of treating severe nasal obstruction on the severity of obstructive sleep apnoea. Eur Respir J 25: 521–527. McNicholas WT, Tarlo S, Cole P et al. (1982). Obstructive apneas during sleep in patients with seasonal allergic rhinitis. Am Rev Respir Dis 126: 625–628. Manber R, Kuo TF, Cataldo N et al. (2003). The effects of hormone replacement therapy on sleep-disordered breathing in postmenopausal women: a pilot study. Sleep 26: 163–168. Marklund M (2006). Predictors of long-term orthodontic side-effects from mandibular advancement devices in patients with snoring and obstructive sleep apnea. Am J Orthod Dentofacial Orthop 129: 214–221. Marklund M, Sahlin C, Stenlund H et al. (2001). Mandibular advancement device in patients with obstructive sleep apnea: long-term effects on apnea and sleep. Chest 120: 162–169. Marklund M, Stenlund H, Franklin KA (2004). Mandibular advancement devices in 630 men and women with obstructive sleep apnea and snoring: tolerability and predictors of treatment success. Chest 125: 1270–1278. Martin RJ, Sanders MH, Gray BA et al. (1982). Acute and long-term ventilatory effects of hyperoxia in the adult sleep apnea syndrome. Am Rev Respir Dis 125: 175–180. Mehta A, Qian J, Petocz P et al. (2001). A randomized, controlled study of a mandibular advancement splint for obstructive sleep apnea. Am J Respir Crit Care Med 163: 1457–1461. Mendelson WB, Garnett D, Gillin JC (1981). Flurazepaminduced sleep apnea syndrome in a patient with insomnia and mild sleep-related respiratory changes. J Nerv Ment Dis 169: 261–264. Meoli AM, Rosen CL, Kristo D et al. (2003). Nonprescription treatments of snoring or obstructive sleep apnea: an evaluation of products with limited scientific evidence. Sleep 26: 619–624. Meurice J-C, Marc I, Carrier G et al. (1996). Effect of mouth opening on upper airway collapsibility in normal sleeping subjects. Am J Respir Crit Care Med 153: 255–259. Miljeteig H, Moteika S, Haight JS et al. (1994). Subjective and objective assessment of uvulopalatopharyngoplasty for treatment of snoring and obstructive sleep apnea. Am J Respir Crit Care Med 150: 1286–1290. Millman RP, Rosenberg CL, Carlisle CC et al. (1998). The efficacy of oral appliances in the treatment of persistent sleep apnea after uvulopalatopharyngoplasty. Chest 113: 992–996. Mitler MM, Dawson A, Henriksen SJ et al. (1988). Bedtime ethanol increases resistance of upper airways and produces sleep apneas in asymptomatic snorers. Alcohol Clin Exp Res 12: 801–805. Mortimore IL, Bradley PA, Murray JA et al. (1996). Uvulopalatopharyngoplasty may compromise nasal CPAP therapy in sleep apnea syndrome. Am J Respir Crit Care Med 154: 1759–1762.
MEDICAL AND SURGICAL TREATMENT OF OBSTRUCTIVE SLEEP APNEA SYNDROME Motta J, Guilleminault HC, Schroeder JS et al. (1978). Tracheostomy and hemodynamic changes in sleep-induced apnea. Ann Intern Med 89: 454–458. Mulloy E, McNicholas WT (1992). Theophylline in obstructive sleep apnea: a double-blind evaluation. Chest 101: 753–757. Mun EC, Blackburn GL, Matthews JB (2001). Current status of medical and surgical therapy for obesity. Gastroenterology 120: 669–681. Nahmias JS, Karetzky MS (1988). Treatment of the obstructive sleep apnea syndrome using a nasopharyngeal tube. Chest 94: 1142–1147. Naismith SL, Winter VR, Hickie IB et al. (2005). Effect of oral appliance therapy on neurobehavioral functioning in obstructive sleep apnea: a randomized controlled trial. J Clin Sleep Med 1: 374–380. Nakano H, Ikeda M, Hayashi E (2003). Effects of body position on snoring in apneic and nonapneic snorers. Sleep 26: 169–172. Newman AB, Nieto FJ, Guidry U et al. (2001). Relation of sleep-disordered breathing to cardiovascular disease risk factors: the Sleep Heart Health Study. Am J Epidemiol 154: 50–59. Ng AT, Gotsopoulos H, Qian J et al. (2003). Effect of oral appliance therapy on upper airway collapsibility in obstructive sleep apnea. Am J Respir Crit Care Med 168: 238–241. Ng AT, Qian J, Cistulli PA (2006). Oropharyngeal collapse predicts treatment response with oral appliance therapy in obstructive sleep apnea. Sleep 29: 666–671. Oksenberg A, Silverberg DS, Arons E et al. (1997). Positional vs nonpositional obstructive sleep apnea patients: anthropomorphic, nocturnal polysomnographic, and multiple sleep latency test data. Chest 112: 629–639. Oksenberg A, Khamaysi I, Silverberg DS et al. (2000). Association of body position with severity of apneic events in patients with severe nonpositional obstructive sleep apnea. Chest 118: 1018–1024. Olsen KD, Kern EB, Westbrook PR (1981). Sleep and breathing disturbances secondary to nasal obstruction. Otolaryngol Head Neck Surg 89: 804–810. Osman EZ, Osborne JE, Hill PD et al. (2000). Uvulopalatopharyngoplasty versus laser assisted uvulopalatoplasty for the treatment of snoring: an objective randomised clinical trial. Clin Otolaryngol 25: 305–310. Otsuka R, Almeida FR, Lowe AA et al. (2006). A comparison of responders and nonresponders to oral appliance therapy for the treatment of obstructive sleep apnea. Am J Orthod Dentofacial Orthop 129: 222–229. Pack AI, Black JE, Schwartz JR et al. (2001). Modafinil as adjunct therapy for daytime sleepiness in obstructive sleep apnea. Am J Respir Crit Care Med 164: 1675–1681. Pantin CC, Tennant M (1999). Dental side-effects of an oral device to treat snoring and obstructive sleep apnea. Sleep 22: 237–240. Peiser P, Lavie P, Ovnat A et al. (1984). Sleep apnea syndrome in the morbidly obese as an indication for weight reduction surgery. Ann Surg 199: 112–115.
455
Penzel T, Moller M, Becker HF et al. (2001). Effect of sleep position and sleep stage on the collapsibility of the upper airways in patients with sleep apnea. Sleep 24: 90–95. Peppard PE, Young T, Palta M et al. (2000). Longitudinal study of moderate weight change and sleep-disordered breathing. JAMA 284: 3015–3021. Pevernagie DA, Shepard JW Jr (1992). Relations between sleep stage, posture and effective nasal CPAP levels in OSA. Sleep 15: 162–167. Pevernagie D, Hamans E, Van Cauwenberge P (2000). External nasal dilation reduces snoring in chronic rhinitis patients: a randomized controlled trial. Eur Respir J 15: 996–1000. Pories WJ, Swanson MS, MacDonald KG et al. (1995). Who would have thought it? An operation proves to be the most effective therapy for adult-onset diabetes mellitus. Ann Surg 222: 339–350. Powell NB, Zonato AI, Weaver EM et al. (2001). Radiofrequency treatment of turbinate hypertrophy in subjects using continuous positive airway pressure: a randomized, double-blind, placebo-controlled clinical pilot trial. Laryngoscope 111: 1783–1790. Prinsell J (1999). Maxillomandibular advancement surgery in a site-specific treatment approach for obstructive sleep apnea in 50 consecutive patients. Chest 116: 1519–1529. Rajala R, Partinen M, Sane T et al. (1991). Obstructive sleep apnea syndrome in morbidly obese patients. J Intern Med 230: 125–129. Riley RW, Powell NB, Guilleminault C (1993). Obstructive sleep apnea syndrome: a review of 306 consecutively treated surgical patients. Otolaryngol Head Neck Surg 102: 117–125. ˚ et al. Ringqvist M, Walker-Engstrom ML, Tegelberg A (2003). Dental and skeletal changes after 4 years of obstructive sleep apnea treatment with a mandibular advancement device: a prospective, randomized study. Am J Orthod Dentofacial Orthop 124: 53–60. Rojeweski T, Schuller D, Clark R et al. (1984). Videoendoscopic determination of the mechanism of obstruction in obstructive sleep apnea. Otolaryngol Head Neck Surg 92: 127–131. Ryan CF (2005). An approach to treatment of obstructive sleep apnoea/hypopnoea syndrome including upper airway surgery. Thorax 60: 595–604. Ryan CF, Love LL, Peat D et al. (1999). Mandibular advancement oral appliance therapy for obstructive sleep apnea: effect on awake calibre of the velopharynx. Thorax 54: 972–977. Sadatsafavi M, Marra CE, Ayas N et al. (2009). Costeffectiveness of oral appliances in the treatment of obstructive sleep apnoea-hypopnoea. Sleep Breath 13: 241–252. Schechter MS (2002). Technical report: diagnosis and management of childhood obstructive sleep apnea. Pediatrics 109: e69. Schmidt Nowara WW, Meade TE, Hays MB (1991). Treatment of snoring and obstructive sleep apnea with a dental orthosis. Chest 99: 1378–1385.
456
J.A. FLEETHAM
Schneider H, O’Hearn DJ, Leblanc K et al. (2000). Highflow transtracheal insufflation treats obstructive sleep apnea: a pilot study. Am J Respir Crit Care Med 161: 1869–1876. Schonhofer B, Franklin KA, Brunig H et al. (2000). Effect of nasal-valve dilation on obstructive sleep apnea. Chest 118: 587–590. Schwartz AR, Gold AR, Schubert N, Stryzak A et al. (1991). Effect of weight loss on upper airway collapsibility in obstructive sleep apnea. Am Rev Respir Dis 144: 494–498. Schwartz AR, Bennett ML, Smith PL et al. (2001). Therapeutic electrical stimulation of the hypoglossal nerve in obstructive sleep apnea. Arch Otolaryngol Head Neck Surg 127: 1216–1223. Schwartz AR, Patil SP, Laffan AM et al. (2008). Obesity and obstructive sleep apnea: pathogenic mechanisms and therapeutic approaches. Proc Am Thor Soc 5 (2): 179–184. Series F, St Pierre S, Carrier G (1992). Effects of surgical correction of nasal obstruction in the treatment of obstructive sleep apnea. Am Rev Respir Dis 146: 1261–1265. Series F, Roy N, Marc I (1994). Effects of sleep deprivation and sleep fragmentation on upper airway collapsibility in normal subjects. Am J Respir Crit Care Med 150: 481–485. Serima L, Broudy M, Nay KN et al. (1982). Increased severity of obstructive sleep apnea after bedtime alcohol ingestion: diagnostic potential and proposed mechanism of action. Sleep 5: 318–328. Sher A (1990). Obstructive sleep apnea syndrome: a complex disorder of the upper airway. Otolaryngol Head Neck Surg 23: 593–608. Sher AE, Schechtman KB, Piccirillo JF (1996). The efficacy of surgical modifications of the upper airway in adults with obstructive sleep apnea syndrome. Sleep 19: 156–177. Shneerson J, Wright J (2006). Lifestyle modification for obstructive sleep apnoea. In: The Cochrane Database of Systematic Reviews. The Cochrane Collaboration, John Wiley, Chichester. Skinner MA, Kingshott RN, Jones DR et al. (2004a). Lack of efficacy for a cervicomandibular support collar in the management of obstructive sleep apnea. Chest 125: 118–126. Skinner MA, Kingshott RN, Jones DR et al. (2004b). Elevated posture for the management of obstructive sleep apnea. Sleep Breath 8: 193–200. Smith DM, Stradling JR (2002). Can mandibular advancement devices be a satisfactory substitute for short term use in patients on nasal continuous positive airway pressure? Thorax 57 (4): 305–308. Smith PL, Wise RA, Gold AR et al. (1982). Upper airway pressure area relationships in obstructive sleep apnea. J Appl Physiol 53: 855–858. Smith PL, Gold AR, Meyers DA et al. (1985). Weight loss in mildly to moderately obese patients with obstructive sleep apnea. Ann Intern Med 103: 850–855. Smith I, Lasserson T, Wright J (2002). Drug treatments for obstructive sleep apnoea. Cochrane Database Syst Rev CD003002.
Stepanski EJ, Conway WA, Young DK et al. (1988). A double-blind trial of protriptyline in the treatment of sleep apnea syndrome. Henry Ford Hosp Med J 36: 5–8. Stradling JR, Crosby JH (1991). Predictors and prevalence of obstructive sleep apnea and snoring in 1001 middle-aged men. Thorax 46: 85–90. Strobel RJ, Rosen RL (1996). Obesity and weight loss in obstructive sleep apnea: a critical review. Sleep 19: 104–115. Stuck B, Maurer JT, Hein G et al. (2004). Radiofrequency surgery of the soft palate in the treatment of snoring: a review of the literature. Sleep 27: 551–555. Sundaram S, Bridgman SA, Lim J et al. (2006). Surgery for obstructive sleep apnoea. In: The Cochrane Database of Systematic Reviews. The Cochrane Collaboration, John Wiley, Chichester. Suratt PM, Turner BL, Wilhoit SC (1986). Effect of intranasal obstruction on breathing during sleep. Chest 90: 324–329. Taasen V, Wynne JW, Cassisi N et al. (1981). The effect of nasal packing on sleep-disordered breathing and nocturnal oxygen desaturation. Laryngoscope 91: 1163–1172. Takhar J, Bishop J (2000). Influence of chronic barbiturate administration on sleep apnea after hypersomnia presentation: case study. J Psychiatry Neurosci 25: 321–324. Teculescu D, Hannhart B, Cornette A et al. (2001). Prevalence of habitual snoring in a sample of French males. Role of “minor” nose–throat abnormalities. Respiration 68: 365–370. Terris DJ, Clarke AA, Norbash AM et al. (1996). Characterization of post-operative edema following laser-assisted uvulopalatoplasty using MRI and polysomnography: implications for the outpatient treatment of obstructive sleep apnea syndrome. Laryngoscope 106: 124–128. Teschler H, Berthon-Jones M, Wessendorf T et al. (1996). Influence of moderate alcohol consumption on obstructive sleep apnoea with and without AutoSet nasal CPAP therapy. Eur Respir J 9: 2371–2377. Thomas AJ, Chavova M, Terris DJ (2003). Preliminary findings from a prospective, randomized trial of two tonguebase surgeries for sleep-disordered breathing. Otolaryngol Head Neck Surg 129: 539–546. Tischler PV, Larkin EK, Schluchter MD et al. (2003). Incidence of sleep-disordered breathing in an urban adult population: the relative importance of risk factors in the development of sleep-disordered breathing. JAMA 289: 2230–2237. Todorova A, Schellenberg R, Hofmann HC et al. (1998). Effect of the external nasal dilator Breathe Right on snoring. Eur J Med Res 3: 367–379. Verse T, Pirsig W (2000). Meta-analysis of laser-assisted uvulopalatopharyngoplasty. What is clinically relevant up to now? Laryngorhinootologie 79: 273–284 Verse T, Kroker B, Pirsig W et al. (2000). Tonsillectomy as a treatment of obstructive sleep apnea in adults with tonsillar hypertrophy. Laryngoscope 110: 1556–1559. Verse T, Maurer JT, Pirsig W (2002). Effect of nasal surgery on sleep-related breathing disorders. Laryngoscope 112: 64–68.
MEDICAL AND SURGICAL TREATMENT OF OBSTRUCTIVE SLEEP APNEA SYNDROME Vgontzas AN, Zoumakis E, Lin HM et al. (2004). Marked decrease in sleepiness in patients with sleep apnea by etanercept, a tumor necrosis factor-alpha antagonist. J Clin Endocrinol Metab 89: 4409–4413. Waite PD, Wooten V, Lachner J et al. (1989). Maxillomandibular advancement surgery in 23 patients with obstructive sleep apnea syndrome. J Oral Maxillofac Surg 47: 1256–1261. Walker-Engstro¨m ML, Tegelberg A, Wilhelmsson B et al. (2002). 4-year follow-up of treatment with dental appliance or uvulopalatopharyngoplasty in patients with obstructive sleep apnea: a randomized study. Chest 121: 739–746. Wassmuth Z, Mair E, Loube D et al. (2000). Cauteryassisted palatal stiffening for the treatment of obstructive sleep apnea syndrome. Otolaryngol Head Neck Surg 123: 55–60. Weitzman ED, Kahn E, Pollak CP (1980). Quantitative analysis of sleep apnea before and after tracheostomy in patients with the hypersomnia-sleep apnea syndrome. Sleep 3: 407–423. Wesstrom J, Ulfberg J, Nilsson S (2005). Sleep apnea and hormone replacement therapy: a pilot study and a literature review. Acta Obstet. Gynecol Scand 84: 54–57. Wetter DW, Young TB, Bidwell TR et al. (1994). Smoking as a risk factor for sleep-disordered breathing. Arch Int Med 154: 2219–2224.
457
White DP, Douglas NJ, Pickell CK et al. (1983). Sleep deprivation and the control of breathing. Am Rev Respir Dis 128: 984–986. Whyte KF, Gould GA, Airlie MA et al. (1988). Role of protriptyline and acetazolamide in the sleep apnea/hypopnea syndrome. Sleep 11: 463–472. Won CH, Li KK, Guilleminault C (2008). Surgical treatment of obstructive sleep apnea: upper airway and maxillomandibular surgery. Proc Am Thorac Soc 5 (2): 185–192. Woodson BT, Steward DL, Weaver EM et al. (2003). A randomized trial of temperature-controlled radiofrequency, continuous positive airway pressure, and placebo for obstructive sleep apnea syndrome. Otolaryngol Head Neck Surg 128: 848–861. Young T, Finn L, Palta M (2001). Chronic nasal congestion at night is a risk factor for snoring in a population-based cohort study. Arch Intern Med 161: 1514–1519. Young T, Peppard PE, Gottlieb DJ (2002). Epidemiology of obstructive sleep apnea. A population health perspective. Am J Respir Crit Care Med 165: 1217–1223. Zohar Y, Finkelstein Y, Talmi YP et al. (1991). Uvulopalatopharyngoplasty: evaluation of postoperative complications, sequelae, and results. Laryngoscope 101: 775–779. Zuberi NA, Rekab K, Nguyen HV (2004). Sleep apnea avoidance pillow effects on obstructive sleep apnea syndrome and snoring. Sleep Breath 8: 201–207.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 30
Noninvasive positive ventilation in the treatment of sleep-related breathing disorders DOMINIQUE ROBERT * AND LAURENT ARGAUD Emergency and Intensive Care Department, Edouard Herriot Hospital, Lyon, France
INTRODUCTION As a result of the experience of nasal continuous positive airway pressure (CPAP) in the treatment of obstructive apnea (Sullivan et al., 1981), it was recognized that intermittent positive pressure ventilation (IPPV) could also be comfortably and efficiently delivered noninvasively (NIPPV) through a facial interface. Positive pressure is applied to the airway during inspiration at higher rates than during expiration. Thus, NIPPV delivers part or even all of the tidal volume. Depending on the underlying disease, either IPPV is administered continuously to avoid death in cases where there is complete or almost complete paralysis, or it is used at night, producing enough improvement to allow the patient to breathe unaided during the day. This chapter covers the use of NIPPV (but not CPAP) in those diseases in which it is currently proposed: mainly diseases responsible for chronic hypoventilation, and secondarily in others such as obstructive apnea or central apnea (Cheyne–Stokes breathing, the curse of Ondine). NIPPV, which is currently the predominant technique, enables long-term home ventilation to be carried out (Lloyd-Owen et al., 2005).
NIPPV METHODS AND USES
minimize leaks, improve comfort, and use the mask easily. There is now a wide variety of different manufactured masks of different designs, shapes, sizes, and materials. It is usually possible to find a mask to suit most individuals. The previous practice of individually tailoring interfaces is now seldom needed, even if it does remain probably the best interface (Leger et al., 1989, 1994; Hill, 2002; Schonhofer and Sortor-Leger, 2002; Elliott, 2004; Fauroux et al., 2005). There are four different types of interface: (1) nasal mask; (2) facial mask covering the nose and mouth; (3) nasal pillows; and (4) mouthpieces. Nasal masks are mainly used for nocturnal ventilation (Leger and Leger, 1999; Schonhofer and Sortor-Leger, 2002). Mouthpieces are indicated for daytime ventilation (Bach et al., 1993; Finder et al., 2004). This may provide an excellent interface to daylight ventilation, principally in neuromuscular patients who are unable to maintain acceptable diurnal arterial blood gases without frequent intermittent periods of assistance. The mouthpiece is positioned close to the patient’s mouth where it is intermittently captured to take a few assisted breaths from the ventilator and subsequently released. An advantage is to free the face from face-attached interfaces. Thus, the patient who needs assistance night and day may use a combination of interfaces.
Interfaces
Ventilator and mode for NIPPV
The need to select an appropriate and properly fitted interface cannot be overemphasized due to its impact on quality of ventilation (Hill, 2002; Schonhofer and Sortor-Leger, 2002; Elliott, 2004). The aim is to reach a compromise between different objectives: to
Ventilators use one of two basic methods: volume-preset and pressure-preset (Schonhofer and Sortor-Leger, 2002). In the volume-preset method the ventilator always delivers the tidal volume which is set by the clinician, regardless of the patient’s pulmonary system
*Correspondence to: Dominique Robert, M.D., FCCP, Chief of the Emergency and Intensive Care Department, Edouard Herriot Hospital, 5 place d’Arsonval, 69008 Lyon, France. Tel: 33 (0)4 72 11 00 41, Fax: 33 (0)4 72 11 00 42, E-mail: dominique.
[email protected]
460
D. ROBERT AND L. ARGAUD
mechanics (compliance, resistance, and active inspiration). However, leaks, at the interface between skin and mask or through the mouth when using a nasal mask, reduce the volume received by the patient. Conversely, with the pressure-preset methods, changes in pulmonary mechanics directly influence the flow and the delivered tidal volume (decreased or increased) since the ventilator delivers the set pressure throughout inspiration. Leaks increase the flow from the ventilator and maintain the volume received by the patient (Mehta et al., 2001; Tuggey and Elliott, 2006). It is important to understand that NIPPV is dominated both by rapid variations in nonintentional leaks and by the geometry and resistance of the upper airway (Jounieaux et al., 1995). The start and end of inspiration are initiated either by the ventilator or in response to patient effort; thus the main modes are: (1) control; (2) assisted control; (3) assisted or spontaneous (this is only possible with the pressure-preset method). Most home ventilators only function in either volume- or pressure-preset mode, but modern ones may deliver inspiration in either mode. In addition to the classical circuitry including two valves (on the inspiratory and expiratory limbs) alternatively closing and opening, bilevel positive airway pressure (BLPAP) ventilators are simpler and therefore lend themselves to home mechanical ventilation (Strumpf et al., 1990). Inspiratory and expiratory pressures are alternatively established in a single circuit incorporating an intentional, calibrated leak close to the patient or even on the mask. The theoretical disadvantage with such a circuit is the risk of variable CO2 rebreathing. The trend is to consider it as negligible (Hill et al., 2002; Hill, 2003; Saatci et al., 2004; Szkulmowski et al., 2010) provided positive expiratory pressure is applied to eliminate CO2 through the intentional leak (at least 2–4 cm H2O). Depending on the ventilator, all the different modes and refined settings and even closed-loop modes usually applied in the Intensive Care Unit are available. Although attractive as a concept, sufficient studies have not been performed to document or refute the advantages of such complexity in the context of noninvasive home ventilation.
Choice of ventilator and mode Many clinicians currently prefer pressure-preset ventilator in assist mode as their first choice with a view to offering better synchronization and comfort (Lloyd-Owen et al., 2005). In fact, in studies comparing volume- and pressure-preset ventilators no clear differences in the correction of hypoventilation in short-term studies (Meecham Jones and Wedzichia, 1993; Restrick et al., 1993; Cinnella et al., 1996; Girault
et al., 1997; Tejeda et al., 1997; Lien et al., 2000; Laserna et al., 2003; Tuggey and Elliott, 2005; Windisch et al., 2005a) and in long-term outcomes (Smith et al., 1996; Schonhofer et al., 1997; Janssens et al., 2003) have been shown. This is understandable since during NIPPV, leaks and resistance changes alternate in quick succession and when pressure target delivers tidal ventilation to the patient effectively, volume target is not effective, and vice versa. However, it is important to remain flexible by trying alternative approaches if problems occur with a particular type of ventilator. Besides, it should be noted that batteries are not available or only offer a short life for BLPAP ventilators and this limits the security and mobility of neuromuscular patients with hypoventilation, tipping the scales towards a volume ventilator.
CRITERIA FOR USE OF NIPPV Signs and symptoms of hypoventilation The presence of clinical symptoms and/or of physiologic markers of hypoventilation is useful in identifying clinical severity as it relates to therapeutic decision-making with regard to when to start nocturnal NIPPV. In the course of a typical progressive disease two successive steps occur quickly: (1) reversible nocturnal hypoventilation during wakefulness associated with no or few clinical symptoms; (2) nocturnal and daytime hypoventilation associated with clinical symptoms, indicating a low respiratory reserve and indicating an unstable state with increased susceptibility for life-threatening acute ventilatory failure (Ragette et al., 2002; Lo Coco et al., 2006). Sleep study continuously recording CO2 (end-tidal CO2 or TcCO2) and/or SpO2 is required to document nocturnal hypoventilation which may occur throughout all sleep stages, but in the less severe stage occurs exclusively during rapid eye movement (REM) sleep. Daylight hypoventilation is defined by an abnormally elevated PaCO2, high serum bicarbonate level, and relatively normal pH with associated reduction of PaO2. Chronic daytime hypoventilation is an important indicator which is invariably associated with sleep-related hypoventilation. Thus, in the presence of diurnal hypoventilation, overnight recording is only required when apnea is suspected, to rule out sleep apnea syndrome. Clinical symptoms indicating consequences of hypoventilation are neither sensitive nor specific but must be carefully evaluated to evaluate disease severity and indicate NIPPV. These symptoms are nocturnal (insomnia, nightmares, arousals) and/or diurnal (morning headaches, fatigue, sleepiness, decrease of intellectual performance, loss of appetite and weight, cor pulmonale). They are associated with symptoms
NONINVASIVE POSITIVE VENTILATION IN SLEEP-RELATED BREATHING DISORDERS related to respiratory insufficiency: shortness of breath (in the absence of paralysis) and recurrent respiratory infections. Pulmonary function tests help define and quantify the ventilatory-respiratory disease but have low predictive value for chronic sleep-related hypoventilation except in neuromuscular cases. Indeed, in Duchenne hypoventilation during REM only, all night, or daylight hypoventilation appears when supine inspiratory vital capacity is < 40%, < 25%, and < 12% respectively (Ragette et al., 2002). Similarly, a peak cough flow < 160 l/min, related to expiratory muscle deficit, means an increased risk of accumulation of secretions which may worsen hypoventilation and trigger acute failure (Bach, 1993, 1994; Bach and Saporito, 1996; Chaudri et al., 2002; Finder et al., 2004). It is crucial to notice that isolated reduced PaO2 means not hypoventilation but a mismatching of ventilation and perfusion adequately compensated or even overcompensated (low PaCO2) which does not require support with mechanical ventilation but possibly does require supplemental oxygen.
Diseases which may potentially be treated with NIPPV The principal diseases which may be addressed using NIPPV therapy are shown in Table 30.1. With the exception of illnesses due to respiratory control or upper-airway abnormalities, all illnesses may become
461
severe enough to cause alveolar hypoventilation during sleep and wakefulness, and eventually impair quality of life and prove to be life-threatening. In neuromuscular disorders it is important to consider progression of each disease and individual cases.
NIPPV SURVIVAL IN DIFFERENT DISEASES It is important to discuss NIPPV efficacy in terms of survival compared to control treatment. In addition to a few randomized controlled trials (Pinto et al., 1995; Casanova et al., 2000; Clini et al., 2002; Bourke et al., 2006; McEvoy et al., 2009), there is information from retrospective series compared to usual prognosis (Jackson et al., 1994; Leger et al., 1994; Simonds and Elliott, 1995; Aboussouan et al., 1997; Kleopa et al., 1999; Nugent et al., 2002; Gonzalez et al., 2003a; Janssens et al., 2003; Chu et al., 2004; Farrero et al., 2005). In order to extend this analysis results obtained with negative pressure ventilation (Shapiro et al., 1992) or tracheostomy (Robert et al., 1983; Muir et al., 1994) can also be considered. These authors’ conclusions are informative and generally accepted by the medical community, even if not evidence-based medicine. In neuromuscular disorders, NIPPV always increases survival. Approximate median prolongation of life depends on the disease and comorbidity (including
Table 30.1 Main diseases which may benefit from noninvasive intermittent positive pressure ventilation classified according to cause and progression of the respiratory impairment Parietal disorders: (PFT abnormal: # VC, # FEV1, ! FEV1 / VC, # RV, # TLC)* Chest wall Kyphoscoliosis No worsening Sequelae of tuberculosis Slow worsening Obesity hypoventilation syndrome Depends on obesity Neuromuscular Spinal muscular atrophy No worsening Acid maltase deficit Slow worsening (> 15 years) Duchenne muscular dystrophy Intermediate worsening (5–15 years) Myotonic myopathy Intermediate worsening (5–15 years) Amyotrophic lateral sclerosis Rapid worsening (0–3 years) Lung diseases: (PFT abnormal: ! or # VC, # FEV1, # FEV1 / VC, " RV, " TLC)* Chronic obstructive pulmonary disease Continuous worsening Bronchiectasis, cystic fibrosis Continuous worsening Predominant ventilatory control abnormalities: (PFT normal) Ondine’s curse Improvement? Cheyne–Stokes breathing Depends on heart failure Upper-airway abnormalities: (PFT normal) Pierre Robin No worsening Obstructive sleep apnea No worsening *Symbols indicate actual compared to theoretical values: # or " decrease or increase; ! normal; PFT, pulmonary funtions tests; FEV1, forced expiratory volume in 1 second; VC, vital capacity; RV, residual volume; TLC, total lung capacity.
462
D. ROBERT AND L. ARGAUD
extensive paralysis): very long (> 20 years) in sequelae of polio; long (10 years) in spinal muscular atrophy type 2 and 3, Duchenne muscular dystrophy, and acid maltase deficit; short in myotonic dystrophy (4 years) and very short in amyotrophic lateral sclerosis (ALS: 1 year). In chest wall abnormalities NIPPV also prolongs life: in kyphosis (15 years) and in sequelae of tuberculosis (7 years). In lung disease no data support a positive effect on survival: in chronic obstructive pulmonary disease (COPD) randomized trials have been either negative or reporting minor conflicting positive results (Shapiro et al., 1992; Casanova et al., 2000; Clini et al., 2002; McEvoy et al., 2009) and in cystic fibrosis or bronchiectasis data are too scarce.
INDICATIONS FOR NIPPV In clinical practice, NIPPV is initiated either electively or in the context of acute ventilatory failure (Keenan et al., 2003). In the latter circumstances, the long-term need for NIPPV should be re-evaluated during followup since the indications for NIPPV may change as the clinical condition improves, or worsens. In chronic and stable awake hypoventilation the cornerstone to predict NIPPV use is advanced severity with clinical symptoms of hypoventilation and a balance of several other issues: (1) the main primary process requiring hypoventilation: mechanical or lung deficit; (2) the natural rate of progression; (3) the clinical severity at the time of decision-making: symptoms and history of previously acute or subacute failure; (4) the patient’s willingness, including the family and social environment, to undertake this therapy. Indications are outlined in Table 30.2.
NIPPV is strongly indicated in patients with chest wall and neuromuscular disorders in the presence of clinical symptoms attributable to diurnal hypoventilation (Robert et al., 1993; Make et al., 1998; Anonymous, 1999; Simonds et al., 2000; Norregaard, 2002; Shneerson and Simonds, 2002; Finder et al., 2004). There are no validated values above which NIPPV is definitely indicated; however, many clinicians consider treatment in scoliosis and sequelae of tuberculosis with awake PaCO2 > 50–55 mmHg and a PaO2 < 60 mmHg and in neuromuscular disorders with a PaCO2 around 45–50 mmHg and a PaO2 < 70 mmHg. Where there are clear clinical symptoms less severe values may be considered as an indication to start NIPPV (Shneerson and Simonds, 2002). Conversely, in COPD and probably in other lung diseases, diurnal hypoventilation does not support the unequivocal usefulness of NPPV (Wijkstra et al., 2002, 2003). Nevertheless this question remains open since clinical trials are underpowered and secondary parameters, such as quality of life or hospitalization days, may have improved. Some observational series suggest better results (Sivasothy et al., 1998; Nava et al., 2001; Diaz et al., 2005; Windisch et al., 2005b). At present, we may admit NIPPV as an option in COPD patients who have symptoms of hypoventilation contributing to the recurrence of acute or subacute failure, provided that long-term oxygen and drug therapy have already been optimally adjusted. During the early stage with isolated nocturnal hypoventilation, NIPPV is not mandatory but could be optional in kyphoscoliosis (Masa et al., 1997; Ward et al., 2005) and in neuromuscular diseases (Ward et al., 2005). In the latter, when worsening is both inevitable and rapid (e.g., ALS),
Table 30.2 Typical indications for nocturnal noninvasive intermittent positive pressure ventilation (NIPPV) according to disease process and severity
Disease Scoliosis Tuberculosis Neuromuscular: stable or slow Neuromuscular: Intermediate Neuromuscular: rapid Chronic obstructive pulmonary disease Bronchiectasis Cystic fibrosis Obesity-hypoventilation
Symptoms Day CO2"
Symptoms Night CO2"
No symptoms Day CO2"
Usual daily duration of NIPPV
Yes Yes Yes
Yes Yes Perhaps
Perhaps Perhaps Perhaps
< 12 hours < 12 hours 18–24 hours
Yes
Perhaps
Perhaps
18–24 hours
Yes Perhaps
Yes No
Yes No
24 hours 12 hours
Perhaps
No
No
18–24 hours
Perhaps
Perhaps
No
< 12 hours
NONINVASIVE POSITIVE VENTILATION IN SLEEP-RELATED BREATHING DISORDERS NIPPV is valuable in the early stages provided the patient accepts this therapeutic option. Other diseases may also merit consideration of NIPPV use, even if clinical experience remains inconclusive. Obesity-hypoventilation syndrome is characterized by morbid obesity impeding ventilation, frequent obstructive apnea, and reversible decreased reactivity of the respiratory centers (Olson and Zwillich, 2005). NIPPV has been shown to reverse hypoventilation in acute or subacute conditions as well as in chronic situations (Sullivan et al., 1983; Masa et al., 2001; de Lucas-Ramos et al., 2004; Perez de Llano et al., 2005). However, considering the high prevalence of obstructive apnea, CPAP is a simpler and more efficient treatment. Cheyne–Stokes breathing with central and obstructive apnea in the context of severe heart insufficiency has been shown to worsen the clinical situation and reduce survival (Bradley and Floras, 2003a, b; Pepin et al., 2006). Conventional NIPPV or new techniques such as adaptative servo-ventilation has been shown to alleviate apnea and improve cardiac function (Teschler et al., 2001; Willson et al., 2001; Kohnlein et al., 2002; Pepperell et al., 2003; Arzt and Bradley, 2006; Philippe et al., 2006). Nevertheless no conclusion has been drawn about the usefulness of nocturnal NIPPV in terms of survival and main outcome. A large study comparing O2 and CPAP, which alleviates apnea and improves cardiac function, does not prove the clinical superiority of CPAP in terms of survival, even if apnea was significantly reduced (Bradley et al., 2005). Pure obstructive apnea in the context of OSAS could be suppressed with NIPPV. Some authors have proposed NIPPV as a second-line treatment if CPAP fails. There are not enough definitive studies to support such treatment (Resta et al., 1998; Han et al., 2001; Gay et al., 2003). Ondine’s disease, in children, is characterized by lack of metabolic response of the respiratory centers during sleep and causes severe nocturnal hypoventilation. The usual treatment is tracheostomy and nocturnal ventilation. Some clinical experience suggests that, after years, in some cases tracheostomy may be converted to nocturnal NIPPV. Such options must remain in the hands of specialized teams (Trang et al., 2005).
MANAGEMENT OF NIPPV Nocturnal ventilation The main goal of NIPPV, preferably used only at night, is improvement in arterial blood gases to nearly normal values without discomfort and sleep disruption. Where there is residual muscle ability to breathe, the objective is to provide enough improvement to allow comfortable time off the ventilator. Even when there are no absolute recommendations, it is good practice
463
to proceed in three steps. The first consists of selecting and adjusting the ventilator settings while the patient is awake, reversing hypoventilation without discomfort for at least 1 or 2 hours (Vitacca et al., 2000; Fanfulla et al., 2005). Secondly, the clinician should judge adequacy when the patient is taking a nap and/or nocturnal use. Depending on the resources available in each center, different options could be used to make this assessment. Arterial blood gas measurements throughout the night, besides their invasiveness, do not reproduce the rapid changes observed over several continuous hours of sleep when monitoring different parameters noninvasively, making noninvasive measurements preferable. Ideally multiple recordings of SpO2 and PtcCO2 or PEtCO2, flow, tidal volume, airway pressure, ribcage and abdomen excursion, and sleep staging permit a complete assessment (Lofaso and Quera-Salva, 2002). When resources are not available to perform these detailed recordings, fewer overnight records will still provide information. The minimal requirement is to record SpO2 overnight in room air, assessing whether normalization of SpO2 correlates with normalization, or at least improvement, of PaCO2. In addition, data related to patient tolerance, comfort, sleep quality, and well-being should be obtained. The third step consists of looking for a reduction in PaCO2 and increase in PaO2, without dyspnea, during the day in unassisted ventilation after several NIPPV nights, to confirm that the settings are adequate. This also gives information about the need to add daylight hours of NIPPV (at first when the patient is taking a nap and more when necessary). If the results are not satisfactory, alterations must be made to the settings and possibly the mask and the ventilator, and then these effects checked again. In most cases, it takes a few days to achieve the correct outcome. When using BLPAP, 10 cmH2O inspiratory pressure support is a suggested starting point. If necessary, the pressure level is progressively increased. Pressure higher than 20 cmH2O is rarely necessary. A back-up frequency set close to the spontaneous frequency of the patient while asleep is a reasonable substitute to avoid central apnea induced by transitory but repeated hyperventilation when passing the apnea threshold (Johnson and Johnson, 2005). In COPD, the addition of an expiratory positive pressure (positive end-expiratory pressure (PEEP) or expiratory positive airway pressure), also necessary to reduce rebreathing with BLPAP, should improve patient triggering when intrinsic PEEP exists. However, there is no long-term study that proves its clinical usefulness (Nava et al., 1993; Appendini et al., 1994). Depending on the ventilator capabilities and observations made of the patient’s response to the ventilator, adjustments can be made to the settings for triggers, initial flow, and inspiratory time limit.
464
D. ROBERT AND L. ARGAUD
When employing a volume-preset ventilator, the initial suggested settings may be established by adjusting the frequency of ventilator-delivered breaths so that it approximates the patient’s spontaneous breathing frequency during sleep, an inspiratory time/total breathing cycle time between 0.33 and 0.5, and a relatively high tidal volume of 10–15 ml/kg to insure sufficient tidal volume in case of leaks (Mehta et al., 2001). Supplemental O2 should be added to the ventilator circuit in those patients requiring oxygen while awake due to lung parenchymal diseases (e.g., COPD, cystic fibrosis, bronchiectasis). In the absence of parenchymal disease it is only after all technical parameters have been optimized that residual desaturation may justify additional O2 being introduced into the ventilator circuit (Thys et al., 2002; Schwartz et al., 2004).
Continuous ventilation In neuromuscular disorders (and to a lesser degree in end-stage lung disease), ventilator dependency may be total when starting NIPPV or may progressively increase following the gradual worsening of the disease. When there is a need for continuous ventilation, NIPPV can be used provided that the techniques are adapted: using alternate interfaces night and day and providing assisted coughing (Bach, 1995a; Tzeng and Bach, 2000; Finder et al., 2004; Dohna-Schwake et al., 2006). A well-trained team is required for this approach in patients who accept the constraints and dangers. Such application has been reported by different teams in stable neuromuscular patients, such as those with sequelae of poliomyelitis, high-level spinal cord injury, or Duchenne muscular dystrophy (Splaingard et al., 1983; Curran and Colbert, 1989; Bach et al., 1993). Alternatively, a tracheostomy may be performed to facilitate ventilatory assistance and secretion removal. There is no clear answer as to whether a totally ventilator-dependent patient would be better or more safely ventilated by tracheostomy (Bach, 1995b; Cazzolli and Oppenheimer, 1996; Shneerson and Simonds, 2002; Hayashi and Oppenheimer, 2003; Bach et al., 2004). In addition, swallowing dysfunction, which is responsible for frequent massive aspirations and pneumonia, observed during the course of ALS (frequent, due to bulbar origin) or of Duchenne muscular dystrophy (rarely, due to muscle weakness), is an absolute indication for tracheostomy to prolong survival. However, tracheostomy creates communication difficulties and demands on medical staff (e.g., the locked-in state) (Cazzolli and Oppenheimer, 1996; Hayashi and Oppenheimer, 2003; Tsara et al., 2006). From this point of view, NIPPV, which may be easily stopped, could be
the best option in rapidly devastating diseases like ALS and can be considered by both patient and medical team as a limitation of care or a palliative approach (Polkey et al., 1999; Simonds, 2003). This was confirmed by a study showing that patients with ALS with bulbar symptoms on NIPPV did not survive longer than controls (Bourke et al., 2006).
Follow-up Clinical follow-up and daytime arterial blood gases should be conducted regularly (twice a year, for example). When possible, recordings during sleep on NIPPV, identical to those used to start NIPPV, are useful. At any time, when there are unsatisfactory results such as recurrence of clinical symptoms or hypoventilation on arterial blood gases, inadequate NIPPV must be suspected and an objective evaluation during sleep must be undertaken. When NIPPV is determined to be suboptimal, a change in ventilator modality or setting and a review of the mask fitting may be indicated. Increasing the total duration of NIPPV use per day should also be considered, particularly when the underlying disease has progressed. Masks must be regularly checked and changed or adapted as needed.
MANAGEMENT OF COMPLICATIONS Air leaks during NIPPV To some degree, leaks are present in all patients when using nasal NIPPV during sleep. The major potential adverse effects of such leaks are reduced efficiency of ventilation and sleep fragmentation (Bach et al., 1995; Meyer et al., 1997; Teschler et al., 1999; Gonzalez et al., 2003b). Various measures to overcome this problem have been suggested. These include preventing neck flexion, using the semirecumbent position, discouraging the mouth from opening by using a chin strap (Teschler et al., 1999) or a cervical collar, switching to pressure-preset mode (Mehta et al., 2001), decreasing the peak inspiratory pressure, increasing the delivered volume (Tuggey and Elliott, 2006), optimizing the interface (Leger and Leger, 1999; Elliott, 2004) and possibly switching to nasal pillows or full face mask (Mehta and Hill, 2001). The effectiveness of these measures must be confirmed with sleep records.
Nasal and mouth dryness, nasal congestion, rhinitis According to the CPAP literature these side-effects are related to a defect of humidification promoted by air leaks (Richards et al., 1996). In such cases, a cold passover or a heated humidifier (which is more effective)
NONINVASIVE POSITIVE VENTILATION IN SLEEP-RELATED BREATHING DISORDERS (Randerath et al., 2002) can be used. Nevertheless, in a large series it is only a minority of patients who need humidifiers (Schonhofer and Sortor-Leger, 2002).
Aerophagia Aerophagia, or swallowing air, is frequently reported by patients, but rarely intolerable (Hill, 2000). Aerophagia is usually dependent on the level of inspiratory pressure and the incidence decreases if peak inspiratory pressure is kept below 25 cmH2O pressure.
NIPPV EFFECTS (OTHER THAN SURVIVAL) AND RELATED MECHANISMS During ventilatory assistance As expected, when using NIPPV, ventilation and gas exchange are improved in all types of disease (Strumpf et al., 1991; Meecham Jones et al., 1995; Barbe´ et al., 1996; Benhamou et al., 1997; Masa et al., 1997; Schonhofer et al., 1997; Sivasothy et al., 1998; Elliott, 2002). Duration of sleep is increased without clear changes in quality (Bach et al., 1995; Meyer et al., 1997; Schonhofer and Kohler, 2000). Respiratory muscles are normally relaxed but there are many exceptions due to air leaks and patient–ventilator asynchrony (Carrey et al., 1990; Brochard, 1997; L’Her et al., 2005).
After ventilation When spontaneous ventilation exists and in the absence of major lung disease, gas exchange remains improved. It may persist for hours and even days before hypoventilation recurs (Jimenez et al., 1995; Karakurt et al., 2001; Petitjean et al., 2008). This improvement, which has been reported in many studies, is important in chest wall and neuromuscular disease but inconsistent in COPD (Strumpf et al., 1991; Meecham Jones et al., 1995; Gay et al., 1996; Lin, 1996). Certainly, it explains the improvement in clinical symptoms such as general well-being, appetite, ability to exercise, headaches, ankle edema, resurgence of acute failure, less spent time in hospital, and quality of life (Markstrom et al., 2002; Windisch et al., 2002; Domenech-Clar et al., 2003), and finally survival. Three main explanations have been proposed: (1) improved respiratory muscle strength; (2) resetting of the chemoreceptors; and (3) decrease in ventilatory load with increased compliance. It seems probable that, even if the mechanisms that explain the efficacy of NIPPV are imperfectly understood, several factors, even if not individually significant, change and synthesize to improve alveolar ventilation.
465
In COPD patients, the lack of clinical results compared to scoliosis and neuromuscular disorder, even when resetting of the respiratory centers has also been shown (Meecham Jones et al., 1995; Elliott, 1999), could be explained by the relatively low impairment of respiratory muscles and the importance of the lesions on the lung itself and the progressive nature of the condition.
CONCLUSION Chronic ventilatory support using NIPPV improves and stabilizes the clinical course of many patients with chronic ventilatory failure. The results appear to be good in patients with restrictive disorders but poor in COPD. Among the neuromuscular disorders, results are better in slowly progressive conditions. The benefit of NIPPV is reflected in an improvement in survival, blood gas composition, and clinical stability. As it is relatively simple and noninvasive, NIPPV permits long-term mechanical ventilation to be an acceptable option in patients who otherwise would not have been treated if tracheostomy were the only alternative. In this way, nocturnal NIPPV represents huge progress.
REFERENCES Aboussouan LS, Khan SU, Meeker DP et al. (1997). Effect of noninvasive positive-pressure ventilation on survival in amyotrophic lateral sclerosis. Ann Intern Med 127: 450–453. Anonymous (1999). Clinical indications for noninvasive positive pressure ventilation in chronic respiratory failure due to restrictive lung disease, COPD, and nocturnal hypoventilation – a consensus conference report. Chest 116: 521–534. Appendini L, Patessio A, Zanaboni S et al. (1994). Physiologic effects of positive end expiratory pressure and mask pressure support during exacerbation of chronic obstructive pulmonary disease. Am J Respir Crit Care Med 149: 1069–1076. Arzt M, Bradley TD (2006). Treatment of sleep apnea in heart failure. Am J Respir Crit Care Med 173: 1300–1308. Bach JR (1993). Mechanical insufflation-exsufflation. Comparison of peak expiratory flows with manually assisted and unassisted coughing techniques. Chest 104: 1553–1562. Bach JR (1994). Update and perspective on noninvasive respiratory muscle aids. Part 2: the expiratory aids. Chest 105: 1538–1544. Bach JR (1995a). Amyotrophic lateral sclerosis: predictors for prolongation of life by noninvasive respiratory aids. Arch Phys Med Rehabil 76: 828–832. Bach JR (1995b). Indications for tracheostomy and decannulation of tracheostomized ventilator users. Monaldi Arch Chest Dis 50: 223–227. Bach JR, Saporito LR (1996). Criteria for extubation and tracheostomy tube removal for patients with ventilatory failure. A different approach to weaning. Chest 110: 1566–1571.
466
D. ROBERT AND L. ARGAUD
Bach JR, Alba AS, Saporito LR (1993). Intermittent positive pressure ventilation via the mouth as an alternative to tracheostomy for 257 ventilators users. Chest 103: 174–182. Bach JR, Robert D, Leger P et al. (1995). Sleep fragmentation in kyphoscoliotic individuals with alveolar hypoventilation treated by NIPPV. Chest 107: 1552–1558. Bach JR, Bianchi C, Aufiero E (2004). Oximetry and indications for tracheotomy for amyotrophic lateral sclerosis. Chest 126: 1502–1507. Barbe´ F, Quera-Salva MA, de Lattre J et al. (1996). Long-term effects of nasal intermittent positive-pressure ventilation on pulmonary function and sleep architecture in patients with neuromuscular diseases. Chest 110: 1179–1183. Benhamou D, Muir JF, Raspaud C et al. (1997). Long-term efficiency of home nasal mask ventilation in patients with diffuse bronchiectasis and severe chronic respiratory failure. Chest 112: 1259–1266. Bourke SC, Tomlinson M, Williams TL et al. (2006). Effects of non-invasive ventilation on survival and quality of life in patients with amyotrophic lateral sclerosis: a randomised controlled trial. Lancet Neurol 5: 140–147. Bradley TD, Floras JS (2003a). Sleep apnea and heart failure. Part II: central sleep apnea. Circulation 107: 1822–1826. Bradley TD, Floras JS (2003b). Sleep apnea and heart failure. Part I: obstructive sleep apnea. Circulation 107: 1671–1678. Bradley TD, Logan AG, Kimoff RJ et al. (2005). Continuous positive airway pressure for central sleep apnea and heart failure. N Engl J Med 353: 2025–2033. Brochard L (1997). Noninvasive pressure support ventilation: physiological and clinical results in patients with COPD and acute respiratory failure. Monaldi Arch Chest Dis 52: 64–67. Carrey Z, Gottfried SB, Levy RD (1990). Ventilatory muscle support in respiratory failure with nasal positive pressure ventilation. Chest 97: 150–158. Casanova C, Celli BR, Tost L et al. (2000). Long-term controlled trial of nocturnal nasal positive pressure ventilation in patients with severe COPD. Chest 118: 1582–1590. Cazzolli PA, Oppenheimer EA (1996). Home mechanical ventilation for amyotrophic lateral sclerosis: nasal compared to tracheostomy-intermittent positive pressure ventilation. J Neurol Sci 139 (Suppl): 123–128. Chaudri MB, Liu C, Hubbard R et al. (2002). Relationship between supramaximal flow during cough and mortality in motor neurone disease. Eur Respir J 19: 434–438. Chu CM, Yu WC, Tam CM et al. (2004). Home mechanical ventilation in Hong Kong. Eur Respir J 23: 136–141. Cinnella G, Conti G, Lofaso F et al. (1996). Effects of assisted ventilation on the work of breathing: volumecontrolled versus pressure-controlled ventilation. Am J Respir Crit Care Med 153: 1025–1033. Clini E, Sturani C, Rossi A et al. (2002). The Italian multicentre study on noninvasive ventilation in chronic obstructive pulmonary disease patients. Eur Respir J 20: 529–538. Curran FJ, Colbert AP (1989). Ventilator management in Duchenne muscular dystrophy and postpoliomyelitis
syndrome: twelve years’ experience. Arch Phys Med Rehabil 70: 180–185. de Lucas-Ramos P, de Miguel-Diez J, Santacruz-Siminiani A et al. (2004). Benefits at 1 year of nocturnal intermittent positive pressure ventilation in patients with obesity-hypoventilation syndrome. Respir Med 98: 961–967. Diaz O, Begin P, Andresen M et al. (2005). Physiological and clinical effects of diurnal noninvasive ventilation in hypercapnic COPD. Eur Respir J 26: 1016–1023. Dohna-Schwake C, Ragette R, Teschler H et al. (2006). Predictors of severe chest infections in pediatric neuromuscular disorders. Neuromuscul Disord 16: 325–328. Domenech-Clar R, Nauffal-Manzur D, Perpina-Tordera M et al. (2003). Home mechanical ventilation for restrictive thoracic diseases: effects on patient quality-of-life and hospitalizations. Respir Med 97: 1320–1327. Elliott MW (1999). Non-invasive ventilation – mechanisms of benefit. Med Klin (Munich) 94: 2–6. Elliott MW (2002). Noninvasive ventilation in chronic ventilatory failure due to chronic obstructive pulmonary disease. Eur Respir J 20: 511–514. Elliott MW (2004). The interface: crucial for successful noninvasive ventilation. Eur Respir J 23: 7–8. Fanfulla F, Delmastro M, Berardinelli A et al. (2005). Effects of different ventilator settings on sleep and inspiratory effort in patients with neuromuscular disease. Am J Respir Crit Care Med 172: 619–624. Farrero E, Prats E, Povedano M et al. (2005). Survival in amyotrophic lateral sclerosis with home mechanical ventilation: the impact of systematic respiratory assessment and bulbar involvement. Chest 127: 2132–2138. Fauroux B, Lavis JF, Nicot F et al. (2005). Facial side effects during noninvasive positive pressure ventilation in children. Intensive Care Med 31: 965–969. Finder JD, Birnkrant D, Carl J et al. (2004). Respiratory care of the patient with Duchenne muscular dystrophy: ATS consensus statement. Am J Respir Crit Care Med 170: 456–465. Gay PC, Hubmayr RD, Stroetz RW (1996). Efficacy of nocturnal nasal ventilation in stable, severe chronic obstructive pulmonary disease during a 3-month controlled trial. Mayo Clin Proc 71: 533–542. Gay PC, Herold DL, Olson EJ (2003). A randomized, double-blind clinical trial comparing continuous positive airway pressure with a novel bilevel pressure system for treatment of obstructive sleep apnea syndrome. Sleep 26: 864–869. Girault C, Richard JC, Chevron V et al. (1997). Comparative physiologic effects of noninvasive assist-control and pressure support ventilation in acute hypercapnic respiratory failure [see comments]. Chest 111: 1639–1648. Gonzalez C, Ferris G, Diaz J et al. (2003a). Kyphoscoliotic ventilatory insufficiency: effects of long-term intermittent positive-pressure ventilation. Chest 124: 857–862. Gonzalez J, Sharshar T, Hart N et al. (2003b). Air leaks during mechanical ventilation as a cause of persistent hypercapnia in neuromuscular disorders. Intensive Care Med 29: 596–602.
NONINVASIVE POSITIVE VENTILATION IN SLEEP-RELATED BREATHING DISORDERS Han F, Chen E, Wei H et al. (2001). Treatment effects on carbon dioxide retention in patients with obstructive sleep apnea-hypopnea syndrome. Chest 119: 1814–1819. Hayashi H, Oppenheimer E (2003). ALS patients on TPPV Totally locked-in state, neurologic findings and clinical implications. Neurology 61: 135–137. Hill N (2003). What mask for noninvasive ventilation: is dead space an issue? Crit Care Med 31: 2247–2248. Hill NS (2000). Complications of noninvasive ventilation. Respir Care 45: 480–481. Hill NS (2002). Saving face: better interfaces for noninvasive ventilation. Intensive Care Med 28: 227–229. Hill NS, Carlisle C, Kramer NR (2002). Effect of a nonrebreathing exhalation valve on long-term nasal ventilation using a bilevel device. Chest 122: 84–91. Jackson M, Smith I, King M et al. (1994). Long term noninvasive domiciliary assisted ventilation for respiratory failure following thoracoplasty. Thorax 49: 915–919. Janssens JP, Derivaz S, Breitenstein E et al. (2003). Changing patterns in long-term noninvasive ventilation: a 7-year prospective study in the Geneva Lake area. Chest 123: 67–79. Jimenez JFM, de Cos Escuin JS, Vicente CD et al. (1995). Nasal intermittent positive pressure ventilation. Analysis of its withdrawal. Chest 107: 383–388. Johnson KG, Johnson DC (2005). Bilevel positive airway pressure worsens central apneas during sleep. Chest 128: 2141–2150. Jounieaux V, Aubert G, Dury M et al. (1995). Effects of nasal positive-pressure hyperventilation on the glottis in normal sleeping subjects. J Appl Physiol 79: 186–193. Karakurt S, Fanfulla F, Nava S (2001). Is it safe for patients with chronic hypercapnic respiratory failure undergoing home noninvasive ventilation to discontinue ventilation briefly? Chest 119: 1379–1386. Keenan SP, Sinuff T, Cook DJ et al. (2003). Which patients with acute exacerbation of chronic obstructive pulmonary disease benefit from noninvasive positive-pressure ventilation? A systematic review of the literature. Ann Intern Med 138: 861–870. Kleopa KA, Sherman M, Neal B et al. (1999). Bipap improves survival and rate of pulmonary function decline in patients with ALS. J Neurol Sci 164: 82–88. Kohnlein T, Welte T, Tan LB et al. (2002). Assisted ventilation for heart failure patients with Cheyne–Stokes respiration. Eur Respir J 20: 934–941. Laserna E, Barrot E, Beiztegui A et al. (2003). [Non-invasive ventilation in kyphoscoliosis. A comparison of a volumetric ventilator and a BIPAP support pressure device.] Arch Bronconeumol 39: 13–18. Leger SS, Leger P (1999). The art of interface. Tools for administering noninvasive ventilation. Med Klin 94: 35–39. Leger P, Jennequin J, Gerard M et al. (1989). Home positive pressure ventilation via nasal mask for patients with neuromuscular weakness or restrictive lung or chest-wall disease. Respir Care 34: 73–77. Leger P, Bedicam JM, Cornette A et al. (1994). Nasal intermittent positive pressure ventilation. Long-term
467
follow-up in patients with severe chronic respiratory insufficiency. Chest 105: 100–105. L’Her E, Deye N, Lellouche F et al. (2005). Physiologic effects of noninvasive ventilation during acute lung injury. Am J Respir Crit Care Med 172: 1112–1118. Lien TC, Wang JH, Huang SH et al. (2000). Comparison of bilevel positive airway pressure and volume ventilation via nasal or facial masks in patients with severe, stable COPD. Chung Hua I Hsueh Tsa Chih (Taipei) 63: 542–551. Lin CC (1996). Comparison between nocturnal nasal positive pressure ventilation combined with oxygen therapy and oxygen monotherapy in patients with severe COPD. Am J Respir Crit Care Med 154: 353–358. Lloyd-Owen SJ, Donaldson GC, Ambrosino N et al. (2005). Patterns of home mechanical ventilation use in Europe: results from the Eurovent survey. Eur Respir J 25: 1025–1031. Lo Coco D, Marchese S, Corrao S et al. (2006). Development of chronic hypoventilation in amyotrophic lateral sclerosis patients. Respir Med 100: 1028–1036. Lofaso F, Quera-Salva MA (2002). Polysomnography for the management of progressive neuromuscular disorders. Eur Respir J 19: 989–990. McEvoy RD, Pierce RJ, Hillman D et al. (2009). Nocturnal non-invasive nasal ventilation in stable hypercapnic COPD: a randomised control trial. Thorax 64: 561–566. Make BJ, Hill NS, Goldberg AI et al. (1998). Mechanical ventilation beyond the intensive care unit. Report of a consensus conference of the American College of Chest Physicians. Chest 113: 289S–344S. Markstrom A, Sundell K, Lysdahl M et al. (2002). Qualityof-life evaluation of patients with neuromuscular and skeletal diseases treated with noninvasive and invasive home mechanical ventilation. Chest 122: 1695–1700. Masa JF, Celli BR, Riesco JA et al. (1997). Noninvasive positive pressure ventilation and not oxygen may prevent overt ventilatory failure in patients with chest wall diseases. Chest 112: 207–213. Masa JF, Celli BR, Riesco JA et al. (2001). The obesity hypoventilation syndrome can be treated with noninvasive mechanical ventilation. Chest 119: 1102–1107. Meecham Jones DJ, Wedzichia JA (1993). Comparison of pressure and volume preset nasal ventilator systems in stable chronic respiratory failure. Eur Respir J 6: 1060–1064. Meecham Jones DJ, Paul EA, Jones PW et al. (1995). Nasal pressure support ventilation plus oxygen compared with oxygen therapy alone in hypercapnic COPD. Am J Respir Crit Care Med 152: 538–544. Mehta S, Hill NS (2001). Noninvasive ventilation. Am J Respir Crit Care Med 163: 540–577. Mehta S, McCool FD, Hill NS (2001). Leak compensation in positive pressure ventilators: a lung model study. Eur Respir J 17: 259–267. Meyer TJ, Pressman MR, Benditt J et al. (1997). Air leaking through the mouth during nocturnal nasal ventilation: effect on sleep quality. Sleep 20: 561–569.
468
D. ROBERT AND L. ARGAUD
Muir JF, Girault C, Cardinaud JP et al. (1994). Survival and long-term follow-up of tracheostomized patients with COPD treated by home mechanical ventilation. A multicenter French study in 259 patients. French Cooperative Study Group. Chest 106: 201–209. Nava S, Ambrosino N, Rubini F et al. (1993). Effect of nasal pressure support ventilation and external PEEP on diaphragmatic activity in patients with severe stable COPD. Chest 103: 143–150. Nava S, Fanfulla F, Frigerio P et al. (2001). Physiologic evaluation of 4 weeks of nocturnal nasal positive pressure ventilation in stable hypercapnic patients with chronic obstructive pulmonary disease. Respiration 68: 573–583. Norregaard O (2002). Noninvasive ventilation in children. Eur Respir J 20: 1332–1342. Nugent AM, Smith IE, Shneerson JM (2002). Domiciliaryassisted ventilation in patients with myotonic dystrophy. Chest 121: 459–464. Olson AL, Zwillich C (2005). The obesity hypoventilation syndrome. Am J Med 118: 948–956. Pepin JL, Chouri-Pontarollo N, Tamisier R et al. (2006). Cheyne–Stokes respiration with central sleep apnoea in chronic heart failure: proposals for a diagnostic and therapeutic strategy. Sleep Med Rev 10: 33–47. Pepperell JC, Maskell NA, Jones DR et al. (2003). A randomized controlled trial of adaptive ventilation for Cheyne– Stokes breathing in heart failure. Am J Respir Crit Care Med 168: 1109–1114. Perez de Llano LA, Golpe R, Ortiz Piquer M et al. (2005). Short-term and long-term effects of nasal intermittent positive pressure ventilation in patients with obesity–hypoventilation syndrome. Chest 128: 587–594. Petitjean T, Philip F, Germain-Pastenne M et al. (2008). Sleep and respiratory function after withdrawal of noninvasive ventilation in patients with chronic respiratory failure. Respir Care 53: 1316–1323. Philippe C, Stoica-Herman M, Drouot X et al. (2006). Compliance with and effectiveness of adaptive servoventilation versus continuous positive airway pressure in the treatment of Cheyne–Stokes respiration in heart failure over a six month period. Heart 92: 337–342. Pinto AC, Evangelista T, Carvalho M et al. (1995). Respiratory assistance with a non-invasive ventilator (Bipap) in MND/ALS patients: survival rates in a controlled trial. J Neurol Sci 129 (Suppl): 19–26. Polkey MI, Lyall RA, Davidson AC et al. (1999). Ethical and clinical issues in the use of home non-invasive mechanical ventilation for the palliation of breathlessness in motor neurone disease. Thorax 54: 367–371. Ragette R, Mellies U, Schwake C et al. (2002). Patterns and predictors of sleep disordered breathing in primary myopathies. Thorax 57: 724–728. Randerath WJ, Meier J, Genger H et al. (2002). Efficiency of cold passover and heated humidification under continuous positive airway pressure. Eur Respir J 20: 183–186. Resta O, Guido P, Picca V et al. (1998). Prescription of nCPAP and nBIPAP in obstructive sleep apnea
syndrome: Italian exprience in 105 subjects. A prospective two centre study. Respir Med 92: 820–827. Restrick LJ, Fox NC, Braid G et al. (1993). Comparison of nasal pressure support ventilation with nasal intermittent positive pressure ventilation in patients with nocturnal hypoventilation. Eur Respir J 6: 364–370. Richards GN, Cistulli PA, Ungar RG et al. (1996). Mouth leak with nasal continuous positive airway pressure increases nasal airway resistance. Am J Respir Crit Care Med 154: 182–186. Robert D, Gerard M, Leger P et al. (1983). Permanent mechanical ventilation at home via a tracheotomy in chronic respiratory insufficiency. Rev Fr Mal Respir 11: 923–936. Robert D, Willig TN, Paulus J et al. (1993). Long-term nasal ventilation in neuromuscular disorders: report of a consensus conference. Eur Respir J 6: 599–606. Saatci E, Miller DM, Stell IM et al. (2004). Dynamic dead space in face masks used with noninvasive ventilators: a lung model study. Eur Respir J 23: 129–135. Schonhofer B, Kohler D (2000). Effect of non-invasive mechanical ventilation on sleep and nocturnal ventilation in patients with chronic respiratory failure. Thorax 55: 308–313. Schonhofer B, Sortor-Leger S (2002). Equipment needs for noninvasive mechanical ventilation. Eur Respir J 20: 1029–1036. Schonhofer B, Sonneborn M, Haidl P et al. (1997). Comparison of two different modes for noninvasive mechanical ventilation in chronic respiratory failure: volume versus pressure controlled device. Eur Respir J 10: 184–191. Schwartz AR, Kacmarek RM, Hess DR (2004). Factors affecting oxygen delivery with bi-level positive airway pressure. Respir Care 49: 270–275. Shapiro SH, Ernst P, Gray-Donald K et al. (1992). Effect of negative pressure ventilation in severe chronic obstructive pulmonary disease [see comments]. Lancet 340: 1425–1429. Shneerson JM, Simonds AK (2002). Noninvasive ventilation for chest wall and neuromuscular disorders. Eur Respir J 20: 480–487. Simonds AK (2003). Ethics and decision making in end stage lung disease. Thorax 58: 272–277. Simonds AK, Elliott MW (1995). Outcome of domiciliary nasal intermittent positive pressure ventilation in restrictive and obstructive disorders. Thorax 50: 604–609. Simonds AK, Ward S, Heather S et al. (2000). Outcome of paediatric domiciliary mask ventilation in neuromuscular and skeletal disease. Eur Respir J 16: 476–481. Sivasothy P, Smith IE, Shneerson JM (1998). Mask intermittent positive pressure ventilation in chronic hypercapnic respiratory failure due to chronic obstructive pulmonary disease. Eur Respir J 11: 34–40. Smith IE, Laroche CM, Jamieson SA et al. (1996). Kyphosis secondary to tuberculosis osteomyelitis as a cause of ventilatory failure. Clinical features, mechanisms, and management. Chest 110: 1105–1110.
NONINVASIVE POSITIVE VENTILATION IN SLEEP-RELATED BREATHING DISORDERS Splaingard ML, Frates RC Jr., Harrison GM et al. (1983). Home positive-pressure ventilation. Twenty years’ experience. Chest 84: 376–382. Strumpf DA, Carlisle CC, Millman RP et al. (1990). An evaluation of the respironics BiPAP Bi-Level CPAP device for delivery of assited ventilation. Respir Care 35: 415–422. Strumpf DA, Millman RP, Carlisle CC et al. (1991). Nocturnal positive-pressure ventilation via nasal mask in patients with severe chronic obstructive pulmonary disease. Am Rev Respir Dis 144: 1234–1239. Sullivan CE, Issa FG, Berthon-Jones M et al. (1981). Reversal of obstructive sleep apnea by continuous positive airway pressure applied the nares. Lancet 1: 862–865. Sullivan CE, Berthon-Jones M, Issa FG (1983). Remission of severe obesity–hypoventilation syndrome after short-term treatment during sleep with nasal continuous positive airway pressure. Am Rev Respir Dis 128: 177–181. Szkulmowski S, Belkhouja K, Le QH et al. (2010). Bilevel positive airway pressure ventilation: Factors influencing rebreathing. Intensive Care Med 36: 688–691. Tejeda M, Boix JH, Alvarez F et al. (1997). Comparison of pressure support ventilation and assist-control ventilation in the treatment of respiratory failure. Chest 111: 1322–1325. Teschler H, Stampa J, Ragette R et al. (1999). Effect of mouth leak on effectiveness of nasal bilevel ventilatory assistance and sleep architecture. Eur Respir J 14: 1251–1257. Teschler H, Dohring J, Wang YM et al. (2001). Adaptive pressure support servo-ventilation: a novel treatment for Cheyne–Stokes respiration in heart failure. Am J Respir Crit Care Med 164: 614–619. Thys F, Liistro G, Dozin O et al. (2002). Determinants of Fi,O2 with oxygen supplementation during noninvasive two-level positive pressure ventilation. Eur Respir J 19: 653–657. Trang H, Dehan M, Beaufils F et al. (2005). The French Congenital Central Hypoventilation Syndrome Registry: general data, phenotype, and genotype. Chest 127: 72–79. Tsara V, Serasli E, Voutsas V et al. (2006). Burden and coping strategies in families of patients under noninvasive home mechanical ventilation. Respiration 73: 61–67.
469
Tuggey JM, Elliott MW (2005). Randomised crossover study of pressure and volume non-invasive ventilation in chest wall deformity. Thorax 60: 859–864. Tuggey JM, Elliott MW (2006). Titration of non-invasive positive pressure ventilation in chronic respiratory failure. Respir Med 100: 1262–1269. Tzeng AC, Bach JR (2000). Prevention of pulmonary morbidity for patients with neuromuscular disease. Chest 118: 1390–1396. Vitacca M, Nava S, Confalonieri M et al. (2000). The appropriate setting of noninvasive pressure support ventilation in stable COPD patients. Chest 118: 1286–1293. Ward S, Chatwin M, Heather S et al. (2005). Randomised controlled trial of non-invasive ventilation (NIV) for nocturnal hypoventilation in neuromuscular and chest wall disease patients with daytime normocapnia. Thorax 60: 1019–1024. Wijkstra PJ, Lacasse Y, Guyatt GH et al. (2002). Nocturnal non-invasive positive pressure ventilation for stable chronic obstructive pulmonary disease. Cochrane Database Syst Rev CD002878. Wijkstra PJ, Lacasse Y, Guyatt GH et al. (2003). A metaanalysis of nocturnal noninvasive positive pressure ventilation in patients with stable COPD. Chest 124: 337–343. Willson GN, Wilcox I, Piper AJ et al. (2001). Noninvasive pressure preset ventilation for the treatment of Cheyne– Stokes respiration during sleep. Eur Respir J 17: 1250–1257. Windisch W, Freidel K, Matthys H et al. (2002). [Healthrelated auality of life (HRQL) in patients receiving home mechanical ventilation.] Pneumologie 56: 610–620. Windisch W, Storre JH, Sorichter S et al. (2005a). Comparison of volume- and pressure-limited NPPV at night: a prospective randomized cross-over trial. Respir Med 99: 52–59. Windisch W, Kostic S, Dreher M et al. (2005b). Outcome of patients with stable COPD receiving controlled noninvasive positive pressure ventilation aimed at a maximal reduction of Pa(CO2). Chest 128: 657–662.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 31
Sleep and pulmonary diseases R. TAMISIER, J.L. PE´PIN, AND P. LE´VY * Pulmonary Function Test and Sleep Laboratory, Department of Rehabilitation and Physiology and HP2 Laboratory, INSERM-ERI 17, University Hospital, Grenoble, France
HISTORICAL PERSPECTIVE OF SLEEP AND PULMONARY DISEASES The initial reports on changes in oxygen saturation that were published when a commercial ear oximeter became available in the late 1970s did not focus on sleep apnea but rather on chronic obstructive pulmonary disease (COPD) (Wynne et al., 1978; Flick and Block, 1979; De Olazabal et al., 1982). This was pioneered by Lugaresi and his colleagues who studied breathing during sleep in normal individuals and patients with COPD (Coccagna and Lugaresi, 1978; Lugaresi et al., 1978). This initial report was followed by very productive research on the mechanisms of blood gases and hemodynamics during sleep in COPD. The main reason for the relative decline in interest for sleep and COPD since the 1990s is that it has never been proven that nocturnal desaturations per se have a significant impact on prognosis in COPD (Connaughton et al., 1988). Accordingly, we failed to demonstrate that treating isolated oxygen desaturations that occur during sleep has an impact on hemodynamics or prognosis in COPD (Chaouat et al., 1997, 2001; Weitzenblum and Chaouat, 2004). This is in contrast with what has been shown in restrictive patients, where hypoventilation occurring mainly during REM sleep reveals diaphragmatic inability to maintain an adequate level of ventilation in mechanical impairment of the respiratory system or respiratory muscle weakness (Bradley et al., 1984; Cirignotta et al., 1987). Surprisingly, this did not stimulate much sleep research in this area, whereas sleep apnea research has exploded since the 1990s. Nevertheless, the relation between sleep and many pulmonary conditions has become a frequent medical concern, as COPD, asthma, and obesity are encountered
daily in primary practice. It might explain, however, why the level of evidence is relatively low in many of these areas.
INTRODUCTION Sleep alters ventilatory control and neuromuscular output, both for ventilatory and upper-airway muscles. As a consequence, respiratory physiology is considerably different during sleep compared to wakefulness. Although these modifications do not have significant consequences for healthy patients, they may alter the efficiency of the respiratory system in patients with underlying pulmonary disease. The particular ventilatory weakness during sleep leads to an earlier expression or an aggravation of respiratory conditions, hence both for diagnosis and follow-up purposes, sleep in pulmonary diseases should be a particular pathophysiological state of interest.
Quality of sleep Normal physiological ventilatory changes are associated with the different sleep stages. Thus, sleep structure is an important factor to consider when assessing patients with pulmonary disease. Quality of sleep is altered in chronic obstructive respiratory failure and characterized by a decrease or even an absence of deep slow-wave sleep and a reduction in rapid eye movement (REM) sleep. Overall, sleep is highly fragmented (Calverley et al., 1982; Douglas and Flenley, 1990). In one study of patients with kyphoscoliosis, total sleep time and proportion of time spent in REM sleep did not differ between study patients and control
*Correspondence to: Professor Patrick Le´vy, EFCR, Poˆle Re´e´ducation et Physiologie, CHU de Grenoble, BP 217 X, 38043, Grenoble, France. Tel: (33) 4 76 76 55 16, Fax: (33) 4 76 76 56 17, E-mail:
[email protected]
472
R. TAMISIER ET AL.
subjects (Sawicka and Branthwaite, 1987). No details were reported concerning the quality of deep slowwave sleep or sleep fragmentation. In another study of only 5 patients (Mezon et al., 1980), 2 showed an absence of deep slow-wave sleep and a reduced amount of REM sleep, pointing to the fact that sleep structure depends on the severity of the pulmonary condition. In a study of 14 patients with various muscular diseases, there was no significant change in sleep structure, although sleep microstructure was not reported (Smith et al., 1988). Among the reported studies on sleep in patients with interstitial lung disease (Bye et al., 1984; PerezPadilla et al., 1985; McNicholas et al., 1986), a decrease in the quality of sleep is usually found. The quantity of REM sleep is decreased, the number of stage changes and arousals are increased, and the total duration of phasic non-REM (NREM) sleep is diminished (PerezPadilla et al., 1985; McNicholas et al., 1986). In asthma as a clinical syndrome, symptoms occurring during sleep are often encountered and indicate an unstable state. As many as 75% of asthmatic subjects are awakened by asthma symptoms at least once per week, with approximately 40% experiencing sleep symptoms every night. In a recent study, further investigation of sleep architecture has been completed in hypercapnic cystic fibrosis patients, evaluating the interesting and still unresolved point of oxygen versus noninvasive ventilation (NIV) versus nasal air flow as sham therapy (Young et al., 2008). Although NIV did improve nocturnal hypoventilation, chest symptoms, exertional dyspnea, and peak exercise capacity, there was no difference in any of the sleep variables assessed. The clinical significance of these changes in sleep quality has still to be determined. Do they represent protective mechanisms or pathological effects? One might speculate that the duration of REM sleep is limited because REM sleep is a “risky” ventilatory state owing to enhanced arousal threshold, aggravation of ventilation–perfusion mismatch, and impaired ventilatory responses to hypoxia. However, this hypothesis is not supported by the absence of sleep quality improvement when using oxygen therapy (Douglas and Flenley, 1990).
Ventilatory abnormalities Ventilatory mechanical features are altered in chronic respiratory failure. The mechanically unfavorable position of the diaphragm may lead to muscular ineffectiveness and fatigue. As a consequence, ventilatory accessory muscles are activated even during resting
ventilation. Therefore, the loss of accessory inspiratory muscles with sleep and specifically REM sleep will affect ventilation efficiency in patients although it is well tolerated in normal subjects. Furthermore, some kinds of respiratory failure are associated with ventilation–perfusion mismatches, which may be accentuated by the pulmonary volume changes occurring during sleep. These patients exhibit low functional residual capacity (FRC), which may result in further closure of the small airways and thus in aggravation of ventilation–perfusion mismatch during sleep. In terms of blood gas exchange effectiveness, diurnal hypoxemia and/or hypercapnia will be aggravated. In fact, owing to the shape of the oxyhemoglobin dissociation curve, a modest supplementary drop in PaO2 results in a major drop in SaO2 in these hypoxemic patients.
Alveolar hypoventilation Alveolar hypoventilation is defined as insufficient ventilation, resulting in both an increase in PaCO2 and a decrease in PaO2. This is the major mechanism of nocturnal impairment in gas exchange. Although diurnal hypoventilation can be easily characterized using arterial blood gas analysis, nocturnal hypoventilation during sleep remains difficult to explore. Indeed, no direct assessment of carbon dioxide and oxygen level can be achieved. Thus indirect measurement of PaO2 through SpO2 is mostly performed and hypoventilation is usually defined as time spent with SpO2 less than 90% for more than 5 minutes during sleep. Indeed, this excludes other mechanisms that could account for changes in oxygen saturation such as apneic events or ventilation–perfusion imbalance. Apneic events are usually easily excluded on the shape of SpO2, as shown by repeated cyclical changes. In the absence of CO2 measurement, it is hardly feasible to exclude ventilation–perfusion imbalance. Thus, interesting information would be drawn from transcutaneous oxygen and carbon dioxide pressure measurement. However, technical constraints and limited sensitivity to acute changes limit its use in clinical research and practice.
GENERAL
MECHANISMS OF ALVEOLAR
HYPOVENTILATION DURING
REM
SLEEP
As already mentioned, the tonic activity of intercostal muscles is abolished during REM sleep (Phillipson and Bowes, 1986). Intercostal phasic activity is also reduced to a marked extent. Tonic activity of the diaphragm is abolished, but diaphragmatic phasic activity is preserved or even increased, which prevents the occurrence of alveolar hypoventilation during REM sleep in normal subjects. In pathological conditions, the existence of a myogenic (myopathies) or neurogenic deficit in the
SLEEP AND PULMONARY DISEASES diaphragm (phrenic paralysis) will cause alveolar hypoventilation. Similarly, a diaphragm having to work in an unfavorable mechanical situation (kyphoscoliosis, chronic obstructive respiratory disease) will be unable to ensure adequate ventilation owing to intercostal muscle atony during REM sleep.
SPECIFIC ETIOLOGIES Chronic obstructive pulmonary disease Sleep-related respiratory abnormalities in COPD patients have been described for many years. In these patients, the most significant abnormalities during sleep are nocturnal hypoxemia and hypercapnia. Increases in PaCO2 have been reported in the literature since the late 1950s (Robin, 1958; Robin et al., 1958). Soon after, other authors also reported decreases in oxygen saturation during sleep using early oximeters (Trask and Cree, 1962). These findings were confirmed by nocturnal arterial blood gas measurements (Pierce et al., 1966). Using electroencephalographic measurements, further studies have demonstrated that nocturnal hypercapnia and hypoxemia episodes were closely related to REM sleep periods (Koo et al., 1975; Leitch et al., 1976; Coccagna and Lugaresi, 1978). The longer the REM duration, the more profound is the hypoxemia (Connaughton et al., 1988). In order to identify better patients presenting with nocturnal desaturation during sleep, Connaughton et al. (1988) evaluated COPD patients and found that the level of desaturation was related to the level of daytime PaO2 and PaCO2, and to the overall duration of REM sleep. The lowest levels of nocturnal oxygen saturation were found in patients having the most severe daytime hypoxemia. The decrease in arterial oxygen tension was found to be more pronounced during sleep than during maximal exercise (Mulloy and McNicholas, 1996). Owing to the usual duration of sleep, it was suggested that the hypoxemic stress related to sleep affected the prognosis more significantly than the limited periods of daily physical activity. It should be pointed out that this was never prospectively tested. In the same study, the authors found a similar increase in CO2 transcutaneous pressure (PtcCO2) in both minor and major desaturators. They interpreted this as supporting the presence of gas exchange abnormalities such as ventilation–perfusion mismatch as a major cause of excess desaturation during sleep in some COPD patients (Mulloy and McNicholas, 1996). Patients with awake hypercapnia are more likely to have nocturnal oxygen desaturation (Douglas et al., 1979; Stradling and Lane, 1983; McKeon et al., 1988; Mulloy and McNicholas, 1996). However, whether
473
awake PaCO2 is an independent predictor of nocturnal oxygen desaturation remains controversial. Whilst some studies did confirm this (Connaughton et al., 1988; Pe´pin et al., 1989; Fletcher et al., 1992b), others did not (McKeon et al., 1988; Mulloy and McNicholas, 1996). The relationship between daytime PaCO2 and the rise in sleep PtcCO2 has been found to be weak. There was no significant correlation in multiple regression analysis between daytime variables and the rise in sleep PtcCO2 (Mulloy and McNicholas, 1996). These findings suggest that the reduction in ventilation during sleep secondary to the withdrawal of the wakefulness drive to breath is critical in all patients, regardless of daytime PaCO2.
MECHANISMS As previously suggested, several mechanisms for nocturnal blood gas changes in COPD have been postulated and, much more rarely, demonstrated. It appears that nocturnal hypoventilation is the major cause of hypoxemia during REM sleep in these patients (Figure 31.1). A contribution of both impaired ventilation–perfusion matching and reduction in FRC has also been envisaged. Other conditions, such as obstructive sleep apnea (OSA), may be found in a small percentage of COPD patients and contribute to sleep-related respiratory abnormalities. They do not represent the primary abnormalities in these patients, however. Changes in ventilatory control. Ventilatory control is physiologically altered during sleep, resulting in a diminished responsiveness to chemical, mechanical, and cortical inputs. This is, however, mainly associated with REM sleep (Phillipson, 1978; Gothe et al., 1981), when there is virtually no metabolic control in ventilation. The respiratory muscles also exhibit a diminished response to ventilatory drive during sleep (Gothe et al., 1981) and the upper-airway resistance to flow is increased, secondary to reduction in both tonic and phasic activity of the upper-airway muscles. These upper-airway muscles are responsible for preventing the pharynx collapsing during contraction of the diaphragm (phasic activity) and for maintaining upper-airway tone during sleep (tonic activity) (Lopes et al., 1983; Hudgel et al., 1984; Skatrud and Dempsey, 1985). There is a physiological reduction in basal metabolic rate during sleep with a concomitant decrease in minute ventilation (White et al., 1985). As a result of the fall in ventilation, in normal individuals, PaCO2 rises by 2–8 mmHg, PaO2 decreases by 3–10 mmHg, and oxygen saturation drops by less than 2% (Robin et al., 1958; Bulow, 1963; Douglas et al., 1982a). These changes occur despite the reduction in oxygen consumption and CO2 production during sleep (Douglas et al., 1982a).
474
R. TAMISIER ET AL.
Fig. 31.1. Typical inhibition of ventilation during phasic rapid eye movement (REM) sleep episodes. This occurs to various degrees in normal subjects as well as in pathological conditions. From top to bottom: SAT, oxygen saturation; THO, thoracic movements; ABD, abdominal movements; DEB, nasal airflow; PTS, pulse transit time as an index of respiratory effort; FIN, noninvasive measurement of blood pressure; EO1, eye movements; POS, body position. The green circles underline the bursts of REM that coincide with the inhibition of ventilation.
The decrease in ventilation occurs during all stages of sleep and worsens during REM, particularly during phasic REM, as compared to wakefulness (Lopes et al., 1983; Hudgel et al., 1984; Skatrud and Dempsey, 1985). During REM sleep, phasic REM activity is associated with a dramatic reduction in intercostal muscle phasic and tonic activity. This is associated with a slight reduction in tonic activity of the diaphragm and, more critically, in persistent phasic activity (Phillipson, 1978; Gothe et al., 1981). This is why diaphragmatic functioning is so critical in REM sleep, as no other respiratory muscle is spontaneously able to contribute to maintain alveolar ventilation during this period (Figure 31.2). The decrease in muscular activity seems to affect particularly patients with obstructive lung disease, because lungs are hyperinflated and the flattened diaphragm cannot contribute as efficiently to ventilation. As the diaphragm is the unique active respiratory muscle during REM sleep (White et al., 1985), alveolar ventilation will be highly affected during REM sleep in these subjects.
Breathing irregularity with rapid shallow breathing during REM sleep (Gould et al., 1988) also increases the physiologic dead space in COPD patients and thus impairs gas exchange (Tusiewicz et al., 1977; Gothe et al., 1982; Krieger et al., 1983; Stradling et al., 1985). All of these features may contribute to greater oxyhemoglobin desaturation, as found in patients with COPD when compared to patients with other lung diseases (e.g., interstitial pulmonary fibrosis (Midgren, 1990)). Another important contributing factor relates to the ventilatory responses to hypoxia and hypercapnia that are decreased during sleep in normal individuals, with further decrease during REM sleep (Bellville et al., 1959; Berthon-Jones and Sullivan, 1982, 1984; Douglas et al., 1982a, b, c; White et al., 1982). It should be noted that ventilatory response to hypoxia appears to be differently affected in males than in females: women have shown nearly no decline in the response to hypoxia during sleep. The mechanisms are still unclear but both increased airway resistance and decreased activity of the
SLEEP AND PULMONARY DISEASES
475
Fig. 31.2. Representative tracing of a patient with chronic obstructive pulmonary disease exhibiting alveolar hypoventilation during rapid eye movement sleep. Poes, esophageal pressure.
medullary respiratory neurons during sleep have been suggested (Orem, 1980; Lopes et al., 1983; Hudgel et al., 1984). The reduction in ventilatory drive associated with the loss of the wakefulness stimulus appears to be a major factor (Hudgel et al., 1983). In summary, as already mentioned, tonic activity of the intercostal muscles is abolished during REM sleep but diaphragmatic phasic activity is preserved or even increased, which prevents the occurrence of alveolar hypoventilation during REM sleep in normal subjects. In COPD, as the diaphragm has to work in an unfavorable mechanical situation, alveolar hypoventilation is expected in the absence of intercostal muscle activity. Other additional factors further aggravate this primary change in ventilation. Changes in functional residual capacity. In normal subjects, FRC has been reported to decrease during REM sleep secondary to supine positioning and atonia of the intercostal muscles (Tusiewicz et al., 1977; Hudgel et al., 1983). In COPD, there are contradictory data resulting from inductive plethysmography measurements (Hudgel et al., 1983; Ballard et al., 1995) that do not provide accurate measurement during sleep (Whyte et al., 1991). In a study dealing with adult patients with cystic fibrosis, a condition clearly distinct from usual COPD, respiratory function was studied during sleep using a horizontal body plethysmograph (Ballard et al., 1996). Only data from NREM sleep
were obtained. There was no significant decrease in FRC. The contribution of neuromuscular output was also confirmed with progressive reduction in tidal volume and minute ventilation from wakefulness to slowwave sleep. Occlusion pressure at 100 ms (P0–1) was also significantly reduced during sleep, which may represent a reduction in neuromuscular output as the main contributor to the reduction in ventilation observed during NREM sleep. Change in ventilation–perfusion mismatch. Ventilation–perfusion mismatches have been postulated to explain the blood gas disturbances that occur during sleep in COPD (Fletcher et al., 1983; Catterall et al., 1985). It is presumably what occurs in major desaturators, as identified in some studies (Mulloy and McNicholas, 1996). As already mentioned, a similar change in PtcCO2 in both minor and major desaturators supports the presence of ventilation–perfusion ratio disturbance as a major cause of excess desaturation during sleep in major desaturators (Mulloy and McNicholas, 1996). It should be noted, however, that no direct evidence has been provided to support this hypothesis. Associated sleep-disordered breathing. OSA is a common condition and thus its association with another frequent disease, such as COPD, is expected. In a large series of patients diagnosed with OSA in a sleep center, the average frequency of concomitant obstructive lung disease, determined by pulmonary
476
R. TAMISIER ET AL.
function testing, was 11% (Weitzenblum et al., 1992). In these patients, the pattern of nocturnal oxygen saturation was different than with solely COPD. The desaturation was widespread during the night, with further drops during REM sleep, in which hypoventilation was the most important contributing factor. This association of COPD and OSA resulting in a combined ventilatory pattern has been named overlap syndrome. This does not imply, however, that the prevalence of sleep apnea in COPD is higher than in the general population (Sanders et al., 2003). Obesity might also be considered as a comorbidity factor for COPD patients since it has been correlated with a higher drop in oxygen tension during sleep (Becker et al., 1999). However, in the study of Nizet et al. (2005) it has been demonstrated that body mass index did not correlate with higher morbidity rate.
WHOM TO STUDY The importance of sleep studies in a selected group of COPD patients cannot be overstated. Routine polysomnography is unlikely to be performed in COPD patients. There is thus a need to identify the patients who may either benefit from this diagnostic procedure or should rather be studied with simplified techniques (e.g., oximetry, ventilatory assessment). Based on daytime PaO2 or SaO2, we are not able to identify those patients who would develop nocturnal desaturation. Douglas et al. (1979) have demonstrated a relationship between mean oxygen saturation during wakefulness and the lowest oxygen saturation during sleep. However, nocturnal desaturation could not be predicted from lung function and clinical features (McKeon et al., 1988; Fletcher et al., 1992b). Thus, this evaluation is at least needed to adjust oxygen therapy and adequately control for oxygenation during sleep. However, simple oximetry is sufficient in most cases. There is a particular group of patients who have both COPD and OSA and are prone to develop pulmonary hypertension and CO2 retention at higher rates than patients with OSA without associated COPD (Weitzenblum et al., 1992). Thus, the major indications for nocturnal polysomnography in COPD patients with nocturnal hypoxemia, including those who develop hypoxemic complications such as cor pulmonale and polycythemia despite reasonable levels of daytime oxygen tension (e.g., PaO2 above 60 mmHg), represent the search for an associated OSA, the so-called overlap syndrome, as previously described (Chaouat et al., 1995). It should, however, be remembered that clinical scores and questionnaires assessing symptoms of OSA are not effective in these patients. The only difference may be the
predominance of dyspnea and daytime fatigue as compared to the usual predominance of excessive daytime sleepiness (EDS). It should also be kept in mind that EDS is common during acute exacerbations of chronic respiratory failure owing to acute CO2 retention and acidosis. In stable conditions, however, EDS is usually explained by sleep fragmentation. Thus, quality of sleep is altered in chronic obstructive respiratory failure and characterized by reduction or suppression of slow-wave sleep, occurrence of sleep fragmentation, and reduction in REM sleep (Brezinova et al., 1982; Calverley et al., 1982; Fleetham et al., 1982; Douglas and Flenley, 1990). Ventilation and sleep monitoring are also envisaged in COPD patients for therapeutic purposes, i.e., titrating nocturnal oxygen, as already mentioned, adjusting continuous positive airway pressure (CPAP) or noninvasive positive pressure ventilation (NPPV). Besides, it may be clinically indicated when using continuous overnight oximetry alone and proceeding to various changes in ventilator parameters does not result in a sufficient improvement in nocturnal oxygen saturation.
Detection of patients with excessive nocturnal hypoxemia The definition of significant nocturnal desaturation is not well established. The most commonly used definitions in the literature are: (1) greater than 30% of total time in bed spent below 90% of oxygen saturation, or (2) a drop in oxygen saturation below a baseline of 90% for longer than 5 minutes, reaching a nadir of 85% or lower (Levi-Valensi et al., 1990; Fletcher et al., 1992a). In a study by Connaughton et al. (1988), 97 patients with COPD were followed after sleep studies. The authors were able to demonstrate a significantly higher mortality in patients with the lowest levels of oxygen saturation during sleep. Despite this finding, similar predictions could be made by analyzing daytime oxygen levels only and vital capacity, both of which were associated with a reduced survival after a mean follow-up of 70 months, independently of nocturnal SaO2. Based on further analysis, the data from nocturnal polysomnography or oximetry did not influence the prognosis more than wakefulness SaO2 and daytime pulmonary function (Connaughton et al., 1988). Whether nocturnal hypoxemia per se carries a higher mortality risk for COPD patients without daytime hypoxemia (Fletcher et al., 1987, 1992c) has been much debated. Several authors have evaluated nocturnal desaturation as a potential negative prognostic factor for survival in these patients. However, data issued from a European multicenter trial coordinated
SLEEP AND PULMONARY DISEASES by Emmanuel Weitzenblum (Chaouat et al., 1999) clearly demonstrated that, in patients with daytime PaO2 over 60 mmHg and nocturnal desaturation much more severe than usually considered ( 30% of recording time with a SaO2 less than 90%), there was no significant change in pulmonary hemodynamics during a 2-year follow-up and no difference in terms of hemodynamic changes and survival rate for the same observation period, when comparing patients with or without oxygen supplementation. In patients with cor pulmonale and polycythemia despite normal daytime oxygen tension, sleep studies may, however, uncover nocturnal hypoventilation that might contribute.
Identification of associated OSA It appears that OSA can be suspected clinically by asking for history of snoring, EDS, and witnessed apneas. At this point, there is no proof that sleep studies would yield unsuspected cases of OSA (Connaughton et al., 1988). Moreover, there is not a higher prevalence of OSA in patients with mild COPD (Sanders et al., 2003). Physicians should seek for sleep apnea symptoms in COPD patients, and when symptoms are elicited, should then perform polysomnography or simplified recordings.
Therapeutic intervention evaluation It is difficult to predict oxygen requirements during sleep in patients with COPD. The current recommendations of the American Thoracic Society (1995) suggest increasing oxygen daytime requirements at rest by 1 l/min during exercise and sleep in patients who are qualified for supplemental oxygen. However, it is unclear whether this is adequate or not. As previously discussed, it is difficult to predict nocturnal hypoxemia based solely on wakefulness arterial blood gas, although in several studies daytime PaO2 below 65 mmHg combined with PaCO2 above 45 mmHg were the best predictors of nocturnal desaturation (Pe´pin et al., 1989; Plywaczewski et al., 2000). Other therapeutic indications represent the followup of interventions such as CPAP and NIPPV. COPD patients should be adapted on the basis of an optimal recording of flow, volume, and mask pressure during sleep. Sleep recording per se is not systematically required. In any case, overnight monitoring is required in order to establish an adequate level of nocturnal ventilation with a limited amount of side-effects (i.e., mouth or mask leaks). Leaks may be associated with ineffective mechanical ventilation and induced sleep fragmentation (Rodenstein and Levy, 1999). When both are suppressed with adequate interface adjustment,
477
there is an improvement in both alveolar ventilation and daytime function, e.g., there is no residual EDS (Teschler et al., 1999).
HOW TO TREAT The most important consideration when dealing with COPD patients remains to optimize their management for the underlying condition. Additional therapeutic interventions are targeted towards sleep-related abnormalities, as discussed below.
Oxygen With the use of supplemental oxygen, nocturnal oxygen saturation improves in patients with COPD (Douglas et al., 1979; Fleetham et al., 1980; Goldstein et al., 1984). Despite that, some milder dips in saturation, mainly during REM sleep, may persist. In one study, there was also a nonsignificant trend for nocturnal oxygen to reduce the frequency of ectopic heart beats in COPD patients (Flick and Block, 1979). As long-term use of oxygen is the only measure shown to date to decrease mortality in this population (Nocturnal Oxygen Therapy Trial Group, 1980; Medical Research Council Working Party, 1981), one would assume that the decrease in hypoxemia during sleep is, at least, one adjuvant factor in the improved survival. The oxygen fractions prescribed in these studies were, however, based solely on awake arterial oxygen tensions. Another study demonstrated improvement in pulmonary arterial pressure without survival difference between two groups of COPD patients without daytime hypoxemia or hypercapnia when randomized to receive nocturnal oxygen (Fletcher and Levin, 1984; Fletcher et al., 1992b). However, other data showed the opposite (Chaouat et al., 1999). In this last study, the authors reached the conclusion that nocturnal oxygen therapy (NOT) did not modify the evolution of pulmonary hemodynamics during a 2-year follow-up and did not allow any delay in the prescription of long-term oxygen therapy (over 15 hours per 24 hours). There was no effect of NOT on survival, although the limited number of deaths precluded any firm conclusion. Consequently, the authors have suggested that the prescription of NOT in isolation is probably not justified in COPD and consequently that the current international guidelines should be reconsidered (Chaouat et al., 1999). From this perspective, another paper issued from the national French network Antadir has shown, in a very large series of 7700 COPD patients, that about 18% of these patients exhibited a stable PaO2 over 60 mmHg. There was also no difference in survival when comparing the patients having a stable
478
R. TAMISIER ET AL.
PaO2 above or below this threshold (Veale et al., 1998). These last results do not, however, support the use of oxygen therapy in moderate to mild hypoxemia or the use of NOT in this patient population. Physicians should be careful when using oxygen in patients with associated OSA, as it has been demonstrated that periods of apnea or hypopnea may be prolonged and occur with increased frequency during the acute application of oxygen (Alford et al., 1986). Increase in PaCO2 monitored by transcutaneous CO2 during supplemental oxygen has been found to be mild when compared to wakefulness, and not progressive through the night (Goldstein et al., 1984). Nevertheless, when prescribing oxygen to COPD patients, careful clinical monitoring is required (i.e., new complaints such as morning headaches, insomnia, and sudden EDS) in order to prevent any further CO2 retention. Thus there is a need for careful oxygen titration and adequate follow-up using arterial blood gas sampling during wakefulness when carbon dioxide retention is clinically suspected. It should be emphasized that this is rarely an issue. The device used for nocturnal oxygen delivery does not seem to matter, but when a demand delivery device is prescribed it would be judicious to evaluate its efficacy by continuous overnight oximetry to ensure an effective oxygen delivery. Oxygen has also been shown by some investigators to improve sleep quality (Calverley et al., 1982; Goldstein et al., 1984), although others have failed to demonstrate any improvement with respect to arousal frequency (Fleetham et al., 1982).
Medications
ALMITRINE
BISMESYLATE
This is a peripheral chemoreceptor agonist that improves PaO2 during wakefulness. Its stimulant effects are only present at high dosage and probably mediated by calcium-dependent potassium channel inhibition. Almitrine increases minute ventilation. The drug improves ventilation–perfusion matching even at lower dosage and was shown to improve both awake and nocturnal oxygenation in COPD patients, with a less pronounced effect on PaCO2 (Connaughton et al., 1985; Gothe et al., 1988). This agent is known to cause peripheral neuropathy and there is controversy regarding possible coincident pulmonary hypertension. At this point, its dosage for safe use in chronic conditions is still not well defined (Howard, 1989).
BRONCHODILATORS In a randomized double-blind placebo-controlled study by Martin et al. (1999), ipratropium bromide was associated with improvement in oxygenation and sleep quality in COPD patients without daytime CO2 retention or superimposed OSA. There was also an improvement in subjective sleep quality and breathlessness. This reminds the reader of the importance of adequate treatment of the underlying obstructive lung disease in order to improve nocturnal gas exchange. Regarding b2-agonists, there are not enough data to reach any firm conclusion with respect to their effects on sleep-related anomalies.
MEDROXYPROGESTERONE
The role of medical treatment specifically dedicated to the nocturnal hypoxemia of COPD has not been well defined. There are some medications known to improve oxyhemoglobin levels during sleep but that carry undesirable side-effects. The recommended management is to be aggressive when treating underlying airway obstruction with safe medications in an attempt to decrease the deleterious effects that sleep, mainly REM sleep, has on ventilation and gas exchange in COPD patients.
Reduction in arterial CO2 tension and improvement in oxygen levels during wakefulness and NREM sleep were demonstrated in patients with hypercapnia and COPD using medroxyprogesterone (Dolly and Block, 1983). Another study in COPD patients demonstrated a limited improvement in nocturnal oxygen saturation when compared to almitrine (Daskalopoulou et al., 1990). It seems that, despite some reported improvements, the role of this agent is limited, particularly owing to its side-effects.
ACETAZOLAMIDE
PROTRIPTYLINE
Skatrud and Dempsey (1983) compared the use of acetazolamide and medroxyprogesterone acetate in COPD patients. Acetazolamide improved arterial oxygenation during both wake and sleep. Its side-effect profile, however, limits its chronic use by causing potential acidosis, paresthesias, and nephrolithiasis.
Studies have demonstrated improvement in daytime and nocturnal oxygenation in COPD patients (Series and Cormier, 1990). The improvement in nocturnal saturation is considered to rely on REM sleep suppression. It is unclear whether other mechanisms are involved. More data regarding its safety with
SLEEP AND PULMONARY DISEASES long-term utilization, morbidity, and mortality charts are required. It is known that side-effects limit protriptyline use. The risks of prolonged REM suppression are also a concern. REM rebound when withdrawing the drug may be associated with profound hypoxemia and hypercapnia, with potentially serious risks for patients.
THEOPHYLLINE Berry et al. (1991) demonstrated improvement in overnight oxygen saturation and transcutaneous CO2 after oral ingestion of theophylline during NREM sleep in nonhypercapnic patients with COPD. The effects were not continued during REM sleep. Mulloy and McNicholas (1993) described similar findings regarding nocturnal oxygenation. However, significant impairment in sleep quality has been described after oral ingestion of theophylline (Ebden and Vathenen, 1987; Mulloy and McNicholas, 1993). Ebden and Vathenen (1987) studied patients with COPD on 3 consecutive nights using intravenous theophylline infusion, and were not able to demonstrate significant improvement in overnight oxygenation. Based on the current data, the use of theophylline to improve nocturnal oxygenation in COPD patients remains uncertain. The use of other medications, such as hypnotic and sedative agents in patients with COPD, must be very cautious, as benzodiazepines may cause worsening of ventilatory responses during sleep, precipitating nocturnal hypoxemia and, possibly, acute respiratory failure. Newer hypnotic agents like zolpidem did not demonstrate deleterious effects in nocturnal oxygenation or early-morning arterial blood gases when taken for 7 consecutive nights by a series of stable hypercapnic COPD patients (Girault et al., 1996).
Inspiratory muscle training and pulmonary rehabilitation It has been demonstrated that 10 weeks of inspiratory muscle training improves nocturnal saturation (þ1.9 2.2%) in patients with severe COPD by improving respiratory muscle strength and endurance (Heijdra et al., 1996). This may be helpful in increasing ventilatory reserve during sleep; however, more data are needed before definite recommendations can be made. Pulmonary rehabilitation might enhance pulmonary function during sleep. However, no study is currently available in this area. In a study comparing lung volume reduction surgery with medical therapy, there was a significant improvement in total sleep time, sleep efficiency, but also in oxygen saturation from 90 7 to 93 4% (P < 0.05) (Krachman et al., 2005).
479
Negative-pressure ventilation Despite positive effects on arterial gases in patients with COPD (Brown and Marino, 1984; Cropp and DiMarco, 1987), Levy et al. (1989) demonstrated deleterious effects on the upper airway during sleep, causing collapse and airway obstruction with sleep alteration. Its use has been discouraged.
Continuous positive airway pressure Mezzanotte et al. (1994) found improved inspiratory muscle strength and endurance and better functional ability in COPD patients treated with nocturnal CPAP. Mansfield and Naughton (1999) also demonstrated that CPAP was very effective in treating patients with combined COPD and OSA, with improvement in arterial blood gases and reduced hospitalization rates when adequate levels of CPAP were delivered and tolerated. Lately, we have found that the use of NPPV may be more beneficial to this population, at least for short-term usage (unpublished data). Nevertheless, the use of CPAP may be a good option for patients with COPD presenting with OSA. In such cases, oxygen should be added as needed when titrating CPAP in order to maintain adequate levels of saturation.
Noninvasive positive pressure ventilation NPPV can be offered to COPD patients when the optimization of their disease and the adjunctive use of oxygen are not providing adequate control of hematosis, particularly during sleep. Studies have demonstrated an increase in total sleep time without significant changes in the respective percentage of REM and NREM sleep in COPD patients treated with NPPV (Lin, 1996; Jones et al., 1998). There did not seem to be a marked improvement in daytime respiratory function in those patients, but the number of hospitalizations during their first year on NPPV was significantly lower (Leger et al., 1994). Meecham Jones et al. (1995) were able to demonstrate improved daytime PaCO2 and PaO2 after a 3-month period of NPPV with additional nocturnal oxygen, when compared to oxygen therapy alone in patients with daytime hypercapnia. There was no difference between treatment arms in regard to nocturnal oxygen saturation. There were, however, clear indicators of improved sleep efficiency and quality of life associated with NPPV. Although there are some controversies regarding the optimal device for patients with COPD, a few studies found no major differences in the correction of hypoventilation when using a pressure- or volumepreset devices (Meecham Jones and Wedzicha, 1993;
480
R. TAMISIER ET AL.
Elliott et al., 1994). In clinical practice, pressure devices are often favored in COPD patients. It may relate to improved comfort and leak compensation by increase in flow. The disadvantages are mostly secondary to the variability in tidal volume and delivered oxygen fraction. In most patients, inspiratory pressures lower than 20 cmH2O are sufficient to improve tidal volume and deliver effective ventilatory assistance. Pressures above those limits are rarely needed and anyway poorly tolerated. A back-up preset respiratory rate may be needed in some cases to ensure minimum ventilation. This can be done by using the assist (pressure- or flow-triggered) or control mode. If patients are unable to trigger the ventilator, a back-up rate similar to their respiratory rates during sleep should be preset on the device. Lower respiratory rates are also well tolerated and carry a lower risk of hyperinflation. To help synchronization between patient and ventilator, there is an option to discontinue the inspiration when airflow approximates zero. The availability of positive end-expiratory pressure (PEEP) is also convenient for patients with COPD, because they frequently have intrinsic PEEP which considerably increases the effort required for triggering the ventilator. PEEP is also important in such devices because there is no separate expiratory port and thus maintaining PEEP will reduce or avoid CO2 rebreathing. It also allows airway patency to be maintained during sleep, an important consideration in patients with OSA. When a ventilation device is used, it is critical to assess patient comfort. Daytime sessions using the device for adaptation prior to the sleep study are recommended. NIPPV can worsen hyperinflation and subjective patient evaluation during these sessions is important. It will also improve patients’ compliance. After proper adjustment of the equipment, a full nocturnal polysomnography is indicated (Rodenstein and Levy, 1999; Teschler et al., 1999). When not available, nocturnal oximetry with daytime arterial blood gas sampling while breathing spontaneously may help to assess the efficacy of nocturnal ventilation. A reduction in previously elevated PCO2 levels should be expected after the initial nights of treatment. Close follow-up is recommended when treating such patients. Indications for this treatment were addressed by a consensus conference report (1999). It was found that there are enough data demonstrating favorable effects of NPPV in COPD, determined by either arterial blood gas analysis or sleep quality data. Although significant long-term data with survival advantage when compared to long-term oxygen therapy are still lacking, the use of NPPV in hypercapnic COPD patients was considered likely to be beneficial.
FINAL REMARKS It is likely that the severity of nocturnal oxygen desaturation does not correlate with excess mortality in patients with COPD. Other factors associated with hypoxemia in COPD patients should be considered during their evaluation and management. Cardiovascular issues should be addressed, as there are now data showing early cardiovascular impairment in COPD (Barr et al., 2007; McAllister et al., 2007; Sabit et al., 2007; Mills et al., 2008). Whether nocturnal oxygen desaturations specifically contribute to these subclinical cardiovascular changes is unknown but will require further investigation. Systemic inflammation and oxidative stress presumably play a major role in this context and could be triggered or aggravated by nocturnal hypoxia. A frequent comorbid association between COPD and various cardiovascular diseases has also been demonstrated (Dahlstrom, 2005). In this field several studies have suggested a specific effect of nocturnal oxygen desaturation on cardiac function (Shepard et al., 1984; Levy et al., 1991). We have, for instance, shown in a very limited subset of patients that REMrelated desaturations have an impact on left ventricular ejection fraction that is comparable to maximal exercise (Levy et al., 1991). In fact, very little tissue impact of nocturnal hypoxemia has been established in patients with COPD. Increased levels of erythropoietin in the morning in patients with COPD has been demonstrated (Wedzicha et al., 1985). Nocturnal levels of erythropoietin may also rise in this patient population when nocturnal oxygen saturation falls below 60% (Fitzpatrick et al., 1993). In another study, red cell mass increased in patients with nocturnal oxygen desaturation (Fletcher et al., 1989). Those patients also had lower daytime oxygen saturation, which may have accounted for the difference. Fitzpatrick et al. (1993) reported rises in nocturnal erythropoietin only in patients in whom daytime PaO2 was lower than 45 mmHg. This issue is much complicated by the occurrence of anemia in COPD patients. Anemic COPD patients show high erythropoietin levels, which may indicate the presence of erythropoietin resistance, possibly mediated by inflammatory mechanisms (John et al., 2005).
SUMMARY COPD is a prevalent disease associated with several sleep-related abnormalities in gas exchange and respiratory physiology. Long-term survival for these patients is poor, not only due to respiratory failure but also to comorbid conditions, including cardiovascular diseases. Treating oxygen desaturation is an
SLEEP AND PULMONARY DISEASES important part of the modern care of COPD. Nocturnal polysomnography should be considered in these patients when OSA is suspected or when further therapeutic intervention is needed. Long-term home use of oxygen is the treatment of choice for hypoxemia in COPD patients and has been associated with an improved survival. The morbidity of nocturnal desaturation is still largely unknown, however. For patients with associated OSA, other treatment modalities such as the combined use of CPAP should be considered. NPPV seems to be a better alternative for patients with nocturnal desaturations that are presenting with daytime hypercapnia despite long-term oxygen treatment. No single medication has been clearly indicated, but adequate treatment of the underlying pulmonary disease is mandatory and associated with improvement in sleep quality. The importance of adequate treatment of nocturnal desaturation is under current investigation and further outcome studies are necessary in order to establish the best treatment strategy.
Kyphoscoliosis The major mechanism responsible for abnormal nocturnal ventilation in kyphoscoliosis is alveolar hypoventilation. As a result of changes in the thoracic shape, the diaphragm has to work in a mechanically disadvantageous posture. The suppression of accessory muscle activity during REM sleep leads to hypoventilation. This has been illustrated by the work of Sawicka and Branthwaite (1987), who have shown that the elevation of PaCO2 is identical in NREM sleep in control subjects and kyphoscoliotic patients (loss of “wakefulness stimulus”). Conversely, during REM sleep there is an increase in PaCO2 in kyphoscoliotic patients: in normal subjects this is limited. The decrease in ventilation associated with REM sleep favors microatelectasis and ventilation–perfusion mismatches. Such a drop in oxygen saturations is especially marked in patients with low lung volumes. Finally, alveolar hypoventilation may cause fatigue of the respiratory muscles and in turn may prolong diurnal hypoventilation, thus creating a vicious circle (Jardim et al., 1981; Juan et al., 1984). With respect to the choice between pressure support and volume ventilator, a study of 13 patients with chronic respiratory failure and chest wall deformity did not find any difference in sleep quality between the two types of ventilator (Tuggey and Elliott, 2005).
Neuromuscular disorders The disorder for which most of the data are available is Duchenne muscular dystrophy. Alveolar hypoventilation is related to a reduction in intercostal muscle
481
activity in REM sleep. This can be shown directly by a decrease in intercostal electromyogram and indirectly by a decrease in thoracic movement amplitude (Smith et al., 1988). In the context of diaphragmatic weakness related to the myopathy, the reduction in intercostal muscle activity occurring during sleep leads to alveolar hypoventilation. This is a major issue during REM sleep. Adaptive mechanisms may occur, as illustrated by an unusual phasic activity of accessory inspiratory muscle during REM in subjects with amyotrophic lateral sclerosis, presenting with severe diaphragmatic weakness (Arnulf et al., 2000). Reduction in REM sleep or its complete suppression has been suggested as a compensatory mechanism in order to avoid hypoventilation during these sleep stages (Bye et al., 1990; Arnulf et al., 2000). Vital capacity or diurnal blood gases are not useful predictors of nocturnal desaturations. Conversely, the lower the residual functional capacity and total lung volume, the more pronounced the nocturnal oxyhemoglobin desaturations. This underlies the relationship between oxygen stores and oxygen desaturations. Finally, there is a linear relationship between REM sleep desaturations and both the abdominal contribution in NREM sleep (Smith et al., 1989) and the transdiaphragmatic pressures generated (Davis and Loh, 1979). These two indirect and direct diaphragmatic forces indicate diaphragm weakness and/or diaphragmatic mechanically unfavorable position. Alveolar hypoventilation thus occurs when the diaphragm can no longer compensate for the loss of intercostal muscle tone during REM sleep (Skatrud et al., 1980; Stradling et al., 1987). NIV has become a standard treatment, by normalizing arterial blood gases during both sleep and wakefulness. In adults, NIV improves sleep structure with an increase in slow-wave sleep proportion and sleep efficiency (Barbe et al., 1996). This was also shown in infants with neuromuscular disease, confirming the positive effects of NIV on sleep architecture (Mellies et al., 2003).
Interstitial lung disease Few studies have been carried out on ventilation abnormalities during sleep in the context of interstitial lung disease (Bye et al., 1984; Perez-Padilla et al., 1985). Some investigators have considered nocturnal desaturations to be minor in these diseases and of no clinical significance, whereas others consider them to be extremely significant, exceeding values observed during effort and requiring consideration for NOT (Bye et al., 1984; Perez-Padilla et al., 1985). Upon awakening, increase in ventilatory control is responsible for an increased ventilatory frequency which is out of proportion to that required by the drop in vital capacity.
482
R. TAMISIER ET AL.
Pulmonary receptors may be implicated through mediation of the vagus nerve endings sensitive to inflammation (Kornbluth and Turino, 1980). Here again the data regarding the changes in respiratory frequency during sleep are contradictory. According to McNicholas et al. (1986), respiratory frequency would decrease during sleep as a result of wakefulness-associated changes in reflexes being mediated by the vagus (see above). This sleep-induced decrease in respiratory frequency was not found in two other studies (Bye et al., 1984; Perez-Padilla et al., 1985). Moreover, comparing normal subjects to patients with interstitial lung disease, breathing frequency was higher in patients versus controls, decreasing with oxygen supplementation but remaining higher than in controls (Vazquez and Perez-Padilla, 2001). The decrease in diaphragmatic electromyogram activity and the reduction in thoracic and abdominal volumes are arguments in support of the occurrence of alveolar hypoventilation (Bye et al., 1984). Nocturnal hypoxemia in interstitial lung disease is common; mean oxygen saturation during the daytime has been found to be well correlated with nocturnal desaturation while percentage predicted forced vital capacity is not (Clark et al., 2001). In this last study there was a correlation between nocturnal hypoxemia and energy levels and daytime social and physical functioning (Clark et al., 2001).
Cystic fibrosis Alveolar hypoventilation may occur during REM sleep, with a significant decrease in diaphragmatic and intercostal electromyogram (Muller et al., 1980). Several studies have produced conflicting results: some authors have shown a decrease in sleep efficiency and total sleep time (Milross et al., 2001b) associated with increased sleepiness, as shown by reduced sleep time latency on Multiple Sleep Latency Test (Dancey et al., 2002). Conversely these anomalies were improved by bilevel ventilation (Milross et al., 2001a). Others have not found any difference between cystic fibrosis patients and healthy subjects (Bradley et al., 1999; Jankelowitz et al., 2005). Cystic fibrosis patients exhibit poor sleep quality, however (Jankelowitz et al., 2005). In these studies, Milross et al. and Dancey et al. explored much more severe patients (mean forced expiratory volume in 1 second (FEV1) 36%) compared to Jankelowitz et al. (mean FEV1 ¼ 62%) (Milross et al., 2001a, b; Dancey et al., 2002; Jankelowitz et al., 2005). However, in a randomized, placebo-controlled, crossover study when NIV was compared to oxygen or sham therapy, no difference in sleep parameters was found after 6 weeks of treatment (Young et al., 2008).
Asthma It is well known that bronchoconstriction is likely to increase during sleep. Several factors may explain this phenomenon, including circadian changes in airway narrowing, gastroesophageal reflux aggravated by the supine position, and lengthening of the period between medication intakes (Douglas, 2000). Many symptoms of asthma thus occur during sleep and may impair sleep quality. Wheezing causes sleep disturbances and in severe asthma may aggravate the prognosis. Sleep disruption has been incriminated in a decrease in sleep efficiency, and in sleep time. As a consequence, daytime cognitive function may be impaired. Besides, during acute exacerbations of asthma, patients may have little or no sleep. Patients with severe airway narrowing may become hypoxemic owing to the decrease in ventilation occurring at sleep onset. However, this nocturnal hypoxemia was found to be related more to the level of daytime oxygenation than to the degree of bronchoconstriction (Catterall et al., 1982). Data suggest a link between sleep-related breathing disorders and asthma-related symptoms. Moreover, the presence of snoring and observed apnea in individuals with asthma-related symptoms causes further impairment in quality of life (Ekici et al., 2005). Daytime sleepiness and tiredness are more common in wheezing than in nonwheezing children and upperairway symptoms are related to sleep disturbances (Desager et al., 2005). Treatments need to be evaluated, as insufficient treatment is likely to be associated with symptoms during sleep and an overall impairment in sleep quality. Salmeterol has been shown to be associated with sustained improvement in morning peak expiratory flow, protection from nighttime lung function deterioration, reduction in albuterol use, and improvement in patient sleep perceptions. No differences have been seen, however, in polysomnographic measures of sleep quality (Wiegand et al., 1999). It should be remembered that both corticoids and b2-agonists may disrupt sleep.
CONCLUSIONS Sleep represents a specific risk period for pulmonary diseases. The physiological changes occurring during sleep, and specifically during REM sleep, have a limited impact on healthy subjects but may severely compromise respiration during sleep in chronic respiratory disease. This may result in gas exchange perturbation due to the inability of the diaphragm to maintain ventilation during REM sleep when all other respiratory muscles are inactivated. Whether this nocturnal
SLEEP AND PULMONARY DISEASES desaturation has an impact per se on prognosis in COPD is less clear. Treatments should anyway be adjusted in order to prevent nocturnal desaturation and in specific cases full sleep studies will be required, although, in most cases, simplified studies are sufficient. Oxygen therapy during at least 15/24 hours is the best validated treatment, particularly with respect to survival. In COPD with daytime hypercapnia, however, there is sufficient evidence to propose NIV. In restrictive or neuromuscular disorders, sleep abnormalities are common and seem to contribute significantly to daytime hypercapnia. NIV is usually the treatment of choice.
REFERENCES Alford NJ, Fletcher EC, Nickeson D (1986). Acute oxygen in patients with sleep apnea and COPD. Chest 89: 30–38. American Thoracic Society (1995). Standards for the diagnosis and care of patients with chronic obstructive pulmonary disease. Am J Respir Crit Care Med 152: S77–S121. Arnulf I, Similowski T, Salachas F et al. (2000). Sleep disorders and diaphragmatic function in patients with amyotrophic lateral sclerosis. Am J Respir Crit Care Med 161: 849–856. Ballard RD, Clover CW, Suh BY (1995). Influence of sleep on respiratory function in emphysema. Am J Respir Crit Care Med 151: 945–951. Ballard RD, Sutarik JM, Clover CW et al. (1996). Effects of non-REM sleep on ventilation and respiratory mechanics in adults with cystic fibrosis. Am J Respir Crit Care Med 153: 266–271. Barbe F, Quera-Salva M, de Lattre J et al. (1996). Long-term effects of nasal intermittent positive-pressure ventilation on pulmonary function and sleep architecture in patients with neuromuscular diseases. Chest 110: 1179–1183. Barr RG, Mesia-Vela S, Austin JH et al. (2007). Impaired flow-mediated dilation is associated with low pulmonary function and emphysema in ex-smokers: the Emphysema and Cancer Action Project (EMCAP) Study. Am J Respir Crit Care Med 176: 1200–1207. Becker HF, Piper AJ, Flynn WE et al. (1999). Breathing during sleep in patients with nocturnal desaturation. Am J Respir Crit Care Med 159: 112–118. Bellville JW, Howland WS, Seed JC et al. (1959). The effect of sleep on the respiratory response to carbon dioxide. Anesthesiology 20: 628–634. Berry RB, Desa MM, Branum JP et al. (1991). Effect of theophylline on sleep and sleep-disordered breathing in patients with chronic obstructive pulmonary disease. Am Rev Respir Dis 143: 245–250. Berthon-Jones M, Sullivan CE (1982). Ventilatory and arousal responses to hypoxia in sleeping humans. Am Rev Respir Dis 125: 632–639. Berthon-Jones M, Sullivan CE (1984). Ventilation and arousal responses to hypercapnia in normal sleeping humans. J Appl Physiol 57: 59–67.
483
Bradley TD, Day A, Hyland RH et al. (1984). Chronic ventilatory failure caused by abnormal respiratory pattern generation during sleep. Am Rev Respir Dis 130: 678–681. Bradley S, Solin P, Wilson J et al. (1999). Hypoxemia and hypercapnia during exercise and sleep in patients with cystic fibrosis. Chest 116: 647–654. Brezinova V, Catterall JR, Douglas NJ et al. (1982). Night sleep of patients with chronic ventilatory failure and age matched controls: number and duration of the EEG episodes of intervening wakefulness and drowsiness. Sleep 5: 123–130. Brown NMT, Marino WD (1984). Effective daily intermittent rest of respiratory muscles in patients with severe chronic airflow limitation. Chest 85: 59S–60S. Bulow K (1963). Respiration and wakefulness in man. Acta Physiol Scand 59 (Suppl 209): 1–110. Bye PT, Issa F, Berthon-Jones M et al. (1984). Studies of oxygenation during sleep in patients with interstitial lung disease. Am Rev Respir Dis 129: 27–32. Bye PT, Ellis ER, Issa FG et al. (1990). Respiratory failure and sleep in neuromuscular disease. Thorax 45: 241–247. Calverley PM, Brezinova V, Douglas NJ et al. (1982). The effect of oxygenation on sleep quality in chronic bronchitis and emphysema. Am Rev Respir Dis 126: 206–210. Catterall JR, Douglas NJ, Calverley PM et al. (1982). Irregular breathing and hypoxaemia during sleep in chronic stable asthma. Lancet 1: 301–304. Catterall JR, Calverley PM, MacNee W et al. (1985). Mechanism of transient nocturnal hypoxemia in hypoxic chronic bronchitis and emphysema. J Appl Physiol 59: 1698–1703. Chaouat A, Weitzenblum E, Krieger J et al. (1995). Association of chronic obstructive pulmonary disease and sleep apnea syndrome. Am J Respir Crit Care Med 151: 82–86. Chaouat A, Weitzenblum E, Kessler R et al. (1997). Sleeprelated O2 desaturation and daytime pulmonary haemodynamics in COPD patients with mild hypoxaemia. Eur Respir J 10: 1730–1735. Chaouat A, Weitzenblum E, Kessler R et al. (1999). A randomized trial of nocturnal oxygen therapy in chronic obstructive pulmonary disease patients. Eur Respir J 14: 1002–1008. Chaouat A, Weitzenblum E, Kessler R et al. (2001). Outcome of COPD patients with mild daytime hypoxaemia with or without sleep-related oxygen desaturation. Eur Respir J 17: 848–855. Cirignotta F, Mondini S, Zucconi M et al. (1987). Sleeprelated breathing impairment in myotonic dystrophy. J Neurol 235: 80–85. Clark M, Cooper B, Singh S et al. (2001). A survey of nocturnal hypoxaemia and health related quality of life in patients with cryptogenic fibrosing alveolitis. Thorax 56: 482–486. Coccagna G, Lugaresi E (1978). Arterial blood gases and pulmonary and systemic arterial pressure during sleep in chronic obstructive pulmonary disease. Sleep 1: 117–124. Connaughton JJ, Douglas NJ, Morgan AD et al. (1985). Almitrine improves oxygenation when both awake and
484
R. TAMISIER ET AL.
asleep in patients with hypoxia and carbon dioxide retention caused by chronic bronchitis and emphysema. Am Rev Respir Dis 132: 206–210. Connaughton JJ, Catterall JR, Elton RA et al. (1988). Do sleep studies contribute to the management of patients with severe chronic obstructive pulmonary disease? Am Rev Respir Dis 138: 341–344. Consensus Conference Report (1999). Clinical indications for noninvasive positive pressure ventilation in chronic respiratory failure due to restrictive lung disease, COPD, and nocturnal hypoventilation. Chest 116: 521–534. Cropp A, DiMarco AF (1987). Effects of intermittent negative pressure ventilation on respiratory muscle function in patients with severe chronic obstructive pulmonary disease. Am Rev Respir Dis 135: 1056–1061. Dahlstrom U (2005). Frequent non-cardiac comorbidities in patients with chronic heart failure. Eur J Heart Fail 7: 309–316. Dancey DR, Tullis ED, Heslegrave R et al. (2002). Sleep quality and daytime function in adults with cystic fibrosis and severe lung disease. Eur Respir J 19: 504–510. Daskalopoulou E, Patakas D, Tsara V et al. (1990). Comparison of almitrine bismesylate and medroxyprogesterone acetate on oxygenation during wakefulness and sleep in patients with chronic obstructive lung disease. Thorax 45: 666–669. Davis JN, Loh L (1979). Alveolar hypoventilation and respiratory muscle weakness. Bull Eur Physiopathol Respir 15 (Suppl): 45–53. De Olazabal JR, Miller MJ, Cook WR et al. (1982). Disordered breathing and hypoxia during sleep in coronary artery disease. Chest 82: 548–552. Desager KN, Nelen V, Weyler JJJ et al. (2005). Sleep disturbance and daytime symptoms in wheezing school-aged children. J Sleep Res 14: 77–82. Dolly FR, Block AJ (1983). Medroxyprogesterone acetate and COPD. Effect on breathing and oxygenation in sleeping and awake patients. Chest 84: 394–398. Douglas NJ (2000). Asthma. In: MH Kryger, T Roth, WC Dement (Eds.), Principles and Practice of Sleep Medicine. 3rd edn. WB Saunders, Philadelphia, pp. 955–964. Douglas NJ, Flenley DC (1990). Breathing during sleep in patients with obstructive lung disease. Am Rev Respir Dis 141: 1055–1070. Douglas NJ, Calverley PM, Leggett RJ et al. (1979). Transient hypoxaemia during sleep in chronic bronchitis and emphysema. Lancet 1: 1–4. Douglas NJ, White DP, Pickett CK et al. (1982a). Respiration during sleep in normal man. Thorax 37: 840–844. Douglas NJ, White DP, Weil JV et al. (1982b). Hypoxic ventilatory response decreases during sleep in normal men. Am Rev Respir Dis 125: 286–289. Douglas NJ, White DP, Weil JV et al. (1982c). Hypercapnic ventilatory response in sleeping adults. Am Rev Respir Dis 126: 758–762. Ebden P, Vathenen AS (1987). Does aminophylline improve nocturnal hypoxia in patients with chronic airflow obstruction? Eur J Respir Dis 71: 384–387.
Ekici A, Ekici M, Kurtipek E et al. (2005). Association of asthma-related symptoms with snoring and apnea and effect on health-related quality of life. Chest 128: 3358–3363. Elliott MW, Aquilina R, Green M et al. (1994). A comparison of different modes of noninvasive ventilatory support: effects on ventilation and inspiratory muscle effort. Anaesthesia 49: 279–283. Fitzpatrick MF, Mackay T, Whyte KF et al. (1993). Nocturnal desaturation and serum erythropoietin: a study in patients with chronic obstructive pulmonary disease and in normal subjects. Clin Sci (Lond) 84: 319–324. Fleetham JA, Mezon B, West P et al. (1980). Chemical control of ventilation and sleep arterial oxygen desaturation in patients with COPD. Am Rev Respir Dis 122: 583–589. Fleetham J, West P, Mezon B et al. (1982). Sleep, arousals, and oxygen desaturation in chronic obstructive pulmonary disease. The effect of oxygen therapy. Am Rev Respir Dis 126: 429–433. Fletcher EC, Levin DC (1984). Cardiopulmonary hemodynamics during sleep in subjects with chronic obstructive pulmonary disease. The effect of short- and long-term oxygen. Chest 85: 6–14. Fletcher EC, Gray BA, Levin DC (1983). Nonapneic mechanisms of arterial oxygen desaturation during rapid-eye-movement sleep. J Appl Physiol 54: 632–639. Fletcher EC, Miller J, Divine GW et al. (1987). Nocturnal oxyhemoglobin desaturation in COPD patients with arterial oxygen tensions above 60 mm Hg. Chest 92: 604–608. Fletcher EC, Luckett RA, Miller T et al. (1989). Pulmonary vascular hemodynamics in chronic lung disease patients with and without oxyhemoglobin desaturation during sleep. Chest 95: 757–764. Fletcher EC, Lesske J, Qian W et al. (1992a). Repetitive, episodic hypoxia causes diurnal elevation of blood pressure in rats. Hypertension 19: 555–561. Fletcher EC, Luckett RA, Goodnight-White S et al. (1992b). A double-blind trial of nocturnal supplemental oxygen for sleep desaturation in patients with chronic obstructive pulmonary disease and a daytime pao2 above 60 mm Hg. Am Rev Respir Dis 145: 1070–1076. Fletcher EC, Donner CF, Midgren B et al. (1992c). Survival in COPD patients with a daytime PaO2 greater than 60 mm Hg with and without nocturnal oxyhemoglobin desaturation. Chest 101: 649–655. Flick MR, Block AJ (1979). Nocturnal vs diurnal cardiac arrhythmias in patients with chronic obstructive pulmonary disease. Chest 75: 8–11. Girault C, Muir JF, Mihaltan F et al. (1996). Effects of repeated administration of zolpidem on sleep, diurnal and nocturnal respiratory function, vigilance, and physical performance in patients with COPD. Chest 110: 1203–1211. Goldstein RS, Ramcharan V, Bowes G et al. (1984). Effect of supplemental nocturnal oxygen on gas exchange in patients with severe obstructive lung disease. N Engl J Med 310: 425–429. Gothe B, Altose MD, Goldman MD et al. (1981). Effect of quiet sleep on resting and CO2-stimulated breathing in humans. J Appl Physiol 50: 724–730.
SLEEP AND PULMONARY DISEASES Gothe B, Goldman MD, Cherniack NS et al. (1982). Effect of progressive hypoxia on breathing during sleep. Am Rev Respir Dis 126: 97–102. Gothe B, Cherniack NS, Bachand RT Jr et al. (1988). Longterm effects of almitrine bismesylate on oxygenation during wakefulness and sleep in chronic obstructive pulmonary disease. Am J Med 84: 436–444. Gould GA, Gugger M, Molloy J et al. (1988). Breathing pattern and eye movement density during REM sleep in humans. Am Rev Respir Dis 138: 874–877. Heijdra YF, Dekhuijzen PN, van Herwaarden CL et al. (1996). Nocturnal saturation improves by target-flow inspiratory muscle training in patients with COPD. Am J Respir Crit Care Med 153: 260–265. Howard P (1989). Hypoxia, almitrine, and peripheral neuropathy. Thorax 44: 247–250. Hudgel DW, Martin RJ, Capehart M et al. (1983). Contribution of hypoventilation to sleep oxygen desaturation in chronic obstructive pulmonary disease. J Appl Physiol 55: 669–677. Hudgel DW, Martin RJ, Johnson B et al. (1984). Mechanics of the respiratory system and breathing pattern during sleep in normal humans. J Appl Physiol 56: 133–137. Jankelowitz L, Reid KJ, Wolfe L et al. (2005). Cystic fibrosis patients have poor sleep quality despite normal sleep latency and efficiency. Chest 127: 1593–1599. Jardim J, Farkas G, Prefaut C et al. (1981). The failing inspiratory muscles under normoxic and hypoxic conditions. Am Rev Respir Dis 124: 274–279. John M, Hoernig S, Doehner W et al. (2005). Anemia and inflammation in COPD. Chest 127: 825–829. Jones SE, Packham S, Hebden M et al. (1998). Domiciliary nocturnal intermittent positive pressure ventilation in patients with respiratory failure due to severe COPD: long-term follow up and effect on survival. Thorax 53: 495–498. Juan G, Calverley P, Talamo C et al. (1984). Effect of carbon dioxide on diaphragmatic function in human beings. N Engl J Med 310: 874–879. Koo KW, Sax DS, Snider GL (1975). Arterial blood gases and pH during sleep in chronic obstructive pulmonary disease. Am J Med 58: 663–670. Kornbluth RS, Turino GM (1980). Respiratory control in diffuse interstitial lung disease and diseases of the pulmonary vasculature. Clin Chest Med 1: 91–102. Krachman SL, Chatila W, Martin UJ et al. (2005). Effects of lung volume reduction surgery on sleep quality and nocturnal gas exchange in patients with severe emphysema. Chest 128: 3221–3228. Krieger J, Turlot JC, Mangin P et al. (1983). Breathing during sleep in normal young and elderly subjects: hypopneas, apneas, and correlated factors. Sleep 6: 108–120. Leger P, Bedicam JM, Cornette A et al. (1994). Nasal intermittent positive pressure ventilation. Long-term follow-up in patients with severe chronic respiratory insufficiency. Chest 105: 100–105. Leitch AG, Clancy LJ, Leggett RJ et al. (1976). Arterial blood gas tensions, hydrogen ion, and electroencephalogram
485
during sleep in patients with chronic ventilatory failure. Thorax 31: 730–735. Levi-Valensi P, Aubry P, Rida Z (1990). Nocturnal hypoxemia and long-term oxygen therapy in COPD patients with daytime PaO2 60–70 mmHg. Lung 168 (Suppl): 770–775. Levy RD, Bradley TD, Newman SL et al. (1989). Negative pressure ventilation. Effects on ventilation during sleep in normal subjects. Chest 95: 95–99. Levy PA, Guilleminault C, Fagret D et al. (1991). Changes in left ventricular ejection fraction during REM sleep and exercise in chronic obstructive pulmonary disease and sleep apnoea syndrome. Eur Respir J 4: 347–352. Lin CC (1996). Comparison between nocturnal nasal positive pressure ventilation combined with oxygen therapy and oxygen monotherapy in patients with severe COPD. Am J Respir Crit Care Med 154: 353–358. Lopes JM, Tabachnik E, Muller NL et al. (1983). Total airway resistance and respiratory muscle activity during sleep. J Appl Physiol 54: 773–777. Lugaresi E, Coccagna G, Cirignotta F et al. (1978). Breathing during sleep in man in normal and pathological conditions. Adv Exp Med Biol 99: 35–45. McAllister DA, Maclay JD, Mills NL et al. (2007). Arterial stiffness is independently associated with emphysema severity in patients with chronic obstructive pulmonary disease. Am J Respir Crit Care Med 176: 1208–1214. McKeon JL, Murree-Allen K, Saunders NA (1988). Prediction of oxygenation during sleep in patients with chronic obstructive lung disease. Thorax 43: 312–317. McNicholas WT, Coffey M, Fitzgerald MX (1986). Ventilation and gas exchange during sleep in patients with interstitial lung disease. Thorax 41: 777–782. Mansfield D, Naughton MT (1999). Effects of continuous positive airway pressure on lung function in patients with chronic obstructive pulmonary disease and sleep disordered breathing. Respirology 4: 365–370. Martin RJ, Bartelson BL, Smith P et al. (1999). Effect of ipratropium bromide treatment on oxygen saturation and sleep quality in COPD. Chest 115: 1338–1345. Medical Research Council Working Party (1981). Long term domiciliary oxygen therapy in chronic hypoxic cor pulmonale complicating chronic bronchitis and emphysema. Lancet 1: 681–686. Meecham Jones DJ, Wedzicha JA (1993). Comparison of pressure and volume preset nasal ventilator systems in stable chronic respiratory failure. Eur Respir J 6: 1060–1064. Meecham Jones DJ, Paul EA, Jones PW et al. (1995). Nasal pressure support ventilation plus oxygen compared with oxygen therapy alone in hypercapnic COPD. Am J Respir Crit Care Med 152: 538–544. Mellies U, Ragette R, Dohna Schwake C et al. (2003). Longterm noninvasive ventilation in children and adolescents with neuromuscular disorders. Eur Respir J 22: 631–636. Mezon BL, West P, Israels J et al. (1980). Sleep breathing abnormalities in kyphoscoliosis. Am Rev Respir Dis 122: 617–621. Mezzanotte WS, Tangel DJ, Fox AM et al. (1994). Nocturnal nasal continuous positive airway pressure in patients with
486
R. TAMISIER ET AL.
chronic obstructive pulmonary disease. Influence on waking respiratory muscle function. Chest 106: 1100–1108. Midgren B (1990). Oxygen desaturation during sleep as a function of the underlying respiratory disease. Am Rev Respir Dis 141: 43–46. Mills NL, Miller JJ, Anand A et al. (2008). Increased arterial stiffness in patients with chronic obstructive pulmonary disease; a mechanism for increased cardiovascular risk. Thorax 63: 306–311. Milross MA, Piper AJ, Norman M et al. (2001a). Low-flow oxygen and bilevel ventilatory support. Effects on ventilation during sleep in cystic fibrosis. Am J Respir Crit Care Med 163: 129–134. Milross MA, Piper AJ, Norman M et al. (2001b). Predicting sleep-disordered breathing in patients with cystic fibrosis. Chest 120: 1239–1245. Muller NL, Francis PW, Gurwitz D et al. (1980). Mechanism of hemoglobin desaturation during rapid-eye-movement sleep in normal subjects and in patients with cystic fibrosis. Am Rev Respir Dis 121: 463–469. Mulloy E, McNicholas WT (1993). Theophylline improves gas exchange during rest, exercise, and sleep in severe chronic obstructive pulmonary disease. Am Rev Respir Dis 148: 1030–1036. Mulloy E, McNicholas WT (1996). Ventilation and gas exchange during sleep and exercise in severe COPD. Chest 109: 387–394. Nizet TAC, van den Elshout FJJ, Heijdra YF et al. (2005). Survival of chronic hypercapnic COPD patients is predicted by smoking habits, comorbidity, and hypoxemia. Chest 127: 1904–1910. Nocturnal Oxygen Therapy Trial Group (1980). Continuous or nocturnal oxygen therapy in hypoxemic chronic obstructive lung disease: a clinical trial. Ann Intern Med 93: 391–398. Orem J (1980). Medullary respiratory neuron activity: relationship to tonic and phasic REM sleep. J Appl Physiol 48: 54–65. Pe´pin JL, Le´vy P, Lepaulle B et al. (1989). [Development of nocturnal desaturation in 35 patients with chronic obstructive bronchopneumopathy (COBP). Relation to functional and hemodynamic data.] Rev Mal Respir 6: 357–364. Perez-Padilla R, West P, Lertzman M et al. (1985). Breathing during sleep in patients with interstitial lung disease. Am Rev Respir Dis 132: 224–229. Phillipson EA (1978). Control of breathing during sleep. Am Rev Respir Dis 118: 909–939. Phillipson EA, Bowes G (1986). Control of breathing during sleep. In: Handbook of Physiology Section 3, The Respiratory System. Part 2: Control of Breathing. Vol. 2. American Physiological Society, Bethesda, MD, pp. 649–690. Pierce AK, Jarrett CE, Werkle G Jr et al. (1966). Respiratory function during sleep in patients with chronic obstructive lung disease. J Clin Invest 45: 631–636. Plywaczewski R, Sliwinski P, Nowinski A et al. (2000). Incidence of nocturnal desaturation while breathing oxygen
in COPD patients undergoing long-term oxygen therapy. Chest 117: 679–683. Robin ED (1958). Some interrelations between sleep and disease. AMA Arch Intern Med 102: 669–675. Robin ED, Whaley RD, Crump CH et al. (1958). Alveolar gas tensions, pulmonary ventilation and blood pH during physiologic sleep in normal subjects. J Clin Invest 37: 981–989. Rodenstein DO, Levy P (1999). To sleep, perchance to leak. Eur Respir J 14: 1241–1243. Sabit R, Bolton CE, Edwards PH et al. (2007). Arterial stiffness and osteoporosis in chronic obstructive pulmonary disease. Am J Respir Crit Care Med 175: 1259–1265. Sanders MH, Newman AB, Haggerty CL et al. (2003). Sleep and sleep-disordered breathing in adults with predominantly mild obstructive airway disease. Am J Respir Crit Care Med 167: 7–14. Sawicka EH, Branthwaite MA (1987). Respiration during sleep in kyphoscoliosis. Thorax 42: 801–808. Series F, Cormier Y (1990). Effects of protriptyline on diurnal and nocturnal oxygenation in patients with chronic obstructive pulmonary disease. Ann Intern Med 113: 507–511. Shepard JW Jr., Schweitzer PK, Keller CA et al. (1984). Myocardial stress. Exercise versus sleep in patients with COPD. Chest 86: 366–374. Skatrud JB, Dempsey JA (1983). Relative effectiveness of acetazolamide versus medroxyprogesterone acetate in correction of chronic carbon dioxide retention. Am Rev Respir Dis 127: 405–412. Skatrud JB, Dempsey JA (1985). Airway resistance and respiratory muscle function in snorers during NREM sleep. J Appl Physiol 59: 328–335. Skatrud J, Iber C, McHugh W et al. (1980). Determinants of hypoventilation during wakefulness and sleep in diaphragmatic paralysis. Am Rev Respir Dis 121: 587–593. Smith PE, Calverley PM, Edwards RH (1988). Hypoxemia during sleep in Duchenne muscular dystrophy. Am Rev Respir Dis 137: 884–888. Smith PE, Edwards RH, Calverley PM (1989). Ventilation and breathing pattern during sleep in Duchenne muscular dystrophy. Chest 96: 1346–1351. Stradling JR, Lane DJ (1983). Nocturnal hypoxaemia in chronic obstructive pulmonary disease. Clin Sci (Lond) 64: 213–222. Stradling JR, Chadwick GA, Frew AJ (1985). Changes in ventilation and its components in normal subjects during sleep. Thorax 40: 364–370. Stradling JR, Kozar LF, Dark J et al. (1987). Effect of acute diaphragm paralysis on ventilation in awake and sleeping dogs. Am Rev Respir Dis 136: 633–637. Teschler H, Stampa J, Ragette R et al. (1999). Effect of mouth leak on effectiveness of nasal bilevel ventilatory assistance and sleep architecture. Eur Respir J 14: 1251–1257. Trask CH, Cree EM (1962). Oximeter studies on patients with chronic obstructive emphysema, awake and during sleep. N Engl J Med 266: 639–642.
SLEEP AND PULMONARY DISEASES Tuggey JM, Elliott MW (2005). Randomised crossover study of pressure and volume non-invasive ventilation in chest wall deformity. Thorax 60: 859–864. Tusiewicz K, Moldofsky H, Bryan AC et al. (1977). Mechanics of the rib cage and diaphragm during sleep. J Appl Physiol 43: 600–602. Vazquez JC, Perez-Padilla R (2001). Effect of oxygen on sleep and breathing in patients with interstitial lung disease at moderate altitude. Respiration 68: 584–589. Veale D, Chailleux E, Taytard A et al. (1998). Characteristics and survival of patients prescribed long-term oxygen therapy outside prescription guidelines. Eur Respir J 12: 780–784. Wedzicha JA, Cotes PM, Empey DW et al. (1985). Serum immunoreactive erythropoietin in hypoxic lung disease with and without polycythaemia. Clin Sci (Lond) 69: 413–422. Weitzenblum E, Chaouat A (2004). Sleep and chronic obstructive pulmonary disease. Sleep Med Rev 8: 281–294. Weitzenblum E, Krieger J, Oswald M et al. (1992). Chronic obstructive pulmonary disease and sleep apnea syndrome. Sleep 15: S33–S35.
487
White DP, Douglas NJ, Pickett CK et al. (1982). Hypoxic ventilatory response during sleep in normal premenopausal women. Am Rev Respir Dis 126: 530–533. White DP, Weil JV, Zwillich CW (1985). Metabolic rate and breathing during sleep. J Appl Physiol 59: 384–391. Whyte KF, Gugger M, Gould GA et al. (1991). Accuracy of respiratory inductive plethysmograph in measuring tidal volume during sleep. J Appl Physiol 71: 1866–1871. Wiegand L, Mende CN, Zaidel G et al. (1999). Salmeterol vs theophylline: sleep and efficacy outcomes in patients with nocturnal asthma. Chest 115: 1525–1532. Wynne JW, Block AJ, Hemenway J et al. (1978). Disordered breathing and oxygen desaturation during sleep in patients with chronic obstructive pulmonary disease. Chest 73: 301–303. Young AC, Wilson J, Kotsimbos T et al. (2008). Randomised placebo-controlled trial of non-invasive ventilation for hypercapnia in cystic fibrosis. Thorax 63: 72–77.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 32
Sleep-associated respiratory disorders and their psychobehavioral consequences in children 1 2
HAWLEY E. MONTGOMERY-DOWNS 1 AND DAVID GOZAL 2 * Departments of Psychology and Pediatrics, West Virginia University, Morgantown, WV, USA
Department of Pediatrics, Comer Children’s Hospital, The University of Chicago, Chicago, IL, USA
SLEEP DISTURBANCES IN CHILDREN Pediatric sleep continues to gain significant recognition due to both increasing evidence of a high prevalence of sleep disorders among children, and by virtue of the potential somatic and psychobehavioral effects of disrupted sleep during early development. Obstructive sleep apnea (OSA) is by far the most frequently diagnosed pediatric sleep disorder, affecting at least 1–3% of children, while symptoms consistent with risk for sleep-disordered breathing (SDB) have been reported in 6–27% of children (Brouillette et al., 1984; Ali et al., 1993; Gislason and Benediktsdottir, 1995; Hulcrantz et al., 1995; Archbold et al., 2002; Young et al., 2002; Montgomery-Downs et al., 2003). Children with SDB experience more frequent pulmonary hypertension (Shiomi et al., 1993), systemic hypertension, and other cardiovascular disturbances such as left ventricular hypertrophy (Marcus et al., 1998; Amin et al., 2002, 2005; O’Brien and Gozal, 2005), deficient somatic growth (Everett et al., 1987), and comorbid chronic illnesses (Rona et al., 1998; Archbold et al., 2002). In addition, pediatric OSA is associated with poor quality of life (Rosen et al., 2002; Crabtree et al., 2004; Mitchell and Kelly, 2005; Stewart et al., 2005), depressed mood (Crabtree et al., 2004; Mitchell and Kelly, 2006), and increased health care utilization (Reuveni et al., 2002; Tarasiuk et al., 2004). For the majority of children with mild to moderate SDB, psychobehavioral comorbidities are understood to be the most crucial consequence. Studies on these specific costs have focused on the daytime effects of
sleep restriction and sleep-related breathing disorders (e.g., snoring and OSA), which are also associated with both intermittent hypoxia and sleep fragmentation. The consequences of disrupted sleep specific to the effects of sleep-associated respiratory disorders will form the specific focus of this review.
Sleepiness The predominant manifestation of sleeplessness or sleep disturbance is “sleepiness” and thus it is important first to address what is meant by this sometimes ambiguous term. Originally described by Carskadon and Dement (1977), one objective technique used to quantify sleepiness is the Multiple Sleep Latency Test (MSLT). This simple method involves a series of 20–30-minute polysomnographically recorded daytime nap opportunities in a sleep-promoting environment (i.e., darkened and quiet room, comfortable bed and temperature). Under such standardized circumstances, the shorter the latency to sleep onset during these nap opportunities, the higher the degree of sleepiness. Such assessment is expensive, labor-intensive, and difficult with children so rare studies have objectively measured daytime sleepiness in children, though it has been found that compared to control children, those with attention deficit hyperactivity disorder (ADHD) have greater daytime sleepiness (Golan et al., 2004). Like studies with adults, for sleepiness measured by MSLT with children there seems to be a limited relationship with subjective report (Chervin et al., 2006a). However, it is important to note that
*Correspondence to: David Gozal, M.D., Herbert T. Abelson Distinguished Professor and Chair, Department of Pediatrics, Physician-in-Chief, Comer Children’s Hospital, The University of Chicago, 5721 S. Maryland Avenue, MC 8000, Suite K-160, Chicago, IL 60637, USA. Tel: (773) 702-3360, Fax: (773) 702-4523, E-mail:
[email protected]
490 H.E. MONTGOMERY-DOWNS AND D. GOZAL behavioral sleepiness may display differently in chilbehavioral problems (Lavigne et al., 1999), and the dren than it does in adults. The manifestations of reciprocal of this observation holds true as well, since sleepiness in children will be discussed throughout this improvements in sleep are associated with improvereview. ment in daytime behavior (Minde et al., 1994; Ali et al., 1996; Chervin et al., 2006a). Thus, sleep and behavior exhibit dynamic interacBEHAVIORAL CONSEQUENCES tions that may either interfere with each other or synerOF SLEEP DISTURBANCE gistically enhance each other in children. In order to When sleep fragmentation is experimentally induced in understand further the potential impact of SDB on healthy adults using auditory stimuli to elicit arousals cognitive and behavioral functioning it is necessary to throughout the night, performance detriments are understand that hypoxia is unlikely to occur in isolaclearly apparent the following day (Stepansky et al., tion. Rather, SDB is typified by the co-occurrence of 1984, 1987; Chugh et al., 1996). In this context, cogniintermittent hypoxia and brief arousals that cause fragtive functions requiring concentration and motor mented architecture. Therefore, a short review of the dexterity are preferentially affected by sleep fragmeneffects of sleep restriction on higher-level functioning tation and often confusion and disorientation also in children is appropriate. occur, and have led to the term “sleep drunkenness.” Aggressive outbursts, irritability, anxiety, and depresSleep restriction sion are all known manifestations of excessive daytime Acute sleep restriction for one night in children has sleepiness in adults, and appear to be fully reversed been shown to increase inattentive behavior the followonce sleep is allowed and recovery occurs (for review, ing day, although without changes in hyperactive or see Roth and Roehrs, 1996). impulsive behaviors (Fallone et al., 2001). Extended Similar to adult findings, Sadeh and colleagues sleep restriction for 7 nights led to increased parent(2000) reported a high prevalence of sleep fragmentareported oppositional and inattentive behaviors tion in children but the effects of sleep fragmentation (Fallone et al., 2000) and teacher-reported academic on daytime functioning have yet to be examined in problems and attention problems (Fallone et al., detail among pediatric populations. It is known that 2005). Notwithstanding such observations, total sleep infants, toddlers, and school-age children who are time does not appear to be the major determinant of reported by their parents to be poor sleepers display daytime behavior problems in children. Rather, disrupincreased incidence and severity of behavioral issues tion of the sleep process instead of total amount of compared to children without reported sleep problems sleep may be the key factor underlying behavioral (Zuckerman et al., 1987; Ali et al., 1993, 1994; Minde alterations that are vulnerable to sleep disruption et al., 1993; Chervin et al., 1997; Stein et al., 2001). (Stores, 1996). Thus, an association between neuroThese observations have been confirmed by objective behavioral disturbances and the fragmentation by assessments, in which the degree of sleep disturbance multiple arousals observed in OSA or in periodic limb and the severity of behavioral changes are strongly movement disorder of sleep would be expected. To associated in most studies (Guilleminault et al., 1981; corroborate this supposition, a study from our laboraAli et al., 1996; Aronen et al., 2000; Chervin et al., tory found significant relationships between arousals 2000; Chervin and Archbold, 2001; O’Brien et al., associated with periodic limb movements during sleep 2003). However, work by Chervin and colleagues and ADHD (Crabtree et al., 2003). Thus, an associative (2006a) showed that, although adenotonsillectomy and possibly causal link appears to be present between improved neurobehavioral and parent report measures fragmented sleep and hyperactive behaviors. of hyperactivity to the extent that children no longer Developmental changes during adolescence also differed from controls (who did not change), neither afford an opportunity to examine the effects of sleep baseline SDB measures nor improvement predicted restriction. It has been clear for some time that both the degree of improvement on any outcome measure homeostatic influences (e.g., the time elapsed since the other than sleepiness. previous sleep period and circadian clock regulatory sysNevertheless, 36% of young children with global tems), and individual differences (e.g., motivation to fall reports of sleep problems presented with significant asleep and psychological tension or anxiety) affect daybehavioral problems (Smedje et al., 2001) and daytime time sleepiness in this age group. Extensive work by hyperactivity, and anxiety and depressive symptoms Carskadon and colleagues has shown that pubertal have been associated with prolonged sleep latency development is associated with increased daytime sleep(Smedje et al., 2001; Stein et al., 2001). Preschool chiliness, such that postpubertal adolescents require more dren with shorter total sleep time exhibited more
SLEEP-ASSOCIATED RESPIRATORY DISORDERS IN CHILDREN 491 sleep to retain prepubertal levels of alertness (Carskadon looking” and slow to respond to questions, yet it took et al., 1980; Carskadon and Dement, 1987). a century before Osler’s observations on neurocognitive The Carskadon lab has established that there is a decrements in pediatric OSA were investigated using biological shift in the homeostatic drive during adolesobjective methodology. Of particular emphasis is the fact cence, inhibiting later-stage pubertal adolescents’ ability that OSA in children is radically distinct from the OSA to obtain sleep early in the night (Jenni et al., 2005). that occurs in adults, and such differences are particuDespite the physiological evidence, school start times larly striking in relation to racial and gender distriin the USA and many countries around the world are bution, clinical manifestations, and treatment (Carroll organized so that secondary school students have to and McLoughlin, 1992; Rosen et al., 1992). wake up earlier than primary school students, an In children, OSA is frequently diagnosed in associaarrangement that appears in paradox with the biological tion with adenotonsillar hypertrophy, and is common in preferences for later bed and wake-up times during the children with craniofacial abnormalities and neurologimore advanced stages of puberty (Carskadon et al., cal disorders affecting upper-airway patency during 1993; Jenni et al., 2005; Taylor et al., 2005). The resultsleep. In early reports, Guilleminault et al. (1976) suging sleepiness has been repeatedly shown to have an gested that removal of the enlarged adenotonsillar impact on students’ learning and behavior and, in distissue would lead to complete resolution of clinical tricts where school start times are delayed for secondary symptoms and cure of OSA. However, although students, improvements can be dramatic (for review, see enlarged tonsils and adenoids are by far the most Carskadon et al., 2004; Millman, 2005). An awareness important contributor to the pathophysiology of OSA of increased adolescent risk-taking behaviors in associain children, children with OSA also demonstrate the tion with inadequate sleep has also emerged (O’Brien presence of increased upper-airway collapsibility and Mindell, 2005). (Isono et al., 1998; Gozal and Burnside, 2004). Thus, In addition to these experimental and naturalistic adenotonsillar hypertrophy alone is usually not suffiexamples of the effects of sleep restriction on daytime cient to cause OSA; in fact, some children with sleepiness in children and adolescents, sleep disorders “kissing tonsils” will not have OSA, while others with may contribute to sleep that is inadequate, fragmented, relatively small adenotonsillar tissue will manifest or both and have been shown repeatedly to have an severe OSA and may not be cured after adenotonsiladverse impact on daytime functioning, while early lectomy (Suen et al., 1995; Lipton and Gozal, 2003). treatment often reverses these effects. Among these, Emphasis has also been placed on the importance of OSA is the most frequently diagnosed disorder and a multispecialty approach to clinical assessment and has received the greatest attention from research treatment of pediatric OSA, including sleep medicine laboratories around the world. specialists, maxillofacial and otolaryngologist surgeons, and orthodontists, particularly for patients with craniofacial abnormalities (Guilleminault and Abad, Sleep-disordered breathing 2004). Clearly, OSA is a complicated disorder, but addOSA is a more severe form of SDB, and is a relatively ing to this is the emerging perspective that OSA is only common disorder among both adults and children, with one end of a spectrum disorder. up to 3% of young children affected (Brouillette et al., The primary symptom of OSA is habitual snoring, 1984; Ali et al., 1993; Gislason and Benediktsdottir, a symptom that may affect up to 27% of children, with a 1995; Hulcrantz et al., 1995; Young et al., 2002; median revolving around 10–12% (Teculescu et al., 1992; Montgomery-Downs et al., 2003). OSA is characterAli et al., 1993; Gislason and Benediktsdottir, 1995; ized by repeated events of partial or complete upperHulcrantz et al., 1995; Owen et al., 1996; Ferreira et al., airway obstruction during sleep. These upper-airway 2000; O’Brien et al., 2003; Montgomery-Downs et al., changes induce disruption of normal alveolar ventila2003). Prevalence rates of snoring similar to those of tion and sleep structure, and lead to blood gas abnormpreschool and early school-age children have also been alities and sleep fragmentation (American Thoracic reported among infants. Indeed, habitual snoring was Society, 1995) (Figures 32.1 and 32.2). found in 5% of 2–4-month-olds (Kelmanson, 2000) and Despite the fact that OSA and its associated mani6–12-month-olds (Gislason and Benediktsdottir, 1995), festations were first described over 130 years ago with higher rates in infants aged 1–8 months (16–26%) (McKenzie, 1880; Osler, 1892), it was not until 1976 (Mitchell and Thompson, 2003). We have found habitual that Guilleminault et al. reported OSA as a clinically snoring in 1–9% of infants and toddlers (2–24 months of relevant entity in children. Furthermore, Osler (1892) age) (Montgomery-Downs and Gozal, 2006a). This relareported that children with “loud and snorting” respiratively high frequency of habitual snoring usually decreases tions with “prolonged pauses” were often “stupid in 9–14-year-olds to around 3–5% (Corbo et al., 2001).
492
H.E. MONTGOMERY-DOWNS AND D. GOZAL
Fig. 32.1. Illustrative 1-minute example of a partial upper-airway obstruction (hypopnea), with repeated reductions (OH) of oronasal airflow in the presence of respiratory efforts, and with associated oxyhemoglobin desaturation, and sleep arousal (circles). These events occurred during rapid eye movement sleep (R). EEG, electroencephalogram; ECG, electrocardiogram; Chin EMG, chin electromyogram; Snore, sound channel; Flow, airflow; Abd, abdominal respiratory effort; SaO2, oxyhemoglobin saturation.
It needs to be stressed that the presence of snoring should not be viewed as a normal feature of sleeping children, because it indicates that increased upperairway resistance is present. A substantial percentage of snoring children may have primary snoring (i.e., habitual snoring without obvious visually recognizable disruptions in sleep architecture, alveolar ventilation, and oxygenation) but despite the traditional view of primary snoring as a benign condition, our laboratory has reported that primary snoring may in fact be associated with a higher risk for neurobehavioral deficits, albeit less severe than the deficits found in children with OSA (O’Brien et al., 2003). Of note, daytime sleepiness, behavioral hyperactivity, learning problems, and restless sleep are all significantly more common in habitual snorers (Ali et al., 1993; Blunden et al., 2000; Ferreira et al., 2000; Blunden et al., 2001; Chervin et al., 2002; O’Brien et al., 2003). Another report from our lab indicates that infants with higher snore-related arousal indices had lower
scores on a standardized mental development assessment. Because neither apneas nor hypopneas were present in these otherwise normal, healthy children, these findings constitute further evidence that snoring is not just an innocent noise during sleep in infants, but may in fact represent the lower end of the disease spectrum associated with SDB (Montgomery-Downs and Gozal, 2006b). We still do not know enough about the natural history of snoring and snore-induced arousals in infancy or early childhood to disregard any snoring. Zucconi and colleagues (1993) found that, among 18–24-month-olds evaluated for nightly snoring and referred for surgical treatment, the parents of >50% reported that the habitual snoring had developed during the child’s first year of life, and 16% reported an onset in the first month of life. The consequences of snoring and OSA with their associated hypoxemia and sleep fragmentation in children reveal complex pathophysiological mechanisms (Bass et al., 2004). If left untreated or treated late,
SLEEP-ASSOCIATED RESPIRATORY DISORDERS IN CHILDREN
493
Fig. 32.2. Overnight hypnogram of an 8-year-old child with mild to moderate obstructive sleep apnea illustrating the clustering of respiratory events during rapid eye movement (REM) sleep periods (circles). PLM, periodic limb movement; A/H, apnea/ hypopnea; SaO2, oxyhemoglobin saturation.
pediatric OSA may lead to significant morbidity affecting multiple target organs and systems, and such injurious consequences may, under certain circumstances, be partially irreversible despite appropriate therapy.
PSYCHOBEHAVIORAL CONSEQUENCES OF SLEEP DISRUPTION IN SDB Behavior Both habitual snoring and OSA are associated with behavioral problems, particularly hyperactivity and ADHD (Ali et al., 1993, 1996; Chervin and Archbold, 2001). Hyperactive and inattentive behaviors occur frequently in children with OSA (Guilleminault et al., 1981; Carroll and McLoughlin, 1992; Gozal, 1998; Blunden et al., 2000) and with habitual snoring (Weissbluth et al., 1983; Ali et al., 1993; Chervin et al., 1997, 2002; Blunden et al., 2000; Chervin and Archbold, 2001; O’Brien et al., 2003). Furthermore, approximately 30% of all children with frequent, loud
snoring or OSA manifest parentally reported hyperactivity and inattentive symptoms (Ali et al., 1993), with improvements noted following surgical treatment of SDB (Ali et al., 1996; Dagan-Friedman et al., 2002; Chervin et al., 2006b; Mitchell and Kelly, 2006). Interestingly, although children with ADHD appear to exhibit more sleep disturbances than normal children (Berry et al., 1986; Trommer et al., 1988), we found that, despite parental reports of sleep disturbances in >70% of children with ADHD, only 20% of these children had sleep disturbances when assessed by objective polysomnographic criteria (O’Brien et al., 2003). In this study, SDB was not more likely to occur among children with true ADHD (i.e., diagnoses following the stringent criteria recommended by the Academy of Pediatrics and the Academy of Psychiatry), yet SDB was significantly more prevalent among children with parent-reported hyperactive behaviors that do not fulfill strict ADHD criteria, suggesting that the subtle disruptions of sleep elicited by the presence of SDB may be associated with significant behavioral effects.
494 H.E. MONTGOMERY-DOWNS AND D. GOZAL In contrast, Chervin and colleagues (2006b) found that via disruption of PFC-dependent processes (Beebe and children diagnosed with ADHD and reported by their Gozal, 2002) and this is also the foundation for a proparents to be hyperactive improved following adenoposed heuristic model for interpreting the prolific and tonsillectomy, but that severity of sleep measures dynamic research on both animal models and humans did not predict either baseline or improvement post(Beebe, 2005). The individual processes that make up surgery. As mentioned earlier, sleep fragmentation neurocognitive processes will be described separately associated with periodic limb jerks is more frequent below. in children with ADHD, thus supporting the notion that restless sleep is indeed more common in ADHD Attention patients. The ability to remain focused on a task and respond appropriately to extraneous stimuli in the environment Neurocognition plays an important role in learning, and consequently In adult patients, substantial cumulative evidence indiin social and academic development. Using acute sleep cates that neurocognitive deficits emanate from sleep restriction and sleep deprivation, Carskadon and coldisruption induced by SDB. These may include deficits leagues (1981a, b) have shown that, despite increased in attention, concentration, memory, and verbal and sleep propensity, as measured by the MSLT, no impairnonverbal intelligence (Greenberg et al., 1987; Bedard ments could be found on auditory attention, visual suset al., 1991; Naegele et al., 1995; Kim et al., 1997; tained attention, or inhibition (Fallone et al., 2001). Engleman and Joffe, 1999; Lee et al., 1999). Sleep depThese laboratory findings contradict parental and rivation exerts profound effects on cognitive function self-reports of impaired attention following acute sleep in adults, with complex tasks being more susceptible restriction. For example, children with early school to such deprivation when compared to more simple start times have reported more difficulty than their or automatic tasks (Harrison and Horne, 1998). Arnedt later-starting peers when asked to rate their level of and colleagues (2005) found that postcall performance attention and concentration abilities during school impairment during a heavy call rotation is comparable hours (Epstein et al., 1998). Sadeh and colleagues to impairment from blood alcohol concentration (2002) found no correlations between sleep schedules 0.04–0.05 g% (per 100 ml of blood) during a light call or duration and neurobehavioral functioning, and rotation, as measured by sustained attention, vigilance, Meijer and colleagues (2000) found no significant relaand simulated driving tasks. Further, adult patients tionships between subjective sleep variables such as with OSA exhibit a wide range of neurocognitive defitime in bed, quality of sleep, feeling rested, and difficits, particularly those underlying executive functionculty getting up in the morning, and performance on ing (i.e., the brain processes mediating the planning, a task of selective attention. Thus, the cumulative eviinitiation, and self-regulation of goal-oriented behadence would suggest that sleep deprivation rather than viors) (Lezak, 1995). While the literature is not as restriction is associated with more important effects on extensive in children, similar deficits in neurocognitive attention. function emerge as a result of sleep disruption. However, inattentive behavior has been reported in In the context of SDB, the magnitude and probabilchildren with OSA (Guilleminault et al., 1981, 1982) ity of neurocognitive dysfunction in children with OSA and with habitual snoring (Ali et al., 1993; Chervin are more profound than those associated with primary et al., 1997, 2002). Furthermore, a dose–response in snoring (Shiomi et al., 1993; Blunden et al., 2000; the scores obtained using attention-impulsivity scales O’Brien et al., 2003). Furthermore, hypoxemia is in the presence of OSA in children has been suggested closely correlated with deficits in executive function, (Owens-Stively et al., 1997). Blunden and colleagues whereas sleepiness is preferentially associated with (2000) also reported that children with mild SDB attention loss (Bedard et al., 1991; Naegele et al., demonstrated diminished selective and sustained atten1995). The frequently reported deficits in executive tion compared with control children. Studies from our performance in adults with SDB may emanate from laboratory further buttress the concept that children hypoxemia-induced frontal lobe dysfunction (Beebe with primary snoring (O’Brien et al., 2003) as well as and Gozal, 2002). Several groups of investigators have those with OSA (O’Brien et al., 2004a, b) are at higher posited that sleep disturbances are associated with dysrisk for deficits in attention compared to control chilfunction of the prefrontal cortex (PFC) in adults, and dren when measured on parental report scales, and that the same principles should be applicable to children such deficits are substantially improved following ade(Dahl, 1996). We have introduced a theoretical model, notonsillectomy (Guilleminault et al., 1982; Ali et al., whereby sleep apnea induces daytime cognitive deficits 1996; Owens et al., 2000; Chervin et al., 2006b).
SLEEP-ASSOCIATED RESPIRATORY DISORDERS IN CHILDREN
Memory Following acute sleep restriction, no deficits are usually apparent in word memory tasks (Carskadon et al., 1981a), yet such deficits emerge following 38 hours of sleep deprivation in a sample of similar-aged children (Carskadon et al., 1981b). Performance of a verbal memory task was unaffected by acute sleep restriction (Randazzo et al., 1998a) and 3 nights of restricted sleep in children aged 10–14 years did not suggest the presence of any deficits on a workingmemory task (Randazzo et al., 1998b). However, in children with OSA, memory performance on standardized psychometric tests is significantly affected compared with control children (Rhodes et al., 1995; Blunden et al., 2000), with children with higher respiratory disturbance indices showing greater memory deficits (Rhodes et al., 1995). These findings are not consistently reported; neither Owens-Stively and colleagues (1997) nor O’Brien and colleagues (2004a, b) found any differences in memory performance in children with varying degrees of OSA severity when compared to control children. The limited number of studies in this area and the contradictory results emphasize the need for further investigation.
Intelligence Children’s general cognitive ability appears to be unaffected by acute sleep restriction but is impaired on abstract problem-solving tests and verbal fluency (Randazzo et al., 1998a, b). Acute sleep restriction (Carskadon et al., 1981a), sleep restriction for 3 nights (Randazzo et al., 1998b), and total sleep deprivation for 38 hours (Carskadon et al., 1981b) did not lead to significant decrements on computational accuracy, although computational speed declines after total sleep deprivation. Thus, cognitive functions that require verbal creativity and abstract thinking may be more sensitive to sleep restriction in children than their visual/ imagery counterparts. In children with OSA, several studies have documented significantly reduced IQ scores (obtained from the Wechsler Intelligence Scale for Children – WISC-III) compared with control children (Rhodes et al., 1995; Blunden et al., 2000; Beebe et al., 2004). In these studies, the probability for lower normal or borderline range performance was much higher in children with SDB. We have documented significantly impaired General Conceptual Ability scores (a measure of IQ obtained from the Differential Ability Scales: DAS) in school-age (O’Brien et al., 2004a) and preschoolage (Montgomery-Downs et al., 2005) children with OSA when compared with control children. However, Ali and colleagues (1996) failed to detect any
495
differences in the short-form version of the WISC-III. Interestingly, Lewin and colleagues (2002) found an inverse relationship between the severity of OSA and verbal ability (obtained from DAS). These investigators suggested that only severe OSA is a risk factor for disruption of verbal abilities. However, this issue merits further investigation because in our extensive study the majority of children had an apnea–hypopnea index between 5 and 10, i.e., not severe OSA, and despite relatively modest level of SDB severity, the verbal abilities and overall language scores were adversely affected (O’Brien et al., 2004a). In a study of preschoolers with OSA who were prospectively screened through parental questionnaires, we were further able to show complete reversibility of cognitive deficits following timely treatment (Montgomery-Downs et al., 2005). Thus, these studies suggest that early SDB diagnosis and intervention may lead to overall favorable outcomes (Friedman et al., 2003).
Learning and school performance School problems have been reported in multiple case series of children with OSA, and such findings may underscore more extensive behavioral disturbances such as restlessness, aggressive behavior, excessive daytime sleepiness, and poor test performances (Guilleminault et al., 1981; Weissbluth et al., 1983; Ali et al., 1993, 1996; Rhodes et al., 1995; Chervin et al., 1997; Owens et al., 1998; Chervin and Archbold, 2001). Improvements in behavior emerge following treatment for OSA in children (Stradling et al., 1990; Ali et al., 1996; Gozal, 1998), suggesting that at least some of the deficits may be reversible. Epidemiological surveys in which the total amount of sleep is assessed with questionnaires have indicated that children with later, irregular bedtimes, short sleep duration, and increased daytime sleepiness have lower academic achievements than other children (Kahn et al., 1989; Wolfson and Carskadon, 1998), although such findings have not been consistent (Eliasson et al., 2002). Lower school performance has also been described in children with OSA (Guilleminault et al., 1981, 1982, 1996; Stradling et al., 1990; Carroll and McLoughlin, 1992; Richards and Ferdman, 2000) and the reciprocal has also been shown to be true, i.e., children with poor academic performance are more likely to have sleep disturbances such as snoring and breathing difficulties (Weissbluth et al., 1983; Gozal, 1998). Indeed, we found a six- to ninefold increase in the expected incidence of OSA among first-grade children who ranked in the lowest 10th percentile of their class (Gozal, 1998), and significant improvements emerged in school grades after those children with OSA were
496
H.E. MONTGOMERY-DOWNS AND D. GOZAL
effectively treated. Since the optimal intellectual ability and academic performance for these children were unknown, we cannot exclude the possibility that longterm residual deficits may be present after treatment. To examine this possibility further, we investigated the history of snoring during early childhood in two groups of 13–14-year-old children who were matched for age, gender, race, school attended, and socioeconomic status, but whose performance was either in the upper or lower quartile of their class, and found that children who snored frequently and loudly during early childhood were at greater risk for lower academic performance in later years, well after snoring had resolved (Gozal and Pope, 2001). These findings suggest that, even if the major portion of OSA-induced learning deficits is reversible, there may be long-lasting residual deficits in learning capability. The latter could represent either a “learning debt,” i.e., the decreased learning capacity during OSA may have led to such a delay in learned skills that recuperation is only possible with additional teaching assistance, or may suggest that OSA may have irreversibly altered the performance characteristics of the neuronal circuitry responsible for learning particular skills. In summary, sleep disturbance in children, whether due to poor sleep habits, developmental changes, or SDB, is accompanied by marked and obvious behavioral and neurocognitive deficits. Both sleep fragmentation and intermittent hypoxia contribute to elicit neurobehavioral morbidity in pediatric SDB. While the long-term outcome for children with untreated SDB is currently unknown, reversibility of neurobehavioral morbidities following treatment has been reported. These findings have been extended to those children with snoring, now considered the end of the SDB spectrum disorder. Increased awareness by physicians and parents and early identification and treatment of conditions leading to altered sleep and nocturnal oxygenation should lead to improved psychobehavioral outcomes in pediatric sleep-related respiratory disorders.
ACKNOWLEDGMENTS This work was supported by grants from the National Institutes of Health (HL65270 and HL69932), The Children’s Foundation Endowment for Sleep Research, and The Commonwealth of Kentucky Research Challenge Trust Fund.
REFERENCES Ali NJ, Pitson DJ, Stradling JR (1993). Snoring, sleep disturbance, and behaviour in 4–5 year olds. Arch Dis Child 68: 360–366.
Ali NJ, Pitson DJ, Stradling JR (1994). Natural history of snoring and related behaviour problems between the ages of 4 and 7 years. Arch Dis Child 71: 74–76. Ali NJ, Pitson D, Stradling JR (1996). Sleep disordered breathing: effects of adenotonsillectomy on behaviour and psychological functioning. Eur J Pediatr 155: 56–62. American Thoracic Society (1995). Standards and indications for cardiopulmonary sleep studies in children. Am J Respir Crit Care Med 153: 866–878. Amin RS, Kimball TR, Bean JA et al. (2002). Left ventricular hypertrophy and abnormal ventricular geometry in children and adolescents with obstructive sleep apnea. Am J Respir Crit Care Med 165: 1395–1399. Amin RS, Kimball TR, Kalra M et al. (2005). Left ventricular function in children with sleep-disordered breathing. Am J Cardiol 95: 801–804. Archbold KH, Pituch KJ, Panahi P et al. (2002). Symptoms of sleep disturbances among children at two general pediatrics clinics. J Pediatr 140 (1): 97–102. Arnedt JT, Owens J, Crouch M et al. (2005). Neurobehavioral performance of residents after heavy night call vs after alcohol ingestion. JAMA 294 (9): 1025–1033. Aronen ET, Paavonen EJ, Fjallberg M et al. (2000). Sleep and psychiatric symptoms in school-age children. J Am Acad Child Adolesc Psychiatry 39: 502–508. Bass JL, Corwin M, Gozal D et al. (2004). The effect of chronic or intermittent hypoxia on cognition in childhood: a systematic review of the literature. Pediatrics 114: 805–816. Bedard MA, Montplasir J, Richer F et al. (1991). Obstructive sleep apnea syndrome: pathogenesis of neuropsychological deficits. J Clin Exp Neuropsychol 13: 950–964. Beebe DW (2005). Neurobehavioral effects of obstructive sleep apnea: an overview and heuristic model. Curr Opin Pulm Med 11 (6): 494–500. Beebe DW, Gozal D (2002). Obstructive sleep apnea and the prefrontal cortex: towards a comprehensive model linking nocturnal upper airway obstruction to daytime cognitive and behavioral deficits. J Sleep Res 11: 1–16. Beebe DW, Wells CT, Jeffries J et al. (2004). Neuropsychological effects of pediatric obstructive sleep apnea. J Int Neuropsychol Soc 10: 962–975. Berry DTR, Webb WB, Block AJ et al. (1986). Nocturnal hypoxia and neuropsychological variables. J Clin Exp Neuropsychol 8: 229–238. Blunden S, Lushington K, Kennedy D et al. (2000). Behavior and neurocognitive performance in children aged 5–10 years who snore compared to controls. J Clin Exp Neuropsychol 22: 554–568. Blunden S, Lushington K, Kennedy D (2001). Cognitive and behavioral performance in children with sleep-related obstructive breathing disorders. Sleep Med Rev 5: 447–461. Brouillette R, Hanson D, David R et al. (1984). A diagnostic approach to suspected obstructive sleep apnea in children. J Pediatr 105: 10–14. Carroll JL, McLoughlin GM (1992). Diagnostic criteria for obstructive sleep apnea in children. Pediatr Pulmonol 14: 71–74.
SLEEP-ASSOCIATED RESPIRATORY DISORDERS IN CHILDREN Carskadon MA, Dement WC (1977). Sleep tendency: an objective measure of sleep loss. Sleep Res 6: 200. Carskadon MA, Dement WC (1987). Sleepiness in the normal adolescent. In: C Guilleminault (Ed.), Sleep and Its Disorders in Children. Raven Press, New York, pp. 53–66. Carskadon MA, Harvey K, Duke P et al. (1980). Pubertal changes in daytime sleepiness. Sleep 2: 453–460. Carskadon MA, Harvey K, Dement WC (1981a). Sleep loss in young adolescents. Sleep 4: 299–312. Carskadon MA, Harvey K, Dement WC (1981b). Acute restriction of nocturnal sleep in children. Percept Mot Skills 53: 103–112. Carskadon MA, Viera C, Acebo C (1993). Association between puberty and delayed phase preference. Sleep 16: 258–262. Carskadon MA, Acebo C, Jenni OG (2004). Regulation of adolescent sleep: implications for behavior. Ann N Y Acad Sci 1021: 276–291. Chervin RD, Archbold KH (2001). Hyperactivity and polysomnographic findings in children evaluated for sleep-disordered breathing. Sleep 24: 313–320. Chervin R, Dillon J, Bassetti C et al. (1997). Symptoms of sleep disorders, inattention, and hyperactivity in children. Sleep 20: 1185–1192. Chervin RD, Hedger K, Dillon JE et al. (2000). Pediatric sleep questionnaire (PSQ): validity and reliability of scales for sleep-disordered breathing, snoring, sleepiness, and behavioral problems. Sleep Med 1: 21–32. Chervin RD, Archbold KH, Dillon JE et al. (2002). Inattention, hyperactivity, and symptoms of sleep disordered breathing. Pediatrics 109: 449–456. Chervin RD, Weatherly RA, Ruzicka DL et al. (2006a). Subjective sleepiness and polysomnographic correlates in children scheduled for adenotonsillectomy vs other surgical care. Sleep 29: 495–503. Chervin RD, Ruzicka DL, Giordani BJ et al. (2006b). Sleepdisordered breathing, behavior, and cognition in children before and after adenotonsillectomy. Pediatrics 117 (4): e769–e778. Chugh DK, Weaver TE, Dinges DF (1996). Neurobehavioral consequences of arousals. Sleep 19: S198–S201. Corbo GM, Forastiere F, Agabiti N et al. (2001). Snoring in 9- to 15-year-old children: risk factors and clinical relevance. Pediatrics 180: 1149–1154. Crabtree VM, Ivanenko A, O’Brien LM et al. (2003). Periodic limb movement disorder of sleep in children. J Sleep Res 12: 73–81. Crabtree V, Varni JW, Gozal D (2004). Quality of life and depressive symptoms in children with suspected sleepdisordered breathing. Sleep 27: 1131–1138. Dagan-Friedman B, Hendeles-Amitay A, Kozminzki E et al. (2002). Impaired cognitive performance in children with obstructive sleep apnea syndrome. Am J Resp Crit Care Med 165: A263. Dahl RE (1996). The impact of inadequate sleep on children’s daytime and cognitive function. Semin Pediatr Neurol 3: 44–50.
497
Eliasson A, Eliasson A, King J et al. (2002). Association of sleep and academic performance. Sleep Breath 6: 45–48. Engleman H, Joffe D (1999). Neuropsychological function in obstructive sleep apnoea. Sleep Med Rev 3: 59–78. Epstein R, Chillag N, Lavie P (1998). Starting times of school: effects on daytime functioning of fifth-grade children in Israel. Sleep 21: 250–256. Everett AD, Koch WC, Saulsbury FT (1987). Failure to thrive due to obstructive sleep apnea. Clin Pediatr 26: 90–92. Fallone G, Seifer R, Acebo C et al. (2000). Prolonged sleep restriction in 11- and 12-year-old children: effects on behavior, sleepiness, and mood. Sleep 23 (Suppl. 2): A28. Fallone G, Acebo C, Arnedt TA et al. (2001). Effects of acute sleep restriction on behavior, sustained attention, and response inhibition in children. Percept Mot Skills 93: 213–229. Fallone G, Acebo C, Seifer R et al. (2005). Experimental restriction of sleep opportunity in children: effects on teacher ratings. Sleep 28 (12): 1561–1567. Ferreira AM, Clemente V, Gozal D et al. (2000). Snoring in Portuguese primary school children. Pediatrics 106 (5). Friedman BC, Hendeles-Amitai A, Kozminsky E et al. (2003). Adenotonsillectomy improves neurocognitive function in children with obstructive sleep apnea syndrome. Sleep 26: 999–1005. Gislason T, Benediktsdottir B (1995). Snoring, apneic episodes, and nocturnal hypoxemia among children 6 months to 6-years-old. Chest 107: 963–966. Golan N, Shahar E, Ravid S et al. (2004). Sleep disorders and daytime sleepiness in children with attention-deficit/ hyperactive disorder. Sleep 15; 27 (2): 261–266. Gozal D (1998). Sleep-disordered breathing and school performance in children. Pediatrics 102: 616–620. Gozal D, Burnside MM (2004). Increased upper airway collapsibility in awake children with obstructive sleep apnea. Am J Resp Crit Care Med 169: 163–167. Gozal D, Pope DW (2001). Snoring during early childhood and academic performance at age thirteen to fourteen years. Pediatrics 107: 1394–1399. Greenberg GD, Watson RK, Deptula D (1987). Neuropsychological dysfunction in sleep apnea. Sleep 10: 254–262. Guilleminault C, Abad VC (2004). Obstructive sleep apnea. Curr Treat Options Neurol 6 (4): 309–317. Guilleminault C, Eldridge F, Simmons FB et al. (1976). Sleep apnea in eight children. Pediatrics 58: 28–31. Guilleminault C, Korobkin R, Winkle R (1981). A review of 50 children with obstructive sleep apnea syndrome. Lung 159: 275–287. Guilleminault C, Winkle R, Korobkin R et al. (1982). Children and nocturnal snoring – evaluation of the effects of sleep related respiratory resistive load and daytime functioning. Eur J Pediatr 139: 165–171. Guilleminault C, Pelayo R, Ledger D et al. (1996). Recognition of sleep disordered breathing in children. Pediatrics 98: 871–882. Harrison Y, Horne JA (1998). Sleep loss impairs short and novel language tasks having a prefrontal focus. J Sleep Res 7: 95–100.
498
H.E. MONTGOMERY-DOWNS AND D. GOZAL
Hulcrantz E, Lofstarnd TB, Ahlquist RJ (1995). The epidemiology of sleep related breathing disorders in children. Int J Pediatr Otorhinolaryngol 32: S63–S66. Isono S, Shimada A, Utsugi M et al. (1998). Comparison of static mechanical properties of the passive pharynx between normal children and children with sleepdisordered breathing. Am J Respir Crit Care Med 157: 1201–1212. Jenni OG, Achermann P, Carskadon MA (2005). Homeostatic sleep regulation in adolescents. Sleep 28: 1446–1454. Kahn A, Van de Merckt C, Rebuffat E et al. (1989). Sleep problems in healthy preadolescents. Pediatrics 84: 542–546. Kelmanson IA (2000). Snoring, noisy breathing in sleep and daytime behaviour in 2–4-month-old infants. Eur J Pediatr 159: 734–739. Kim HC, Young T, Matthews CG et al. (1997). Sleep disordered breathing and neuropsychological deficits. Am J Respir Crit Care Med 156: 1813–1819. Lavigne JV, Arend R, Rosenbaum D et al. (1999). Sleep and behaviour problems among preschoolers. J Dev Behav Pediatr 20: 164–169. Lee MM, Strauss ME, Adams N et al. (1999). Executive functions in persons with sleep apnea. Sleep Breath 3: 13–16. Lewin DS, Rosen RC, England SJ et al. (2002). Preliminary evidence of behavioral and cognitive sequelae of obstructive sleep apnea in children. Sleep Med 3: 5–13. Lezak MD (1995). Neuropsychological Assessment. 3rd edn. Oxford University Press, New York. Lipton AJ, Gozal D (2003). Treatment of obstructive sleep apnea in children: do we really know how? Sleep Med Rev 7: 61–80. McKenzie M (1880). A Manual of Diseases of the Throat and Nose, Including the Pharynx, Larynx, Trachea Oesophagus, Nasal Cavities, and Neck. Churchill, London. Marcus CL, Greene MG, Carroll JL (1998). Blood pressure in children with obstructive sleep apnea. Am J Respir Crit Care Med 157: 1098–1103. Meijer AM, Habekothe HT, Van Den Wittenboer GL (2000). Time in bed, quality of sleep and school functioning of children. J Sleep Res 9: 145–153. Millman RP (2005). Working Group on Sleepiness in Adolescents/Young Adults; AAP Committee on Adolescence. Excessive sleepiness in adolescents and young adults: causes, consequences, and treatment strategies. Pediatrics 115: 1774–1786. Minde K, Popiel K, Leos N et al. (1993). The evaluation and treatment of sleep disorders in young children. J Child Psychology and Psychiatry 34: 521–533. Minde K, Faucon A, Falkner S (1994). Sleep problems in toddlers: effects of treatment on their daytime behavior. J Child Adolescent Psychiatry 33: 1114–1121. Mitchell RB, Kelly J (2005). Quality of life after adenotonsillectomy for SDB in children. Otolaryngol Head Neck Surg 133 (4): 569–572. Mitchell RB, Kelly J (2006). Long-term changes in behavior after adenotonsillectomy for obstructive sleep apnea
syndrome in children. Otolaryngol Head Neck Surg 134 (3): 374–378. Mitchell EA, Thompson JMD (2003). Snoring in the first year of life. Acta Paediatr 92: 425–429. Montgomery-Downs HE, Gozal D (2006a). Snore-associated sleep fragmentation in infancy: mental development effects and contribution of secondhand cigarette smoke exposure. Pediatrics 117 (3): e496–e502. Montgomery-Downs HE, Gozal D (2006b). Sleep habits and risk factors for sleep-disordered breathing in infants and young toddlers in Louisville, Kentucky. Sleep Med 7 (3): 211–219. Montgomery-Downs HE, Jones VF, Molfese V et al. (2003). Snoring in preschoolers: potential associations with sleepiness, ethnicity, and learning. Clin Pediatr (Phila) 42 (8): 719–726. Montgomery-Downs HE, Crabtree VM, Gozal D (2005). Cognition sleep and respiration in at-risk children treated for obstructive sleep apnea. Eur Resp J 25: 336–342. Naegele B, Thouvard V, Pepin JL et al. (1995). Deficits of cognitive executive functions in patients with sleep apnea syndrome. Sleep 18: 43–52. O’Brien LM, Gozal D (2005). Autonomic dysfunction in children with sleep-disordered breathing. Sleep 28: 747–752. O’Brien EM, Mindell JA (2005). Sleep and risk-taking behavior in adolescents. Behav Sleep Med 3 (3): 113–133. O’Brien LM, Holbrook CR, Mervis CB et al. (2003). Sleep and neurobehavioral characteristics in 5–7 year old hyperactive children. Pediatrics 111: 554–563. O’Brien LM, Mervis CB, Holbrook CR et al. (2004a). Neurobehavioral implications of habitual snoring in children. Pediatrics 114: 44–49. O’Brien LM, Mervis CB, Holbrook CR et al. (2004b). Neurobehavioral correlates of sleep disordered breathing in children. J Sleep Res 13: 165–172. Osler W (1892). The Principles and Practice of Medicine. Appleton, New York, pp. 335–339. Owen GO, Canter RJ, Robinson A (1996). Snoring, apnea and ENT symptoms in the paediatric community. Clin Otolaryngol Allied Sci 21: 130–134. Owens J, Opipari L, Nobile C et al. (1998). Sleep and daytime behavior in children with obstructive sleep apnea and behavioral sleep disorders. Pediatrics 102: 1178–1184. Owens JA, Spiritio A, Marcotte A et al. (2000). Neuropsychological and behavioral correlates of obstructive sleep apnea in children: a preliminary study. Sleep Breath 2: 67–78. Owens-Stively J, McGuinn M, Berkelhammer L et al. (1997). Neuropsychological and behavioral correlates of obstructive sleep apnea in children. Sleep Res 26 (Suppl): 452. Randazzo AC, Schweitzer PK, Walsh JK (1998a). Cognitive function following 3 nights of sleep restriction in children ages 10–14. Sleep 21: 249. Randazzo AC, Muehlbach MJ, Schweitzer PK et al. (1998b). Cognitive function following acute sleep restriction in children ages 10–14. Sleep 21: 861–868.
SLEEP-ASSOCIATED RESPIRATORY DISORDERS IN CHILDREN Reuveni H, Simon T, Tal A et al. (2002). Healthcare services utilization in children with obstructive sleep apnea syndrome. Pediatrics 110: 68–72. Rhodes SK, Shimoda KC, Wald LR et al. (1995). Neurocognitive deficits in morbidly obese children with obstructive sleep apnea. J Pediatr 127: 741–744. Richards W, Ferdman RM (2000). Prolonged morbidity due to delays in the diagnosis and treatment of obstructive sleep apnea in children. Clin Pediatr 39: 103–108. Rona JR, Li L, Gulliford MC et al. (1998). Disturbed sleep: effects of sociocultural factors and illness. Arch Dis Child 78: 20–25. Rosen CL, D’Andrea L, Haddad GG (1992). Adult criteria for obstructive sleep apnea do not identify children with serious obstruction. Am Rev Resp Dis 146: 1231–1234. Rosen CL, Palermo TM, Larkin EK et al. (2002). Healthrelated quality of life and sleep-disordered breathing in children. Sleep 25: 648–657. Roth T, Roehrs TA (1996). Etiologies and sequelae of excessive daytime sleepiness. Clin Ther 18 (4): 562–576. Sadeh A, Raviv A, Gruber R (2000). Sleep patterns and sleep disruptions in school age children. Dev Psychol 36: 291–301. Sadeh A, Gruber R, Raviv A (2002). Sleep, neurobehavioral functioning, and behavior problems in school-age children. Child Dev 73: 405–417. Shiomi T, Guilleminault C, Stoohs R et al. (1993). Obstructed breathing in children during sleep monitored by echocardiography. Acta Paediatr 82: 863–871. Smedje H, Broman JE, Hetta J (2001). Associations between disturbed sleep and behavioural difficulties in 635 children aged six to eight years: a study based on parents’ perceptions. Eur Child Adolesc Psychiatry 10: 1–9. Stein MA, Mendelsohn J, Obermeyer WH et al. (2001). Sleep and behavior problems in school-aged children. Pediatrics 107: e60. Stepansky EJ, Lamphere P, Badia P (1984). Sleep fragmentation and daytime sleepiness. Sleep 7: 18–26. Stepansky EJ, Lamphere J, Roehrs T (1987). Experimental sleep fragmentation in normal subjects. Int J Neurosci 33: 207–214.
499
Stewart MG, Glaze DG, Friedman EM et al. (2005). Quality of life and sleep study findings after adenotonsillectomy in children with obstructive sleep apnea. Arch Otolaryngol Head Neck Surg 131 (4): 308–314. Stores G (1996). Practitioner review: assessment and treatment of sleep disorders in children and adolescents. J Child Adolesc Psychol Psychiatry 37: 907–925. Stradling JR, Thomas G, Warley ARH et al. (1990). Effect of adenotonsillectomy on nocturnal hypoxaemia, sleep disturbance, and symptoms in snoring children. Lancet 335: 249–253. Suen JS, Arnold JE, Brooks LJ (1995). Adenotonsillectomy for treatment of obstructive sleep apnea in children. Arch Otolaryngol Head Neck Surg 121: 525–530. Tarasiuk A, Simon T, Tal A et al. (2004). Adenotonsillectomy in children with obstructive sleep apnea syndrome reduces health care utilization. Pediatrics 113: 351–356. Taylor DJ, Jenni OG, Acebo C et al. (2005). Sleep tendency during extended wakefulness: insights into adolescent sleep regulation and behavior. J Sleep Res 14 (3): 239–244. Teculescu DB, Caillier I, Perrin P et al. (1992). Snoring in French preschool children. Pediatr Pulmonol 13: 239–244. Trommer BL, Hoeppner JB, Rosenberg RS et al. (1988). Sleep disturbance in children with attention deficit disorder. Ann Neurol 24: 322. Weissbluth M, Davis A, Poncher J et al. (1983). Signs of airway obstruction during sleep and behavioral, developmental and academic problems. Dev Behav Pediatr 4: 119–121. Wolfson AR, Carskadon MA (1998). Sleep schedules and daytime functioning in adolescents. Child Dev 69: 875–887. Young T, Peppard PE, Gottlieb DJ (2002). Epidemiology of obstructive sleep apnea: a population health perspective. Am J Respir Crit Care Med 165: 1217–1239. Zucconi M, Ferini Strambi L, Pestalozza G et al. (1993). Habitual snoring and obstructive sleep apnea syndrome in children: effects of early tonsil survery. Int J Pediatr Otorhinolaryngol 26: 235–243. Zuckerman B, Stevenson J, Bailey V (1987). Sleep problems in early childhood: continuities, predictive factors, and behavioral correlates. Pediatrics 80: 664–671.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 33
Sudden death in infants during sleep P. FRANCO, 1 * A. RAOUX, 1 B. KUGENER, 1 F. DIJOUD, 1 S. SCAILLET, 2 J. GROSWASSER, 2 INEKO KATO, 3 ENZA MONTEMITRO, 4 J.S. LIN, 1 AND A. KAHN 2 (DECEASED) 1 Pediatric Sleep Unit, H^ opital Femme-M ere-Enfant, SIDS Reference Center of Lyon & INSERM-628, Universite Lyon 1, Lyon, France 2
Pediatric Sleep Unit, Children’s University Hospital, Free University of Brussels, Brussels, Belgium 3
Department of Pediatrics, Nagoya City University Medical School, Nagoya, Japan
4
Department of Paediatric, Sleep Disease Centre, University of Rome “La Sapienza”-S Andrea Hospital, Rome, Italy
DEFINITIONS Sudden infant death syndrome (SIDS) is defined as the sudden death of an infant under 1 year of age that remains unexplained after a complete postmortem examination, including an investigation of the death scene and a review of the case history (Willinger et al., 1991). Since 1978, SIDS has been indexed in the International Classification of Diseases, 9th revision, under the category 798 or 799.9. To incorporate epidemiological features, risk factors, pathologic features, and ancillary test findings, an expert panel of pediatric and forensic pathologists and pediatricians developed a new general definition of SIDS in 2004 (Krous et al., 2004). The new definition incorporates positive criteria such as the occurrence of death during sleep and the relatively narrow age range of death between the third week and ninth month of life. This more inclusive SIDS definition could give an opportunity to facilitate uniformity in diagnosis, to provide more precise monitoring of changing epidemiological patterns in sudden infant deaths, and to allow more valid international comparisons. Apparent life-threatening event (ALTE) is defined as an episode that is frightening to the observer and that is characterized by some combination of apnea, color change, marked changes in muscle tone, choking or gasping, and an apparent need for resuscitation by vigorous stimulation or mouth-to-mouth ventilation. Although the natural history of ALTE is most often benign, there is a risk for subsequent morbidity and mortality. The European Society for the Study and
Prevention of Infant Death published recommendations for the clinical evaluation of infants with ALTE in 2004 (Kahn, 2004). Standard and specific evaluation procedures could identify the cause of the incident in more than 50% of cases. The heterogeneity of both ALTE and SIDS infants renders comparison between both conditions difficult (Valdes-Dapena, 1980). Factors responsible for difficulties in comparing studies of ALTE infants include varied types of presenting spells, incomplete histories, varied terminologies, inconsistent efforts to identify causes of the episodes, dependence on untrained observers, validity of parents to perceive correctly a true life-threatening event, and lack of follow-up programs. Although there are some similarities in the clinical presentation and epidemiology of SIDS and ALTE, differences clearly predominate. The frequency of ALTE did not change after a SIDS preventive campaign (Kiechl-Kohlendorfer et al., 2005). The risk profiles for SIDS and overall ALTE showed only a modest overlap. Smoking in pregnancy was the only prominent SIDS risk condition that emerged as a significant risk predictor of ALTE. Infants with an ALTE were, however, 1-3 weeks younger than the SIDS victims and benefited from more favorable circumstances at the time of the event, such as being found during daytime (Kahn et al., 1984; Kiechl-Kohlendorfer et al., 2005). If, following an initial ALTE, some infants were reported with extreme cardiorespiratory events, a relationship with SIDS could involve only a fraction of all SIDS
*Correspondence to: Patricia Franco, Pediatric Sleep Unit, Hoˆpital Femme-Me`re-Enfant, Universite Lyon 1, 59, bd Pinel, 69500 Lyon, France. Tel: (þ33).4.27856052, Fax: (þ33).4.27869230, E-mail:
[email protected]
502
P. FRANCO ET AL.
cases as fewer than 10% of future SIDS victims had presented with a cyanotic or pale episode during sleep at some time before death (Mitchell and Thompson, 2001). Comparing surviving ALTE infants to ALTE infants who became SIDS victims, Edner et al. (2007) cannot exclude the possibility that there is a subpopulation of ALTE infants who did not die in SIDS due to more favorable environmental conditions. In the ALTE group 13.3% of the survivors had the combination of prone sleeping and maternal smoking, compared with 33.3% of those who became SIDS victims.
PATHOLOGIC EXAMINATIONS The results of the postmortem investigations in SIDS are by definition insufficient to explain the cause of deaths. In most infants dying suddenly and unexpectedly during sleep, the autopsy findings were very subtle and yielded only supportive rather than conclusive findings. Up to 80% of SIDS victims showed intrathoracic petechiae, postulated to result from the combination of hypoxia and persistent respiratory movements. Autopsy studies demonstrated structural evidence or tissue markers of asphyxia in nearly 75% of SIDS subjects. These included excessive retention of periadrenal brown fat, increased extramedullary hematopoiesis, or abnormal astroglial proliferation, especially in the brainstem. Additional postmortem evidence of premortem hypoxia included growth retardation, elevated blood cortisol levels, brain lactate and Hþ concentrations, pulmonary neuroendocrine cell hyperplasia, elevated hypoxanthine levels in the vitreous humor, and vascular endothelial growth factor in the cerebrospinal fluid (Valdes-Dapena, 1992; Rognum, 2001; Jones et al., 2003). A complete pathologic examination is required for the diagnosis of SIDS, including microscopic, toxicological, microbiological, immunohistochemical, molecular, and metabolic exams (Bajanowski et al., 2007). These postmortem investigations permitted the identification of a medical or surgical origin of death in 15–50% of cases depending on the number of investigations performed (Valdes-Dapena, 1992; Rognum, 2001). In a retrospective analysis in the province of Quebec, heart disease was present in 10% of all autopsies of infants with sudden death. A structural malformation was present in the majority of cases (54%), although nonstructural pathologic features of the heart were common (46%). If most anatomic malformations were detected before death, the nonstructural heart diseases were usually unrecognized before an autopsy was performed (Dancea et al., 2002). These findings have been confirmed in a retrospective study performed on all cases of sudden death
from 1993 to 2005 registered in the Regional SIDS Reference Center in Lyon (France) (Dr. Dijoud, personal communication). Among 162 consecutive autopsies, 20 cardiovascular alterations were found, 15 of which were considered to be responsible for death (9.2%). These abnormalities were unknown before death in 12 of these infants (7%). The abnormalities were represented by myocarditis, morphological change in cardiac conduction system, multiple rhabdomyoma, pulmonary hypertension with alveolar dysplasia, and metabolic cardiomyopathy. When combined investigations using molecular pathologic techniques and immunohistochemical methods were used, the incidence of potentially lethal viral myocardial afflictions could be more than twice that assumed by the literature (43.5% versus 16.8%) (Dettmeyer et al., 2004).
INCIDENCE In the early 1990s, the incidence of SIDS was estimated between 1 and 3 per 1000 live births for most industrialized countries (Hoffman and Hillman, 1992; Hunt, 1992; Glotzbach et al., 1995). There has been a greater than 50% reduction in the incidence of SIDS since the American Academy of Pediatrics released its recommendation in 1992 that infants have to be placed down to sleep in a nonprone position (American Academy of Pediatrics, 1992; Dwyer and Ponsonby, 1996; Hauck, 2001). Infants dying of SIDS still constituted the largest component of postneonatal infant mortality, accounting for approximately 30% of postnatal deaths (between 28 days and 1 year). Most deaths from SIDS occur in the first 6 months of life, with a specific peak between 2 and 4 months of age. The deaths occur during sleep, whether a nap or sleep at night. Male infants have a 50% greater risk of dying of SIDS than female infants. In 10% of cases, SIDS victims had experienced an ALTE some days or weeks before their death. The infant surviving such an event is usually considered to have 5–10% increased risk of dying of SIDS. SIDS infants are more likely to be of higher birth order. The reported rates of SIDS differ greatly among various countries, ranging from 0.05 in Japan to 0.75 in the USA. This discrepancy could result from a variety of causes. Incomplete or absent postmortem examination, inexperienced pathologists, and differences in classification of causes of deaths can lead to potential misclassification of causes of deaths (Rognum, 2001).
RISK AND PROTECTIVE FACTORS A number of factors have been found to be associated with increased (and decreased) SIDS risk.
SUDDEN DEATH IN INFANTS DURING SLEEP
Sociodemographic and climatic factors SOCIOECONOMIC
CLASS
An increased risk of SIDS was related to lower socioeconomic status, measured by the parents’ occupation, income, or education (Froggat, 1970; Little and Peterson, 1990). Various factors strongly related to lower socioeconomic classes were also associated with an increased risk of SIDS: young maternal age (< 20 years), short duration of schooling, illegitimacy, lack of prenatal care, multiparity, short birth intervals, smoking, drug consumption, increased incidence of urinary tract infections, or poor postnatal care (Haglund and Cnattingius, 1990; Hoffman and Hillman, 1992). Migrant populations, families of low social class, young mothers (< 20 years), mothers with a minimum level of education (< 11 years) and noncohabiting mothers are particularly resistant to changes in infant care practices after information campaigns and have the highest prevalence rates of these risk factors (Hill et al., 2004). The risk for SIDS associated with lower social class increased after the Back to Sleep campaign. This public health intervention did not reduce the social inequalities in SIDS but rather increased the gap (Pickett et al., 2005). A determinant factor for SIDS risk associated with social privation is the educational level of the mother (Kahn et al., 2001).
RACE
AND GEOGRAPHY
All studies on SIDS incidence have shown significantly higher rates in black than in white infants, independently of any other factor, such as low birth weight, young maternal age, or parity (Hoffman and Hillman, 1992). The relative risk for black infants was 1.7–4.0. SIDS rates are low in ethnic Chinese in Hong Kong. However California-derived data suggested that assimilation of Chinese immigrants into US culture increased the rates of SIDS to a level comparable to that of Native Americans (Grether and Schulman, 1990). Genetic influences, cultural practices of child care, or socioeconomic factors could all be responsible for the differences in racial risk ratios (Hauck, 2001).
SEASON,
CLIMATE, AND AIR POLLUTION
Many studies throughout the world have confirmed that the occurrence of SIDS in cold months is approximately double that during hot weather (Little and Peterson, 1990). A significant negative correlation was found between the incidence of SIDS and the daily minimum temperature some 4–5 days before death (Mitchell et al., 1992a). It is unclear what mechanisms are responsible for this finding. Cold months could
503
have an effect on SIDS rates through multiple associated risk factors, such as infectious agents, nutritional or metabolic processes, infant care practices, excessive ambient temperature in the infants’ room, or other lifestyle factors. In countries where campaigns to reduce environmental risks have been conducted, the seasonal discrepancy of SIDS incidence has markedly decreased (Wigfield et al., 1994). Air pollution could have an influence on the incidence of SIDS. SIDS may be related to high levels of acute outdoor sulfur dioxide (SO2) and nitrogen dioxide (NO2) exposure during the last day of life (Dales et al., 2004; Klonoff-Cohen et al., 2005).
Perinatal risk factors PREMATURITY
AND FETAL GROWTH RETARDATION
The relative risk of SIDS incidence is 4–6 times higher in infants born prematurely. The relative risk increases as gestational age decreases (Hoffman and Hillman, 1992; Hauck, 2001). In utero growth retardation is also a major risk factor. SIDS infants are more often born with a lower birth weight than control infants (Hoffman and Hillman, 1992; Glotzbach et al., 1995; Hauck, 2001; Carpenter et al., 2004). The incidence is estimated to be 8.7 per 1000 live births in premature infants of less than 1500 grams. Low-birth-weight SIDS represents 16.7% of all SIDS cases. The inverse relationship seen between SIDS and birth weight could explain the increased risk reported for multiple births. Twins and triplets have a SIDS incidence of respectively 3.9 and 8.3 per 1000 live births. Although prone sleeping decreased among infants after preventive campaigns, “small at birth” infants (preterm (< 37 weeks), low birth weight (<2500 grams), or both) who are at very high risk for SIDS are more likely to sleep in prone or in side position than age-matched control infants (Vernacchio et al., 2003; Blair et al., 2006). Physicians and nurses caring for small-at-birth infants frequently recommend the prone or sidesleeping position (Vernacchio et al., 2003).
MATERNAL
AND ANTENATAL RISK FACTORS:
CIGARETTE SMOKING, ALCOHOL, AND OTHER DRUGS
The risk for SIDS in infants of mothers addicted to drugs (marijuana, methadone, cocaine, heroin) is higher than that for the general population (Hoffman and Hillman, 1992). In a meta-analysis comparing cocaine-exposed infants with drug-free infants, the pooled odds ratio for SIDS was 4.10 (3.17–5.30) (Fares et al., 1997). Parental alcohol use during pregnancy is likely associated with increased SIDS risk and can act synergistically with other substance use (Iyasu et al.,
504
P. FRANCO ET AL.
2002; Friend et al., 2004). Postnatal alcohol use also appears to be implicated, particularly when combined with bed-sharing (Carpenter et al., 2004). Epidemiological surveys confirmed that smoking is associated with an increased risk of SIDS (Haglund and Cnattingius, 1990; Mitchell et al., 1993a; KlonoffCohen et al., 1995) with a risk ratio of 1.7–4.1. This risk ratio is dose-dependent and is mainly associated with prenatal maternal smoking, and, to a lesser extent, to postnatal exposure to cigarette smoke (Klonoff-Cohen et al., 1995). After a preventive campaign, the prevalence of maternal smoking increased among SIDS deaths, while it decreased among both the live birth controls and the non-SIDS postneonatal deaths (Chong et al., 2004). Smoke-exposed infants are twice as likely to die of SIDS (Anderson et al., 2005). Maternal smoking during pregnancy became the most important modifiable risk factor for SIDS in the postcampaign period. The effects of tobacco exposure have been well studied in infants and in model animals (Hafstro¨m et al., 2005). Infants’ lung and brain structures could be modified by tobacco smoke exposure, especially during fetal life. In infants and children, prenatal exposure to maternal tobacco smoking alters lung mechanisms by reducing respiratory compliance and increasing airway resistance (Hanrahan et al., 1992). Animal experiments have strongly linked these effects to nicotine (Slotkin, 2004). Nicotine interacts also on neural networks controlling respiration. In the fetal nervous system, nicotine alters cellular development and leads to early termination of cell division, mistiming of cellular differentiation, and alteration of the synaptogenesis and synaptic activities of a variety of neurotransmitter pathways (Navarro et al., 1989). These changes affect both central and peripheral neural tissues and are most prominent in tissues rich in nicotinic cholinergic receptors. Blunted responses to hypoxic challenges in prenatally nicotine-exposed animals suggested that nicotine could affect peripheral chemoreceptors (Hafstro¨m et al., 2002), possibly through a dopaminergic mechanism (Holgert et al., 1995). Brief exposure to nicotine could significantly impair breathing (and possibly arousal) responses to hypoxia by disrupting functions normally regulated by particular nicotinic acetylcholine receptors responsible for protective responses to hypoxia during sleep (Cohen et al., 2002). Prenatal exposure to nicotine produces alterations in nicotine-binding sites that were heavily concentrated during midgestation such in brainstem areas related to cardiopulmonary integration, to regulation of arousal, to somatic motor control and hypoglossal nucleus (Kinney et al., 1993). In rats, nicotine exposure, during a critical developmental period, could produce
cardiac and brainstem receptor imbalances that favor inhibitory responses such as marked rapid bradycardia during severe hypoxia (Fewell and Smith, 1998; Slotkin et al., 1999; Neff et al., 2004; Evans et al., 2005). This mechanism could explain the exaggerated bradycardia observed before death in some victims of SIDS.
SIDS
RECURRENCE RATES
Several studies have shown that siblings of infants with SIDS are at increased risk of SIDS (Beal and Blundell, 1988; Oyen et al., 1997). The recurrence rate for siblings of SIDS victims could be 3–6 times higher than that in the nonselected population. Such studies of recurrence have been criticized for not considering the possibility of serial infanticide (Firstman and Talan, 2001). There have been suggestions that when two or three unexpected unexplained infant deaths occur within a family they are more likely to be unnatural than natural (Meadow, 1999). In one study, cases of repeat sudden unexpected and unexplained infant deaths were reviewed (Carpenter et al., 2005). Second deaths were not rare (6.2 per 1000 living births) and the majority of deaths, 80–90%, were natural. There are also families who have experienced three unexpected deaths (Carpenter et al., 2005). The risk for twins appears to be at least twice as high as that for a subsequent sibling (Hoffman and Hillman, 1992; Hunt, 1992; Glotzbach et al., 1995). First cousins and other members of a SIDS family share the same risk as the general population.
Sleep environment PRONE
SLEEPING POSITION
Case-control reviews on sleeping position and SIDS showed that the relative risk for SIDS increased fourto ninefold when infants sleep prone than when they sleep supine (Engelberts and de Jong, 1990; Fleming et al., 1990; Beal and Finch, 1991). In countries where preventive campaigns were conducted, SIDS rates fell substantially (Thach et al., 1998). This reduction in mortality has been mainly attributed to the avoidance of the prone sleeping position. The prone sleeping position reduced from 70% in 1992 to less than 10% in 2004, and led to an over 50% reduction in postneonatal mortality and frequency of SIDS (Carpenter et al., 2004). Various mechanisms have been postulated to explain the association of prone sleeping and SIDS (Horne et al., 2002b). These include accidental suffocation, oropharyngeal obstruction due to nasal obstruction, posterior displacement of the mandible, increased upper-airway resistance, inhibitory inputs from atrial stretch receptors, compromise of cerebral blood flow during cervical hyperextension, rebreathing of carbon dioxide overheating, development of nasal bacterial
SUDDEN DEATH IN INFANTS DURING SLEEP toxins, imbalance of autonomic function, or impairment of arousal mechanisms. Inexperienced prone sleeping was a determinant for SIDS. The infants who were usually placed nonprone but were placed prone for their last night had the higher risk ratio than infants who were usually placed prone (Oyen et al., 1997). Infants who are inexperienced in prone sleeping have decreased ability to escape from asphyxiating sleep environments when placed prone (Paluszynska et al., 2004). The combination of prone positioning and the use of soft bedding further increased the risk of dying, probably because the nose and mouth were often trapped and covered (L’Hoir et al., 1998), or because of reduced carbon dioxide dispersal (Kemp et al., 1998). Side-sleeping position is an intermediate risk factor between prone and supine position (Scragg and Mitchell, 1998). As prone sleeping rates have declined following SIDS risk reduction campaigns, side sleeping has become a more critical risk factor in some groups, such as lowbirth-weight infants (Vernacchio et al., 2003; Blair et al., 2006). The instability associated with the side position is the likely explanation for the increased risk in this position. Infants placed on their side have a greater probability of rolling into the prone position.
BED
COVERINGS, OVERHEATING, AND HEAD COVERING
Hyperthermia due to overdressing or to a high environmental temperature was suggested to be a risk factor for SIDS (Ponsonby et al., 1992). Most SIDS victims were reported to be overdressed and overdraped at the time of death. Many infants were inappropriately hot and sweaty when found dead (Stanton, 1984). For every thermal insulation unit (or tog value), the relative risk for SIDS increased by 1.26 (Ponsonby et al., 1992). A combination of factors seems important to create hyperthermia, such as soft bedding combined with the use of a duvet, or a quilted sleeping sack covered with a duvet (Scheers et al., 1998). In a recent systematic review of population-based age-matched controlled studies, more than a quarter of SIDS were found with their heads covered with bedclothes (Blair et al., 2008). Being found with a head covering was associated with older infant age, which probably reflects motor development. The finding that SIDS infants found with their heads covered were often very sweaty suggests that head covering was not an agonal event but that it preceded the death and could be causally related to the death (Mitchell et al., 2008).
CHILD
CARE SETTINGS
Child care settings may be associated with an increased risk of SIDS (de Jonge et al., 2004). In this study, over 10% of cases took place during some type of child care
505
settings. Based on the hours usually spent in child care by these infants, the number of infants that died from SIDS while attending child care settings was 4.2 times higher than expected. The prevalence of known risk factors for SIDS, such as sleeping position, bedding, and parental smoking, was more favourable in the child care setting than at home, suggesting that stress and change in routine care could be implicated (de Jonge et al., 2004; Moon et al., 2005).
BED-SHARING Co-sleeping may represent a risk factor in SIDS (Mitchell et al., 1992b; Carpenter et al., 2004; Tappin et al., 2005). Bed-sharing is associated with an increased risk of SIDS for infants from smoking mothers but also from nonsmoking mothers for infants younger than 8–11 weeks. The risk associated with maternal smoking, low birth weight at birth, and excessive wrapping was increased by bed-sharing (McGarvey et al., 2006). The mother’s alcohol consumption was a risk factor only when the baby bed-shared all night, with a risk ratio which increased by 1.66 (1.16–2.38) per drink (Carpenter et al., 2004). Couch-sharing was associated with the highest risk for SIDS and should be discouraged at any age (Tappin et al., 2005). Co-sleeping was reported to increase the risk for infant death, through suffocation, asphyxia, entrapment, thermal stress, or overlying (Nakamura et al., 1999), in particular if parents have consumed alcohol or sedative drugs.
Infections In 70% of cases, the sudden death was preceded, within 24 hours of the time of death, by a minor illness, especially gastrointestinal or upper-airway infection (Hoffman and Hillman, 1992). A cytomegalovirus infection, responsible for upper respiratory tract infections, has frequently been implicated in SIDS victims, as in infants dying from other causes. In SIDS cases, the cytomegalovirus infection was often clinically silent. Respiratory syncytial virus was reported to trigger pauses, possibly related to some life-threatening events. However, no differences were found in the frequency of symptoms of infection and illness between control and SIDS infants in the last 4 weeks before the death (Vennemann et al., 2005). No clear association has been identified between SIDS and specific viral or bacterial pathogens. There was no excess in viral infection in the SIDS group compared with living controls when samples were collected from upper respiratory and gastrointestinal tracts (Gilbert, 1994; Heininger et al., 2004). Recent illness appears to interact with other factors to increase the risk of SIDS.
506
P. FRANCO ET AL.
Combined effects of viral infection with prone position or with excessive wrapping produced the highest risk ratios (Gilbert et al., 1992; Ponsonby et al., 1992). It was also reported that treatments for nasopharyngitis with phenothiazine drugs increased the risk for SIDS. These and other sedative drugs were associated with an increased frequency of SIDS and were shown to induce central as well as obstructive sleep apneas, while decreasing the arousability of the infants (Kahn et al., 1985).
Potential protective factors for SIDS: breast-feeding, pacifiers, sleeping bags, firm bedding, swaddling, and room-sharing Pacifier use has been reported to be associated with a reduced risk of SIDS (Mitchell et al., 1993b; Wigfield et al., 1994; L’Hoir et al., 1998). A meta-analysis has been undertaken to evaluate the effect of pacifiers in preventing SIDS (Hauck et al., 2005). This published case-control study demonstrated a significant reduced risk of SIDS with pacifier use, especially when placed for sleep, suggesting that pacifier use should be encouraged in infants up to 1 year to prevent SIDS. The mechanisms responsible for this protective effect are not known. The use of a pacifier was speculated to prevent the tongue from sealing off the airways, to reduce the frequency and duration of gastroesophageal refluxes, to decrease the prevalence of prone sleeping, to favor mouth-breathing, to increase arousability during sleep, and to increase respiratory drive as well as sensory inputs in muscles responsible for the patency of the upper airway (Franco et al., 2000a). Other factors, such as breast-feeding, sleeping bags, and firm bedding, could also protect against SIDS (Wigfield et al., 1994; L’Hoir et al., 1998). Breastfeeding could benefit the infant by reducing the risk for intestinal infections. Sleeping bags could have a protective effect by reducing the risk of hyperthermia, head covering, and prone sleeping (L’Hoir et al., 1998). Firm bedding and reduced covering were also considered useful to prevent hyperthermia and to decrease the risk of SIDS (L’Hoir et al., 1998; Scheers et al., 1998). Even if these protective effects are of little magnitude, they contribute to reduce the risk for SIDS. Low risk of SIDS was also reported in infants who usually shared the parents’ room and who shared it during the last night (Mitchell and Thompson, 1995; Carpenter et al., 2004). Swaddling has also been considered to reduce SIDS. The odds ratio for SIDS in swaddled infants sleeping supine has been reported to be of 0.64–0.69 (Ponsonby et al., 1992; Wilson et al., 1994). The mechanisms responsible for the protective
effect of swaddling are not known. Although swaddling favors sleep continuity, it is associated with an increased responsiveness to environmental auditory stress (Franco et al., 2005). If infants were more easily aroused from sleep when sleeping supine and swaddled, swaddling could have a beneficial effect on self-resuscitation responses in case of life-threatening conditions during sleep. Another potential protective mechanism of swaddling for SIDS could derive from the motor restraint of swaddling, preventing infants from rolling from supine to prone and from getting their heads caught in loose blankets (L’Hoir et al., 1998).
MODEL FOR SIDS Filiano and Kinney (1994) suggested a triple-risk model for SIDS that includes three combined factors (Figure 33.1): (1) an underlying prenatal vulnerability; (2) a critical developmental period; and (3) an exogenous postnatal stressor. The infant’s vulnerability lies latent until the infant enters the critical developmental period from 2 to 6 months and is exposed to an exogenous stressor.
Prenatal vulnerability Prenatal vulnerability could be secondary to genetic alterations or adverse intrauterine environment or due to premature birth.
GENETIC
ALTERATIONS
The genetic component of SIDS can be divided into two categories (Opdal and Rognum, 2004). 1. Genetic alterations that may cause sudden infant death per se, such as: ● fatty acid oxidation disorders (medium-chain acyl coenzyme A dehydrogenase (MCAD), very long-chain acyl coenzyme A dehydrogenase, carnitine transporter deficiencies) (less than 5% of all cases of sudden death: Boles et al., 1998; Wilcox et al., 2002) ● glucose metabolism (mutation in myophosphorylase, glucokinase gene) (Forsyth et al., 2005) ● thrombosis (mutation in genes encoding for coagulation factors: factor V, prothrombin) (Larsen et al., 2000) ● long-QT syndrome (Ackerman et al., 2001). Long-QT syndrome is an inherited condition proposed as the cause of death in some cases of sudden infant death. Long-QT syndrome is a primary cardiac channelopathy with seven cardiac ion channel genes currently implicated: KCNQ1, KCNH2, SCN5A, KCNE1, KCNE2,
SUDDEN DEATH IN INFANTS DURING SLEEP POSTNATAL STRESS FACTOR(S)
VULNERABLE INFANT
- Prematurity - Small-forgestational age - Prenatal smoking - Genetic predisposition - Sex - Adverse in-utero environment - ..
507
-
Prone position
- Ambient temperature - Head covered - Sleep deprivation - Infections - Sedative medications
SIDS: Autonomic, breathing, arousal controls
- Bedsharing - ..
CRITICAL DEVELOPMENTAL PERIOD (2 to 6 months of age)
Fig. 33.1. The three overlapping circles represent the triple-risk model for SIDS. According to this model, sudden infant death syndrome SIDS results from the intersection of three overlapping factors: (1) underlying vulnerability in the infant; (2) a critical period in homeostatic control; and (3) an exogenous stressor(s). (Reproduced from Filiano and Kinney (1994).)
KCNJ2, and CAV3 (Arnestad et al., 2007). Mutations in two of these genes (KVLQT1 and SCNA5A) were identified in cases initially diagnosed as SIDS. Cardiac sodium channel gene (SCN5A) defects have been found in 2% of a prospective SIDS population-based cohort, suggesting that de novo mutations in cardiac ion channels may provide a lethal arrhythmogenic substrate in some infants at risk for SIDS (Ackerman et al., 2001). Arnestad et al. (2007) found 9.4% of the mutations were likely contributors to sudden death in over 200 cases of SIDS. QT prolongation could be an early manifestation of congenital long-QT syndrome. A large prospective cohort study provided evidence of an association between neonatal QT prolongation recorded on electrocardiogram during the first days of life and the later occurrence of SIDS (Schwartz et al., 1998). QT prolongation could increase the vulnerability to ventricular tachycardia and sudden cardiac death in apparently healthy infants. 2. Genetic polymorphisms that may predispose infants to sudden infant death under certain circumstances.
Many SIDS victims have an activated immune system, which may indicate that they are vulnerable to simple infections. Polymorphisms in genes involved in the immune system (complement, human leukocyte antigen (HLA)-DR, interleukin10 (IL-10)), in thermal regulation or cellular energy (mtDNA) are of importance with respect to sudden unexpected infant death (Opdal and Rognum, 2004). Another gene that has been investigated is the serotonin transporter gene, and an association between the long alleles of this gene and SIDS has been demonstrated. The L and XL alleles were more frequently found than S alleles in SIDS victims than in age-matched control participants (Narita et al., 2001; Weese-Mayer et al., 2003). The L allele is associated with increased expression of the serotonin transporter in various brain regions, and thus lower synaptic serotonin availability. Serotonin influences a broad range of physiologic systems, including the regulation of breathing, the cardiovascular system, temperature, and the sleep– wake cycle, as well as interactions between the immune system and the nervous system. The long alleles may be related to SIDS, either through
508
P. FRANCO ET AL.
down-regulation of presynaptic autoreceptors or through a developmental effect on the brainstem (Weese-Mayer et al., 2003). It is necessary to distinguish between lethal mutations leading to diseases such as MCAD and longQT syndrome and polymorphisms (IL-10 gene and mtDNA) that are normal gene variants but might be suboptimal in critical situations and thus predispose infants to sudden infant death. It is unlikely that one mutation or polymorphism is the predisposing factor in all SIDS cases (Opdal and Rognum, 2004). There are probably “SIDS genes” operating as a polygenic inheritance predisposing infants to sudden infant death in combination with environmental risk factors.
ADVERSE
INTRAUTERINE ENVIRONMENT
AND PREMATURE BIRTH
Adverse intrauterine environment during pregnancy may be another important risk for SIDS. A raised maternal serum level of alpha-fetoprotein during the second trimester of pregnancy is a marker of placental dysfunction. The risk for SIDS increased with increasing serum levels of alpha-fetoprotein in the mother during the second trimester of pregnancy (Smith et al., 2004). More mothers in the SIDS group than in the control group were reported to have placenta praevia, abrutio placentae, premature rupture of membranes, or small-for-gestational-age newborns, suggesting that pregnancies complicated by long-standing placental abnormalities might predispose to SIDS (Getahun et al., 2004). Risks associated with placental abnormalities, maternal smoking, and preterm birth suggest an important role for factors that lead to “hypoxic conditions” in either the fetus or the newborn. These conditions could result in subtle neurological damage that contributes to later infant demise.
The critical development period Most deaths from SIDS occur in the first 6 months of life, with a specific peak between 2 and 4 months of age. This age distribution corresponds to a period of the infant’s life when significant changes occur in sleep–wake, breathing, autonomic controls, and immunologic maturation. The deaths occur at a time when the infant is supposed to be sleeping, mainly during the early-morning hours (between midnight and 06.00 a.m.). It could thus be hypothesized that abnormal regulation of some vital physiological control mechanisms develops during sleep. The infant’s sleep–wake pattern matures rapidly during the first 6 months of life (Stern et al., 1969; Louis et al., 1997). By 3 months of age, the proportion of rapid eye movement (REM) sleep begins
to diminish and sleep-onset REM periods begin to be replaced by sleep-onset non-REM (NREM) sleep. The intensity of body motility during REM sleep decreases with increased peripheral muscle atonia and the proportion of indeterminate sleep decreases as sleep states become better organized (Anders et al., 1995). There is also a maturation of the arousal capacity with age. According to McGraw (1976), between the period of reflex dominance and the eventual “voluntary, deliberate behavior” that will be acquired, the infant’s style of response undergoes a period of “disorganized” activity. This important transitional period from principally subcortical to cortical controls occurs between 2 and 5 months of age, typically the age of greater SIDS risk (Lipsitt, 2003). In response to nasal occlusion, 83% of newborns were able to establish an oral airway compared to only 54% of 6-week-old infants (Swift and Emery, 1973). This developmental progression from more to less competent behavior is of great interest and could explain the few deaths from SIDS before 6 weeks of age. This loss of reflexive behaviors could be a risk factor if the voluntary responses are not already acquired.
The role of environmental stressors The importance of environmental stress factors in the development of SIDS is highlighted by the drop in SIDS incidence measured in most countries following the prevention campaigns (Mitchell et al., 1994). Environmental stressors include the prone sleep position, a high room temperature, sleeping with the face covered, and prenatal maternal smoking and drug addiction. Other stressors that modify the infant’s ability to cope with the environment include previous sleep deprivation (Emery, 1959; de Jonge et al., 2004). The incidence of SIDS is enhanced by sleep deprivation. During the last 24 hours before death, future SIDS victims have slept significantly less than control infants (Fleming et al., 2000). Recent changes in normal life routine were more common in SIDS than in control infants (Ford et al., 1996; de Jonge et al., 2004). Sleep deprivation can result from handling conditions as well as from sleep fragmentation due to respiratory or digestive infections, fever or airway obstructions during sleep.
MECHANISMS IMPLICATED IN SIDS DEATHS Three basic mechanisms were postulated to cause SIDS: 1. the breathing control hypothesis 2. the autonomic control hypothesis 3. the sleep and arousal hypothesis.
SUDDEN DEATH IN INFANTS DURING SLEEP
The breathing control hypothesis Breathing pattern abnormalities were observed in infants at risk for SIDS. Compared to control infants, infants who later succumbed to SIDS had fewer short central apneas during both NREM and REM sleep, at ages near that of the peak incidence of SIDS (Schechtman et al., 1991). These data suggested that respiratory patterning in these infants could be less responsive to physiological influences (respiratory, baroreceptor, or other somatic inputs) that modify breathing rates. Infants considered to be at risk for SIDS and infants who later succumbed to SIDS also had more frequent mixed and obstructive sleep apneas than control subjects (Guilleminault et al., 1979; Kahn et al., 1992; Kato et al., 2001). Postmortem findings support the development of frequent hypoxic events, possibly related to airway obstructions. These include a thickening of the basement membrane of the vocal cords (Shatz et al., 1991), the presence of intrathoracic petechiae, excessive retention of periadrenal brown fat, increased extramedullary hematopoiesis (Valdes-Dapena, 1992), or abnormal astroglial proliferation, especially in the brainstem (Takashima et al., 1978; Waters et al., 1999). The mechanisms responsible for obstructive sleep apnea are complex. In infants, obstructive sleep apneas are most frequently due to narrowed upper airways, nasal infection, anatomic abnormalities, neurological lesions impairing muscle contractions, or soft-tissue infiltration (Sullivan et al., 1990). Narrowed upper airways could be inherited, as sleep apneas and smaller airways were also found in some SIDS family members (Guilleminault and Stoohs, 1992). Obstructive sleep apneas could also be associated with abnormal autonomic control of the upper airways (Sullivan et al., 1990) and can be prevented by atropine (Kahn et al., 1991). The mechanisms contributing to the development of airway obstructions could be age-dependent, and favored by the small diameter and patency of the upper airways in young infants, or the greater laryngeal reactivity to stimuli in this age range. In the monkey, electrical stimulation of the superior laryngeal nerve induced glottal closure in infant animals but not in older animals (Sutton et al., 1978). Central and obstructive apneas are seen during the sleep of healthy infants. The frequency of obstructive apnea decreases significantly between the 8th and the 12th week of life. Boys had more obstructive sleep apneas than girls, particularly during the peak age for SIDS (Kato et al., 2000). Although unexplained, this finding is reminiscent of male preponderance among the victims of SIDS (Hoffman and Hillman, 1992). Infants sleeping prone and face-down on soft bedding show episodes of airway obstruction (Tonkin,
509
1975). The frequency of obstructive sleep apnea is, however, not associated with body position in infants, although the duration of the apnea increases when the infants sleep prone (Groswasser et al., 2001). The development of apnea could depend on other environmental factors. Healthy infants develop a greater frequency of obstructive sleep apneas when they are exposed to some risk conditions for SIDS, such as being born from a smoking mother (Kahn et al., 1994), being treated by sedative medications (Kahn et al., 1985), or having been sleep-deprived (Canet et al., 1989; Franco et al., 2004b).
The autonomic control hypothesis Future SIDS victim exhibit symptoms during sleep that reflect a subtle dysautonomia. These include episodes of profuse sweat production during sleep (Kahn et al., 1986), tachycardia, bradycardia, higher overall heart rate, or a reduced heart rate variability (Schechtman et al., 1988). Analysis of the heart rate variability in future SIDS victims showed findings compatible with a decrease in parasympathetic activity, an increase in sympathetic activity, or a combination of both conditions (Kluge et al., 1988; Franco et al., 1998b). Future victims of SIDS have a higher peak of sympathetic tonus, desynchronized from the parasympathetic peak activity during the late hours of the night, when most sudden deaths occur (Franco et al., 1998b). Such imbalance in cardiac autonomic control has been postulated to induce prolongation of the QTc interval in SIDS victims (Schwartz et al., 1998; Franco et al., 2008). The greater sympathovagal control seen in infants at risk of SIDS could result from a delayed maturational process or from repetitive hypoxia that modifies brainstem, cerebellar, or cortical areas involved in autonomic controls (Harper and Bandler, 1998). Autonomic cardiac controls are also dependent on environmental factors. Increases in sympathovagal controls have been measured following prenatal exposure to cigarette smoke (Franco et al., 1999), prone sleep (Franco et al., 1996; Galland et al., 1998), previous sleep deprivation (Franco et al., 2003), sleeping in high ambient temperatures (Franco et al., 2000b), or with the face covered by a bed sheet (Franco et al., 2002a). Pacifier use and sleeping supine in swaddling conditions during sleep, two factors associated with a lower risk for SIDS, were characterized by a reduction of the heart rate sympathovagal ratio (Franco et al., 2004a, 2004c). It has been reported that increased sympathetic activity reduced the electrical stability of the heart and precipitated ventricular fibrillation and sudden cardiac death (Lown and Verrier, 1976; Schwartz et al., 1984). Such autonomic imbalance could also
510
P. FRANCO ET AL.
interfere with the survival of the infants by reducing their reactivity to exogenous or internal stimuli. An intact adrenal function is necessary for gasping and surviving from anoxia in newborn rats (Yuan et al., 1997). These responses are blunted in growth-retarded newborn rats with high basal sympathoadrenal activity (Shaul et al., 1989). Basal parasympathetic tonus reflects the individual’s capacity to respond to stress (Porges, 1992). An attenuated vagal or an increased sympathetic activity could reduce behavioral adaptation to environmental stresses.
The arousal hypothesis The temporal association between SIDS and sleep suggests that arousability from sleep provides a protective mechanism for survival when the infant is confronted with a life-threatening challenge during sleep. Failure to arouse could be involved in the final pathway of SIDS. Several studies have reported a developmental delay in sleep organization and a reduced frequency of awakenings from sleep in future SIDS victims (Kahn et al., 1992; Schechtman et al., 1992). The nycthemeral organization of sleep and arousal was also disturbed in infants who later succumbed to SIDS. Infants who later died of SIDS exhibited less waking during the end of the sleep period (a time of peak incidence for SIDS) and more waking in the period immediately following sleep onset (Schechtman et al., 1992). It has been shown that infants who became victims of SIDS not only aroused less from sleep than control infants, but that their arousal characteristics were different (Kato et al., 2003). Compared to control infants, SIDS victims had significantly more incomplete arousals (subcortical activation) in the first part of the night, between 9:00 p.m. and midnight, and fewer complete arousals (cortical arousals) during the latter part of the night. The data are suggestive of incomplete arousal processes in infants who eventually died. There was also a relationship between arousal and age. From birth to 9 months of age, maturation of the arousal events differed according to sleep state and type of arousal (Montemitro et al., 2008). With age, subcortical activations decreased in active and quiet sleep, although cortical arousals increased in active sleep and decreased in quiet sleep. Future SIDS victims, aged 2 months, had similar frequency of subcortical activations to healthy 3-week-old infants, suggesting a delay in maturation. However, the frequency of cortical arousals was lower in SIDS victims than in healthy infants of both 3 weeks and 3 months, in favor of structural or functional changes, especially at the brainstem level. Moreover, 2–3-month-old infants were less reactive to stimulations than newborn
infants (Newman et al., 1989; Davidson Ward et al., 1990). Twelve percent of infants older than 9 weeks of age and 70% of infants younger than 9 weeks of age aroused in response to hypoxia (Davidson Ward et al., 1992a). These data suggested that, as normal infants mature, their ability to arouse in response to stimuli diminishes by 2–3 months of age. In utero environmental conditions can modify arousal responses. Infants of substance-abusing mothers aroused after longer exposure to hypoxia than control subjects (Davidson Ward et al., 1992b). More infants of cigarette-smoking mothers than control infants failed to awake to environmental challenges (Lewis and Bosque, 1995; Horne et al., 2002a; Chang et al., 2003). Prematurity is also associated with greater arousal thresholds (Horne et al., 2000). Postnatal environmental factors also influence arousability from sleep. Viral infections of the airways (Horne et al., 2002c), administration of sedative drugs (Kahn et al., 1985), previous sleep deprivation (Franco et al., 2004b), sleeping prone (Franco et al., 1998a; Galland et al., 1998; Horne et al., 2001), and sleeping with the face covered (Franco et al., 2002b) or in high ambient temperatures (Franco et al., 2001) increase arousal thresholds. Breast-feeding, pacifier use, and swaddling conditions during sleep, reported to decrease the risk of SIDS, were also associated with lower auditory arousal thresholds (Franco et al., 2000a, 2005; Horne et al., 2004).
PHYSIOPATHOLOGY Alterations in breathing, cardiac, and arousal controls could result from structural or functional changes within the infant’s central nervous system. Pathological and immunohistochemical studies in SIDS infants demonstrated diffuse lesions within different nuclei of the central nervous system, essentially at the brainstem level. It is not known whether these lesions are causes or effects of repeated hypoxic events. Pathological changes described in SIDS victims include brainstem gliosis (Takashima et al., 1978), hypoplasia (Filiano and Kinney, 1992), or apoptosis (Waters et al., 1999). Functional changes could involve specific synaptogenesis or synaptic activities within cardiorespiratory and arousal systems, such as the noradrenergic, serotonergic, dopaminergic, cholinergic, somatostatin, histaminergic, or orexin binding sites (Sparks and Hunsaker, 1991; Carpentier et al., 1998; Obonai et al., 1998; Kinney et al., 2001; Johnson et al., 2005). Abnormalities of serotonergic neurons were shown in the ventral medulla of SIDS victims, in brainstem structures associated with respiratory, cardiovascular, and arousal controls (Kinney et al., 2001).
SUDDEN DEATH IN INFANTS DURING SLEEP In SIDS victims there was a decrease in serotonergic receptor binding in arcuate nucleus but also in raphe nuclei, inferior olive, paragigantocellularis lateralis nucleus, and intermediate zone. These nuclei derived from a common embryologic origin: the rhombic lip (Kinney et al., 2001). Decreased neuronal density in inferior olive in SIDS compared to controls, without increase in density of reactive astrocytes, suggested that SIDS could be due to a developmental abnormality of the ventral network of rhombic lip-derived serotonergic neurons during the first 16–18 weeks of pregnancy (Kinney et al., 2002). This developmental abnormality could be secondary to metabolic, nutritional, toxic insults or genetic susceptibility (Kinney et al., 2002; Weese-Mayer et al., 2003). Recently, brainstem serotonergic deficiency has been reported as one of the potential mechanisms of SIDS (Duncan et al., 2010). Indeed, serotonin (5-HT) levels were 26% lower in SIDS cases compared with age-adjusted controls in two nuclei of the medulla oblongata (raphe obscurus and the paragigantocellularis lateralis). There was no evidence of excessive 5-HT degradation assessed by serotonin metabolites. The biosynthetic enzyme (tryptophan hydroxylase) levels were 22% lower in the SIDS cases compared with controls. Even compared to control infants, SIDS victims had more serotonergic neurons but fewer 5-HT1A receptor bindings (Paterson et al., 2006). Exposure to known risk factors for SIDS, such as male gender (Paterson et al., 2006), tobacco and alcohol exposure in utero (Kinney et al., 2003), decreased the 5-HT1A receptor binding density. Dysregulation in the autonomic nervous system has been recorded in a future SIDS victim whose postmortem investigation later demonstrated brainstem serotoninergic abnormalities (Kinney et al., 2005). Otherwise, cerebellar structures are involved in chemoreception, cardiopulmonary
511
coupling, blood pressure responses, and arousal responses. A central loss of cerebellar control, as hypothesized to occur in SIDS, could have contributed to the death of these infants (Harper and Bandler, 1998).
CONCLUSION These findings could contribute to understand some mechanisms that are factors in the unexpected death of an infant during sleep. An infant could be vulnerable for SIDS because of a deficiency in cardiorespiratory controls during sleep, favoring the development of recurrent episodes of hypoxemia. The risk is increased when the vulnerable infant has a lower propensity to arouse from sleep and to self-resuscitate. The accident has a greater probability of occurring when an infection, or an unfavorable environmental stress factor, aggravates the immature cardiorespiratory and sleep–wake behaviors of the infant. Maturation of cortical arousal process indicates that the critical development period could be a vulnerable period for arousability. Various environmental factors modify the vital cardiocirculatory, respiratory, and arousal controls in healthy infants (Table 33.1). Similar changes in cardiorespiratory and self-resuscitative responses have been found in the analysis of sleep recordings of victims of SIDS. It is not known why some infants died, while others show similar changes but survive the first year of life. The death could be due to the degree of the initial immature controls, to the severity of the additional challenge, or to a combined effect of inadequate self-resuscitative mechanisms and the cumulative influence of infant and/or environmental stressors. To understand why some infants are particularly vulnerable, further studies are required of the neurophysiological mechanisms associated with both normal
Table 33.1 Environmental factors for sudden infant death syndrome (SIDS) Protective factors
Infants exposed to risk factors for SIDS
Prone Breathing controls Obstructive apnea Cardiac autonomic controls Parasympathetic tonus + Orthosympathetic tonus Sleep–wake behavioral controls Arousals +
Maternal smoking
* Ambient temperature
Covered face
*
Sleep deprivation
SIDS victims
*
›
Pacifier Breastfeeding
Swaddling supine
+ *
+
+
+ *
fl ›
*
*
+
+
+
+
fl
*
*
512
P. FRANCO ET AL.
infant development and infants at risk for sudden death. Continuous evaluation is mandatory as risk factors, and protective factors, change with modifications in child-rearing habits and mortality. Most environmental risk factors are modifiable risk factors. They are present in 30–80% of future SIDS victims. Their avoidance contributes to the development of safe sleep environments and reduces the risk for SIDS by the continuous information of health professionals and the public. Special efforts must be addressed to those populations at higher risk, such as those who are poorly influenced by usual prevention campaigns. These include mothers of low education, immigrant families, and families of lower socioeconomic status. Attention should also be focused on most determinant risk factors, such as maternal smoking.
REFERENCES Ackerman MJ, Siu BL, Sturner WQ et al. (2001). Postmortem molecular analysis of SCN5A defects in sudden infant death syndrome. JAMA 286: 2264–2269. American Academy of Pediatrics Task Force on Infant Sleeping Position and SIDS (1992). Pediatrics 89: 1120–1126. Anders T, Sadeh A, Appareddy V (1995). Normal sleep in neonates and children. In: R Ferber, M Kryger (Eds.), Principles and Practice of Sleep Medicine in the child. WB Saunders, pp. 7–18. Anderson ME, Johnson DC, Batal HA (2005). Sudden infant death syndrome and prenatal maternal smoking: rising attributed risk in the Back to Sleep era. BMC Med 11 (3): 4. Arnestad M, Crotti L, Rognum TO et al. (2007). Prevalence of long-QT syndrome gene variants in sudden infant death syndrome. Circulation 115: 361–367. Bajanowski T, Vege A, Byard R et al. (2007). SIDS – standardised investigation and classification. Recommendations. Forensic Sci Int 165: 129–143. Beal SM, Blundell HK (1988). Recurrence of incidence of sudden infant death syndrome. Arch Dis Child 63: 924–930. Beal SM, Finch CF (1991). An overview of retrospective case-control studies investigating the relationship between prone sleeping position and SIDS. J Paediatr Child Health 27: 334–339. Blair P, Ward Platt MP, Smith IJ et al. (2006). Sudden infant death syndrome and sleeping position in pre-term and low birthweight infants: an opportunity for targeted intervention. Arch Dis Child 91: 101–106. Blair PS, Mitchell EA, Heckstall-Smith EM et al. (2008). Head covering - a major modifiable risk factor for sudden infant death syndrome: a systematic review. Arch Dis Child 93: 778–783. Boles RG, Buck EA, Blitzer MG et al. (1998). Retrospective biochemical screening of fatty acid oxidation disorders in
postmortem livers of 418 cases of sudden death in the first year of life. J Pediatr 132 (6): 924–933. Canet E, Gaultier C, D’Allest A et al. (1989). Effects of sleep deprivation on respiratory events during sleep in healthy infants. J Appl Physiol 66: 1158–1163. Carpenter RG, Irgens LM, Blair PS et al. (2004). Sudden unexplained infant death in 20 regions in Europe: case control study. Lancet 363: 185–191. Carpenter RG, Waite A, Daman-Willems C et al. (2005). Repeat sudden unexpected and unexplained infant deaths: natural or unnatural? Lancet 1–7;365: 29–35. Carpentier V, Vaudry H, Mallet E et al. (1998). Increased density of somatostatin bindings sites in respiratory nuclei of the brainstem in sudden infant death syndrome. Neuroscience 86: 159–166. Chang AB, Wilson SJ, Masters IB et al. (2003). Altered arousal response in infants exposed to cigarette smoke. Arch Dis Child 88: 30–33. Chong DSY, Yip PSF, Karlberg J (2004). Maternal smoking: an increasing unique risk factor for sudden infant death syndrome in Sweden. Acta Paediatr 93: 471–478. Cohen G, Han ZY, Grailhe R et al. (2002). Beta 2 nicotinic acetylcholine receptor subunit modulates protective responses to stress: a receptor basis for sleep-disordered breathing after nicotine exposure. Proc Natl Acad Sci U S A 99: 13272–13277. Dales R, Burnett RT, Smith-Doiron M et al. (2004). Air pollution and sudden infant death syndrome. Pediatrics 113: 628–631. Dancea A, Cote A, Rohlicek C et al. (2002). Cardiac pathology in sudden unexpected infant death. J Pediatr 141: 336–342. Davidson Ward SL, Bautista DB, Keens TG (1990). Hypoxic arousal responses in normal infants [abstract]. AARD 141: A 908. Davidson Ward SL, Bautista DB, Keens TG (1992a). Hypoxic arousal responses in normal infants. Pediatrics 89 (5): 860–864. Davidson Ward SL, Bautista DB, Woo MS et al. (1992b). Responses to hypoxia and hypercapnia in infants of substance-abusing mothers. J Pediatr 121: 704–709. deJonge GA, Lanting CI, Brand R et al. (2004). Sudden infant death syndrome in child care settings in the Netherlands. Arch Dis Child 89: 427–430. Dettmeyer R, Baasner A, Schlamann M et al. (2004). Role of virus-induced myocardial affections in SIDS: a prospective postmortem study. Pediatr Res 55: 947–952. Duncan JR, Paterson D, Hoffman JM et al. (2010). Brainstem serotonergic deficiency in sudden infant death syndrome. JAMA 303: 430–437. Dwyer T, Ponsonby AL (1996). The decline of SIDS: a success story for epidemiology. Epidemiology 7: 323–325. Edner A, Wennborg M, Alm B et al. (2007). Why do ALTE infants not die in SIDS? Acta Paediatr 96: 191–194. Emery JL (1959). Epidemiology of “sudden, unexpected, or rapid” deaths in children. Br Med J 7: 925–928. Engelberts AC, de Jong GA (1990). Choice of sleeping position for infants: possible association with cot death. Arch Dis Child 65: 462–467.
SUDDEN DEATH IN INFANTS DURING SLEEP Evans C, Wang J, Neff R et al. (2005). Hypoxia recruits a respiratory-related excitatory pathway to brainstem premotor cardiac vagal neurons in animals exposed to prenatal nicotine. Neuroscience 133: 1073–1079. Fares I, McCulloch KM, Raju TNK (1997). Intrauterine cocaine exposure and the risk for sudden infant death syndrome: a meta-analysis. J Perinatol 17: 179–182. Fewell JE, Smith FG (1998). Perinatal nicotine exposure impairs ability of newborn rats to autoresuscitate from apnea during hypoxia. J Appl Physiol 85: 2066–2074. Filiano JJ, Kinney HC (1992). Arcuate nucleus hypoplasia in the sudden infant death syndrome. J Neuropath Exp Neurol 51: 394–403. Filiano JJ, Kinney HC (1994). A perspective on neuropathologic findings in victims of the sudden infant death syndrome: the triple-risk model. Biol Neonate 65: 194–197. Firstman R, Talan J (2001). SIDS and infanticide. In: RW Byard, HF Krous (Eds.), Sudden Infant Death Syndrome. Arnold, London, pp. 291–300. Fleming PJ, Gilbert R, Aza Y et al. (1990). Interaction between bedding and sleeping position in the sudden infant death syndrome: a population based case-control study. Br Med J 301: 85–89. Fleming PJ, Blair PS, Berry J et al. (2000). Potentially modifiable risk factors of SIDS. In: P Fleming (Ed.), Sudden Unexpected Deaths in Infancy: The CESDI SUDI Studies 1993–1996. The Stationery Office (HMSO), London, pp. 20–21. Ford RP, Hassall IB, Mitchell EA et al. (1996). Life events social support and the risk of sudden infant death syndrome. J Child Psychol Psychiatry 37: 835–840. Forsyth L, Hume R, Howatson A et al. (2005). Identification of novel polymorphisms in the glucokinase and glucose6-phosphatase genes in infants who died suddenly and unexpectedly. J Mol Med 83: 610–618. Franco P, Kahn A, Groswasser J et al. (1996). Decreased cardiac responses to auditory stimulation during prone sleep. Pediatrics 97: 174–178. Franco P, Pardou A, Hassid S et al. (1998a). Auditory arousal thresholds are higher when infants sleep in the prone position. J Pediatr 132: 240–243. Franco P, Szliwowski H, Dramaix M et al. (1998b). Polysomnographic study of the autonomic nervous system in potential victims of sudden infant death syndrome. Clin Auton Res 8: 243–249. Franco P, Groswasser J, Hassid S et al. (1999). Prenatal exposure to cigarette smoking is associated with a decrease in arousal in infants. J Pediatr 135: 34–48. Franco P, Scaillet S, Wermembol V et al. (2000a). The influence of a pacifier on infants’ arousals from sleep. J Pediatr 136: 775–779. Franco P, Szliwowski H, Dramaix M et al. (2000b). Influence of ambient temperature on sleep characteristics and autonomic nervous control in healthy infants. Sleep 23: 401–407. Franco P, Scaillet S, Valente F et al. (2001). Ambient temperature is associated with changes in infants’arousability form sleep. Sleep 24: 325–329.
513
Franco P, Lipshut W, Valente F et al. (2002a). Cardiac autonomic characteristics in infants sleeping with the head covered by bedclothes. Pediatr Res 109: 1112–1127. Franco P, Lipshutz W, Valente F et al. (2002b). Decreased arousals in infants sleeping with the face covered by bedclothes. Pediatrics 109: 112–117. Franco P, Seret N, Van Hees JN et al. (2003). Cardiac autonomic changes during sleep in sleep-deprived infants. Sleep 26: 845–848. Franco P, Chabanski S, Scaillet S et al. (2004a). Pacifier use modifies infant’s cardiac autonomic controls during sleep. Early Hum Develop 77: 99–108. Franco P, Seret N, Van Hees JN et al. (2004b). Decreased arousals in healthy infants following short-term sleep deprivation. Sleep 114: e192–e197. Franco P, Scaillet S, Groswasser J et al. (2004c). Increased cardiac autonomic responses to auditory challenges in swaddled infants. Sleep 15: 1527–1532. Franco P, Seret N, Van Hees JN et al. (2005). The influence of swaddling on sleep and arousal characteristics in healthy infants. Pediatrics 115: 1307–1311. Franco P, Groswasser J, Scaillet S et al. (2008). QT interval prolongation in future SIDS victims: a polysomnographic study. Sleep 31: 1691–1699. Friend KB, Goodwin MS, Lipsitt LP (2004). Alcohol use and sudden infant death syndrome. Developmental Review 24: 235–251. Froggatt P (1970). Epidemiologic aspects of the Northern Ireland study. In: AS Bergman, JB Beckwith, CG Ray (Eds.), Proceedings of the Second International Conference on Causes of Sudden Infant Death. University of Washington Press, Seattle, pp. 32–46. Galland BC, Reeves G, Taylor BJ et al. (1998). Sleep position, autonomic function, and arousal. Arch Dis Child Neonatal Ed 78: F189–F194. Getahun D, Amre D, Rhoads GG et al. (2004). Maternal and obstetric risk factors for sudden infant death syndrome in the United States. Obstet Gynecol 103: 646–652. Gilbert R (1994). The changing epidemiology of SIDS. Br Med J 70: 445–449. Gilbert R, Rudd P, Berry PJ et al. (1992). Combined effect of infection and heavy wrapping on the risk of sudden unexpected infant death. Arch Dis Child 67: 171–177. Glotzbach SF, Ariagno RL, Harper RM (1995). Sleep and the sudden infant death syndrome. In: R Ferber, M Kryger (Eds.), Principles and Practice of Sleep Medecine in the Child. WB Saunders, Philadelphia, pp. 231–244. Grether J, Schulman J (1990). Sudden infant death syndrome among Asians in California. J Pediatr 522: 520–524. Groswasser J, Simon T, Scaillet S et al. (2001). Reduced arousals following obstructive apneas in infants sleeping prone. Pediatr Res 402–406. Guilleminault C, Stoohs R (1992). From apnea of infancy to obstructive sleep apnea syndrome in the young child. Chest 102: 1065–1071. Guilleminault C, Ariagno RL, Forno LS et al. (1979). Obstructive sleep apneas and near miss SIDS: I. Report of an infant with sudden death. Pediatrics 63: 837–843.
514
P. FRANCO ET AL.
Hafstro¨m O, Milerad J, Sundell HW (2002). Altered breathing pattern after prenatal nicotine exposure in the young lamb. Am J Respir Crit Care Med 166: 92–97. Hafstro¨m O, Milerad J, Sandberg KL et al. (2005). Cardiorespiratory effects of nicotine exposure during development. Resp Phys Neurobiol 149: 325–341. Haglund B, Cnattingius S (1990). Cigarette smoking as a risk factor for sudden death syndrome: a population-based study. Am J Public Health 80: 29–32. Hanrahan JP, Tager IB, Segal MR et al. (1992). The effect of maternal smoking during pregnancy on early infant lung function. Am Rev Respir Dis 145: 1129–1135. Harper RM, Bandler R (1998). Finding the failure mechanism in sudden infant death syndrome. Nat Med 4: 157–158. Hauck FR (2001). Changing epidemiology. In: RW Byard, HF Krous (Eds.), Sudden Infant Death Syndrome. Problems, Progress and Possibilities. Arnold, London, pp. 31–57. Hauck FR, Omojokun OO, Siadaty MS (2005). Do pacifiers reduce the risk of sudden infant death syndrome? A metaanalysis. Pediatrics 116: e716–e723. Heininger U, Kleemann WJ, Cherry JD et al. (2004). A controlled study of the relationship between Bordetella pertussis infections and sudden unexpected deaths among German infants. Pediatrics 114: 9–15. Hill SAR, Hjelmeland B, Johannessen NM et al. (2004). Changes in parental risk behavior after an information campaign against sudden infant death syndrome (SIDS) in Norway. Acta Paediatr 93: 205–254. Hoffman HJ, Hillman LS (1992). Epidemiology of the sudden infant death syndrome: maternal, neonatal, and postnatal risk factors. In: CE Hunt (Ed.), Clinics in Perinatology: Apnea and SIDS. WB Saunders, Philadelphia, pp. 717–738. Holgert H, Hokfelt T, Hertzberg T et al. (1995). Functional and developmental studies of the peripheral arterial chemoreceptors in rat: effects of nicotine and possible relation to sudden infant death syndrome. Proc Natl Acad Sci U S A 92: 7575–7579. Horne RSC, Sly DJ, Cranage SM et al. (2000). Effects of prematurity on arousal from sleep in the newborn infant. Pediatr Res 47: 468–474. Horne RSC, Ferens D, Watts AM et al. (2001). The prone sleep impairs arousability in healthy term infants. J Pediatr 138: 811–816. Horne RSC, Ferens D, Watts A-M et al. (2002a). Maternal tobacco smoking impairs arousal in healthy term infants sleeping supine. Arch Dis Child Fetal Neonatal Ed 87: F100–F105. Horne RS, Franco P, Adamson TM et al. (2002b). Effects of body position on sleep and arousal characteristics in infants. Early Hum Dev 69: 25–33. Horne RS, Osborne A, Vitkovic J et al. (2002c). Arousal from sleep in infants is impaired following an infection. Early Hum Dev 66: 89–100. Horne RS, Parslow PM, Ferens D et al. (2004). Comparison of evoked arousability in breast and formula fed infants. Arch Dis Child 89 (1): 22–25.
Hunt C (1992). Sudden infant death syndrome. In: RC Beckerman, RT Brouillette, CE Hunt (Eds.), Respiratory Control Disorders in Infants and Children. Williams and Wilkins, Baltimore, pp. 190–211. International Classification of Diseases: ninth revision (ICD-9) (1978). Ann Intern Med 88 (3): 424–426. Iyasu S, Randall LL, Welty TK et al. (2002). Risk factors for sudden infant death syndrome among northern plains Indians. JAMA 288: 2717–2723. Johnson PL, Moratalla R, Lightman SL et al. (2005). Are tuberomammillary histaminergic neurons involved in CO2-mediated arousal? Exp Neurol 193: 228–233. Jones KL, Krous HF, Nadeau J et al. (2003). Vascular endothelial growth factor in the cerebrospinal fluid of infants who died of sudden infant death syndrome: evidence for antecedent hypoxia. Pediatrics 111: 358–363. Kahn A (2004). Recommended clinical evaluation of infants with an apparent life-threatening event. Consensus document of the European Society for the Study and Prevention of Infant Death, 2003. Eur J Pediatr 163: 108–115. Kahn A, Blum D, Hennart P et al. (1984). A critical comparison of the history of sudden-death infants and infants hospitalised for near-miss for SIDS. Eur J Pediatr 143: 103–107. Kahn A, Hasaerts D, Blum D (1985). Phenothiazine-induced sleep apneas in normal infants. Pediatrics 75: 844–847. Kahn A, Blum D, Muller F et al. (1986). Sudden infant death syndrome in a twin: comparison of sibling histories. Pediatrics 78: 146–150. Kahn A, Rebuffat E, Sottiaux M et al. (1991). Prevention of airway obstructions during sleep in infants with breathholding spells by means of oral belladonna: a prospective double-blind crossover evaluation. Sleep 14: 432–438. Kahn A, Groswasser J, Rebuffat E et al. (1992). Sleep and cardiorespiratory characteristics of infant victims of sudden death: a prospective case-control study. Sleep 15: 287–292. Kahn A, Groswasser J, Sottiaux M et al. (1994). Prenatal exposure to cigarettes in infants with obstructive sleep apneas. Pediatrics 93: 778–783. Kahn A, Bauche P, Groswasser J et al. (2001). Maternal education and risk factors for sudden death in infants. Eur J Pediatr 160: 505–508. Kato I, Franco P, Groswasser J et al. (2000). Prevalence of obstructive and mixed sleep apneas in 1023 infants. Sleep 23: 487–492. Kato I, Groswasser J, Franco P et al. (2001). Developmental characteristics of apnea in infants who succumb to sudden infant death syndrome. Am J Respir Crit Care Med 164: 1464–1469. Kato I, Franco P, Groswasser J et al. (2003). Incomplete arousal processes in infants who were victims of sudden death. Am J Respir Crit Care Med 168: 1298–1303. Kemp JS, Livne M, White DK et al. (1998). Softness and potential to cause rebreathing: differences in bedding used by infants at high and low risk for sudden infant death syndrome. J Pediatr 132 (2): 234–239.
SUDDEN DEATH IN INFANTS DURING SLEEP Kiechl-Kohlendorfer U, Hof D, Peglow UP et al. (2005). Epidemiology of apparent life threatening events. Arch Dis Child 90 (3): 297–300. Kinney HC, O’Donnell TJ, Kriger P et al. (1993). Early developmental changes in [3H]nicotine binding in the human brainstem. Neuroscience 55: 1127–1138. Kinney HC, Filiano JJ, White WF (2001). Medullary serotonergic network deficiency in the sudden infant death syndrome: review of a 15-year study of a single dataset. J Neuropathol Exp Neurol 60: 228–247. Kinney HC, McHugh T, Miller K et al. (2002). Subtle developmental abnormalities in the inferior olive: an indicator of prenatal brainstem injury in the sudden infant death syndrome. J Neuropathol Exp Neurol 61: 427–441. Kinney HC, Randall LL, Sleeper LA et al. (2003). Serotonergic brainstem abnormalities in Northern Plains Indians with the sudden infant death syndrome. J Neuropathol Exp Neurol 62: 1178–1191. Kinney HC, Myers MM, Belliveau RA et al. (2005). Subtle autonomic and respiratory dysfunction in sudden infant death syndrome associated with serotonergic brainstem abnormalities: a case report. J Neuropathol Exp Neurol 64: 689–694. Klonoff-Cohen HS, Edelstein SL, Lefkowitz ES et al. (1995). The effect of passive smoking and tobacco exposure through breast milk on sudden infant death syndrome. JAMA 273: 795–798. Klonoff-Cohen H, Lam PK, Lewis A (2005). Outdoor carbon monoxide, nitrogen dioxide, and sudden infant death syndrome. Arch Dis Child 90: 750–753. Kluge AK, Harper RM, Schechtman VL et al. (1988). Spectral analysis assessment of respiratory sinus arrhythmia in normal infants and infants who subsequently died of sudden infant death syndrome. Pediatr Res 24: 677–682. Krous HF, Beckwith JB, Byard RW et al. (2004). Sudden infant death syndrome and unclassified sudden infant deaths: a definitional and diagnostic approach. Pediatrics 114: 234–238. Larsen TB, Norgaard-Pedersen B, Lundemose JB et al. (2000). Sudden infant death syndrome, childhood thrombosis, and presence of genetic risk factors for thrombosis. Thromb Res 98: 233–239. Lewis KW, Bosque EM (1995). Deficient hypoxia awakening response in infants of smoking mothers: possible relationship to sudden infant death syndrome. J Pediatr 127: 691–699. L’Hoir MP, Engelberts AC, van Well GT et al. (1998). Risk and preventive factors for cot death in Nederlands, a lowincidence country. Eur J Pediatr 157: 681–688. Lipsitt LP (2003). Crib death: a biobehavioral phenomenon? Current Directions in Psychological Science 12: 164–170. Little RE, Peterson DR (1990). Sudden infant death syndrome epidemiology: a review and update. Epidemiol Rev 12: 241–245. Louis J, Cannard C, Bastuji H et al. (1997). Sleep ontogenesis revisited: a longitudinal 24-hour home polygraphic study on 15 normal infants during the first two years of life. Sleep 20: 323–333.
515
Lown B, Verrier RL (1976). Neural activity and ventricular fibrillation. N Engl J Med 294: 1165–1170. McGarvey C, McDonnell M, Hamilton K et al. (2006). An eight-year study of risk factors for SIDS: bed-sharing vs. non bed-sharing. Arch Dis Child 91: 318–323. McGraw MB (1976). The Neuromuscular Maturation of the Human Infant. Hafner (Columbia), New York, pp. 33–36. Meadow R (1999). Unnatural sudden infant death. Arch Dis Child 80: 7–14. Mitchell EA, Thompson JMD (1995). Co-sleeping increases the risk of SIDS, but sleeping in the parents’ bedroom lowers it. In: TO Rognum (Ed.), Sudden Infant Death Syndrome, New Trends in the Nineties. Scandinavian University Press, Oslo, pp. 266–269. Mitchell EA, Thompson JMD (2001). Parental reported apnoea, admissions to hospital and sudden infant death syndrome. Acta Paediatr 90: 417–422. Mitchell EA, Stewart AW, Cowan SF (1992a). Sudden infant death syndrome and weather temperature. Paediatr Perinat Epidemiol 6: 19–28. Mitchell EA, Taylor BJ, Ford RP et al. (1992b). Four modifiable and other major risk factors for cot death: the New Zealand Study. J Paediatr Child Health 28: 3–8. Mitchell EA, Ford RP, Stewart AW et al. (1993a). Smoking and the sudden infant death syndrome. Pediatrics 91: 893–896. Mitchell EA, Taylor BJ, Ford RPK et al. (1993b). Dummies and the sudden infant death syndrome. Arch Dis Child 68: 501–504. Mitchell EA, Brunt JM, Everard C (1994). Reduction in mortality from sudden infant death syndrome in New Zealand: 1986–92. Arch Dis Child 70 (4): 291–294. Mitchell EA, Thompson JM, Becroft DM et al. (2008). Head covering and the risk for SIDS: findings from the New Zealand and German SIDS case-control studies. Pediatrics 121 (6): e1478–e1483. Montemitro E, Franco P, Scaillet S et al. (2008). Maturation of spontaneous arousals in healthy infants. Sleep 31: 47–54. Moon RY, Sprague BM, Patel KM (2005). Stable prevalence but changing risk factors for sudden infant death syndrome in child care settings in 2001. Pediatrics 116: 972–977. Nakamura S, Wind M, Danello MA (1999). Review of hazards associated with children placed in adult beds. Arch Pediatr Adolesc Med 153: 1019–1023. Narita N, Narita M, Takashima S et al. (2001). Serotonin transporter gene variation is a risk factor for sudden infant death syndrome in the Japanese population. Pediatrics 107: 690–692. Navarro HA, Seidler FJ, Schwartz RD et al. (1989). Prenatal exposure to nicotine impairs nervous system development at a dose which does not affect viability or growth. Brain Res Bull 23: 187–192. Neff RA, Simmens SJ, Evans C et al. (2004). Prenatal nicotine exposure alters central cardiorespiratory responses to hypoxia in rats: implications for sudden infant death syndrome. J Neurosci 4: 9261–9268.
516
P. FRANCO ET AL.
Newman NM, Trinder JA, Phillips KA et al. (1989). Arousal deficit: mechanisms of the sudden infant death syndrome? Aust Paediatr J 25: 196–201. Obonai T, Yasuhara M, Nakamura T et al. (1998). Catecholamine neurons alteration in the brainstem of sudden infant death syndrome victims. Pediatrics 101: 285–288. Opdal SH, Rognum TO (2004). The sudden infant death syndrome gene: does it exist? Pediatrics 144: e506–e512. Oyen H, Markstead T, Skjaerven R et al. (1997). Combined effects of sleeping position and the perinatal risk factors in sudden infant death syndrome: the Nordic epidemiological SIDS study. Pediatrics 100: 613–621. Paluszynska D, Harris K, Thach B (2004). Influence of sleep position experience on ability of prone-sleeping infants from asphyxiating microenvironements by changing head position. Pediatrics 114: 1634–1639. Paterson DS, Trachtenberg FL, Thompson EG et al. (2006). Multiple serotonergic brainstem abnormalities in sudden infant death syndrome. JAMA 296: 2124–2132. Pickett KE, Luo Y, Lauderdale DS (2005). Widening social inequalities in risk for sudden infant death syndrome. Am J Public Health 95: 1976–1981. Ponsonby AL, Dwyer T, Gibbons LE et al. (1992). Thermal environment and sudden infant death syndrome: casecontrol study. Br Med J 304: 277–282. Porges SW (1992). Vagal tone: a physiologic marker of stress vulnerability. Pediatrics 90: 498–504. Rognum TO (2001). Definition and pathologic features. In: RW Byard, HF Krous (Eds.), Sudden Infant Death Syndrome. Problems, Progress and Possibilities. Arnold, London, pp. 4–30. Schechtman VL, Harper RM, Kluge KA et al. (1988). Cardiac and respiratory patterns in normal infants and victims of the sudden infant death syndrome. Sleep 11: 413–424. Schechtman VL, Harper RM, Wilson AJ et al. (1991). Sleep apnea in infants who succumb to the sudden infant death syndrome. Pediatrics 87: 841–846. Schechtman V, Harper RM, Wilson JW et al. (1992). Sleep state organization in normal infants and victims of the sudden infant death syndrome. Pediatrics 89: 865–870. Scheers NJ, Mitchell Dayton C, Kemp JS (1998). Sudden infant death with external airways covered: casecomparison study of 206 deaths in the United States. Arch Pediatr Adolesc Med 152: 540–547. Schwartz PJ, Billman GE, Stone HL (1984). Autonomic mechanisms in ventricular fibrillation induced by myocardial ischemia during exercise in dogs with a healed myocardial infarction. An experimental preparation for sudden cardiac death. Circulation 69: 780–790. Schwartz PJ, Stramba-Badiale M, Segantini P et al. (1998). Prolongation of the QT interval and the sudden infant death syndrome. N Engl J Med 338: 1709–1714. Scragg RK, Mitchell EA (1998). Side sleeping position and bed-sharing in the sudden infant death syndrome. Ann Med 30: 345–349. Shatz A, Hiss J, Arensburg B (1991). Basement membrane thickening of the vocal cords in sudden infant death syndrome. Laryngoscope 101: 484–486.
Shaul PW, Cha CM, Oh W (1989). Neonatal sympathoadrenal responses to acute hypoxia: impairment after experimental intrauterine growth retardation. Pediatr Res 25: 466–472. Slotkin TA (2004). Cholinergic systems in brain development and disruption by neurotoxicants: nicotine, environmental tobacco smoke, organophosphates. Toxicol Appl Pharmacol 198: 132–151. Slotkin TA, Epps TA, Stenger ML et al. (1999). Cholinergic receptors in heart and brainstem of rats exposed to nicotine during development: implications for hypoxia tolerance and perinatal mortality. Brain Res Dev Brain Res 113: 1–12. Smith GSC, Wood AM, Pell JP et al. (2004). Secondtrimester maternal serum levels of alpha-fetoprotein and the subsequent risk of SIDS. N Engl J Med 351: 978–986. Sparks DL, Hunsaker JC (1991). Sudden infant death syndrome: altered aminergic-cholinergic synaptic markers in hypothalamus. J Child Neurol 6: 335–339. Stanton AN (1984). Overheating. Lancet 24: 1199–1201. Stern E, Parmelee AH, Akiyama Y et al. (1969). Sleep cycle characteristics in infants. Pediatrics 43: 65–70. Sullivan CE, Grunstein RR, Marrone O (1990). Sleep apneapathophysiology: upper airway and control of breathing. In: C Guilleminault, M Partinnen (Eds.), Obstructive Sleep Apnea Syndrome: Clinical Research and Treatment. Raven Press, New York, pp. 49–69. Sutton D, Taylor EM, Lindeman RC (1978). Prolonged apnea in infant monkeys resulting from stimulation of superior laryngeal nerve. Pediatrics 61: 519–527. Swift PG, Emery JL (1973). Clinical observations on responses to nasal occlusion in infancy. Arch Dis Child 48: 947–951. Takashima S, Armstrong D, Becker LE et al. (1978). Cerebral hypoperfusion in the sudden infant death syndrome? Brainstem gliosis and vasculature. Ann Neurol 4: 257–262. Tappin D, Ecob R, Brooke H (2005). Bedsharing, roomsharing, and sudden infant death syndrome in Scotland: a case-control study. J Pediatr 147 (1): 32–37. Thach BT, Mitchell EA, Thompson JMD et al. (1998). Changing infant’s death position increases risk of sudden infant death syndrome. J Investig Med 46: 260A. Tonkin S (1975). Sudden infant death syndrome: hypothesis of causation. Pediatrics 55: 650–660. Valdes-Dapena MA (1980). Sudden infant death syndrome: a review of the medical literature 1974–79. Pediatrics 66: 597–614. Valdes-Dapena M (1992). The sudden infant death syndrome: pathologic findings. In: CE Hunt (Ed.), Clinics in Perinatology: Apnea and SIDS. WB Saunders, Philadelphia, pp. 701–717. Vennemann MM, Findeisen M, Butterfass-Bahloul T et al. (2005). Infection, health problems, and health care utilisation, and the risk of sudden infant death syndrome. Arch Dis Child 90 (5): 520–522. Vernacchio L, Corwin MJ, Lesko SM et al. (2003). Sleep position of low birth weight infants. Pediatrics 111: 633–640. Waters K, Meehan B, Huang J et al. (1999). Neuronal apoptosis in sudden infant death syndrome. Pediatr Res 45: 166–172.
SUDDEN DEATH IN INFANTS DURING SLEEP Weese-Mayer DE, Zhou L, Berry-Kravis EM et al. (2003). Association of the serotonin transporter gene with sudden infant death syndrome: a haplotype analysis. Am J Med Genet A 122: 238–245. Wigfield R, Gilbert R, Fleming PJ (1994). SIDS: risk reduction measures. Hum Dev 38: 161–164. Wilcox RL, Nelson CC, Stenzel P et al. (2002). Postmortem screening for fatty acid oxidation disorders by analysis of Guthrie cards with tandem mass spectrometry in sudden unexpected death in infancy. J Pediatr 141: 833–836.
517
Willinger M, James LS, Catz C (1991). Defining the sudden infant death syndrome (SIDS): deliberations of an expert panel convened by the National Institute of Child Health and Human Development. Pediatr Pathol 11: 677. Wilson CA, Taylor BJ, Laing RM et al. (1994). Clothing and bedding and its relevance to sudden infant death syndrome: further results from the New Zealand Cot Death Study. J Pediatr Child Health 30: 506–512. Yuan SZ, Runold M, Lagercrantz H (1997). Adrenalectomy reduces the ability of newborn rats to gasp and survive anoxia. Acta Physiol Scand 159: 285–292.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 34
Neurobiology and the neurological basis of dreaming MARK SOLMS * Department of Psychology, University of Cape Town, Rondebosch, South Africa
BACKGROUND Understanding the brain mechanisms of dreaming has lagged behind that of other mental functions. There are two main reasons for this. First, unlike most phenomena that were the focus of 19th- and 20th-century behavioral neuroscience, dreaming is almost entirely subjective. The observable data are retrospective, single-witness verbal descriptions, only indirectly related to dreaming itself. This poses special methodological problems. The second reason for the undeveloped state of this field is closely related to the first. Researchers seeking an objective marker of dreaming eagerly alighted on a physiological state that correlates closely with it – rapid eye movement (REM) sleep (Aserinsky and Kleitman, 1953, 1955; Dement and Kleitman, 1957a, b) – which was then conflated with dreaming itself. This resulted in the development of neuropsychological models of dreaming which were in fact models of REM sleep (Hobson and McCarley, 1977). This conflation was confounded by the fact that the models were empirically grounded in animal studies (where dream reports are precluded) rather than human lesion studies of the kind that informed neuropsychological models of most other mental functions. When the conventional human lesion studies were eventually performed, it became apparent that dreaming and REM sleep were in fact doubly dissociable states (Solms, 2000). A traditional neuropsychology, grounded in the systematic application of clinicoanatomical correlation, which was widely applied to other mental functions since the mid 19th century, is little more than 20 years old in the case of dreaming. Incidental reports of changes in dreaming associated with focal cerebral damage did nevertheless accumulate over a long period, albeit without any systematic attempt to synthesize the
scattered observations into a coherent picture. The available evidence was not comprehensively reviewed before the 1990s (Solms, 1991, 1997; Doricchi and Violani, 1992). Clinicoanatomical group comparisons were first published a decade earlier (Cathala et al., 1983; Murri et al., 1984, 1985). The clinicoanatomical studies have since been complemented by a slew of functional brain imaging studies, with strongly convergent findings (PaceSchott and Hobson, 1998).
CLINICOANATOMICAL FINDINGS Charcot–Wilbrand syndrome The concept of Charcot–Wilbrand syndrome, based on two case reports by Charcot (1883, 1889) and Wilbrand (1887, 1892), was first articulated by Po¨tzl (1928). He defined the syndrome as “mind-blindness with disturbance of optic imagination” (p. 306). Nielsen (1946) defined it as “visual agnosia plus loss of the ability to revisualize” (p. 74). Critchley’s (1953) widely cited definition was: a patient loses the power to conjure up visual images or memories, and furthermore, ceases to dream during his sleeping hours (p. 311). Critchley described proposagnosia and topographical agnosia or amnesia as associated features. The localization of the lesion producing this syndrome was never precisely defined, but the occipital cortex was implicated by most early authors (especially area 19), usually bilaterally. The Charcot–Wilbrand syndrome remained in late 20th-century nosographical usage, although the condition was (until recently) considered rare. A modern definition of the syndrome reads: the association of loss of the ability to conjure up visual images or memories and the loss of
*Correspondence to: Professor Mark Solms, Department of Psychology, University of Cape Town, Private Bag, Rondebosch 7700, South Africa. Tel: þ2721 6503437, E-mail:
[email protected]
520
M. SOLMS
dreaming . . . [indicating] a lesion in an acute phase affecting the posterior regions (Murri et al., 1984, p. 185). Deficient revisualization (called “irreminiscence” in the nomenclature of Nielsen (1946)) was the fundamental symptom in almost all definitions of the syndrome. Cessation of dreaming (“or at least, an alteration in the vivid visual component of the dreaming state”; Critchley, 1953, p. 311) was seen as a secondary consequence of the visual imagery deficit. The associated visual agnosias, too, were originally considered to be secondary consequences of defective revisualization, since visual agnosia was classically understood as a loss of “visual memory images” (Munk, 1878; Lissauer, 1890). Subsequent advances in the agnosia concept, and a misreading of the original case reports, has resulted in considerable nosological confusion regarding this syndrome (Solms et al., 1996). It is widely assumed that Wilbrand’s case could not visualize familiar places (Nielsen, 1946; Critchley, 1953; Gloning and Sternbach, 1953; Farah et al., 1988). However, the original report stated only that she was unable to recognize those places. This symptom (which we would today call topographical agnosia) was conceptualized, in accordance with classical theory, as a disorder of “topographical memory” (Wilbrand, 1887, p. 52, emphasis added). This conceptualization was then misconstrued by secondary authors as a disorder of topographical revisualization. The original report reveals that Wilbrand’s case lacked the cardinal feature of the so-called Charcot–Wilbrand syndrome. As the patient herself clearly stated: With my eyes shut I see the old Hamburg in front of me again (Wilbrand, 1887). Charcot’s case was quite different. He described a striking absence of visual mental imagery. The Charcot– Wilbrand syndrome is therefore misnamed. It is also misconceived. Charcot’s patient ceased to dream in visual images, but he continued to dream in words. Wilbrand’s patient on the other hand dreamed “almost not at all any more” (Wilbrand, 1887, p. 54). The original report is ambiguous as to whether Wilbrand’s patient merely dreamed infrequently or lost the capacity to dream completely (and then gradually recovered it); but in either case, there is no question of an isolated loss of visual dream imagery, which is what Charcot’s patient unequivocally described. The Charcot–Wilbrand syndrome therefore appears to be two different (but related) syndromes, one characterized by loss of visual dream imagery and the other by global cessation or suppression of dreaming. This distinction is supported by a review of the world literature (Solms, 1997).
Charcot’s variant: isolated loss of visual dream imagery At least 10 case reports of isolated loss of visual dream imagery have been published, together with five further reports of patients who experienced submodal deficits of specific aspects of visual dream imagery (e.g., faces, color, movement). These cases are summarized in Table 34.1. Defective revisualization (irreminiscence) is a constant feature in the cases, although it is typically restricted to the affected aspect of vision in cases where the loss of visual dream imagery is submodal. This strongly suggests a common underlying image generation deficit causing the same disorder in both waking and dreaming cognition. Various forms of visual agnosia are commonly associated features, but agnosia is definitely absent in some cases and therefore cannot be considered integral to the syndrome. The lesion responsible for isolated loss of visual dream imagery usually affects the occipital lobe, frequently bilaterally, but precise localizing information is lacking in most reports. Most published reports of changes in visual dream imagery derive from retrospective accounts in clinical settings. However, the reports have been confirmed upon REM awakening in at least 3 cases (Efron, 1968; Brown, 1972; Kerr et al., 1978).
Negative findings Interestingly, modality-specific deficits of dream imagery outside the higher visual sphere cannot be demonstrated. Cortically blind and hemianopic patients report full visual fields in their dreams. Hemiplegic patients experience normal somatomotor and somatosensory function in their dream imagery. Nonfluent aphasics speak normally in their dreams (Solms, 1997). Of related interest, perhaps, is the fact that the dreams of patients with substantial impairments of executive function due to dorsolateral prefrontal lesions are indistinguishable from the dreams of controls (Badenhorst and Solms, unpublished, 2006). These findings point to a differentiated network of forebrain structures involved in dream cognition – a conclusion to which we shall return below.
Wilbrand’s variant: global loss or suppression of dreaming At least 106 cases of global loss or suppression of dreaming have been reported, excluding leukotomy cases, which will be discussed separately. (This also excludes a large number of patients in group studies, for which individual case data were lacking, and “not dreaming” was defined in variable ways: Cathala et al., 1983; Murri et al., 1984, 1985.)
Table 34.1 Cases of cessation or restriction of visual dream imagery Case
Lesion
Irreminiscence
Dreams
Charcot (Bernard) (1883)
Monsieur X
þ
Cessation of visual imagery
Gru¨nstein (1924) Adler (1944, 1950); Sparr et al. (1991)
Patient N., 23y F H.C., 22y F
No information ? Bilateral medial occip. temp. (thrombosis) L. lat occip.* (thrombosis) Bilat. Occip. par.* (CO poisoning)
þ þ
Brain (1950, 1954) Gloning and Sternbach (1953) Macrae and Trolle (1956) Tzavaras (1967) Efron (1968); Benson and Greenberg (1969); Brown (1972)
Case 1, 36y M W. Josef, 53y M 32y M Monsieur P. Maurice, 54y 25y M (Brown’s case 13)
Front. occip.* (trauma) L.{ thalam* (hemorrhage) Bilat. par.* (trauma) L. occip. temp., R. temp.* (hemorrhage) Bilat. occip. par.* (CO poisoning)
þ þ þ for faces þ
Kerr et al. (1978) Botez et al. (1985)
21y F 38y M
?R. par.* (not localizable) (Turner’s syndrome) ?R.{ hemisphere, ?Corp. callosum (?dysgenesis)}
þ þ
Sacks (1985) Sacks and Wasserman (1987) Sacks (1991)
Dr. P., M Jonathan I., 65y M
“Visual parts of his brain” (tumor or atrophy) Bilat. med. occip. temp. (trauma)
? þ for color
No information
(No information) k
Solms (1997)
Patient 201, 26y F Patient 208, 31y M
“Diffuse damage to the occipital cortex”* (Alzheimer’s disease) R. par. (AVM){} R. med. occip. temp. (astrocytoma){}
Cessation of visual imagery Cessation of visual imagery, with subsequent global cessation of dreaming Cessation of visual imagery Cessation of visual imagery Cessation of visual imagery Cessation of facial imagery Nonvisual nightmares for 1 week; residual cessation of visual imagery or global cessation of dreaming (descriptions ambiguous)} Absence of visual imagery Reduction or absence of facial imagery (description ambiguous) and absence of hypnagogic imagery Cessation of visual imagery Cessation of color imagery and reduction of tonal gradation Cessation of visual imagery
þ þ for faces and spatial relationships
Cessation of visual imagery Cessation of kinetic imagery
521
y, years; F, female; M, male; CO, carbon monoxide; AVM, arteriovenous malformation. *Clinical localization or diagnosis. {Left-handed or ambidextrous patient. {Localization or diagnosis based on intraoperative observation. }Localization or diagnosis based on in vivo imaging techniques. k Unless otherwise indicated, it is assumed that the authors comprehensively investigated and reported the neuropsychological status of their cases. } Benson and Greenberg (1969, p.85) described this patient as a case of global cessation of dreaming and reported that “the patient denied dreaming” upon rapid eye movement (REM) awakening, whereas Brown (1972, p. 210) stated that “a REM study was normal in character but revealed absence of visual elements in his dream” (italics added).
NEUROBIOLOGY AND THE NEUROLOGICAL BASIS OF DREAMING
Source
522 M. SOLMS The 106 cases are summarized in Table 34.2. Defeceffects, may help explain the imprecise localization tive revisualization (irreminiscence) is a common but of the associated lesion. by no means invariable feature of these cases. It was overrepresented in the earlier case reports for the probCessation or suppression of dreaming able reason that patients were only asked about their following prefrontal leukotomy dreams once irreminiscence had been established. The In a survey of 200 cases of prefrontal leukotomy, more recent cases reported by Solms (1997) were part Frank (1946) observed that a common result of the of an unselected clinical series and are therefore more procedure was “a poverty or entire lack of dreams” likely to be representative. Global cessation of dream(p. 508). In a later report on the same series of cases, ing (unlike visually deficient dreaming) therefore canthen comprising more than 300 patients, he confirmed not be reduced to irreminiscence. his observation, adding that dreaming was typically No other single cognitive deficit has been identified “simplified” in leukotomy cases with preserved dreamthat discriminates statistically between global nondreaing (Frank, 1950, p. 38). Replication of these findings mers and dreamers, apart from visuospatial short-term was forthcoming from other authors (Table 34.3). Jus memory disorder, which is also not an invariable feature et al. (1973) confirmed the absence of dream reports (Solms, 1997). The lack of association between cessation on REM awakening. of dreaming and long-term memory disorder of any In apparent contradiction to these reports, however, kind excludes the possibility that cessation of dreaming Humphrey and Zangwill (1951), Cathala et al. (1983), is really a disorder of episodic memory – failure to Murri et al. (1984, 1985), and Doricchi and Violani remember dreams as opposed to loss of dreaming (1992) all observed a relatively low incidence of cessaper se (Feinberg, 2000; LaBerge, 2000; Ogilvie et al., tion of dreaming with anterior versus posterior cere2000). This applies also to the various disorders of bral lesions. The same applies to the observation language that have been thought to explain absence of reported above to the effect that the dreams of frontal dream recall (Zinkin, 1959; Anan’ev, 1960; Moss, 1972; lobe patients are indistingishable from those of conJakobson, 1973; Doricchi and Violani, 1992). trols (Badenhorst and Solms, unpublished). This conRetrospective absence of dreaming on morning tradiction was resolved when Solms (1997) reviewed awakening has repeatedly been confirmed on REM the lesions in the previously reported cases and awakening (Michel and Sieroff, 1981; Schanfald et al., described 9 new cases of his own with cessation of 1985; Bischof and Bassetti, 2004; Poza and Marti, dreaming following naturally occurring frontal lesions 2006). This further supports the assumption that this (Table 34.4). His conclusion was that dreaming was disorder concerns cessation of dreaming per se. Even spared with dorsolateral prefrontal cortical lesions and severe amnesiacs with bilateral hippocampal lesions affected only with deep white-matter lesions in the report dreams on REM awakening (Torda, 1969; ventromesial quadrant of the frontal lobes (Figures 34.1 Ramachandran, 2004, personal communication). and 34.2). The lesion site in his 9 cases coincided exactly The first systematic attempt to identify the lesion site with the area that was targeted by prefrontal leukotomy: responsible for global cessation of dreaming pointed to “a circumscribed lesion just anterior to the frontal the inferior parietal lobule of either hemisphere (Solms, horns of the ventricle, in the lower medial quadrant of 1997). Unilateral lesions were shown to be commonthe frontal lobes” (Walsh, 1994, p. 177). place, with no lateralizing bias. However, at least one A reanalysis of the original data in 35 cases from case has since been reported in which the parietal lobe Solms’s series with global cessation of dreaming assowas unequivocally spared (Bischof and Bassetti, 2004), ciated with subcortical lesions revealed that the lesion as indeed it appears to have been in Wilbrand’s original was located in either the deep frontal white matter case (Wilbrand, 1892). A reanalysis of Solms’s data by (areas F09 and F14 in the classification of Damasio Yu (2001a) revealed that the lesions in his parietal cases and Damasio, 1989; Figure 34.3), or the head of the almost always extended into adjacent occipitotemporal caudate nucleus, or both (Yu, 2001b). Of theoretical tissues (especially areas 22, 19, and 37). importance is the fact that the region defined as the It is therefore still not possible to make a more prehead of the caudate nucleus (located in the ventromecise localizing statement than the one offered by Murri sial prefrontal region, attached to the inferior caudal et al. (1984, p. 185): “a lesion in an acute phase affectpart of the frontal horn of the lateral ventricle, suring the posterior regions.” The reference here to an rounded by the white matter enclosing the frontal acute phase is not superfluous. Solms (1997) observed horn) included the nucleus accumbens, which is that almost all cases recover the capacity to dream situated immediately beneath it. within 12 months. This fact, which suggests diaschitic
Table 34.2 Cases of global cessation or suppression of dreaming Case
Lesion
Irreminiscence
Dreams
Wilbrand (1887, 1892)
Fra¨ulein G.
R. med. occip. temp., L. deep occip. (thrombosis)*
_
Mu¨ller (1892) Gru¨nstein (1924) Lyman et al. (1938) Humphrey and Zangwill (1951)
Frau Anna Hoffmann, 50y (p. 420) (p. 420) 42y M Case 1, 26y M
Bilat. occip. (hemorrhage)b (L. lat. temp.) (L. lat. temp.) L. deep occip. par. (meningioma)} R. par.k (trauma)
þ _ _ þ þ
Humphrey and Zangwill (1951)
Case 2, 21y M
Bilat. lat. par.k (trauma)
þ
Humphrey and Zangwill (1951)
Case 3, 32y M
R.} (lat?) par.} (trauma)
þ
Oldfield (Humphrey and Zangwill, 1951) Gloning and Sternbach (1953)
(p. 324n)
R. occip. par. (abscess)}
(No information){
Either global cessation with recovery over approx. 4 years or gross reduction in frequency (description ambiguous) Global cessation Global cessation Global cessation Global cessation Global cessation with partial recovery or gross reduction in frequency (description ambiguous) Global cessation and cessation of hypnagogic imagery Global cessation with recovery after approx. 5 years Global cessation
S. Johann, 48y M
R. deep front. temp. (glioma)}
_
L. Josef, 64y M
L. med. occip. temp., R. post. occip. (thrombosis)* L. med. occip. temp. (thrombosis){
þ
K. Franz, 56y M
_
M Klara, 32y F Sch. Gertrude, 56y F
R.k front.{ (and temp. par.) (thrombosis) R. deep front. temp. (glioma)} Bilat. deep front. (glioma)}
M. Josef, 24y M E. Ernst, 57y M
R. deep par. temp. (hemorrhage)k L. occip. thalam. (thrombosis){
_ _
N. Johann, 51y M
L. thalam (thrombosis){
_
W. Karl, 52y M
Gloning and Sternbach (1953)
þ
_ _
Increased proprioceptive-vestibular imagery (falling and flying); residual reduction in frequency Global cessation Global cessation with recovery after approx. 1 year; residual reduction of visual imagery Global cessation
Continued
523
Global cessation Increased vivacity, later becoming global cessation Gross reduction in frequency Global cessation with gradual recovery over approx. 3 years Global cessation with recovery after 5 months
NEUROBIOLOGY AND THE NEUROLOGICAL BASIS OF DREAMING
Source
524
Table 34.2 Continued Source
Case
Lesion
Irreminiscence
Dreams
Boyle and Nielsen (1954); Nielsen (1955)
E. S., 31y M
þ
Global cessation
Nielsen (1955)
Harley S., M (p. 52) (p. 52) F N. H., 57y M Douglas Ritchie, 50y M
3rd. ventric. (cyst) (with hydroceph.)k L. deep occip. temp.,{ R. occip.} (surgical trauma) L. occip. (glioma)} L. occip. (tumor) L. occip. (tumor) Bilat. occip.} (trauma) R. occip. temp.* (metastatic tumor) L. (thrombosis){
þ þ þ _ þ _
Global cessation Global cessation Global cessation Global cessation Global cessation Global cessation with recovery after approx. 2 years Global cessation
Ettlinger et al. (1957) Ritchie (1959)
Patricia Neal, 39y F
L. temp. (par.) (hemorrhage)}
þ
36y F C. Scott Moss, 43y M
Ventral pons (thrombosis){ L. (thrombosis){
_ _
Wapner et al. (1978) Epstein (1979)
J. R., 73y Mf Patient 1, 56y F
Bilat. occip. (thrombosis)k L.} med. par. occip. (thrombosis){
þ þ
Basso et al. (1980)
M G., 63y M
þ
Epstein and Simmons (1983)
Pen˜a-Casanova et al. (1985)
Case 1, 47y F Case 2, 35y F Case 3, 33y M Case 4, 56y F Case 5, 52y F Case 6, 43y F Case 7, 59y F A. R. 47y M
L. med, occip. temp., cerebellum (thrombosis)k L. front. Temp. (hemorrhage)} L. front. (thrombosis)k L. front. temp. (thrombosis)k L. (thrombosis){ L. (thrombosis){b L. (thrombosis){ L. deep. par. occip.k L. med. occip. temp. (thrombosis)k
_ _ _ _ _ _ _ þ
Habib and Sirigu (1987)
Case 2, 26y F
R.} med. temp. (thrombosis)k
_
Farah et al. (1988) Solms (1997)
R. M, 64y M Patient 8, 10y M Patient 17, 36y M
L. med. occip. temp. (thrombosis)k R. med. par. temp. meningiomak R. par. temp. stab wound with intracerebral hemorrhagek
þ _ _
Global cessation Global cessation with recovery after 4 months Global cessation Global cessation with gradual recovery after approx. 5 months Global cessation and cessation of hypnagogic imagery Global cessation Global cessation Global cessation Global cessation Global cessation Global cessation Global cessation Global cessation with gradual recovery after approx. 5 months Either global cessation or specific amnesia (description ambiguous) Global cessation Global cessation Global cessation
M. SOLMS
Farrell (1969); Neal and Deneut (1988) Feldman (1971) Moss (1972)
Solms (1997)
Patient 23, 28y F
Patient 27, 29y F Patient 43, 22y F
Patient 48, 42y M Patient 49, 29y M Patient 57, 29y M Patient 71, 42y M Patient 86, 46y F
Patient 87, 60y M Patient 99, 34y M
Patient 119, 14y F Patient 122, 37y M Patient 130, 56y F Patient 134, 54y F Patient 143, 27y M Patient 157, 40y F
Patient 162, 73y M Patient 168, 35y M
_
Global cessation
_ _
Global cessation with recovery within 1 year Global cessation
_
Global cessation for at least 2 years
_
R. lat. par. temp. front. chronic subdural hemorrhage (MVA)k R. lat. par. front. chronic subdural hemorrhage (assault)k L. deep par. temp. cyst (cysticercosis)k L. par. front. infarct following subarachnoid hemorrhage (L. mid. cereb. art. aneurysm)k L. par. front. limbic depressed fracture with abscess formation (assault)k L. lat. par. front. temp. acute subdural hemorrhage with L. front. intracerebral extensionk R. deep par. temp. limbic astrocytomak
_
Global cessation with recovery within 1 year Global cessation for at least 2 years
_
Global cessation
_ _
Global cessation Global cessation
_
Global cessation
_
Global cessation
_
Bilat. occip. subdural and cerebellar extradural hemorrhages (assault) R. par. front. meningioma (with cortical infiltration)k R. lat. par. temp. meningiomak R. lat par infarct (R. mid. cereb. art. thrombosis)k L. lat. par. occip. infarct following subarachnoid and intracerebral hemorrhage (L. mid. cereb. art. aneurysm)k R. par. occip. intracerebreal hemorrhage (hypertention)k L. par. temp. limbic astrocytoma
_
Global cessation with recovery within 1 year Global cessation
_ _ _
Global cessation with recovery within 1 year Global cessation Global cessation
_
Global cessation with recovery within 1 year
_
Global cessation
_
Global cessation
525
Continued
NEUROBIOLOGY AND THE NEUROLOGICAL BASIS OF DREAMING
Patient 44, 44y F
L. par. temp. limbic infarct following subarachnoid hemorrhage (L. mid. cereb. art. aneurysm)k L. par. front. depressed fracture with abscess formation (assault)k L. par. infarct (L. int. carotid. art. traumatic occlusion)k R. par. front. meningioma (with R. mid. cereb. art. infarction)k L. par. temp. arachnoid cystk
526
Table 34.2 Continued Case
Lesion
Irreminiscence
Dreams
Solms (1997)
Patient 173, 34y M
_
Global cessation with recovery within 1 year
.
Patient 174, 29y M
Par. temp. limbic intracerebral hemorrhage (AVM fed by R. mid. cereb. art)k Vertex and L. temp stab wounds with medial L. hemispheric subarachnoid and temp. intracerebral hemorrhages (pericallosal traumatic aneurysm) L. lat par. temp. meningiomak R. med. par. meningiomak Bilat. med. occip. temp multiple lacunar infarctions (region of post. cereb. art) Bilat. par. front. and L. temp. multiple intracerebral hemorrhage (lupus erythematosus)k Pontine cerebellar (acoustic neuroma); postsurgery R. occip-temp. intracerebral hemorrhage R. lat. par. front. occip. infarct (R. mid. cereb. art. thrombosis)k R. deep par. occip. temp. limbic gliomak R. med. par. front. limbic meningiomak Bilat. lat. par. front. occip. dermoid cyst with R. front. chronic subdural hemorrhagek L. deep par. occip. Metastatic carcinomak L. med. occip. temp. limbic meningioma R. lat. par. front. subdural empyemak L. par. front. open head injury (MVA)k
_
Global cessation
_ _ _
Global cessation Global cessation Global cessation
_
Global cessation
_
Global cessation
_
Global cessation
_
Global cessation
_ _
Global cessation Global cessation
_
Global cessation
_
Global cessation
_ _
Global cessation Global cessation with recovery within 1 year Global cessation Global cessation
Patient 186, 65y F Patient 187, 17y Ff Patient 189, 49y F
Patient 191, 33y F
Patient 217, 42y F
Patient 224 39y F Patient 234, 77y M Patient 238, 63y F Patient 241, 18y M
Patient 244, 77y M Patient 263, 43y F Patient 268, 67y M Patient 273, 27y M Patient 284, 23y M Patient 285, 18y M Patient 286, 31y F
R. par. open head injury (stab wound)k L. lat. par. front. open head injury (gunshot wound)k L. par. open head injury (stab wound)k
_ _ _
Global cessation with recovery within 1 year
M. SOLMS
Source
Patient 288, 67y F Patient 289, 35y M
Patient 299, 54y M
Patient 303, 25y M Patient 305, 58y M Patient 306, 33y F Patient 312, 59y M Patient 321, 35y M
Patient Patient Patient Patient
327, 44y F 336, 77y M 338, 54y M 341, 18y M
Patient 345, 43y M Patient 349, 63y F Patient 353, 50y M Bischof and Bassetti (2004)
72y F
Poza and Marti (2006)
24y M
L. temp. occip. hemorrhagek
_
Global cessation
_
Global cessation
_
Global cessation
_
Global cessation
_ _
Global cessation with recovery within 1 year Global cessation
_
Global cessation
_
Global cessation with recovery within 1 year Global cessation for at least 2 years
_
_ _ _ _
Global Global Global Global
_
Global cessation
_ _
Global cessation Global cessation
_
Global cessation with gradual recovery after 14 weeks; residual reduction in frequency Global cessation
_
527
y, year; F, female; M, male; AVM, arteriovenous malformation; MVA, motor vehicle accident. *Autopsy-confirmed localization. {Clinical localization or diagnosis. {Unless otherwise indicated, it is assumed that the authors comprehensively investigated and reported the neuropsychological status of their cases. }Localization or diagnosis based on intraoperative observation. }Localization or diagnosis based on in vivo imaging techniques. }Left-handed or ambidextrous patient.
cessation cessation cessation cessation
NEUROBIOLOGY AND THE NEUROLOGICAL BASIS OF DREAMING
Patient 302, 32y F
L. front. temp. subdural and intracerebral hemorrhages (assault) R. temp. and cerebellar intracerebral hemorrhages and shrapnel/bone (bomb blast) L. occip. temp. limbic glioma (astrocytoma) L. lat. par. front. infarct (L. mid. cereb. art. thrombosis)k L. lat. par. front. acute subdural hemorrhage (MVA)k R. lat. par. temp. front. infarct (L. mid. cereb. art. thrombosis)k L. lat. par. temp. infarct (L. mid. cereb. art. thrombosis)k R. lat. par. temp. front. infarct (R. mid. cereb. art. thrombosis)k R. lat par. temp. front. infarct (mid. cereb. art) following subarachnoid hemorrhage (ant. comm. art. aneurysm)k R. deep par. intracerebral hemorrhagek L. lat. par. front. metastatic carcinoma L. deep par. astrocytomak L. lat. par. front. acute subdural hemorrhage (MVA)k R. lat. par. front. acute subdural hemorrhage (MVA)k L. med. par. front. meningiomak R. lat. par. front. subdural-extradural hemorrhage (assault)k Bilat. med. occ. R. thalam. (bilat post. cereb. art. thrombosis)k
528
M. SOLMS
Table 34.3 Global cessation or suppression of dreaming in clinical series of prefrontal leukotomy Source
Series
Dreams
Frank (1946)
100 cases, 22–26 years, 100 M, 100 F
Frank (1950)
300þ cases
Piehler (1950)
58 cases, 21 M, 37 F
Partridge (1950)
300 cases
Slater (cited in Humphrey and Zangwill, 1951) Schindler (1953)
“A number of patients”
Global cessation and decreased frequency or narrative complexity (description ambiguous) in an unspecified number of cases Global cessation or decreased frequency (description ambiguous) and decreased narrative complexity and emotional intensity in an unspecified number of cases Global cessation in 11 cases; recovery over 1 year with residual reduction in frequency, vivacity, narrative complexity, and emotional intensity in 8 of these Global cessation or gross reduction in frequency (description ambiguous) in several cases; recovery over 6 months–1 year in an unspecified number of cases Global cessation or reduction in frequency (description ambiguous) Global cessation in 134 cases; recovery several months to 1 year with residual reduction in narrative complexity in an unspecified number of cases Global cessation in 9 cases (sleep lab confirmed in 7 of these); global cessation claimed by 3 controls (not confirmed in lab)
Jus et al. (1973)
Freeman (cited in Jus et al., 1973)
150þ cases
13 cases, 31–63 years, 1 M, 12 F; 13 matched (schizophrenic) controls No information
Global cessation or reduction in frequency (description ambiguous)
M, male; F, female.
It is noteworthy that the psychotropic medications that replaced prefrontal leukotomy as the treatment of choice for psychotic disorders block dopamine (DA) transmission in a mesial forebrain pathway that projects primarily to the nucleus accumbens. Probably related to this is the observation that both prefrontal leukotomy in general and cessation of dreaming in particular, due to lesions in this general area, are associated with reduced motivational incentive (Solms, 1997), as indeed are most antipsychotic medications (Kapur, 2003). Also of interest in this connection is the observation by Piehler (1950) and Schindler (1953) to the effect that early recovery of dreaming after prefrontal leukotomy typically coincides with psychiatric relapse, suggesting that absence of dreaming could serve as an index of the clinical success of the operation. Dreaming is, after all, a psychotic state.
Effects of pontine brainstem lesions Despite the longstanding assumption that dreaming is caused by – if not identical with – effects on the sleeping forebrain of the cyclical, spontaneous
activation of cholinergic (ACh) cells in the mesopontine tegmentum during the REM state, together with reciprocal inhibition of serotonergic (5-HT) and noradrenergic (NA) cells in the dorsal raphe and locus coeruleus complex (Hobson et al., 1975, 1986), cessation of dreaming following circumscribed pontine lesions, with or without cessation of REM sleep, has never been demonstrated (see Solms 1997, 2000, for reviews). Consciousness in general is of course frequently compromised by pontine lesions, but at least 8 cases with cessation or near-cessation of REM have been reported in which patients were capable of communicating meaningfully about their dreams (Feldman, 1971; Markand and Dyken, 1976; Osorio and Daroff, 1980; Lavie et al., 1984). Indeed, one such patient did actually report loss of dreaming (Feldman, 1971), but the lesion – caused by ruptured traumatic aneurysm of the basilar artery – probably extended beyond the pontine brainstem and included the visual cortical areas discussed above. Even this isolated case therefore does not support the old equation of pontine brainstem mechanisms with dream generation. (The relationship between dreaming and REM sleep is discussed further below.)
NEUROBIOLOGY AND THE NEUROLOGICAL BASIS OF DREAMING
529
Table 34.4 Cases of global cessation of dreaming with frontal lobe lesions Source
Case
Lesion
Irreminiscence
Dreams
Piehler (1950)
Case 1, 49y M
Bilat. deep front. (leukotomy){
_
Case 2, 36y M
Bilat. deep front. (leukotomy){
_
Case 3, 34y F
Bilat. deep front. (leukotomy){
_
Case 4, 33y F
Bilat. deep front. (leukotomy){
_
(p.318)
Bilat. deep front. (leukotomy){ Bilat. deep front. (leukotomy){ Bilat. deep front. (leukotomy){
(No information)*
Global cessation with recovery after approx. 6 weeks; global cessation again after 2nd op. with recovery after approx. 2 years; residual reduction in frequency, narrative complexity, and intensity Global cessation with gradual recovery after approx. 4 months Global cessation with recovery after approx. 3 months; residual reduction in frequency Global cessation with recovery after approx. 3 months Global cessation
(No information)
Global cessation
(No information)
Case 111
Bilat. deep front. (leukotomy){
(No information)
Patient 9, 13y F
Bilat. deep front. thalam. glioma (glioblastoma multiforne){{ Bilat. deep frontal Abscess{ Suprasellar pituitary tumour with med. front. limbicventricular extension (prolactinomamacroadenoma){{ L. deep front.abscess and intracerebral hemorrhage; R med. front. intracerebral hemorrhage and subdural empyema{
_
Global cessation of imagery (dream feeling without imagery) Global cessation of imagery (dream atmosphere without imagery) Global cessation
_
Global cessation
_
Global cessation for at least 12 weeks
_
Global cessation
Gloning and Sternbach (1953)
(pp. 318–319) Schindler (1953)
Solms (1997)
Case 89
Patient 129, 14y M Patient 150, 58y F
Patient 181, 35y M
Continued
530
M. SOLMS
Table 34.4 Continued Source
Case
Lesion
Irreminiscence
Dreams
Solms (1997)
Patient 214, 18y M
L. basal front. intracerebral hemorrhage; R. carotid-cavernous fistula{ Bilat. med. frontal meningioma{{ Bilat. calloso-front. limbic glioma (glioblastoma multiforme){{ Bilat. med. front. limbic subarachnoid and intracerebral hemorrhage (ant. comm. art. aneurysm){ L. med. front. limbic diencephalic abscess (stab wound){
_
Global cessation
_
Global cessation
_
Global cessation
_
Global cessation for at least 10 weeks
_
Global cessation
Patient 261, 62y M Patient 280, 63y F
Patient 281, 44y F
Patient 291, 21y F
M, male; F, female. *Unless otherwise indicated, it is assumed that the authors comprehensively investigated and reported the neuropsychological status of their cases. {Localization or diagnosis based on intraoperative observation. {Localization or diagnosis based on in vivo imaging techniques.
Excesses of dreaming Solms (1997) loosely grouped together 12 case reports in the literature and 10 of his own cases that reported excesses of dreaming, ranging from increased frequency and/or vivacity of dreams to intrusions of dreaming and dream-like thinking into waking cognition (Table 34.5). The principal justification for collecting these cases together under a single nosological heading seems to be that the lesions are frequently located in the transitional zone between the anterior diencephalon and basal forebrain. Kindred phenomena are, however, observed with visual deafferentation, peduncular hallucinosis, delirium, Parkinson’s disease and related disorders, and a variety of toxic and metabolic abnormalities. The common denominator in these cases may therefore simply be degradation of controls and constraints on consciousness.
Recurring nightmares Nocturnal seizures (and complex partial seizures in particular) sometimes present as recurring nightmares. Solms (1997) identified 24 cases of this type
in the literature and 9 in his own series (Table 34.6). Of theoretical interest is the fact that such nightmares typically occur during non-REM sleep, and that complex partial seizures preclude recruitment of pontine brainstem mechanisms. In such cases, the content of the recurring nightmares frequently coincides with that of the patient’s typical aura or “dreamy state” seizures. Penfield was able artificially to generate a waking aura resembling the recurring nightmare in 1 case by stimulating exposed cortex in the region of the epileptogenic focus (Penfield, 1938; Penfield and Erickson, 1941; Penfield and Rasmussen, 1955). Successful pharmacological or surgical treatment of the seizure disorder invariably results in disappearance of the recurring nightmares. These facts support the interpretation of the nightmares as seizure equivalents (and indeed as non-REM phenomena). Seizure disorders may also be associated with increased frequency of nightmares in general (Solms, 1997). However, as with other “excess of dreaming” described above, increased frequency of nightmares is associated with a wide range of toxic and metabolic abnormalities. The common
NEUROBIOLOGY AND THE NEUROLOGICAL BASIS OF DREAMING
531
Fig. 34.1. Combined facsimile of scans in 9 cases with global cessation of dreaming caused by deep frontal lesions, illustrating the strong involvement of the white matter surrounding the frontal horns of the lateral ventricles. (Reproduced from Solms (1997).)
denominator here may therefore simply be nocturnal cerebral irritability.
FUNCTIONAL NEUROIMAGING FINDINGS For technical reasons, functional brain imaging of dreaming sleep has relied mainly upon positron emission tomography (PET). Due to limitations of temporal resolution in PET, “dreaming sleep” has typically been operationalized as REM sleep in these studies. Since dreaming is approximately three times more common
in REM than non-REM sleep, it is reasonable to assume that PET images of the REM state should at least include images of the dreaming brain. In other words, PET at least enables us to visualize the pattern of regional cerebral activation in the combined dreaming and REM state. The canonical studies (Maquet et al., 1996, 1997; Braun et al., 1997, 1998; Nofzinger et al., 1997) are summarized in Maquet (2000). If the well-known brainstem correlates of REM activation are set aside for the methodological reasons just mentioned, the pattern of regional cerebral activation in the available PET studies of dreaming sleep
532
M. SOLMS
Fig. 34.2. Combined facsimile of scans in 14 cases with preserved dreaming with bifrontal lesions, illustrating the relative preponderance of cortical convexity involvement. (Reproduced from Solms (1997).)
(compared to other sleep stages and waking) is strikingly convergent with the clinicoanatomical findings summarized in previous sections (Pace-Schott and Hobson, 1998). The emerging picture seems to be: (1) activation of limbic and paralimbic structures and basal ganglia; (2) activation of modality-specific posterior cortices (including specifically areas 19, 22, and 37; see above); and (3) deactivation of the dorsolateral prefrontal convexity (Figure 34.4). In general, the brain regions implicated in dream generation by lesion studies are relatively activated
in the PET studies, and those not implicated by the lesion studies are deactivated in the PET studies. Particularly impressive in this respect is the precise distinction between early visual projection cortices, where lesions spare visual dreaming and PET shows reduced metabolic activity, and later visual association cortices, where lesions impair visual dreaming and PET shows increased activity (Solms, 1997; Braun et al., 1998). The strong convergence between the lesion and functional neuroimaging findings has prompted wide
NEUROBIOLOGY AND THE NEUROLOGICAL BASIS OF DREAMING F11 F F 1 1 1 1
F06
T12
T12
F06
F12 T 0 3 T 0 5
T 10
T T 10 0 3 T 05
F07
F07
F06
F 08 T 0 8
F 08 T 0 8 T 03 T06
T 11
O 03
O 0 6
T 03
F 14 F12
F10
F06
F06
T03
T10
T 08
F 06
F07
T 0 3 T 05
F07 F F 04 04 F F F09 01 01 F09
F 08 T 07
T 0 9 T 03
T06
T04
T 11 O O 06 0 1 O04
T11 O O 06 01
O04
F06
T 0 8
T10
T 05
F10
F 14
T08
F F F 01 01 F09 09
O T 0 11 6 O 03
F 14
F11
F06
T 03
F 06
F 0 1
T04
F F 0 14 1 T 08
F F 1212
O06 T 05
T 11
T 11
O06
F07
F 04
F07
F 04
F 08 T 07
T 07
T04
F06
F 01 F 09
F 08
T 0 9
T 03 T05
F F09 01 F08 T 07 T 0 9 T 03
533
O 06
F 02 O 0 O 7 0½
O04
F 02 O O 0 0½ 7
O 06
O04
T 09
T04
Fig. 34.3. The classification of Damasio and Damasio (1989).
agreement that “frontal deactivation must play a key role in any neurocognitive theory of dreaming” (Pace-Schott, 2003, pp. 340–341). The hypothesis that sleep involves disengagement of prefrontal systems from posterior perceptual and deeper memory and emotional systems holds great value for explaining dream phenomenology.
NEUROCHEMICAL AND PSYCHOPHARMACOLOGICAL FINDINGS The chemical and pharmacological evidence is difficult to interpret. This is due partly to the dynamic interactions that characterize neurotransmitter systems, and partly to the paucity of rigorous pharmacological studies (Hobson, 2001). Mention will be made here of recent findings which seem particularly relevant to understanding dream generation and the distinction between dreaming and REM sleep. The neurochemical signature of the REM state is well established: autochthonous activation of ascending
pontine ACh cells,which is thought to produce characteristic pontine-geniculate-occipital waves, and reciprocal inhibition of pontine aminergic (5-HT and NA) cells, which is thought to demodulate the dreaming forebrain (Hobson et al., 2000). Equally well established is the fact that non-REM sleep has the opposite pattern. Less widely known is the fact that, unlike other aminergic brainstem cells, the source cells in the ventral tegmental area of the mesocortical DA pathway described above continue to fire at equivalent rates during sleeping and waking (Miller et al., 1983; Trulson and Preussler, 1984). These cells also fire with greater interspike variability during REM than non-REM sleep (Miller et al., 1983). This possibly indicates increased burst activity in the REM state, which would result in greater terminal DA release. Whatever the mechanism, the result is maximal delivery of DA to the nucleus accumbens during REM sleep (Lena et al., 2005). The REM state is also characterized by minimal prefrontal glutamate release (Lena et al., 2005).
534
Table 34.5 Cases of increased frequency and vivacity of dreaming
Case
Lesion
Relevant symptoms and signs
Gru¨nstein (1924)
Patient N., 21y M
Bilat. occip. (trauma)
Cortical blindness
Gloning and Sternbach (1953)
M. Johanna, 27y F
Hypothalam. (tumor)
Blindness
H. Therese, 27y F
Bilat. med. front. (meningioma)
Disinhibition
S. Josef, 54y M
Hypothalam. thalam. (craniopharyngioma)
Disinhibition
E. Gustav, 44y M
R. thalam. (thrombosis)
Disinhibition
K. Rudolf, 50y M Case 1, 58y M
R. thalam. (thrombosis) Bilat. med. front. (cingulectomy)
Disinhibition Disinhibition
Case 2, 31y F
Bilat. med. front. (cingulectomy)
Disinhibition
Case 3, 60y M
Bilat. med. front. (cingulectomy)
Disinhibition
Whitty and Lewin (1957)
Dreams Increased vivacity, recovering gradually over approx. 3 weeks; residual increased frequency Increased vivacity Increased vivacity (with nightmares), gradually decreasing in frequency over 2 years Increased frequency and vivacity (with nightmares), recovery after approx. 1 year Increased frequency and vivacity Increased vivacity Continuous dreaming with increased vivacity, blurred fantasy/reality distinction; recovery over approx. 4 days Continuous dreaming with increased vivacity, blurred fantasy/reality distinction; recovery over approx. 2 days Continuous dreaming with increased vivacity, blurred fantasy/reality distinction; recovery over approx. 4 days
M. SOLMS
Source
S.S., 53y M
Bilat. thalam. (atrophy)
Gallassi et al. (1992)
L.S., 29y F
No information
Morris et al. (1992)
S.J., 51y M
Sacks (1995)
Franco Magnani, 54y M
R. hypothalam. (atrocytoma) No information (febrile illness)
Disinhibition; confabulatory amnesia Blindness
Solms (1997)
Case 17, 62y M
Bilat. med. front. cingulate g., basal forebrain; R. lat. front. temp. par. (ant. comm. aneurysmal rupture with ant. and mid. cereb. spasm) Bilat. cingulate g., postcentral, precentral and premotor g., R. lat. par. occip. (open head injury) R. med. front. cingulate g., basal forebrain (ant. comm. aneurysmal rupture with ant. cereb. spasm)
Disorientation, confabulatory amnesia, disinhibition, fluctuating affect, reduplicative paramnesia, neglect, reduced insight Disinhibition, euphoria/ placidity, visual hallucination, neglect, anosodiaphoria
Case 18, 32y M
Case 19, 30y M
Case 20, 30y M
R. med. thalamic astrocytoma
Disinhibition
Disorientation, confabulatory amnesia, disinhibition, fluctuating affect, reduplicative paramnesia, anosognosia Torpor/stupor, disorientation, confabulatory amnesia, paranoia, neglect, reduced insight
Increased vivacity with enactment, gradually increasing in frequency over approx. 6 months, becoming continuous) Increased vivacity, gradually increasing in frequency Increased vivacity; blurred fantasy/reality distinction Increased frequency (continuous dreaming?) and increased vivacity; blurred fantasy/reality distinction Increased reality in context of global fantasy/reality breakdown
Increased reality and frequency with circumscribed fantasy/ reality breakdown (and with repetitive nightmares) Increased reality in context of global fantasy/reality breakdown
Increased reality in context of global fantasy/reality breakdown
NEUROBIOLOGY AND THE NEUROLOGICAL BASIS OF DREAMING
Lugaresi et al. (1986); Gallassi et al. (1992)
Continued
535
536
Table 34.5 Continued
Case
Lesion
Relevant symptoms and signs
Solms (1997)
Case 21, 61y F
Hypothalam. (suprasellar pituitary adenoma)
Disinhibition, fluctuating affect, reduced insight
Case 22, 44y F
L. med. front., bilat. cingulate g., basal forebrain (ant. comm. aneurysmal rupture with front. intracerebral hemorrhage extension) Bilat. med. thalam. (colloid cyst of the third ventricle)
Amnesia, visual hallucination, reduplicative paramnesia, neglect
Hypothalam, bilat. med. thalam. (craniopharyngioma) Bilat. med. frontal, cingulated g. (open head injury with ?R. ant. cereb. infarct)
Disorientation, amnesia, fluctuating affect, anosognosia Torpor, fluctuating affect, paranoia
Case 23, 27y M
Case 24, 44y F
Case 25, 32y F
Torpor, amnesia, irritability
Dreams Increased reality and frequency (with increased frequency of nightmares) Increased reality in context of global fantasy/reality breakdown and recovery
Increased reality and frequency with circumscribed fantasy/ reality breakdown Increased reality (and frequency of nightmares) Increased reality and frequency with circumscribed fantasy/ reality breakdown (with repetitive nightmares) and recovery
M. SOLMS
Source
NEUROBIOLOGY AND THE NEUROLOGICAL BASIS OF DREAMING
537
Table 34.6 Cases of recurring nightmares associated with seizures Source
Case
Lesion/focus
Dreams
Clarke (1915)
Case 3, 24y M
No information
Case 8, 35y M
No information
Case 4 (A.R.) 13y F
No information
Case 5, 21y F
No information
Naville and Brantmay (1935) Penfield (1938)
Case 18, 11y F
No information
J.V., 14y M
R. lat. temp. occip. (hemorrhage)
Penfield and Erickson (1941)
C. Ft., 27y M
R. deep temp. (glioma)
Rodin et al. (1955)
Case 3, 23y F
Bilat. temp. EEG foci, R.>L.
Ostow (1954)
Case 3, 36y F
R. temp. EEG focus
Case 4, 38y M
Bilat. temp. EEG slowing, L.>R.
H.D. 35y F
R. temp. EEG focus
L.E., 22y F
R. bilat. temp EEG slowing
Snyder (1958)
A.M, 9y M
R. par. EEG focus
Epstein (1964)
38y M
L. temp. EEG focus
23y F
R. temp. EEG focus
Repetitive nightmares, with subsequent development of manifest epilepsy associated with recurrent dreams which sometimes culminated in seizures Recurring nightmare, disappearing with onset of manifest epilepsy Repetitive nightmares of sudden onset, with subsequent development of manifest epilepsy Repetitive nightmares, sometimes continuous, with subsequent development of manifest epilepsy Frequent nightmares associated with onset of epilepsy Recurring nightmare, later becoming hallucinatory aura; reproducible by R. temp. stimulation Repetitive series of dreams, typically culminating in nocturnal seizure; reproducible by R. temp. stimulation Dreams of recurring (unpleasant) form, typically culminating in nocturnal seizure Recurring (unpleasant) dreams, related in content to compulsive waking thoughts and seizure automatisms Nightmares of recurring form, related in content to compulsive waking thoughts Recurring nightmares, related in content to compulsive waking thoughts and seizure automatisms Repetitive nightmares, being nocturnal seizures, related in content to waking complex partial seizures Nightmares of sudden onset, with confusion or complaints of headache on awakening, controlled by anticonvulsant medication Recurring nightmare, later becoming hallucinatory seizure or aura (description ambiguous) Recurring nightmares, gradually becoming more frequent and vivid, later becoming nocturnal seizure or aura with blurred fantasy/reality distinction; controlled by anticonvulsant medication
Kardiner (1932)
Epstein and Ervin (1956)
Continued
538
M. SOLMS
Table 34.6 Continued Source
Case
Lesion/focus
Dreams
Epstein and Hill (1966)
35y F
R. temp. focus (encephalitis)
Epstein (1967)
Case 1, 41y F Case 2, 20y F
Bilat. temp. EEG foci, R.>L. R. par. EEG focus
Boller et al. (1975)
65y M
R. temp. (thrombosis)
Epstein (1979)
Patient 2, 27y M
R. temp. EEG focus
Patient 3, 35y F
Bilat. temp. EEG foci; hemangiomatosis
Patient 4, 27y F
L. temp. EEG focus
Patient 5, 30y F
Bilat. temp. EEG foci
Epstein and Freeman (1981)
38y M
R. temp. (gliosis)
Solms (1997)
Case 9, 33y F
R. temp. focus on EEG (idiopathic) Bilat. paracentr. front. par., R. occip. par., bilat. cingulate g. (open head injury) Bilat. med. frontal/ant. cingulate g. (open head injury)
Recurring nightmares, typically culminating in or being nocturnal seizure; associated with R. temp. spiking during REM sleep Nightmares of recurring form, typically being nocturnal seizures Recurring nightmare, disappearing with onset of manifest epilepsy, later becoming hallucinatory aura Frequent nightmares with enactment; controlled by anticonvulsant medication Recurring nightmares, with same content as compulsive waking thoughts and aura Recurring nightmare, sometimes being or culminating in nocturnal seizure; associated with spiking during REM sleep Recurring nightmare, sometimes culminating in nocturnal seizure; associated with spiking during REM sleep Recurring nightmares, typically being nocturnal seizures; associated with R. temp. occip. spiking during REM sleep Recurring nightmares, with content related to seizure aura; partially controlled by anticonvulsant medication Frequent nightmares with repetitive theme Increased reality and frequency with circumscribed fantasy/reality breakdown and repetitive nightmares Increased reality and frequency with circumscribed fantasy/reality breakdown and repetitive nightmares Recurring stereotypical nightmare incorporating epileptogenic hallucinatory imagery Recurring stereotypical nightmare
Case 18, 32y M
Case 25, 32y F
Case 27, 24y M
Bitemporal foci on EEG (anoxic episode)
Case 28, 25y F
Bitemporal foci on EEG, L.>R. (closed head injury) L. ant. basal temp. (oligodendroglioma) Nonspecific ABN on EEG (closed head injury)
Case 29, 47y F Case 30, 12y F
Recurring incorporation of epileptogenic olfactory image Recurring nightmare incorporating epileptogenic hallucinatory imagery and aura Continued
NEUROBIOLOGY AND THE NEUROLOGICAL BASIS OF DREAMING
539
Table 34.6 Continued Source
Case
Lesion/focus
Dreams
Solms (1997)
Case 31, 46y M
R. lat. front. temp. (aneurysmal rupture) L. deep par. temp. (glioblastoma multiforme)
Recurring stereotypical dream
Case 32, 50y M
Recurring stereotypical nightmare (with increased frequency and vivacity)
EEG, electroencephalogram; REM, rapid eye movment; ABN, abnormality.
SWS - REM 3.5
1.0
Fig. 34.4. Regional cerebral blood flow in rapid eye movement (REM) sleep. SWS, slow-wave sleep. (Reproduced from Braun et al. (1997).)
The chemical signature of the REM state, as regards the neurotransmitter interactions underlying the observed regional patterns of forebrain activation and deactivation, is certainly more complex than was previously assumed (Gottesmann, 2004). This complexity is underscored by the impenetrable thicket of psychopharmacological evidence. Of particular value is any evidence that could clarify the pathophysiology of dream cessation following deep ventromesial frontal lesions. Since the sleep cycle is unaffected by such lesions (Jus et al., 1973) it is reasonable to assume that they impair a mechanism which is specific to dream generation (as opposed to REM generation). Two competing hypotheses have been advanced to account for dream cessation following deep ventromesial frontal lesions (and commensurate activation of this region in PET imaging of dreaming sleep). The first hypothesis is that it reflects activation of ACh cells in the basal forebrain; the second is that it reflects activation of DA cells in the ventral tegmental area. Against the former hypothesis is the observation that ACh antagonists (like scopolamine), rather than suppressing dreaming and dream-like thinking, have the opposite effect (Cartwright, 1966). In fact, anticholinergic drugs mirror the effects of lesions in ACh basal forebrain nuclei (Damasio et al., 1985; Table 34.5).
These and other considerations led Braun (1999) to observe that activation of these nuclei during REM sleep may actually reflect inhibition of forebrain ACh in that state. In favor of the latter hypothesis is the observation that DA agonists (like L-dopa) increase dream bizarreness, vivacity, complexity, and emotionality without having any commensurate effects on REM sleep (Hartmann et al., 1980). Systematic studies of the effects on dreaming of DA antagonists have not yet been performed. However, a preliminary study by Yu (2007) of the effects on dreaming of antipsychotic medications recently found significant dream-suppressing effects. The available pharmacological evidence therefore supports the view that cessation of dreaming following ventromesial frontal lesions reflects interruption of DA rather than ACh pathways in this region (Solms, 2002).
THEORETICAL CONSIDERATIONS Necessary and sufficient conditions for dreaming The well-established fact that 25% of REM-like dreams occur during non-REM sleep (mainly, but not exclusively, at sleep onset and in the late morning), together
540
M. SOLMS
with the clinical evidence reviewed above, renders untenable the view that the REM state provides necessary and sufficient conditions for dream generation. The only way in which the old view could be salvaged would be to argue with Nielsen (2000) that non-REM dreams are somehow generated by “covert” REM states. This argument has limited empirical support at best (Bosinelli and Cicogna, 2000; Ogilvie et al., 2000; Perry and Piggott, 2000; Porte, 2000; Vogel, 2000; Takenchi et al., 2001; Suzuki et al., 2004), and is difficult to reconcile with the available clinicoanatomical evidence. More plausible is the view that REM activation facilitates rather than causes dreaming. This allows for the empirical fact that dreaming is also facilitated by other states, such as sleep onset (descending stages 1 and 2), late-morning arousal (which is hormonally driven), epileptogenic activity (i.e., local forebrain events) and various toxic/metabolic influences (which do not have concomitant effects on REM sleep). The common denominator in all these states is relative cerebral activation. Although cerebral activation may be considered a necessary condition for dream generation (indeed, it is a necessary condition for any conscious state), it is not sufficient to generate the unique state of consciousness known as dreaming. This fact is demonstrated by the simple observation that patients with deep ventromesial frontal lesions do not dream despite preservation of REM (and sleep-onset and late-morning) activation. For dreaming to occur, something specific needs to be added to activation, coupled with the known deactivation of dorsolateral prefrontal convexity (which characterizes all sleep stages and is apparently mediated by reduced glutamate, coupled with reduced 5-HT and NA in the REM state), as well as other as yet unknown variables which vary independently of the classical sleep stages. The requisite “something specific” appears to involve the deep ventromesial frontal region. The converging findings reviewed above suggest that it is the relative increase in mesocortical-mesolimbic DA activity during sleep. This formulation takes for granted the view that dreaming also depends upon posterior cortical mechanisms for the generation of mental imagery.
Functional neuroanatomy of dreaming Although it is therefore not yet possible to provide a definitive account of the functional neuroanatomy of dreaming, the following model may be advanced on the basis of the converging evidence outlined above. The dream process is initiated by a paradoxical conjunction of sleep with relative forebrain activation. From the functional neuroanatomical viewpoint, the first element in this conjunction is characterized above
all by cortical deactivation (with special emphasis on dorsolateral frontal deactivation). Under normal conditions, the most regular source of the second element is REM sleep activation. But REM (i.e., mesopontine) activation is by no means the exclusive source of forebrain activation causing dreaming (c.f., sleep onset, the late-morning effect); and even intrinsic forebrain activation is effective (e.g., complex partial seizures). The above-described paradoxical conjunction, by itself, is necessary but not sufficient to support dreaming. This is demonstrated by the fact that specific forebrain lesions prevent dreaming, despite preservation of normal sleep with REM activation. The available evidence suggests that the additional specific variable which causes dreaming is the activation of certain limbic forebrain structures. The precise delimitation of this final common pathway to dreaming remains controversial, but networks associated with motivational incentive and/or emotional salience are strongly implicated by the clinicoanatomical, functional neuroimaging, and neurochemical evidence. The dream process concludes with activation of posterior cortical structures associated with perceptual (especially visual) imagery and memory.
Function of dreaming Taken together, these considerations suggest that dreaming is: (1) a state of consciousness, characterized by (2) reduced constraints and controls on (3) memory and perceptual imagery with (4) motivational incentive and emotional salience. The occurrence of this hallucinatory mental state during normal sleep probably requires no further explanation than that motivated behavior is precluded during sleep. An adaptive function for dreaming has, however, not been empirically demonstrated.
REFERENCES Adler A (1944). Disintegration and restoration of optic recognition in visual agnosia: analysis of a case. Arch Neurol Psychiatry 51: 243–259. Adler A (1950). Course and outcome of visual agnosia. J Nerv Ment Dis 111: 41–51. Anan’ev B (1960). Psixologija Cuvstvennogo Poznanija [The psychology of learning through experience.] Academy of Pedagogical Science, Moscow. Aserinsky E, Kleitman N (1953). Regularly occurring periods of eye motility and concurrent phenomena during sleep. Science 118: 273–274. Aserinsy E, Kleitman N (1955). Two types of ocular motility during sleep. J Appl Physiol 8: 1–10. Basso A, Bisiach E, Luzzatti C (1980). Loss of mental imagery: a case study. Neuropsychologia 18: 435–442.
NEUROBIOLOGY AND THE NEUROLOGICAL BASIS OF DREAMING Benson DF, Greenberg J (1969). Visual form agnosia: a specific defect in visual discrimination. Arch Neurol 20: 82–89. Bischof M, Bassetti CL (2004). Total dream loss: a distinct neuropsychological dysfunction after bilateral PCA stroke. Ann Neurol 56: 583–586. Boller F, Wright D, Cavalieri R et al. (1975). Paroxysmal “nightmares”: sequel of a stroke responsive to diphenylhydantoin. Neurology 25: 1026–1028. Bosinelli M, Cicogna PC (2000). REM and NREM mentation: Nielsen’s model once again supports the supremacy of REM. Behav Brain Sci 23: 913–914. Botez M, Olvier M, Ve´zina J-L et al. (1985). Defective revisualization: dissociation between cognitive and imagistic thought. Case report and short review of the literature. Cortex 21: 375–389. Boyle J, Nielsen J (1954). Visual agnosia and loss of recall. Bull Los Angel Neuro Soc 19: 39–42. Brain R (1950). The cerebral basis of consciousness. Brain 73: 465–479. Brain R (1954). Loss of visualization. Proc R Soc Med 47: 288–290. Braun AR (1999). The new neuropsychology of sleep. Neuro-Psychoanalysis 1: 196–201. Braun AR, Balkin TJ, Wesenten NJ et al. (1997). Regional cerebral blood flow throughout the sleep–wake cycle – an (H2O)-O-15 PET study. Brain 120: 1173–1197. Braun AR, Balkin TJ, Wesenten NJ et al. (1998). Dissociated pattern of activity in visual cortices and their projections during human rapid eye movement sleep. Science 279: 91–95. Brown JW (1972). Aphasia, Apraxia, Agnosia: Clinical and Theoretical Aspects. Thomas, Springfield, IL. Cartwright R (1966). Dream and drug-induced fantasy behaviour: a comparative study. Arch Gen Psychiatry 15: 7–15. Cathala H, Laffont F, Siksou M et al. (1983). Sommeil et reˆve chez des patients de lesions parietals et frontales. [Sleep and dreams in patients with parietal and frontal lesions.] Rev Neurol (Paris) 139: 497–508. Charcot J-M (1883). Un cas de suppression brusque et isole´e de la vision mentale des signes et des objets (formes et couleurs). [On a case of sudden isolated suppression of the mental vision of signs and objects (forms and colours).] Progr Me´d 11: 568–571. Charcot J-M (1889). Clinical Lectures on Diseases of the Nervous System, vol. 3. (T. Savill, trans.). New Sydenham Society, London. (Original work published 1883.) Clarke LP (1915). The nature and pathogenesis of epilepsy. New York Medical Journal 101: 522, 567–573, 623–628. Critchley M (1953). The parietal lobes. Edward Arnold, London. Damasio H, Damasio A (1989). Lesion Analysis in Neuropsychology. Oxford University Press, New York. Damasio A, Graff-Radford N, Eslinger P et al. (1985). Amnesia following basal forebrain lesions. Arch Neurol 42: 263–271. Dement W, Kleitman N (1957a). Cyclic variations in EEG during sleep and their relation to eye movements, bodily
541
motility and dreaming. Electroencephalogr Clin Neuropshysio 9: 673–690. Dement W, Kleitman N (1957b). The relation of eye movements during sleep to dream activity: an objective method for the study of dreaming. J Exp Psychol 53: 89–97. Doricchi F, Violani C (1992). Dream recall in brain-damaged patients. A contribution to the neuropsychologyof dreaming through a review of the literature. In: J Antrobus, M Bertini (Eds.), The Neuropsychology of Sleep and Dreaming. Lawrence Erlbaum Associates, Hillsdale, NJ, pp. 99–140. Efron R (1968). What is Perception? Boston Studies in the Philosophy of Science. Basic Books, New York. Epstein A (1964). Recurrent dreams: their relationship to temporal lobe seizures. Arch Gen Psychiatry 10: 49–54. Epstein A (1967). Body image alterations during seizures and dreams of epileptics. Arch Neurol 16: 613–619. Epstein A (1979). Effect of certain cerebral hemispheric diseases on dreaming. Biol Psychiatry 14: 77–93. Epstein A, Ervin F (1956). Psychodynamic significance of seizure content in psycho-motor epilepsy. Psychosom Med 18: 43–55. Epstein A, Freeman N (1981). The uncinate focus and dreaming. Epilepsia 22: 603–605. Epstein A, Hill W (1966). Ictal phenomena during REM sleep of a temporal lobe epileptic. Arch Neurol 15: 367–375. Epstein A, Simmons N (1983). Aphasia with reported loss of dreaming. Am J Psychiatry 140: 108–109. Ettlinger G, Warrington E, Zangwill O (1957). A further study of visual-spatial agnosia. Brain 80: 335–361. Farah M, Levine D, Calvanio D (1988). A case study of mental imagery deficit. Brain Cogn 8: 147–164. Farrell B (1969). Pat & Roald. Hutchinson, London. Feinberg I (2000). REM sleep: Desperately seeking isomorphism. Behav Brain Sci 23: 931. Feldman M (1971). Physiological observations in a chronic case of “locked-in” syndrome. Neurology 21: 459–478. Frank J (1946). Clinical survey and results of 200 cases of prefrontal leukotomy. J Ment Sci 92: 497–508. Frank J (1950). Some aspects of lobotomy (prefrontal leukotomy) under psychoanalytic scrutiny. Psychiatry 13: 35–42. Gallassi R, Morreale A, Montagna P et al. (1992). Fatal familial insomnia: neuropsychological study of a disease with thalamic degeneration. Cortex 28: 175–187. ¨ ber das Tra¨umen bei zerebGloning K, Sternbach I (1953). U ralen Herdla¨sionen. [On dreams with focal cerebral lesions.] Wiener Zeitschrif fu¨r die Nervenheilkunde 6: 302–329. Gottesmann C (2004). Brain inhibitory mechanisms involved in basic and higher integrated sleep processes. Brain Res Rev 45: 230–249. Gru¨nstein A (1924). Die Erforschung der Tra¨uma als eine Methode der topishen Diagnostik bei Grobhirnerkrankungen. [Investigation of dreams as a method of topical diagnosis in cerebral disease.] Zeitschrift fu¨r die gesamte Neurologie & Psychiatrie 93: 416–420. Habib M, Sirigu A (1987). Pure topographical disorientation: a definition and anatomical basis. Cortex 23: 73–85.
542
M. SOLMS
Hartmann E, Russ D, Oldfield M et al. (1980). Dream content: effects of L-DOPA. Sleep Res 9: 153. Hobson JA (2001). The Dream Drugstore: Chemically Altered States of Consciousness. Bradford, Cambridge, MA. Hobson JA, McCarley R (1977). The brain as a dream-state generator: an activation-synthesis hypothesis of the dream process. Am J Psychiatry 134: 1335–1368. Hobson JA, McCarley RW, Wyzinki PW (1975). Sleep cycle oscillation: reciprocal discharge by two brainstem neuronal groups. Science 189: 55–58. Hobson JA, Lydic R, Baghdoyan H (1986). Evolving concepts of sleep cycle generation: from brain centers to neuronal populations. Behav Brain Sci 9: 371–448. Hobson JA, Pace-Schott EF, Stickgold R (2000). Consciousness: its vicissitudes in waking and sleep – an integration of recent neurophysiological and neuropsychological evidence. In: M Gazzaniga (Ed.), The New Cognitive Neurosciences. 2nd edn. MIT Press, Cambridge, MA. Humphrey M, Zangwill O (1951). Cessation of dreaming after brain injury. J Neurol Neurosurg Psychiatry 14: 322–325. Jakobson R (1973). Towards a linguistic classification of aphasic impairments. In: H Goodglass, S Blumstein (Eds.), Psycholinguistics & Aphasia. Johns Hopkins University Press, Baltimore, pp. 29–47. Jus A, Jus K, Villeneuve A et al. (1973). Studies on dream recall in chronic schizophrenic patients after prefrontal lobotomy. Biol Psychiatry 6: 275–293. Kapur S (2003). Psychosis as a state of aberrant salience: a framework linking biology, phenomenology, and pharmacology in schizophrenia. Am J Psychiatry 160: 13–23. Kardiner A (1932). The bio-analysis of the epileptic reaction. Psychoanal Q 1: 375–483. Kerr N, Foulkes D, Jurkovic G (1978). Reported absence of visual dream imagery in a normally sighted subject with Turner’s syndrome. Journal of Mental Imagery 2: 247–264. LaBerge S (2000). Lucid dreaming: evidence and methodology. Behav Brain Sci 23: 962–964. Lavie P, Pratt H, Scharf B et al. (1984). Localized pontine lesion: nearly total absence of REM sleep. Neurology 34: 118–120. Lena I, Parrot S, Deschaux O et al. (2005). Variations in extracellular levels of dopamine, noradrenaline, glutamate, and aspartate across the sleep–wake cycle in the medial prefrontal cortex and nucleus accumbens of freely moving rats. J Neurosci Res 81: 891–899. Lissauer H (1890). Ein Fall von Seelenblindheit nebst einen Beitrage zur Theorie derselben. [A case of mind blindness with a contribution to theory.] Archiv fu¨r Psychiatrie 21: 222–270. Lugaresi E, Medori R, Montagna P et al. (1986). Fatal familial insomnia and dysautonomia with selective degeneration of thalamic nuclei. N Engl J Med 315: 997–1003. Lyman R, Kwan S, Chao W (1938). Left occipito-parietal tumour with observations on alexia and agraphia in Chinese and in English. Chin Med J 54: 491–516. Macrae D, Trolle E (1956). The defect of function in visual agnosia. Brain 79: 94–110.
Maquet P (2000). Functional neuroimaging of normal human sleep by positron emission tomography. J Sleep Res 9: 207–231. Maquet P, Peters J-M, Aerts J et al. (1996). Functional neuroanatomy of human rapid-eye-movement sleep and dreaming. Nature 383: 163–166. Maquet P, Degueldre C, Delfiore G et al. (1997). Functional neuroanatomy of human slow wave sleep. J Neurosci 17: 2807–2812. Markand O, Dyken M (1976). Sleep abnormalities in patients with brain stem lesions. Neurology 26: 769–776. Michel F, Sieroff E (1981). Une approche anatomo-clinique des deficits de l’imagerie oneirique, est-elle possible? [A clinico-anatomical approach to dream imagery deficits: Is it possible?] In: Sleep: Proceedings of an International Colloquium, Carlo Erba Farmitalia, Milan. Miller JD, Farber J, Gatz P et al. (1983). Activity of mesencephalic dopamine and non-dopamine neurons across stages of sleep and waking in the rat. Brain Res 273: 133–141. Morris M, Bowers D, Chatterjee A et al. (1992). Amnesia following a discrete basal forebrain lesion. Brain 115: 1827–1847. Moss CS (1972). Recovery with Aphasia: The Aftermath of My Stroke. University of Illinois Press, Urbana. Mu¨ller F (1892). Ein Beitrag zur Kenntniss der Seelenblindheit. [A contribution to the knowledge of mind-blindness.] Arch Psychiatr Nervenkr 24: 856–917. Munk H (1878). Weitere Mittheilungen zur Physiologie des Grosshirnrinde. [Further contribution to the physiology of the cerebral cortex.] Archiv fu¨r Anatomie und Physiologie 2: 161–178. Murri L, Arena R, Siciliano G et al. (1984). Dream recall in patients with focal cerebral lesions. Arch Neurol 41: 183–185. Murri L, Massetani R, Siciliano G et al. (1985). Dream recall after sleep interruption in brain-injured patients. Sleep 8: 356–362. Naville F, Brantmay H (1935). Contribution a` l’e´tude des e´quivalents e´pileptiques chez les enfants. [Contribution to the study of epilepsy in infancy.] Archives Suisses de Neurologie et de Psychiatrie 35: 92–122. Neal P, Deneut R (1988). As I Am. Century, London. Nielsen J (1946). Agnosia, Apraxia, Aphasia: Their Value in Cerebral Localization. 2nd edn. Hoeber, New York. Nielsen J (1955). Occipital lobes, dreams and psychosis. J Nerv Ment Dis 121: 50–52. Nielsen TA (2000). A review of mentation in REM and NREM sleep: “covert” REM sleep as a possible reconciliation of two opposing models. Behav Brain Sci 23: 851–866. Nofzinger EA, Mintum MA, Wiseman MB et al. (1997). Forebrain activation in REM sleep. An FDG PET study. Brain Res 770: 192–201. Ogilvie RD, Takeuchi T, Murphy TI (2000). Expanding Nielsen’s covert REM model, questioning Solm’s approach to dreaming and REM sleep, and re-interpreting the Vertes & Eastman view of REM sleep and memory. Behav Brain Sci 23: 981–983.
NEUROBIOLOGY AND THE NEUROLOGICAL BASIS OF DREAMING Osorio L, Daroff R (1980). Absence of REM and altered NREM sleep in patients with spino-cerebellar degeneration and slow saccades. Ann Neurol 7: 277–280. Ostow M (1954). Psychodynamic disturbances in patients with temporal lobe disorder. J Mt Sinai Hosp 20: 293–308. Pace-Schott EF (2003). Postscript: recent findings on the neurobiology of sleep and dreaming. In: EF Pace-Schott, M Solms, M Blagrove et al. (Eds.), Sleep and Dreaming. University Press, Cambridge, pp. 335–350. Pace-Schott EF, Hobson JA (1998). Review of Mark Solms (1997), The Neuropsychology of Dreams: A ClinicoAnatomical Study. Trends Cogn Sci 2: 199–200. Partridge M (1950). Pre-Frontal Leukotomy: A Survey of 300 Cases Personally Followed for 1½–3 Years. Blackwell, Oxford. Pen˜a-Casanova J, Roig-Rovira T, Bermudez A et al. (1985). Optic aphasia, optic apraxia, and loss of dreaming. Brain Lang 26: 63–71. Penfield W (1938). The cerebral cortex in man: I. The cerebral cortex and consciousness. Arch Neurol Psychiatry 40: 417–442. Penfield W, Erickson T (1941). Epilepsy and Cerebral Localization. Thomas, Springfield, IL. Penfield W, Rasmussen T (1955). The Cerebral Cortex of Man. MacMillan, New York. Perry EK, Piggott MA (2000). Neurotransmitter mechanisms of dreaming: implications of modulatory systems based on dream intensity. BehavBrain Sci 23: 990–992. ¨ ber das Traumleben leukotomierter Piehler R (1950). U (Vorla¨ufige Mitteilung). [On the dream-life of the leukotomized (preliminary communication).] Nervena¨rzt 21: 517–521. Porte HS (2000). Neural constraints on cognition in sleep. Behav Brain Sci 23: 994–995. Po¨tzl O (1928). Die Aphasielehre vom Standpunkt der klinischen Psychiatrie, I: Die Optisch-Agnostischen Storungen (die verschiedenen Formen der Seelenblindheit). [The aphasia doctrine from the standpoint of clinical psychiatry, I: Optic-agnosic disorders (the different forms of mind-blindness).] Deuticke, Leipzig. Poza J, Marti J (2006). Total dream loss secondary to left temporo-occipital brain injury. Neurologia 21: 152–154. Ritchie D (1959). Stroke: A Diary of Recovery. Faber & Faber, London. Rodin E, Mulder D, Faucett R et al. (1955). Psychologic factors in convulsive disorders of focal origin. Arch Neurol 74: 365–374. Sacks O (1985). The Man Who Mistook His Wife for a Hat. Duckworth, London. Sacks O (1991). Neurological dreams. MD February: 29–32. Sacks O (1995). An Anthropologist on Mars. Picador, London. Sacks O, Wasserman R (1987). The case of the colorblind painter. New York Review of Books 34 (18): 25–34. Schanfald D, Pearlman C, Greenberg R (1985). The capacity of stroke patients to report dreams. Cortex 21: 237–247.
543
Schindler R (1953). Das Traumleben der Leukomierten. [The dream-life of the leukotomized.] Wiener Zeitschrift fu¨r die Nervenheilkunde 6: 330. Snyder H (1958). Epileptic equivalents in children. Pediatrics 18: 308–318. Solms M (1991). Anoneira and the Neuropsychology of Dreams. Doctoral dissertation, University of the Witwatersrand, Johannesburg. Solms M (1997). The Neuropsychology of Dreams. A Clinico-Anatomical Study. Erlbaum, New Jersey. Solms M (2000). Dreaming and REM sleep are controlled by different brain mechanisms. Behav Brain Sci 23: 843–850. Solms M (2002). The neurochemistry of dreaming: cholinergic and dopaminergic hypotheses. In: E Perry, H Ashton, A Young (Eds.), The Neurochemistry of Consciousness. Advances in Consciousness Research. John Benjamin’s Publishing, Amsterdam, pp. 123–131. Solms M, Kaplan-Solms K, Brown J (1996). Wilbrand’s case of “mind-blindness.” In: C Code, C-W Wallesch, Y Joanette et al. (Eds.), Classic Cases in Neuropsychology. Psychology Press, Hove, England, pp. 89–110. Sparr S, Jay M, Drislane F et al. (1991). A historic case of visual agnosia. Revisited after 40 years. Brain 114: 789–900. Suzuki H, Uchiyama M, Tagaya H et al. (2004). Dreaming during non-rapid eye movement sleep in the absence of prior rapid eye movement sleep. Sleep 27: 1486–1490. Takenchi T, Miyasita A, Inugami M et al. (2001). Intrinsic dreams are not produced without REM sleep mechanisms: evidence through elicitation of sleep onset REM periods. J Sleep Res 10: 43–52. Torda C (1969). Dreams of subjects with loss of memory for recent years. Psychophysiology 6: 358–365. Trulson ME, Preussler DW (1984). Dopamine-containing ventral tegmental area neurons in freely moving cats: activity during the sleep–waking cycle and effects of stress. Exp Neurol 83: 367–377. Tzavaras A (1967). Contribution a´ l’e´tude de l’agnosie des physiognomies. [Contribution to the study of agnosia for faces.] Unpublished doctoral dissertation, Faculte´ de Me´decine de l’ Universite´ de Paris, Paris. Vogel GW (2000). Critique of current dream theories. Behav Brain Sci 23: 1014–1016. Walsh K (1994). Neuropsychology: A Clinical Approach. 3rd edn. Churchill Livingstone, Edinburgh. Wapner W, Judd T, Gardener H (1978). Visual agnosia in an artist. Cortex 14: 343–364. Whitty C, Lewin W (1957). Vivid day-dreaming: an usual form of confusion following anterior cingulectomy. Brain 80: 72–76. Wilbrand H (1887). Die Seelenblindheit als Herderscheinung und ihre Beziehung zur Alexie und Agraphie. [Mindblindness as a focal symptom and its relationship to alexia and agraphia.] Bergmann, Wiesbaden. Wilbrand H (1892). Ein Fall von Seelenblindheit und Hemianopsie mit Sectionsbefund. [A case of mind-blindness
544
M. SOLMS
and hemianopia with autopsy results.] Deutsche Zeitschrift fur die Nervenheilkunde 2: 361–387. Yu C (2001a). Neuroanatomical correlates of dreaming: the supramarginal gyrus controversy (dream work). NeuroPsychoanalysis 30: 47–59. Yu C (2001b). Neuroanatomical correlates of dreaming. II: The ventromesial frontal lesion controversy (dream investigation). Neuro-Psychoanalysis 30: 193–201.
Yu C (2007). Brain Mechanisms of Dreaming. Doctoral dissertation. University of Cape town, Cape town. Zinkin N (1959). Psixologiceskaja Nauka vSSSR. [Psychological science in the USSR.] Academy of Pedagogical Science, Moscow.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 35
Abnormal dreams and nightmare disorders ALAN S. EISER * Department of Neurology and Department of Psychiatry, University of Michigan Medical Center, Ann Arbor, MI, USA
INTRODUCTION Determining how and where to draw a line of demarcation between normal and abnormal dreaming is not a simple matter. Dreams are by their nature more illogical, obscure, and bizarre than waking thought, and the most frequently occurring affect in dreams is anxiety or fear. The nightmare is the most extensively investigated form of disordered dreaming, yet it is probably a universal human experience, at least at some point over a lifespan. More fundamentally, there is at present no generally accepted perspective on the nature and understanding of dreams. The very wide spectrum of views ranges from those who feel dreams are not essentially meaningful (Hobson et al., 2000) to others, including the present author (Eiser and Schenck, 2005, part I), who see dreams as richly, deeply, personally meaningful. One’s overall perspective on dreaming will have a fundamental effect on considerations about what constitutes and how to think about “abnormal” dreams. One important way of considering abnormalities of dreaming is to take a clinical approach. Here, dreams may be thought of as abnormal on the basis of the degree of distress or dysfunction they cause, or of their being one symptom in a larger syndrome that causes significant difficulty. But there can be changes in dreaming that do not necessarily cause distress, yet seem sufficiently fundamental to warrant being labeled abnormal. And finally, dreams with qualities that are highly unusual or striking constitute another category that may be considered in a discussion of abnormal dreaming. In what follows, I will briefly review basic understanding of the sleep stage correlates and neurobiology of dreaming, as well as two theoretical models for
understanding dreams psychologically, to serve as a backdrop for the discussion. I will proceed to cover clinical disorders and abnormalities of dreaming, including nightmare disorder, some conditions in which there are alterations in basic elements of dreaming that are not necessarily of primary clinical significance, and finally an unusual variant of dreaming that has received attention.
Dreaming and the sleep cycle The discovery of a close association between rapid eye movement (REM) sleep and dreaming (Aserinsky and Kleitman, 1953; Dement and Kleitman, 1957) was a seminal event that launched the modern era of sleep research and ultimately the field of sleep medicine. Originally it was thought that all dreams, defined roughly as vivid, hallucinatory, narrative experiences, might stem from REM sleep, and indeed the association is a strong one. Typically around 80% of awakenings from REM sleep result in report of a dream, whereas most awakenings from non-REM (NREM) sleep yield reports of more fragmentary, thought-like activity related to daily concerns, or no mental activity at all. However, it has become accepted over time that a small percentage of awakenings from NREM sleep result in reports of a dream, most frequently in the sleep-onset period. Periods of REM sleep, and therefore dreaming, occur cyclically throughout the night as part of the 90-minute NREM–REM sleep cycle. They occupy about 20% of sleep in young adults. REM periods become longer and more dense in eye movements as the night goes on, and the associated dreams are correspondingly lengthier and perhaps more vivid and emotional.
*Correspondence to: Alan S. Eiser, Ph.D., Department of Neurology, Sleep Disorders Center, University of Michigan Medical Center, C728 Med Inn Building – Box 0845, 1500 E. Medical Center Drive, Ann Arbor, MI 48109-0845, USA. Tel: (734) 936-7580, Fax: (734) 936-5377, E-mail:
[email protected]
546
A.S. EISER
Neurobiology of dreaming
Psychology of dreaming
Some early efforts to understand the neurobiology of dreaming emphasized the role of the pontine brainstem in generating REM sleep and postulated that this entailed bombardment of the forebrain with random, relatively noisy signals out of which the forebrain struggles to make sense in producing dreams (Hobson and McCarley, 1977). These views seem to many, including the present author, highly arbitrary and not well related to the phenomena of dreaming (Rechtschaffen, 1978; Vogel, 1978; Jones, 2000; Eiser and Schenck, 2005, part I). Recent developments stemming from lesion and neuroimaging studies have delineated the crucial role of the forebrain in dreaming and provide a very different perspective. Overall, the findings show a quite specific, selective pattern of involvement of forebrain structures in dreaming, suggesting the brain is organized to carry out particular functions in a concerted fashion. Lesion studies demonstrate that dreaming ceases to occur with focal damage to certain forebrain sites: not only areas that support cognitive processes essential for mental imagery, but also circuits involved in appetitive interactions with the world, appear to be crucial. Lesions in other specific forebrain sites result in dramatic alterations or dysregulation of dreaming (Solms, 1997) (see below). Findings show that “dreams are not . . . products of nonspecific activation of perceptual and motor cortex” but are “actively constructed through complex cognitive processes” (Solms, 2000). Imaging studies during REM sleep provide quite consistent and complementary results (Maquet et al., 1996; Braun et al., 1997; Nofzinger et al., 1997). They demonstrate a high overall level of brain activity, with involvement of structures that mediate arousal in the brainstem, thalamus, and basal forebrain. There are high levels of activation in parts of the hypothalamus and limbic and paralimbic systems, in some areas higher than during wakefulness, consistent with a major role for emotion and drive. The activation of the amygdala may be linked to the role of anxiety in dreaming. The dorsolateral prefrontal cortex, which is essential in executive functioning, selfmonitoring, and volitional control, is not significantly involved in dreaming based on both lesion and imaging findings. There is an apparent shift in the balance between motives and emotions on the one hand and controlling/inhibitory functions on the other in favor of the former. To what degree the brainstem activation during REM sleep makes an essential contribution to dreaming remains an area of controversy.
Two influential models of the psychology of dreaming are the psychoanalytic, originally developed by Freud (1900) and elaborated and modified by many later contributors, and Hartmann’s (1996a) “contemporary theory of dreaming.” For both, dreams are highly meaningful mental products. In the psychoanalytic view, unconscious mental processes play a major role: the meaning of the dream is not apparent in the manifest content, or the dream as recalled by the dreamer, but rather is to be found in the “latent dream thoughts,” some of which are unconscious. Dreams are seen as attempts at fulfillment of wishes: the wishes are often conflicted instinctual, i.e., sexual and aggressive, wishes with links to childhood sources. Thought processes typically from the preceding day, called “day residues,” are the point of contact between the wishes and present-day concerns. A primitive mode of thinking, primary process thought, predominates, as opposed to the secondary process mode that holds sway in conscious, rational thinking. The latent material of the dream is transformed into the manifest content by the primary process mechanisms of condensation, the combining of two or more elements into a single one, and displacement, a shifting of emphasis from one element to a different one. Symbolization is another mechanism involved. Since the wishes are conflicted, they must be disguised to avoid arousing excessive anxiety or other painful affects and disturbing sleep; the primary process mechanisms subserve this need for censorship. If disguise fails and the dream arouses excessive anxiety, a nightmare with awakening may result. An additional mechanism for nightmares may be the need actively to replay a traumatic situation that was originally experienced passively, i.e., without preparedness or control, in an effort to obtain mastery (Freud, 1920), though it is not certain whether this is truly distinct from the usual processes that enter into dreaming. The psychoanalytic model has been enriched by more recent advances in the understanding of conflict, object relations (internal relatedness to people), and narcissism (development of the self and self-esteem), which provide additional explanatory tools to supplement the original emphasis on instinctual drives in understanding dreams. Hartmann’s (1996a) view of dreaming utilizes progressions in dreams following psychological trauma as a paradigmatic situation. Dreams are seen, in the framework of a neural nets model of the mind, as acting to make connections in a much broader way than waking mental activity and in an “autoassociative” mode. Initially dreams following trauma reflect raw
ABNORMAL DREAMS AND feelings of terror and being overwhelmed, in images such as a tidal wave. Dreaming then functions to connect the trauma with related emotional material in order to “contextualize” the dreamer’s dominant emotion in the form of an explanatory metaphor. Over time, the experience of the trauma is connected more and more broadly with emotionally similar material from the dreamer’s life and mind, and the trauma is integrated. The process is adaptive both in calming the immediate emotional storm and in promoting more ready integration of similar traumatic experiences in the future. When obvious trauma is not operative, dreams function to deal with the dreamer’s dominant emotional concerns at the time in the same (though less dramatically evident) fashion. The model directs attention to the responsiveness of dreams to external events and to important considerations of the adaptive functions of dreaming. However, it appears to the present author that some of the explanatory richness of the psychoanalytic model is lost, and that the importance of internal, subjective contributions to dreaming, including persistent wishes and motivations, may be underemphasized.
CLINICAL DISORDERS AND ABNORMALITIES OF DREAMING Nightmare disorder DEFINITION,
DIAGNOSTIC CRITERIA, AND GENERAL
CONSIDERATIONS
Although alterations in dreaming or other mental activity during sleep figure significantly in the descriptions of several of the disorders in the International Classification of Sleep Disorders, 2nd edition (ICSD-2) (American Academy of Sleep Medicine, 2005), there is only one diagnosis, “nightmare disorder,” for which abnormal dreaming is the primary feature. Nightmares, experienced at least occasionally, are a widespread if not universal part of the human condition; most people have some sense of familiarity with the phenomenon in terms of very frightening dreams that awaken the dreamer. Formally, nightmares have traditionally been defined along the lines of the description in the American Psychiatric Association (2000) Diagnostic and Statistical Manual of Mental Disorders, 4th edition, text revision: “Repeated awakenings from the major sleep period or naps with detailed recall of extended and extremely frightening dreams, usually involving threats to survival, security, or self-esteem.” There has been recent discussion of broadening two elements of the traditional definition: the requirement that the dreams invariably awaken the subject, and
NIGHTMARE DISORDERS 547 the exclusive requirement for anxious or frightened affect as opposed to a wider range of unpleasant feelings (Zadra and Donderi, 2000, 2003). Expanded approaches to these two dimensions are incorporated in the ICSD-2 definition, which refers to “disturbing mental experiences that generally occur during REM sleep and that often result in awakening.” With respect to the disturbing affect, the ICSD-2 states that “Emotions usually involve anxiety, fear, or terror but frequently also anger, rage, embarrassment, disgust, and other negative feelings.” Nightmares are typically extended, elaborate dream narratives, as usually occur during REM sleep, with increasingly disturbed affect culminating in arousal. The ICSD-2 notes “imminent physical danger to the individual” as a particularly common content. Full consciousness is quickly attained with arousal, and there is often detailed recall of the preceding dream. Little or no movement is seen with arousal from nightmares. The subject may have difficulty falling back to sleep. Since the propensity to have REM sleep is greatest in the latter part of the night, most nightmares occur in that time period. The diagnosis of “nightmare disorder” in the ICSD-2 is based upon the following criteria (American Academy of Sleep Medicine, 2005): A. Recurrent episodes of awakenings from sleep with recall of intensely disturbing dream mentation, usually involving fear or anxiety, but also anger, sadness, disgust, and other dysphoric emotions. B. Full alertness on awakening, with little confusion or disorientation; recall of sleep mentation is immediate and clear. C. At least one of the following associated features is present: 1. delayed return to sleep after the episodes 2. occurrence of episodes in the latter half of the habitual sleep period. The prevalence of nightmare disorder in the adult population has not been definitively established, with variable criteria and approaches to assessment contributing to inconsistent findings (even the ICSD-2 does not specify how frequent or distressing the nightmares must be). A prevalence range of 2–8% is given in the ICSD-2. Nightmares are more common in children: a figure of 5–30% has been reported for nightmares occurring “always” or “often” (Partinen, 1994). Nightmares often begin in childhood, at ages 3–5, and may persist through adulthood. Nightmares are more frequent in females, particularly among adults. A genetic predisposition to nightmares which continues into adulthood has been demonstrated in a Finnish twin cohort (Hublin et al., 1999).
548 A.S. EISER The polysomnographic study of nightmares has However, in my view it is essential that nightmares proven somewhat elusive in that they are rarely also be appreciated as psychologically meaningful menobserved in the laboratory. The degree of autonomic tal products, arising from interactions among ongoing arousal, when present at all, seems small in proportion life circumstances, internal conflicts, and personality to the intensity of the affects experienced (Fisher et al., structure, with links to childhood roots and to unre1970). solved disturbing and traumatic experiences. What is at A differentiation is often made between so-called issue is not so much the place in a larger psychiatric synidiopathic nightmares and the nightmares that occur as drome, as the relationship of the nightmares to a nexus a characteristic feature of posttraumatic stress disorder of psychological factors and structures that underlie (PTSD). The latter are described as distinguished by the significant areas of the person’s functioning. To fail to repetitive replay of scenes from a traumatic event, and see nightmares in this light is to miss the message of are the most consistently present symptom of PTSD. the nightmare, the indications expressed of areas of Whether posttraumatic nightmares are based upon a ongoing difficulty and conflict, the present-day circumdifferent mechanism than ordinary nightmares has not stances that evoke these issues, and the matrix of coping been clearly established. PTSD can entail a broad range capacities, resources, and vulnerabilities in which these of disturbance, including mood disorder, and biological are embedded. Omitting these dimensions will inevitably alterations may come into play in some cases. There are diminish the depth of treatment considerations, and limit some suggestions from polysomnographic studies that comprehension of the mode of operation and extent of PTSD nightmares may differ somewhat in that they efficacy of treatments for nightmares, which can only may occur not only out of REM but also out of be fully grasped with reference to the psychological soil NREM sleep, particularly stage 2 (Kramer et al., 1984; out of which the nightmare arises. Woodward et al., 2000a), in a context of greater sleep These considerations apply to posttraumatic as well disruption (Woodward et al., 2000b; Germain and as “idiopathic” nightmares. It is not sufficient to view Nielsen, 2003), on average earlier in the night, and more posttraumatic nightmares simply as replaying trauoften associated with body movement (van der Kolk matic situations that have not been fully assimilated, et al., 1984). Hartmann (1996b), emphasizing differthough this may be one of their functions. Close exploences from ordinary nightmares, has gone so far as to ration of individual cases reveals a much richer fabric argue that repetitive posttraumatic nightmares should of factors at work. A paper by Kramer et al. (1987) not be viewed as dreams at all but as a form of memory on nightmares in Vietnam veterans provides clear illusintrusion; however, it is not clear that the data he cites trations of how the selection of the particular aspect of warrant this conclusion. combat experience that is focused on in nightmares There has been recent discussion regarding whether may be determined by childhood experiences and diffinightmares are better viewed from a sleep medicine culties, which may in turn be stirred up by problems in perspective, as a discrete sleep disorder warranting the patient’s current life. “The Vietnam experience separate evaluation and treatment, or from what is serves as a metaphor to express the difficulties.” characterized as a psychiatric viewpoint regarding Another function of some posttraumatic nightmares them as a symptom of a larger syndrome, e.g., an anxin providing a kind of hidden reassurance is developed iety disorder. A contribution from Spoormaker et al. in several case studies by Renik (1981), and illuminat(2006) has preferentially emphasized the value of a ing illustrations of some of the complex functions, sleep disorders perspective on nightmares. There is no meanings, and origins of traumatic nightmares in a question that taking a sleep disorders view of nightgroup of psychiatric inpatients at a Veterans Adminismares as a discrete symptom can have considerable tration hospital, with particular emphasis on defensive value in focusing attention on the clinical significance screening functions and efforts to cope with shame, of the nightmares and bringing to light certain types injury to self-esteem, and states of vulnerability, may of causative factors. It may be that conditions that disbe found in a book by Lansky (1995). rupt or fragment sleep, such as obstructive sleep A perspective on nightmares that embraces both apnea, can lead to more frequent nightmares (Youakim their dimension as a sleep problem per se, with its et al., 1998; Krakow et al., 2000), as happens with sleep place in the overall picture of the patient’s sleep–wake terrors. Similarly, it is possible that poor sleep hygiene, functioning, and their meaning as a richly informative insufficient sleep, and circadian rhythm disturbances symptom and expression of the patient’s mental life, may increase nightmares. And nightmares have been will best serve the clinician (and researcher) faced with reported to lead to secondary difficulties with sleep a patient’s complaint of nightmares. avoidance and insomnia, which must also be recogMany studies have investigated the relationship nized clinically (Krakow et al., 1995). between nightmare disorder and psychopathology, in
ABNORMAL DREAMS AND NIGHTMARE DISORDERS most, but not all, instances finding an association (Hublin et al., 1999; Zadra and Donderi, 2000). There has been recent interest in the variable of nightmare distress – the negative impact of nightmares on daytime functioning – as a potentially mediating factor in these relationships (Blagrove et al., 2004). It is perhaps not surprising that there is variability and complexity in findings regarding nightmare/ psychopathology associations. Nightmares are specific mental events arising from areas of internal strain: a pressing, troubling impulse, feeling, concern, or experience is not able to be dealt with and modulated effectively and intense anxiety or other unpleasant affect results. Frequent nightmares can occur in many different psychopathological contexts, with wide variability in their relationship to and implications for overall functioning. Indeed, some nightmares are seen in normal functioning under conditions of internal stress and creative crisis. Additional complexity in considering the place of nightmares in overall functioning may be seen in Hartmann’s (1994) finding that many chronic nightmare sufferers do not wish to be rid of their nightmares. Some were artists who made use of the nightmares in their work, while others felt the nightmares to be an integral part of their personality which they did not want changed. Hartmann (1998) has delineated a dimension of personality he refers to as thick versus thin boundaries, and related it to the vulnerability to nightmares. This boundary concept is an aggregate of many different kinds of boundaries, e.g., those between thought and feeling, between self and other, between conscious and unconscious mental activity, indeed between and around a wide range of different mental functions, states, and contents. People with thick boundaries tend to be solid, well-organized, logical, and linear in thought, well-defended, and perhaps rigid. Those with thin boundaries tend to be open, sensitive, to have a quality of experience that is more imagistic and suffused with feeling, can be more vulnerable, and may be creative. Hartmann finds that thin boundaries are associated with greater frequency of dream recall, more vivid, emotional, and dreamlike dream reports, and with nightmares.
DIFFERENTIAL
DIAGNOSIS OF NIGHTMARE DISORDER
An important consideration in differential diagnosis is the distinction between nightmare disorder and sleep terrors. Sleep terrors are a disorder of arousal from NREM sleep, particularly stages 3 and 4 sleep early in the night, as opposed to nightmares, which usually arise out of REM sleep, typically later in the night. Sleep terrors commence with a cry or a scream and
549
involve intense fright, but usually there is only fragmentary imagery or no recalled imagery at all. There is a high degree of autonomic arousal as compared to relatively little with nightmares, and sleep terrors may be associated with considerable movement, including flight and violence. The awakenings from sleep terrors are characterized by confusion, disorientation, unresponsiveness to the environment, and difficulty attaining full alertness, as opposed to the rapid attainment of alertness, orientation, and clarity of thought with nightmares. However, patients are able to fall back to sleep more readily following sleep terrors than after awakenings from nightmares. In terms of further differential diagnosis, somnambulism (sleepwalking), like sleep terrors, arises from NREM sleep early in the night and is usually associated with little or no recall of mental activity, but occasionally can involve elaborate dream mentation. Nocturnal seizures are at times manifest as recurrent, perhaps stereotyped, nightmares, but these arise from an epileptogenic temporal-lobe focus. Dreaming in REM sleep behavior disorder (RBD) is often reported to be altered in the direction of unpleasant, disturbing, very active, and violent dreams, but the context is the loss of muscle atonia, abnormally enhanced muscle activity, and acting out of dreams that characterize this disorder. The hypnagogic hallucinations that are a symptom of narcolepsy may be experienced as nightmares, at times more frightening due to simultaneously occurring sleep paralysis, but these phenomena occur at sleep onset and as part of the clinical symptom picture of narcolepsy. Nightmares can also be associated with the use of certain medications or withdrawal from medications or alcohol, as described below. A careful, detailed clinical history is central to the evaluation of nightmare disorder. Polysomnographic study is warranted when there is reason to suspect in the differential diagnosis a sleep-related seizure disorder, RBD, narcolepsy, or a NREM arousal disorder, such as sleep terrors, especially when associated with potentially injurious behavior. Polysomnography should also be performed if there is evidence for a sleep disorder such as obstructive sleep apnea, which entails frequent arousals that may be contributing to nightmares. The patient who is found to have clinically significant nightmares should be evaluated from both a psychiatric and a psychological point of view.
TREATMENT
OF NIGHTMARE DISORDER
Approaches to the treatment of nightmare disorder can vary considerably, depending in part on theoretical perspective. One way treatments may be classified is in
550
A.S. EISER
terms of whether they target the symptom of nightmares in relative isolation, or whether they aim at working out underlying psychological issues viewed as causing nightmares and other interconnected symptoms and problems. An approach of the former kind that has been developed within sleep medicine is imagery rehearsal therapy (IRT), a brief cognitivebehavioral technique for treating nightmares. In this approach, persistent nightmares are viewed as a learned habit. Patients are taught positive imaging techniques, and then work on changing some of their nightmares and practicing the altered nightmare scenarios. Significant improvement has been reported with utilization of this technique in a number of patient groups. For example, in a large sample of sexual assault survivors with PTSD, improvements in nightmare frequency, sleep quality, and PTSD severity were found among those who completed the three-session treatment (Krakow et al., 2001). A very detailed description of the approach can be found in Krakow and Zadra (2006). Empirical results supporting the efficacy of IRT are impressive, though the conceptual framework for understanding nightmares and their resolution seems limited. In another approach focused relatively specifically on the symptom of nightmares, the medication prazosin has been shown to be effective in reducing traumatic nightmares in combat-related PTSD in two well-controlled studies (Raskind et al., 2003, 2007). Preliminary findings of efficacy in civilian trauma PTSD have also been reported (Taylor et al., 2008). The authors view the beneficial effects of the drug as deriving from its a1-adrenoreceptor antagonist action, which they see as reducing excessive noradrenergic activity in the prefrontal cortex in PTSD patients. Improvements in sleep and in overall clinical status were also reported. Exploratory, or psychodynamic, psychotherapy is a very different kind of treatment approach from IRT or the use of medications. It aims to work out underlying conflicts and traumatic influences that are relevant not only to a specific symptom, such as nightmares, but to other interrelated symptoms, difficulties, and impairments in overall functioning and capacities for satisfaction. It is often more long-term and intensive in scope. In some instances, clarification of an old issue that has been evoked by life events and led fairly directly to a symptom such as nightmares may be obtained rapidly and result in a satisfactory degree of improvement with relatively short-term work; in others, the range of presenting problems may be so broad and their embeddedness in the personality structure so deep as to require much longer and more intensive
treatment. The approach has been shown empirically to have broad benefits (Gabbard, 2005). With respect to the symptom of nightmares, case report evidence of efficacy is available (Renik, 1981). But, in contrast to IRT or medications, the focus is less on direct efforts to diminish a specific symptom seen in relative isolation than on expanding the understanding and mastery of the factors that underlie symptoms and other kinds of difficulties. The individualized nature of the treatment, its scope and length, and the complex relationship between the factors it deals with and any particular symptom such as nightmares, make traditional approaches to assessment of efficacy (i.e., controlled prospective studies with specific symptom outcome measures) less apt and comparisons of efficacy with treatments as differently conceived as IRT or medications quite complicated and perhaps ultimately not very meaningful. The field is nowhere near consensus on an approach to considering which type of treatment to recommend in individual cases, and the perspectives and personal preferences of individual clinicians undoubtedly play a large role in practice. Further development of means for taking into account factors such as the nature of the clinical presentation, the psychological makeup and resources of the patient, psychiatric status, the patient’s personal preferences, and others in making treatment recommendations is much needed.
Sleep terrors Although sleep terrors are typically not, properly speaking, dreams, they do often involve abnormal mental content during sleep and as such will be discussed further here. In a careful, indepth study, Fisher et al. (1970, 1974) found that mental content was recalled from over 50% of episodes. Most typically, there was a single frightening scene or thought, such as the idea of an intruder in the room. Common types of fearful imagery included things closing in or being entrapped in a small area, being crushed or struck, falling, fear of aggression from a person, being left alone, choking, and fear of dying. Unlike in nightmares, the content usually appears to arise more or less instantaneously rather than developing gradually and progressively. Although not typical, at times elaborate dreams may be recalled with sleep terrors. Episodes may arise spontaneously, be precipitated by arousals stemming from another sleep disorder such as obstructive sleep apnea or periodic limb movement disorder, or can be triggered in predisposed people by exogenous stimulation, such as a loud buzzer (Fisher et al., 1970). Effective control of sleep terrors has been obtained with medications such as imipramine, diazepam, and
ABNORMAL DREAMS AND clonazepam. However, in some patients the content of sleep terrors may be seen to be associated with significant areas of trauma and conflict, in a context in which more pervasive psychopathology is present (Fisher et al., 1970); when this is so, psychotherapy may be considered in addition to medication treatment.
Narcolepsy Abnormal dreaming is seen in narcolepsy primarily in the form of the symptom of hypnagogic hallucinations, or vivid experiences of dreaming occurring just at sleep onset (typically in association with a sleep-onset REM period). Found in 40–80% of narcoleptics, these dreams show a predominance of frightening and unpleasant content, with frequent themes of being attacked or of a threatening presence. Humans are the most common threatening figures, but animals, reptiles, and monsters/ghosts are also often seen (Honda, 1988). The dreams may be repetitive, and in their perceptual mode somewhat less predominantly visual, and more tactile, than ordinary dreaming. The state of consciousness appears to be different from ordinary dreaming, with persistence of some elements of wakefulness: aspects of the actual sleeping environment are often incorporated in the dream along with a sense that the frightening experience is really happening (Vogel, 1976; Honda, 1988). Sleep paralysis may accompany the hypnagogic hallucination and the perception of inability to move may add to the fright. The precise mechanism of these abnormalities of dreaming is not known, though they appear to reflect in part the intermingling of elements of REM sleep and wakefulness that characterize many of the manifestations of narcolepsy. There is also evidence to suggest that narcoleptics’ nighttime (as opposed to sleep-onset) dreams may be somewhat altered, with a more negative emotional tone and a higher level of bizarreness (Schredl, 1998). Hypnagogic hallucinations respond to the same treatments as do the other auxiliary symptoms of narcolepsy.
REM sleep behavior disorder RBD is known primarily for the failure of muscle paralysis during REM sleep and acting out of dreams, often with injurious and/or self-injurious consequences. However, there is strong evidence from a number of sources that dreams themselves are altered in RBD (Schenck et al., 1993; Olson et al., 2000). Patients report that their dreams are more vivid, active, and especially aggressive or violent than previously, and objective raters have found more aggression in RBD patients’ dreams than in those of normal controls (Fantini et al., 2005). The content often involves
NIGHTMARE DISORDERS
551
defending against attacks by people or animals. RBD is strongly associated with neurodegenerative disorders, mainly alpha-synucleinopathies, and the pathophysiology is thought to reside in the brainstem; this suggests that the mechanism for dreaming changes in RBD may involve a disinhibition of brainstem generators of aggressive behavior during REM sleep. Interestingly, there may be an interaction with personality factors, in that patients with RBD are often reported to be mild-mannered and placid in their waking lives (Schenck and Mahowald, 2002), and aggression in RBD patients’ dreams is inversely correlated with some measures of daytime aggressiveness (Fantini et al., 2005). The dreams are reported to normalize with standard treatment of RBD.
Epic dreaming “Epic dreaming” is an interesting clinical entity, first described and named by Schenck and Mahowald in an abstract in 1995: the process of characterizing and investigating this proposed dream disorder is ongoing. Patients complained of dreaming relentlessly all night long and awakening feeling exhausted, with subsequent fatigue during the daytime. The dreams involved constant physical activity, usually of a neutral, repetitive kind such as endlessly walking through snow or mud, working on the job, or doing household chores. Patients spoke of their “dream motor running all night long.” There was no accompanying emotion apart from a sense of exhaustion. These symptoms were experienced nightly or on most nights. The disorder was typically longstanding. An abrupt onset was reported in some cases, at times associated with medical illness or stress. Most of the patients were women. Seventy percent of patients complained of nightmares in addition to epic dreaming, and 35% of patients had a history of psychiatric disorder. Polysomnographic studies were performed in most patients and usually showed no abnormality, though obstructive sleep apnea and periodic limb movements were present in a few. Multiple sleep latency tests were normal. Reports of mental content were not systematically collected, though there was said to be dream recall during spontaneous awakenings from both REM and NREM sleep. A variety of treatments were tried but proved largely ineffective. An additional single case of epic dreaming reported by Zadra and Nielsen (1996) had a very similar symptom picture. Here, during two consecutive nights of sleep recording, awakenings were carried out during NREM sleep to elicit mental content; reports were obtained from REM sleep during spontaneous arousals. Elaborate dreaming was not reported from any
552
A.S. EISER
of the NREM awakenings, and the content that characterized the patient’s complaint of relentless dreaming was not seen in NREM or REM reports. Two further samples of epic dreamers, from Taiwan, have been described. In one, the symptoms of relentless dreaming and daytime fatigue were present, but the dream content did not show the predominant physical activity. Patients did feel that their brains and minds were overworked during sleep. In the second report from Taiwan (Shih-Wei et al., 2005), a high frequency of psychopathology was noted in the sample. Both reports suggested a possible lightening of sleep and increased number of arousals in the patients, but it is uncertain how much this may have reflected sleeping for the first time in the laboratory. The female predominance was not found in the Taiwanese samples. There is much that remains unclear about the clinical entity of “epic dreaming.” The possible association with a medical or sleep disorder in some cases suggests that this may be a heterogeneous category. With very limited data on mental content obtained from awakenings during REM and NREM sleep, it is not yet possible to know whether patients are indeed dreaming throughout sleep or whether this is an experience they have that does not literally correspond to the objective situation. The relationship between epic dreaming and the very frequent complaint of nightmares reported in the initial sample remains to be elucidated; perhaps both are connected to the same internal struggles in some patients. More broadly, it would be most helpful to have the opportunity for intensive clinical study of the dream experiences of epic dreamers, to illuminate possible connections between the dream content and qualities and the patients’ internal conflicts, coping efforts and mechanisms, and personality structure.
Epilepsy Abnormal dreaming, most often in the form of recurrent nightmares with repetitive content or stereotyped theme, may be found as a symptom of epilepsy. The picture is most often one of complex partial seizures with a temporal-lobe focus; some, but not all, studies find a right lateral bias. The nightmares may have content similar to daytime ictal visual hallucinations, or include elements of the daytime seizure aura, phosphenes, and other sensory phenomena (Reami et al., 1991; Solms, 1997). Sometimes a nightmare may lead into a generalized nocturnal seizure. In terms of course, in some cases the nightmares begin at the same time as other symptoms of epilepsy; in others they may precede the development of clinical seizures.
The sensory elements and predominance of fear in the nightmares are consistent with temporal limbic mechanisms. Anticonvulsant medication or surgical treatment that is effective in relieving seizures may also relieve accompanying nightmares (Reami et al., 1991; Solms, 1997).
Drug and alcohol use and withdrawal There are a large number of medications which have been reported to be associated with complaints of nightmares, most frequently dopamine agonists, betablockers, and selective serotonin reuptake inhibitors (SSRIs) (Thompson and Pierce, 1999; Pagel and Helfter, 2003). These include many antiparkinsonian agents, antihypertensives, and antidepressants. Some sedative/hypnotics are also reported to be associated with nightmares. A valuable review and integration of data drawn from clinical trials and case reports has been provided by Pagel and Helfter (2003). They found the clearest associations with nightmares in medications that affect the neurotransmitters norepinephrine, serotonin, and dopamine. Medications that affect the immunological response to infectious disease were associated with nightmares in some patients. The individual medication most clearly associated with nightmares was the SSRI paroxetine. Nightmares have also been found to occur with withdrawal from REM-suppressant agents such as alcohol, barbiturates, and some antidepressants. Additionally, increases in qualities such as the intensity and vividness of dreaming, not necessarily entailing frank nightmares, may be seen in some of the same circumstances indicated above, e.g., with use of dopamine agonists or SSRIs (Pace-Schott et al., 2001) and in withdrawal from REM-suppressant agents.
ABNORMALITIES OF DREAMING THAT MAY NOT PRESENT AS CLINICAL COMPLAINTS Decreased dream recall (or dreaming) following severe trauma Although the dreaming abnormality most closely associated with the aftermath of trauma is the posttraumatic nightmare, an additional, thought-provoking alteration that has been reported is a substantial reduction in recall of dreaming, seen even in several studies in which dreams were elicited by laboratory awakenings from REM sleep. In an early study of “war neuroses,” Greenberg et al. (1972) spoke of an “infrequency of dream recall following REM awakenings,” though quantitative data were not provided and their results may have been confounded by the use of
ABNORMAL DREAMS AND NIGHTMARE DISORDERS psychotropic medications. Kramer et al. (1984) compared Vietnam veterans with disturbed dreaming (occurring more prominently out of NREM sleep) to a control group of veterans without disturbed dreaming but matched for Vietnam combat experience. The controls recalled dreams on only 50% of spontaneous REM awakenings in the laboratory as compared to 77% in the dream-disturbed group (no statistical analysis reported). The authors suggested that the low rate of dream recall among combat veterans without dream disturbance might reflect their “not attending to inner processes” as an adaptive means of avoiding potentially disturbing content related to their combat experience. The most systematic and detailed study of this kind was done by Lavie and colleagues (Lavie and Kaminer, 1991, 1996; Kaminer and Lavie, 1991), who compared groups of well-adjusted and less well-adjusted Holocaust survivors and normal, nontraumatized controls. The rates of dream recall found in awakenings from REM sleep were 33.7% for well-adjusted survivors, 50.5% for less well-adjusted survivors, and 80% for the normal controls. Both groups of survivors had strikingly low rates of dream recall (demonstrated more than 40 years after the trauma). The finding of a particularly low rate for well-adjusted survivors may parallel the Kramer et al. (1984) finding of reduced recall in less-disturbed combat veterans. Drawing on clinical and psychometric data, the authors interpreted their findings to suggest that the well-adjusted survivors were making adaptive use of repression and denial to avoid the potentially disruptive effects of the memories of their traumatic experiences. But this explanation may not go far enough. A dream recall percentage of 33.7% with laboratory awakenings is extraordinarily low, and the authors further report that subjects in this group often not only failed to recall a dream when awakened from REM sleep but did not recall that they had been dreaming, in contrast to the other two groups who usually were aware of having dreamt even when they did not recall any specific content. This suggests a profound walling-off of dreaming experience: van der Kolk et al. (1984) discuss the use of dissociation to deal with intense affects in severely traumatized patients. It may even be that dreaming itself, and not just its recall, is diminished, in spite of the unchanged REM sleep parameters. The possibility of an impoverishment in dreaming is consistent with the authors’ finding that the dreams that were recalled by the well-adjusted group were less complex and salient than the dreams of the other two groups. In considering these possibilities, it would be illuminating to know to what degree imaginative experience and fantasy are present, and accessible, in the waking lives
553
of the well-adjusted survivors (notwithstanding their excellent overall adaptation). A final factor that may be at work in the low recall rates found in both groups of survivors is that the extreme traumatic experiences may have done damage to the very capacities for imaginative/fantasy modes of mental activity.
Abnormalities of dreaming in organic brain damage Several types of significant alteration in dreaming have been identified in association with lesions in different brain sites: these are dreaming abnormalities which may not necessarily in and of themselves be a source of clinical complaint or distress. The most systematic work in this area has been done by Solms (1997). He identified two lesion sites associated with complete cessation of dreaming. One is an area at or near the parietal-temporo-occipital junction, where both unilateral and bilateral lesions have this effect. The other site associated with cessation of dreaming is in the white matter surrounding the frontal horns of the lateral ventricles; these deep frontal lesions must be bilateral. Patients with lesions in visual association cortex have been found by Solms to experience loss of visual imagery in dreams as well as loss of the capacity to conjure up visual imagery when awake. Findings are similar in other sensory modalities. Finally, lesions in various anterior limbic structures lead to an inability to distinguish dreams from reality, often in conjunction with increased frequency and vivacity of dreaming, and loss of reality testing, visual hallucinations, and delusions during wakefulness.
AN UNUSUAL VARIANT OF NORMAL DREAMING Lucid dreaming An interesting variant of some of the typical parameters of dreaming is seen in what has been called lucid dreaming. In this state, subjects, though dreaming, are aware that they are dreaming; they may be able to recall aspects of their waking lives, to reflect to some extent and act deliberately, and to exercise some control over what happens in their dreams. Initially, many thought that lucid dreaming must take place during partial arousals from sleep, thus accounting for the admixture of elements of dreaming and wakeful thought. However, accumulating evidence has shown that lucid dreaming usually occurs during unambiguous REM sleep (LaBerge, 1992). This has been demonstrated by having subjects signal when they enter lucidity (i.e., become aware that they are dreaming) in a way that can be detected on a polysomnogram, such as with a particular pattern of eye movements.
554
A.S. EISER
The signals have usually been given during uninterrupted REM sleep. Lucid dreaming has been shown to occur preferentially in periods of REM sleep with higher levels of eye movement activity and of other physiological parameters, suggesting an association with central nervous system activation. The capacity of lucid dreamers to perform predetermined actions in their dreams has been utilized as a method of investigating with enhanced precision correspondences between activity in dreams and physiological parameters detectable on a polysomnogram. The precise nature of the qualities of waking consciousness, dreaming, and their interaction in lucid dreaming requires further clarification. Occasionally, lucid dreaming may take a pathological course, as in a case reported by Schenck and Mahowald (1990) in which the patient lost control of the vivid, previously pleasurable contents of the dreams, and could no longer escape from others chasing him but instead dreamt of being shot at and beaten up. Finally, it may be noted that in lucid dreaming, the dreamer is lucid in the sense of having some clarity about the fact they are dreaming and some preservation of waking consciousness, but not in the sense of having enhanced access to the meaning and understanding of the dream.
REFERENCES American Academy of Sleep Medicine (2005). The International Classification of Sleep Disorders. 2nd edn. Diagnostic and Coding Manual. American Academy of Sleep Medicine, Westchester, IL. American Psychiatric Association (2000). Diagnostic and Statistical Manual of Mental Disorders. 4th edn. Text Revision. American Psychiatric Association, Washington. Aserinsky E, Kleitman N (1953). Regularly occurring periods of eye motility, and concomitant phenomena, during sleep. Science 118: 273–274. Blagrove M, Farmer L, Williams E (2004). The relationship of nightmare frequency and nightmare distress to wellbeing. J Sleep Res 13: 129–136. Braun AR, Balkin TJ, Wesensten NJ et al. (1997). Regional cerebral blood flow throughout the sleep-wake cycle. An H215O PET study. Brain 120: 1173–1197. Dement W, Kleitman N (1957). The relation of eye movements during sleep to dream activity: an objective method for the study of dreaming. J Exp Psychol 53: 339–346. Eiser AS, Schenck CH (2005). Dreaming: a psychiatric view and insights from the study of parasomnias. Part I: Dreaming as seen from a range of approaches. Part II: Insights on dreaming from studying the parasomnias. Schweiz Arch Neurol Psychiatr 156: 440–470. Fantini ML, Corona A, Clerici S et al. (2005). Aggressive dream content without daytime aggressiveness in REM sleep behavior disorder. Neurology 65: 1010–1015.
Fisher C, Byrne J, Edwards A et al. (1970). A psychophysiological study of nightmares. J Am Psychoanal Assoc 18: 747–782. Fisher C, Kahn E, Edwards A et al. (1974). A psychophysiological study of nightmares and night terrors: III. Mental content and recall of stage 4 night terrors. J Nerv Ment Dis 158: 174–188. Freud S (1900). The Interpretation of Dreams. In: J Strachey (Ed.), The Standard Edition of the Complete Psychological Works of Sigmund Freud. Vols. IV–V. Hogarth Press, London. Freud S (1920). Beyond the Pleasure Principle. In: J Strachey (Ed.), The Standard Edition of the Complete Psychological Works of Sigmund Freud. Vol. XVIII. Hogarth Press, London, pp. 7–64. Gabbard GO (2005). Psychodynamic Psychiatry in Clinical Practice. 4th edn. American Psychiatric Publishing, Washington, pp. 120–121. Germain A, Nielsen TA (2003). Sleep pathophysiology in posttraumatic stress disorder and idiopathic nightmare sufferers. Biol Psychiatry 54: 1092–1098. Greenberg R, Pearlman CA, Gampel D (1972). War neuroses and the adaptive function of REM sleep. Br J Med Psychol 45: 27–33. Hartmann E (1994). Nightmares and other dreams. In: MH Kryger, T Roth, WC Dement (Eds.), Principles and Practice of Sleep Medicine. 2nd edn. WB Saunders, Philadelphia, pp. 407–410. Hartmann E (1996a). Outline for a theory on the nature and functions of dreaming. Dreaming 6: 147–170. Hartmann E (1996b). Who develops PTSD nightmares and who doesn’t. In: D Barrett (Ed.), Trauma and Dreams. Harvard University Press, Cambridge, pp. 100–113. Hartmann E (1998). Dreams and Nightmares. The Origin and Meaning of Dreams. Perseus Publishing, Cambridge, MA, pp. 88–91, 219–229. Hobson JA, McCarley RW (1977). The brain as a dream state generator: an activation-synthesis hypothesis of the dream process. Am J Psychiatry 134: 1335–1348. Hobson JA, Pace-Schott EF, Stickgold R (2000). Dreaming and the brain: toward a cognitive neuroscience of conscious states. Behav Brain Sci 23: 793–842. Honda Y (1988). Clinical features of narcolepsy: Japanese experiences. In: Y Honda, T Juji (Eds.), HLA in Narcolepsy. Springer-Verlag, Berlin, pp. 24–57. Hublin C, Kaprio J, Partinen M et al. (1999). Nightmares: familial aggregation and association with psychiatric disorders in a nationwide twin cohort. Am J Med Genet 88: 329–336. Jones BE (2000). The interpretation of physiology. Behav Brain Sci 23: 955–956. Kaminer H, Lavie P (1991). Sleep and dreaming in Holocaust survivors. Dramatic decrease in dream recall in well-adjusted survivors. J Nerv Ment Dis 179: 664–669. Krakow B, Zadra A (2006). Clinical management of chronic nightmares: imagery rehearsal therapy. Behav Sleep Med 4: 45–70.
ABNORMAL DREAMS AND NIGHTMARE DISORDERS Krakow B, Tandberg D, Scriggins L et al. (1995). A controlled comparison of self-rated sleep complaints in acute and chronic nightmare sufferers. J Nerv Ment Dis 183: 623–627. Krakow B, Lowry C, Germain A et al. (2000). A retrospective study on improvements in nightmares and post-traumatic stress disorder following treatment for co-morbid sleepdisordered breathing. J Psychosom Res 49: 291–298. Krakow B, Hollifield M, Johnston L et al. (2001). Imagery rehearsal therapy for chronic nightmares in sexual assault survivors with posttraumatic stress disorder: a randomized controlled trial. JAMA 286: 537–545. Kramer M, Schoen LS, Kinney L (1984). The dream experience in dream-disturbed Vietnam veterans. In: BA Van Der Kolk (Ed.), Post-Traumatic Stress Disorder: Psychological and Biological Sequelae. American Psychiatric Press, Washington. Kramer M, Schoen LS, Kinney L (1987). Nightmares in Vietnam veterans. J Am Acad Psychoanal 15: 67–81. LaBerge S (1992). Physiological studies of lucid dreaming. In: JS Antrobus, M Bertini (Eds.), The Neuropsychology of Sleep and Dreaming. Lawrence Erlbaum, Hillsdale, NJ, pp. 289–303. Lansky MR (1995). Posttraumatic Nightmares: Psychodynamic Explorations. Analytic Press, Hillsdale, NJ. Lavie P, Kaminer H (1991). Dreams that poison sleep: dreaming in Holocaust survivors. Dreaming 1: 11–21. Lavie P, Kaminer H (1996). Sleep, dreaming, and coping style in Holocaust survivors. In: D Barrett (Ed.), Trauma and Dreams. Harvard University Press, Cambridge, pp. 114–124. Maquet P, Pe´ters J-M, Aerts J et al. (1996). Functional neuroanatomy of human rapid-eye-movement sleep and dreaming. Nature 383: 163–166. Nofzinger EA, Mintun MA, Wiseman MB et al. (1997). Forebrain activation in REM sleep: an FDG PET study. Brain Res 770: 192–201. Olson EJ, Boeve BF, Silber MH (2000). Rapid-eyemovement sleep behavior disorder: demographic, clinical and laboratory findings in 93 cases. Brain 123: 331–339. Pace-Schott EF, Gersh T, Silvestri R et al. (2001). SSRI treatment suppresses dream recall frequency but increases subjective dream intensity in normal subjects. J Sleep Res 10: 129–142. Pagel JF, Helfter P (2003). Drug induced nightmares – an etiology based review. Hum Psychopharmacol Clin Exp 18: 59–67. Partinen M (1994). Epidemiology of sleep disorders. In: MH Kryger, T Roth, WC Dement (Eds.), Principles and Practice of Sleep Medicine. 2nd edn. WB Saunders, Philadelphia, pp. 437–452. Raskind MA, Peskind ER, Kanter ED et al. (2003). Reduction of nightmares and other PTSD symptoms in combat veterans by prazosin: a placebo-controlled study. Am J Psychiatry 160: 371–373. Raskind MA, Peskind ER, Hoff DJ et al. (2007). A parallel group placebo controlled study of prazosin for trauma
555
nightmares and sleep disturbance in combat veterans with post-traumatic stress disorder. Biol Psychiatry 61: 928–934. Reami DO, Silva DF, Albuquerque M, Campos CJR (1991). Dreams and epilepsy. Epilepsia 32: 51–53. Rechtschaffen A (1978). The single-mindedness and isolation of dreams. Sleep 1: 97–109. Renik O (1981). Typical examination dreams, “superego dreams”, and traumatic dreams. Psychoanal Q 50: 159–189. Schenck CH, Mahowald MW (1990). A case of pathologic lucid dreaming presenting to a sleep disorders center. Sleep Res 19: 155. Schenck CH, Mahowald MW (1995). A disorder of epic dreaming with daytime fatigue, usually without polysomnographic abnormalities, that predominantly affects women. Sleep Res 24: 137. Schenck CH, Mahowald MW (2002). REM sleep behavior disorder: clinical, developmental, and neuroscience perspectives 16 years after its formal identification in SLEEP. Sleep 25: 120–138. Schenck CH, Hurwitz TD, Mahowald MW (1993). REM sleep behavior disorder: an update on a series of 96 patients and a review of the world literature. J Sleep Res 2: 224–231. Schredl M (1998). Dream content in patients with narcolepsy: preliminary findings. Dreaming 8: 103–107. Shih-Wei L, Chien-Ming Y, Hsiao-Hsui L et al. (2005). Polysomnographic and psychiatric features in patients complain of epic dreaming. Sleep 28: A53–A54. Solms M (1997). The Neuropsychology of Dreams. Lawrence Erlbaum, Mahwah, NJ. Solms M (2000). Dreaming and REM sleep are controlled by different brain mechanisms. Behav Brain Sci 23: 843–850. Spoormaker VI, Schredl M, van den Bout J (2006). Nightmares: from anxiety symptom to sleep disorder. Sleep Med Rev 10: 19–31. Taylor FB, Martin P, Thompson C et al. (2008). Prazosin effects on objective sleep measures and clinical symptoms in civilian trauma posttraumatic stress disorder: a placebo-controlled study. Biol Psychiatry 63: 629–632. Thompson DF, Pierce DR (1999). Drug-induced nightmares. Ann Pharmacother 33: 93–98. van der Kolk B, Blitz R, Burr W et al. (1984). Nightmares and trauma: a comparison of nightmares after combat with lifelong nightmares in veterans. Am J Psychiatry 141: 187–190. Vogel GW (1976). Mentation reported from naps of narcoleptics. In: C Guilleminault, WC Dement, P Passouant (Eds.), Narcolepsy: Proceedings of the First International Symposium on Narcolepsy. Spectrum Publications, New York, pp. 161–168. Vogel GW (1978). An alternative view of the neurobiology of dreaming. Am J Psychiatry 135: 1531–1535. Woodward SH, Arsenault NJ, Michel GE et al. (2000a). Polysomnographic features of trauma-related nightmares. Sleep 23: A356–A357. Woodward SH, Arsenault NJ, Murray C et al. (2000b). Laboratory sleep correlates of nightmare complaint in PTSD inpatients. Biol Psychiatry 48: 1081–1087.
556
A.S. EISER
Youakim JM, Doghramji K, Schutte SL (1998). Posttraumatic stress disorder and obstructive sleep apnea syndrome. Psychosomatics 39: 168–171. Zadra A, Donderi DC (2000). Nightmares and bad dreams: their prevalence and relationship to well-being. J Abnorm Psychol 109: 273–281.
Zadra A, Donderi DC (2003). Affective content and intensity of nightmares and bad dreams. Sleep 26: A93–A94. Zadra AL, Nielsen TA (1996). Epic dreaming: a case report. Sleep Res 25: 148.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 36
Sleep and psychiatric diseases V.S. ROTENBERG * Department of Psychiatry, Tel Aviv University, Tel Aviv, Israel
INTRODUCTION
Objective sleep variables
The goal of this chapter is to discuss subjective sleep disorders and objective sleep variables in the main psychiatric diseases, as well as the relationships between sleep variables and other clinical symptoms. The scientific period of sleep investigation started around 50 years ago after polysomnography was used and the structure of sleep was discovered. Since then many old hypotheses have been refuted and some new hypotheses have appeared. Some alterations of sleep may reflect psychophysiological mechanisms determined by the disease and may be part of the development of the disease while other alterations may represent compensatory brain mechanisms.
Patients with affective disorders differ from their matched normal controls on objective sleep variables more often than do other diagnostic categories (Benca et al., 1992). Sleep in different clinical subgroups of depression is characterized by slow-wave sleep (SWS) deficiency and its redistribution with a relative decrease in the first nonrapid eye movement (NREM) period and increase in the second NREM period or even later, decreased sleep duration caused by increased sleep-onset latency, awakenings during the night and early-morning awakening, low sleep efficiency (SE), redistribution of REM sleep with its concentration in the first half of the night, decreased REM sleep latency, increased eye movement (EM) density, especially in the first REM sleep period (Reynolds and Kupfer, 1988; Benca et al., 1992; Benson and Zarcone, 1993; Perlis et al., 1997; Rotenberg et al., 1997a; Thase, 1998; Riemann et al., 2001). According to Rao et al. (1997) objective sleep variables in depressed adolescents are trait-like, meaning that they do not change from exacerbation of the disease to remission. Probably in adolescents, like in adults, persistent sleep disturbances increase the risk for relapse. In adults sleep continuity measures (increased sleeponset latency, decreased total sleep time (TST), decreased SE, increased number of awakenings, increased duration of night wakefulness) during the untreated acute state of depression were associated with previous exacerbations of depression (Hatzinger et al., 2004). Though improved under treatment, these sleep continuity measures did not correlate with the prospective course of the disease whereas decreased amount of SWS and especially increased EM density, particularly in the first two sleep cycles, were
DEPRESSION Subjective sleep complaints Complaints about sleep disorders are among the most prominent subjective feelings in all types of depression and in all age groups (Benca et al., 1992; Williamson et al., 1995; Saletu-Zyhlarz et al., 2002). A complaint of hypersomnia is usually characteristic of depressive episodes of bipolar disorders (Thase et al., 1989). Subjective complaints of insomnia cannot discriminate one type of depression from another but are a sign of the severity of depression and of the predisposition to suicidality (Agargun et al., 1997). According to Riemann et al. (2001), subjective insomnia may became a trigger of depression or its exacerbation in line with the mechanism of learned helplessness: unsuccessful attempts to achieve normal sleep can cause depression. Healthy women display subjective alterations of sleep variables after an emotional load more often than healthy men, and this may be a reason why the difference of these variables between depressed and healthy men is more prominent (Rotenberg et al., 2003).
*Correspondence to: V.S. Rotenberg, M.D., Ph.D., D.Sc., Levi Eshkol str. 22-B, flat 6. Raanana 43703, Israel. E-mail: vadir@post. tau.ac.il
558 V.S. ROTENBERG predictive for the recurrence of the disease (Kupfer opportunity to explain some complaints of depressed et al., 1990; Thase et al., 1995; Hatzinger et al., 2004). patients. The unexpected and paradoxical underestiThese authors considered them as trait-like markers mation of awakenings may relate to the prominent of depression. underestimation of sleep duration, that is, to the overReduced delta sleep ratio, if present after remisestimation of wakefulness during the night. If subjects sion, has been associated with an early recurrence of feel that they are in a state of wakefulness while actudepressive symptoms (Kupfer et al., 1990). ally sleeping, then they will estimate the awakening Reduction in sleep continuity and in SWS as well as as the continuation of previous “wakefulness,” thus increase in REM density were prominent in post- but underestimating the number of awakenings. Even not in premenopausal patients (Antonijevic et al., healthy subjects often are not aware of sleep after 2003). awakening in NREM sleep before the REM sleep In elderly female patients elevated cortisol secretion period (Rotenberg, 1993). was associated with melancholic depression, marked In depression, phasic REM sleep activity may intersleep disturbances, and a central hypernoradrenergic fere with sleep estimation. In healthy subjects EM denfunction (Wong et al., 2000). In young female patients sity correlates with mental (dream) activity in REM who showed no elevation in nocturnal cortisol secretion sleep (Rotenberg, 1988a; Hong et al., 1997). In typical sleep alterations associated with depression are depressed patients the number of dream reports in absent (Antonijevic et al., 2003). REM sleep is reduced (Kramer and Roth, 1973). It is possible to suggest that in patients mental activity in REM sleep is often not perceived as dream mentation Psychophysiological relationships but is considered subjectively as wakefulness. Only a few investigations have shown that the alteraMany above-mentioned alterations of sleep in tions of objective sleep variables, such as the number depressed patients (increased sleep-onset latency, of awakenings, sleep-onset latency, and TST in decreased TST, SE, SWS) can be explained by the hyperdepressed patients parallel the subjective estimation arousal model of depression (Zung et al., 1964). This of the same variables (Hemmeter et al., 1995). In other model takes into consideration the increased biosynthestudies electroencephalogram (EEG) sleep measures did sis and release of the corticotropin-releasing hormone not correlate with subjective sleep quality (Pasternak (CRH) that is the outcome of disturbed hypothalamoet al., 1992), and in double-blind placebo maintenance pituitary-adrenal (HPA) axis regulation and that therapy, an improvement in subjective sleep quality increases the secretion of the stress hormone cortisol was achieved despite most polysomnographic measures (Hatzinger et al., 2004). According to this model, remaining unchanged (Lee et al., 1993). The number of depressed patients are unable to terminate the arousal correct estimates of sleep duration was low in both response that appears in healthy subjects in stressful depressed patients and healthy controls and almost conditions and that disappears after stress is removed. equal in both groups (Rotenberg et al., 2000a). Patients Normalization of the excessive HPA system activity by displayed extreme variability of sleep estimates in antidepressant treatment is related to clinical recovery. both directions (over- and underestimation). The numThe hyperarousal model is confirmed by investigations ber of correct estimations of the number of awakenshowing increased beta EEG power in different brain ings was almost equally low in both groups, while regions of depressed patients (Nofzinger et al., 2000). underestimation was surprisingly more frequent in Beta EEG power negatively correlates with subjective depressed patients and overestimation in healthy subsleep quality in both depressed and healthy subjects. At jects. In depressed patients subjective estimation of the same time, only depressed patients display a trend sleep duration correlated positively with SWS percentfor beta EEG power to correlate with the whole-brain age but SWS was not correlated with the subjective metabolism during NREM sleep. sleep quality, in contrast to healthy subjects (Keklund It is possible to suggest that the difference between and Ackerstedt, 1997) and to insomniac patients healthy subjects and depressed patients is not only in the (Rotenberg, 1993). Subjective estimation of the number level of activation, but, more importantly, in the quality of awakenings correlated with the total EM scores and of activation (Kayumov et al., 2000) – it is a dysfunctional subjective estimation of sleep-onset latency in depresarousal. Increased EEG arousal, as reflected by EEG sion correlated with EM density in the first cycle sleep measures, is associated with poor response to psy(Rotenberg et al., 2000a). chotherapy as well as with an increased recurrence rate. Thus, in depressed patients the subjective estimation Brain glucose metabolic rate was increased in the first of sleep is not correlated with the relevant objective NREM period in depressed patients compared with norsleep variables. Nevertheless, these data provide an mal controls (Ho et al., 1996). Elevated brain metabolism
SLEEP AND PSYCHIATRIC DISEASES 559 before sleep deprivation predicted clinical benefits of this the requirement for SWS is not formed in wakefultreatment in depressed patients. Normalization of these ness? If in depression SWS is accumulated less in measures was associated with clinical improvement (Wu the wakefulness that precedes sleep, why does SWS et al., 1999). activity display a tendency toward a relative increase A special sign of physiological arousal and sleep in the second cycle, in comparison to healthy subjects instability – the cyclic alternating pattern – is increased (Hoffmann et al., 2000)? The hypothesis of a low in depressed patients even when formal variables of SWS accumulation during wakefulness hardly explains sleep architecture do not discriminate these patients the positive effects of REM sleep deprivation and from controls (Farina et al., 2002). deprivation of the second part of the night sleep in A particular feature of the physiological hyperdepression, especially when this positive effect is arousal in depression manifests itself in a paradoxical accompanied by restoration of the normal sleep combination of sleep disturbances and daytime alertstructure. ness. In healthy subjects, Akerstedt and Foulkard Another hypothesis suggests that SWS activity is (1995) found a negative relationship between subjective impaired in major depression due to the increased chosleepiness and objective alertness, while in depressed linergic activation and REM sleep disinhibition in patients complaints of sleepiness were often combined depression (McCarley, 1982; Berger and Riemann, with a physiological arousal that prevented sleep 1993). However, in some investigations neither REM (Kayumov et al., 2000). The shorter the TST and latency nor the REM sleep percentage differed SWS, the longer the patient is able to keep alert. In between depressed and control groups, although sleep apnea patients the relationship was the opposite. depressed patients showed abnormalities of slow-wave In depressed patients sleep latency increases in parallel activity (Hoffmann et al., 2000). These authors conwith the night sleep disturbances while in sleep apnea cluded that between-group differences in SWS amplithe more disturbed the nighttime sleep, the more diffitude and regulation cannot be explained on the basis cult for patients to maintain alertness. This pattern corof REM characteristics. responds to the decreased alertness in healthy subjects Although the hypothesis of a direct inhibition of after sleep deprivation. SWS by cholinergic REM sleep mechanisms seems It is possible that in depressed patients the same oversimplified, REM sleep characteristics may contribfactor causes night sleep disturbances and prevents ute to SWS distribution and activity. The redistribution sleepiness during wakefulness. This factor may be a malof SWS in depression, its concentration in the third or adaptive emotional tension (Rotenberg and Boucsein, even fourth cycles, where it sometimes becomes higher 1993) that creates a vicious circle because sleep disthan in the first two cycles, is usually preceded by a turbances cannot be compensated for by a lessening of prominent increase of EM density in REM sleep period daytime alertness and patients became exhausted and just before the “explosion” of SWS (Rotenberg et al., excited at the same time; this is what really happens in 1999b). In contrast to healthy subjects, EM density in depression, especially in agitated depression. As opposed depressed patients does not increase regularly from to normal adaptive emotional tension, which mobilizes cycle to cycle and is usually at its maximum level in subjects to solve problems and achieve goals, malthe first cycle, with a flattened distribution in the adaptive emotional tension is neither goal-oriented nor subsequent cycles. While the increase in SWS in the last flexible, persists without any pragmatic reasons, and cycles was regularly preceded by increased EM dendecreases attention instead of increasing it. Depressed sity, the increased EM density by itself was not regumood, anxiety, and self-blame may increase arousal larly followed by SWS “explosion:” it is an essential during sleep and interfere with the maintenance of deep but not sufficient condition for such explosion. Thus, sleep (Perlis et al., 1997). the increase of REM sleep phasic activity in some conAs well as the hyperarousal theory, there are alterditions precedes the restoration of the initially deficient native explanations for the NREM sleep disturbances SWS and is not compatible with the hypothesis that (and particularly SWS reduction) in depressed patients. SWS in depression is regularly suppressed by the overBorbely (1987) suggested that the reduced amplitude activated cholinergic REM sleep system. and power of slow-wave activity result from failure to It is possible to propose an alternative hypothesis. accumulate SWS pressure (process S) during the dayDepression is characterized by a relative increase in time. This means that SWS is decreased because the the acetylcholine/monoamine systems ratio. This is a requirement of the brain (or organism) for SWS to be particular mechanism of hyperarousal in depression. formed during wakefulness is low. However, if this Acetylcholine is responsible for the general activation is the case, some questions remain. Why has SWS of cortical neurons initiated by the reticular activating deficiency a negative outcome on sleep estimation if system of the brainstem (Kinai and Scerb, 1965). This
560
V.S. ROTENBERG
nondifferentiated activation of the cortex is important for maintaining the stable tonic vigilance that characterizes depression. However, such tonic vigilance is just a nonspecific predisposition toward the goal-oriented selective activity that requires discrimination between meaningful and meaningless information elicited from the environment. Such discrimination is based on the partial flexible inhibition of cortical neuronal activity and, as a result, on the increase of the signal-to-noise ratio that makes neuronal activity task-relevant. Norepinephrine and 5-hydroxytryptamine in wakefulness are responsible for this partial cortical inhibition. Depression is, however, characterized by decreased norepinephrine and 5-hydroxytryptamine levels in the brain, and as a result depressed patients are in chronic distress, being unable to discriminate meaningful and meaningless information and consequently to perform goal-oriented adaptive activity. This chronic distress on the one hand suppresses SWS and on the other hand increases the requirement for REM sleep.
REM sleep variables The increase in REM sleep pressure displays itself by the combination of shortened REM sleep latency, increased first REM sleep period, and increased EM activity in the first cycle. While in normal subjects and in schizophrenic patients the incorporation of wakefulness in the first sleep cycle increased REM latency in proportion to the incorporated wakefulness,
in depression REM sleep latency remained short in spite of the incorporated wakefulness (Rotenberg et al., 2002). The absence of the normal “first-night effect” in depression (Akiskal et al., 1982; Ansseau et al., 1985; Kupfer et al., 1989) can be considered not only as an outcome of the diminished orienting reaction in unfamiliar environment, but as a sign of the increased REM sleep pressure. Absence of firstnight effect correlates with more severe depressive disorders and with mood-congruent psychotic disorders (Ansseau et al., 1985; Rotenberg et al., 1997a). In depressed patients who exhibited first-night effect (according to the increased REM sleep latency), the delayed first REM sleep period in the first night was increased, instead of being decreased, in comparison to the first REM sleep period in the subsequent nights of the same patients as well as in comparison to the first REM sleep period in all nights of patients without first-night effect. In addition, REM sleep latencies on the subsequent nights in these patients were significantly shorter than those of the corresponding nights in patients without first-night effect. There was also an increased number of short cycles (less than 40 minutes) in all nights (Rotenberg et al., 1997a, b), confirming an increased REM sleep pressure (Tables 36.1 and 36.2). At the same time, the total amount of SWS in this group was higher than in patients without first-night effect, and correlated with the subjective estimation of sleep duration and feeling of being refreshed after sleep, as in healthy subjects.
Table 36.1 Sleep variables in the control group and in depressed patients with and without first-night effect
Sleep variables First night LPREM (minutes) SWS% SWS1,2min SWS3,4min REM% REM1/REMt% Second night LPREM (minutes) SWS% SWS1,2min SWS3,4min REM% REM1/REMt%
Group I (first-night effect present)
Level of significance
Control group
Level of significance
Group II (first-night effect absent)
108.0 58.0 10.0 9.7 17.8 16.8 17.1 27.9 18.2 10.9 39.3
NS NS P <0.01 P <0.05 NS P <0.01
113.2 34.4 12.4 6.3 46.1 23.7 6.8 8.0 19.4 4.0 10.0
P<0.01 P <0.01 P <0.01 NS NS P <0.01
44.6 42.9 4.7 67 11.9 13.1 8.2 24.5 23.7 8.8 33.5
35.8 41.8 11.3 13.6 17.6 24.0 20.5 27.9 24.7 10.2 22.5
P <0.01 NS P < 0.01 P <0.05 NS P < 0.02
69.3 16.9 15.9 6.1 51.6 13.8 9.0 12.5 19.0 3.8 9.5
NS P <005 P <0.01 NS P <0.05 P <0.01
86.5 62.9 5.5 5.8 18.2 17.4 4.6 8.7 25.4 8.4 32.1
LPREM, rapid eye movement sleep latency; SWS, slow-wave sleep; 1, 2, 3, 4, sleep cycles; REM, total rapid eye movement sleep in minutes; NS, not significant. (Reproduced from Rotenberg et al. (1997a).)
SLEEP AND PSYCHIATRIC DISEASES
561
Table 36.2 Eye movement density in the control group and in depressed patients with and without first-night effect
Sleep cycles First night 1 2 3 4 Second night 1 2 3 4
Group I
Level of significance
Control
Level of significance
Group II
6.9 5.6 5.7 3.5 5.7 6.4 4.6 7.6
P < 0.02 NS NS NS
2.7 2.5 3.7 2.3 5.0 4.4 5.8 3.7
P < 0.05 NS NS NS
5.0 3.7 4.4 3.8 4.0 4.4 6.1 5.2
5.9 4.5 7.3 3.9 4.9 4.1 6.9 4.8
P < 0.02 P < 0.01 NS NS
1.5 1.7 3.7 2.1 5.9 4.1 4.9 3.3
P < 0.02 P < 0.02 P < 0.05 NS
4.6 5.0 3.0 6.8
2.5 2.4 2.3 4.3
1, 2, 3, 4, sleep cycles; NS, not significant. (Reproduced from Rotenberg et al. (1997b).)
It is possible to suggest that the increased REM sleep pressure is combined with a normal ability to react to the environment and with flexibility of the REM system, and that it may relate to smaller resistance to treatment in these patients. In this context, it is worth stressing that depressed patients who had enhanced dream-like quality of mentation during the first REM period showed decreased Beck depression inventory scores at follow-up assessments (Cartwright and Lloyd, 1994). The first REM sleep period seems to be the first barrier for the negative feelings related to the preceding wakefulness and bears the stamp of these feelings in an attempt to cope with them. However, the functional meaning of the increased REM sleep pressure remains unclear. There is a general tendency in the literature (with few exceptions, like Cartwright and Lloyd (1994)) to consider the increased REM sleep pressure in depression as a pathological symptom and part of pathogenesis. Some authors (Thase, 1998) have shown that reduced REM sleep latency is a trait-like correlate of the vulnerability to depression and patients with a short REM latency have a great risk of relapse into depression. According to Nofzinger et al. (1994), a persistent intense dysphoric affect is associated with increased phasic REM sleep components. Buysse et al. (1999) found that patients who do not remit from depression display elevated EM activity in REM sleep. However, this approach to increased REM sleep pressure ignores data on the functional role of REM sleep in healthy subjects, and, more broadly, in highly developed species. In healthy subjects REM sleep is increased in long sleepers in comparison to short sleepers (Hartmann, 1973). Long sleepers are characterized by increased emotional sensitivity and vulnerability and
are predisposed to subclinical depression and anxiety with a tendency to worsen during the day and improve after the night’s sleep. It is reasonable to suggest that REM sleep contributes to this dynamic of their psychic state. This corresponds to data of Zarcone and Benson (1983) showing that healthy veterans displayed a positive correlation between measures of self-rated depression and measures of EM activity, while in clinically depressed patients the correlation between EM density and the Hamilton Depression Rating Scale was absent (Benson and Zarcone, 1993). The relationship between the severity of depression and REM sleep duration is nonlinear: when the Minnesota Multiphasic Personality Inventory (MMPI) scale D (depression) dominates but is moderate, REM sleep increases. When the scale gets higher, REM sleep becomes reduced (Rotenberg, 1988b). It is possible to suggest that, before depression becomes clinically manifest it correlates with REM sleep duration and phasic EM activity, and that precisely the increase in the latter activity prevents subdepression from turning into clinical depression. Elevated EM density is a characteristic feature of late-life bereavement in the absence of depression (Reynolds et al., 1993). The second REM sleep period increases in healthy students in the process of adaptation to stress (Rotenberg and Arshavsky, 1979). Cartwright et al. (1998b) have shown that in healthy subjects with depressed mood before sleep, the depressed mood improves after a night’s sleep, when dreams reported from the successive REM sleep periods were characterized by a decreasing negative and increasing positive affect. This confirmed findings of Kramer (1993) that dreaming modulates mood. In healthy subjects morning mood improves when REM sleep is intact but worsens after a night of sleep
562 V.S. ROTENBERG deprivation (Colecchia et al., 1997; Cartwright et al., Search activity has a very important biological 1998b). In healthy subjects REM sleep deprivation meaning. All forms of behavior that include search alters psychological defense mechanisms (Greenberg activity but differ in other aspects increase body resiset al., 1970) and increases repression (Grieser et al., tance to stress and to different deteriorative factors. 1972) that correlates with MMPI depressive scale D All forms of behavior not accompanied by search (Rotenberg and Michailov, 1993). activity (and particularly renunciation of search) All these data show that REM sleep in healthy subdecrease body resistance and predispose the subject jects plays an important role in adaptation and in prevento somatic disorders (Rotenberg, 1984). Search activity tion of mental (depressive) disorders. However, in as a process requires effort and stimulates the subject depression the relationship between clinical state and to confront stressful, potentially dangerous and EM activity is complicated. On the one hand, increased exhausting situations. Thus if search activity does not EM density, especially in the first cycle, predicts the protect the subject’s health in such situations, the most recurrence of depression and is a marker of poor creative and active members of the population would response to treatment. On the other hand, in the subgroup suffer. It is worth mentioning in this context that of depressed patients who demonstrate the first-night depression decreases body resistance, suppresses the effect accompanied by almost-normal levels of SWS immune system, and predisposes patients to psychosoand a positive clinical response to antidepressant treatmatic disorders (Stein et al., 1991; Bottomley, 1998). ment, EM density was relatively higher in the first two REM sleep and dreams restore search activity after cycles, especially in the second cycle of the second night, occasional renunciation of search (Rotenberg, 1984, in comparison to the subgroup that does not demonstrate 2003). Because of this adaptive function of REM the first-night effect, and displays reduced SWS and sleep, it is possible to suggest that the increased REM no response to antidepressants (Rotenberg et al., 1997b). sleep pressure in depression reflects the increased Buysse et al. (1994) showed that depressed patients withrequirement of depressed patients for REM sleep and out recurrence of depression after psychotherapeutic dreams. This suggestion corresponds to some experitreatment showed at baseline an increase in EM density mental data. In patients with bipolar mood disorder from night 1 to night 2, whereas those with recurrence the shifts from decreased to an elevated mood were showed no change. Rao et al. (2004) found a tendency associated with increased REM activity, while the for baseline EM density to be higher during remission. shifts to a depressed mood were associated with An attempt to solve these and many other contradicdecreased REM activity during the second half of the tions was performed in the context of the “search night (Kupfer and Henninger, 1972). In those relatively activity” concept. According to this concept, the main rare cases when mood in depressed patients improved task of the functionally efficient REM sleep is the resin the morning in comparison to the previous evening, toration of search activity (for details, see Rotenberg, the dynamic of EM density from the first to the last 1984, 2003). Search activity is defined as activity that REM sleep period was similar to those in healthy subis oriented to change the situation (or at least the subjects: it increased from cycle to cycle and achieved its ject’s attitude to it) in the absence of the precise predicmaximal value in the last cycle. At the same time, in tion of the outcome of such activity (i.e., without a all other cases, when, as is more typical for depresdefinite probability forecast) but taking into considersion, mood either became worse from evening to the ation the results at each stage of the activity. Search morning or at least did not change, EM activity disactivity is present in self-stimulation in animals, creaplayed a flattened distribution during cycles or demontive behavior in humans, as well as in exploratory and strated the highest values in the first cycle (Indursky active defense (fight/flight) behavior in all species. and Rotenberg, 1998) (Figure 36.1). When in depressed The opposite psychobiological state – renunciation of patients SWS dramatically increased in the last cycles, search – encompasses depression and neurotic (malthe subjective estimation of mood improvement on adaptive) anxiety in humans, and freezing and learned the next morning correlated positively (0.93) with EM helplessness in animals. Panic and stereotyped behavior density in the fourth cycle and negatively with REM too do not contain search activity. Subjects in a state of sleep latency (Rotenberg et al., 1999b). This confirms panic do not consider the real outcome of their behavour assumption that in these cases REM sleep successior in order to correct it. Depression is the common fully performed its adaptive function and was a reason clinical outcome of panic. In stereotyped behavior for the SWS “explosion” just after the preceding probability forecast is definite. increase in EM density. The proposal that depression is opposite to search According to Cartwright et al. (1998a), depressed activity was confirmed in our investigation (Rotenberg patients reporting more negative dreams after awakenand Cholostoy, 2004). ings in initial REM sleep periods and fewer negative
SLEEP AND PSYCHIATRIC DISEASES EM/min 12
EM/min 12
11
11
10
A
9 8 7 6
8
B
7
C
6 B C
4 2
A B C
B C
5 4 3
A
2
1
A
10 9
5 3
563
A
1 1
2
3
4 Cycles
All nights
B
1
2
3
4 Cycles
After first night
Fig. 36.1. The dynamic of eye movement (EM) activity in different groups of depressed patients: (A) all nights; (B) after first night. The morning mood in depression groups: A, better than in the evening; B, no change; C, worse than in the evening. (Reproduced from Indursky and Rotenberg (1998).)
dreams at the night’s end were more likely to be in remission 1 year later than were those with fewer negative dreams at the beginning and more at the end of the night. The absence of this positive dynamic of dreams or even a negative dynamic with increase in negative dreams may indicate a failure in the completion of the process of adaptation. A partial REM deprivation (by awakening in the middle of REM sleep periods) increases REM sleep pressure, and those depressed patients who were able to construct and report dream experiences during REM awakenings appeared to benefit from this increased REM pressure (Cartwright et al., 2003). In this context it seems interesting to compare depression and narcolepsy. Total amount of REM sleep, mean EM density, and mean REM sleep latency are similar in depressed patients and in narcoleptics; however, in many cases the latter are characterized by an extremely short REM sleep latency (the so-called sleep-onset REM sleep). However, in narcoleptics short compared to long REM sleep latencies were associated with longer TST, higher SE, higher amount of SWS, lower amount of wakefulness, and lower mean REM density. Thus, in comparison to depressed patients with short REM sleep latency, the sleep of narcoleptic patients was more normal (Pollmacher et al., 1997). Reynolds et al. (1983) found no difference in sleep patterns between narcoleptic patients with and without a past history of depression. Pollmacher et al. (1997) excluded narcoleptic patients with depressive features from their investigation and came to the conclusion that REM sleep disinhibition in narcolepsy is not related to depressive symptoms. However, it is possible to assume
that, even if there is a predisposition to depression in narcolepsy, two important features of narcolepsy can prevent its clinical manifestation. First, narcolepsy is manifested by the decreased alertness and low threshold for sleep initiation and this would abolish the physiological hyperactivation that characterizes depression. Second, adaptive REM sleep mechanisms are still functionally efficient in narcolepsy and, being disinhibited and activated (partly due to the low sleep threshold), they are able to prevent depression just before it displays itself in the clinical picture. For such compensation REM sleep has to be functionally sufficient while in depression it is usually insufficient. If the pressure on the REM sleep system outweighs its resources, then increased EM density reflects the inefficient strain of the system and corresponds to resistance to treatment and to recurrence of depression. In healthy subjects EM density correlates with the dreamer’s active participation in his/her dream (Rotenberg, 1988a), and dream content seems important for the restorative function of REM sleep. That is why the value of the first REM sleep period, characterized by the relatively lower dream activity in comparison to the subsequent periods, is lower for psychological adaptation and why the increased EM in the first REM period is less protective, although its contribution in adaptation cannot be totally ignored (Cartwright and Lloyd, 1994). In healthy highly sensitive subjects, dreams in REM sleep are more vivid in comparison to less emotionally sensitive subjects (Pivik and Foulkes, 1966). In contrast, depressed patients, in spite of their high emotional
564 V.S. ROTENBERG sensitivity, are characterized by a low level of dream Total sleep deprivation (TSD) has a dramatic posiactivity, by decreased dream recall, and short dream tive effect in 67% of all cases of endogenous depresreports (Riemann et al., 1990; Armitage et al., 1995), sion and in 48% of neurotic depression. TSD is as well as by passive position of the dreamer (Kramer, equally effective in single versus recurrent depression 1993). Greenberg (1977) proposed that dreams in and in unipolar versus bipolar depression. Patients with depressed patients, in contrast to dreams of healthy typical diurnal variations of mood exhibit the best TSD subjects, are maladaptive. Brain metabolism and effect. At the same time, in rapid cyclers TSD may electrophysiological activity in REM sleep are different trigger a switch to mania and in nonresponders it in depressed patients from healthy subjects (Nofzinger may increase psychomotor agitation (Kuhs and Tolle, et al., 2004). In healthy subjects, metabolism increases 1997). from waking to REM sleep in limbic and paralimbic The main question is whether the beneficial effect structures – it is less prominent in depression. of sleep deprivation is related to increased wakefulness or to sleep suppression. According to Van den Hoofdakker (1990), sleep deprivation simply prolongs Treatment natural remission that starts in endogenous depression The problem of the functionally efficient versus ineffiin evening hours while the natural relapse is related cient REM sleep is also related to the mechanisms of to morning hours. This point of view is confirmed by treatment. As shown in many investigations (Jobert the fact that patients who display an improvement et al., 1999; Landolt and de Boer, 2001; Feng and Ma, of mood from morning to evening respond to sleep 2002), most antidepressants – monoamine oxidase inhideprivation better than patients who do not display bitors that enhance the noradrenergic transmission in such mood improvement (Haug, 1992). However, if synapses, as well as blockers of the norepinephrine these natural remissions were related only to the diurand serotonin reuptake – suppress REM sleep in healthy nal biological rhythm of mood, it would be reasonable and depressed patients. Kupfer et al. (1981) showed that to expect mood to be worse in the morning hours clinical response to amitryptiline could be predicted from immediately after the sleep loss, in comparison to the the initial changes in REM sleep (reduced REM%, night hours during sleep deprivation. This is not the increased REM sleep latency). Selective REM sleep case. Wakefulness by itself, being accompanied by deprivation by regular awakenings in REM sleep some sort of goal-directed activity (like participating (Vogel et al., 1975) also gives a gradually positive outin games or performing tasks during sleep deprivation) come. Vogel and colleagues came to the conclusion can improve mood (Rotenberg, 2003). that REM sleep suppression is the main mechanism According to Clark et al. (2000), the lower the baseof treatment. However, some modern antidepressants line EM density, the more robust the antidepressant like nefazadone (Rush et al., 1998) and mirtazapine response to sleep deprivation. This is in line with other (Winocur et al., 2003) do not cause REM sleep supmethods of treatment: those patients who are resistant pression at all, while bupropion even reduces REM to interpersonal psychotherapy display increased EM sleep latency and increases REM% in parallel with its activity (Buysse et al., 2001). In this context it is worth therapeutic effect (Nofzinger et al., 1995). Thus, mentioning the antidepressant effect of selective REM REM sleep suppression is not necessary for the theradeprivation (Vogel et al., 1975). The positive effect of peutic effect of antidepressants, and its relation to this REM sleep deprivation does not support the hypothesis effect is not clear. In some cases REM sleep reduction of a shifted circadian sleep–wakefulness rhythm as a may be an outcome of the successful treatment. main cause of depression, since REM deprivation does Antidepressants have variable effects on sleep not affect this rhythm. It also does not support the maintenance (Thase, 1998): many of them, including hypothesis that activation of S-process (Borbely, 1987) tricyclic antidepressants, are sedating and increase is responsible for the positive outcome of sleep sleep duration, while others, also including tricyclics, deprivation. have an activating effect and disrupt sleep mainteSleep on the next night or on the next morning after nance. Both types of antidepressant may have equally total sleep deprivation abolishes the therapeutic effect effective outcome on depressive symptoms; however, (Elsenga et al., 1995), presumably due to the incorporamore sedating antidepressants have an advantage in tion of the small episodes of REM sleep or dream-like treatment of depressed patients with severe insomnia states in such sleep. Wiegand et al. (1987) have shown (Thase, 1998). Antidepressants usually do not increase that 5 of 6 patients who relapsed after the day naps the SWS% and may even decrease it; however, ritanhad naps with REM sleep. A review of the literature serin, a 5-HT2a/2c receptor antagonist, increases SWS (Wu and Bunney, 1990) confirmed that the longer in depressed patients and in insomniacs (Thase, 1998). the naps, the more frequent the relapses after sleep
SLEEP AND PSYCHIATRIC DISEASES 565 deprivation. Longer naps usually incorporate REM of the circadian rhythm where REM sleep is usually less sleep. In addition, dream experience can shift to prominent. This difference in REM latency is worth NREM sleep, especially after total or partial sleep taking into account. The antidepressant effect of sleep deprivation (Cartwright et al., 1967; Nielsen, 2000) deprivation may relate to modifications of serotonerand particularly in early-morning naps. In such cases, gic neurotransmission (Holsboer-Trachsler and Seifritz, the presence of dream experience during day naps 2000) and serotonin leads to REM sleep suppression may lead to a relapse, even if REM sleep is absent (Gillin et al., 2000). Thus, suppression of the function(Rotenberg, 2003). ally insufficient REM sleep in addition to waking activFunctionally insufficient dreams may correspond to ity may represent one of the mechanisms of the the sleep-associated depressogenic process proposed by therapeutic effect of SD. Wu and Bunney (1990), and sleep deprivation and REM sleep deprivation may stop this vicious circle. MANIA This hypothesis can help to solve some contraPatients in this state are usually unable to tolerate the dictions. Depressed patients often complain of polysomnographic procedures, and they need immediearly-morning awakenings, and this early-morning ate pharmacological treatment that may influence sleep wakefulness is accompanied by especially harmful emostructure. In a few investigations performed in unmedtional feelings. At the same time, partial sleep depriicated patients (Riemann et al., 2002), the disturbances vation as a treatment is more effective when it is of sleep continuity were more pronounced in the manic performed in the second part of the night, in compariversus the depressed state. TST was reduced but SWS son to the first part. Considering that in depression was not reduced, whereas REM sleep abnormalities psychic activity in REM sleep is often estimated as occurred with the same frequency and, what is espewakefulness, it is possible to suggest that early-morning cially interesting, in the same direction as during the wakefulness is mixed with functionally insufficient depressed state: shortened REM latency, increased REM sleep. This insufficient REM sleep, not wakefulREM activity, and increased REM density. In a rapidly ness by itself, may be responsible for negative emotional cycling patient with day-to-day changes from hypofeelings, and that is why total awakening caused by manic to depressed mood, sleep following a manic sleep deprivation is beneficial. day showed the same REM sleep abnormalities as REM sleep and dream-like mental activity are more sleep following a depressed day (Riemann et al., prominent in the morning. Sleep in the afternoon is 2002). It is possible to suggest that, although depresusually characterized by NREM sleep predominance. sion and mania are clinically opposite states, they are If total sleep deprivation was performed in the previequally maladaptive and both require REM sleep for ous night the pressure of SWS becomes especially high compensation. in the afternoon of the next day. This may be why Bipolar disorders provide an opportunity to investirelapse of depression was absent when sleep deprivagate sleep during switches into and out of mania. tion was followed by an acute 6-hour phase advance Rapid switches occurred more often in the morning of sleep (Berger et al., 1997). and in the first part of the day than in the evening Riemann et al. (1999) combined TSD with advanced and at night (Sitaram et al., 1978). Patients who sleep phase versus delayed sleep phase conditions and switched into mania at night were rated as more manic showed a stabilized therapeutic effect, mostly in the during the 4 days following the switch, in comparison advanced phase condition. The first sleep period after to patients who switched in the morning or evening. TSD in the delayed phase condition started after 44 Reduced sleep duration predicted hypomanic symphours of wakefulness and in advanced phase condition toms (Barbini et al., 1996). Riemann et al. (2002) sugafter 35 hours. In both groups, and especially in the gested avoiding shift work in subjects with a risk of delayed phase group, SWS was increased in the first bipolar disorder. Sleep deprivation provokes a switch sleep period after wakefulness (rebound effect). into mania (Colombo et al., 1999). REM sleep latency in the advanced phase group was Patients who rapidly responded to treatment (within increased in the first sleep period after TSD. In the 2 days of hospitalization), in comparison to those who delayed phase group REM latency was shorter just did not respond rapidly, were more often in a first after TSD than in the basal night and than in the manic episode, had a stressor associated with the onset advanced phase group. This difference between groups of mania, and spent more hours in sleep on the first in REM sleep latency after TSD may relate to the fact night of hospitalization (Nowlin-Finch et al., 1994). that delayed phase patients slept just after TSD in hours The authors concluded that sleep might induce a rapid that are usually occupied by REM sleep. In the opposite antimanic response. By taking into consideration that group the first sleep period after TSD was at that point
566 V.S. ROTENBERG sleep in mania is characterized by increased REM sleep was increased, and sleep structure was changed in the pressure, it is possible to suggest that REM sleep parsame direction as in depression (stage 4 was decreased, ticipates in this antimanic response, when REM sleep REM latency was shortened). However, in more recent functions are still efficient. investigations sleep architecture, particularly REM sleep variables, did not differ between OCD patients ANXIETY and healthy matched controls (Hohagen et al., 1994). Even a secondary depression did not influence sleep Anxiety may appear in two opposite forms: adaptive of OCD patients in this investigation. REM variables versus maladaptive. Adaptive anxiety mobilizes the are less sensitive to tryptophan depletion in OCD subject to solve problems and to overcome obstacles. patients than healthy subjects (Huvig-Poppe et al., However, adaptive anxiety may become exaggerated 1999), while subjects predisposed to depression are and destroy sleep. In undergraduate students high anxhighly sensitive to tryptophan depletion. This appears iety was characterized by longer sleep-onset latency, to be paradoxical, considering that OCD is also treated lower SWS% and increased stage 1 %, especially in by selective serotonin reuptake inhibitors. the first half of sleep, higher number of stage 1 episodes, lower EM density, higher mean level of arousals POSTTRAUMATIC STRESS in the first sleep hours, and more epochs with electroDISORDER (PTSD) dermal activity (Fuller et al., 1997). All these features are signs of hyperarousal. Up to 70% of patients with Sleep disturbances affect around 70% of PTSD generalized anxiety disorder (GAD) complain of dispatients. turbed sleep. In contrast to depression, GAD is characComplaints of difficulty falling and staying asleep, terized by prominent first-night effect in the sleep decreased TST, nonrestorative sleep, increased spontalaboratory (Saletu et al., 1996). When sleep investiganeous panic-like awakenings, and especially recurrent tion was performed at home, the dynamic of sleep distressing dreams (nightmares) related or not directly variables was different: the number of awakenings related to the previous traumatic events belong to the and the number of sleep stage shifts increased from main diagnostic features of PTSD. The dream content the first to the second night, and attention decreased of PTSD patients is often stereotypical and contains after the second night. It is possible to assume that, direct signs of the originally experienced traumatic in the unfamiliar conditions of the sleep laboratory, events when compared to traumatized patients without patients with GAD display a terminal adaptive reaction PTSD. Military dream content was found in almost to the environment, while in the familiar environment one-half of Vietnam war veterans and either exactly pathological anxiety dominates. replicated prior traumatic events or contained recogIn patients with GAD of a mild degree, sleep comnizable elements of such events (Geuze and Vermetten, plaints corresponded to objective sleep measures 2004). The direct representation of traumatic events in (decreased TST, SE, and increased wakefulness: Saletusleep dreams differentiates PTSD from other traumaZyhlarz et al., 1997). While during wakefulness in the related sleep disorders like sleepwalking or night tervigilance-controlled recording conditions patients with ror. On the basis of sleep complaints 1 month after GAD demonstrate heightened central nervous system the trauma it is possible to predict which individuals arousal, during rest they demonstrate a decrease in vigiwill later develop chronic PTSD (Koren et al., 2002). lance and increased sleep pressure. This may explain conThe subjective difficulties in the initiation and maintradictions in literature according to the sleep structure. tenance of night sleep caused by inappropriate hyperMethods used to reduce anxiety, like anxiety manarousal (Neylan et al., 1998) are not consistently agement training or progressive relaxation, decrease verified in the sleep laboratory (Dow et al., 1996; subjective and objective sleep-onset latency, and Mellman et al., 1997). Moreover, in these patients some improve the self-rated sleep satisfaction although, as investigations have shown elevated awakening threshin depression, this improvement was not related old (Lavie et al., 1998), deepening of sleep, and lowerdirectly to improvement of sleep architecture (Viens ing of arousal rates (Geuze and Vermetten, 2004) that et al., 2003). paradoxically can partly relate to the same factor – exciting and capturing dream content – that in other OBSESSIVE-COMPULSIVE cases causes recurrent awakenings. DISORDERS (OCD) Data on sleep structure in PTSD, especially those In the early investigation performed by Insel et al. concerning REM sleep variables, are controversial. Thus, (1982) in OCD patients in comparison to healthy conin comparison to healthy control subjects, REM latency trols, TST was decreased, the number of awakenings in PTSD patients was either shortened or lengthened
SLEEP AND PSYCHIATRIC DISEASES 567 (Greenberg et al., 1972; Schlosberg and Benjamin, 1978; In PTSD traumatic experiences are fragmented, not Hefez et al., 1987; Geuze and Vermetten, 2004) and integrated into a holistic picture of the world, and reapREM sleep time was either increased (van Kammen pear every time in a rigid form of primitive flashbacks et al., 1990) or decreased (Schlosberg and Benjamin, in wakefulness, in altered states of consciousness, and 1978; Mellman et al., 1997). in nightmares. The unsuccessful fight with traumatic Woodward et al. (1996a) compared sleep structure events is periodically displaced by giving up and pasin PTSD patients with and without comorbid depressive avoidance, which can explain the instability and sion and found that both groups had similar mean contradictions of sleep structure in PTSD (Rotenberg, REM sleep latencies, although the variability was 2004). higher in patients with comorbid depression. The The data of HPA system activity confirm the authors concluded that “a [unknown] factor emerges hypothesis that some core clinical symptoms of PTSD in PTSD which exerts a specific effect upon REM display an active coping behavior. In contrast to sleep timing and amount.” This factor may relate to depressed patients, PTSD patients are usually characthe peculiar reaction on the environment of the PTSD terized by decreased or normal basal cortisol level patients. In comparison to healthy control subjects, and by augmented cortisol suppression in response inpatients familiar with the laboratory environment to dexamethasone (Yehuda et al., 2004; Young and demonstrated reduced first-night effect whereas unfaBreslau, 2004). At the same time, PTSD patients miliar PTSD patients displayed enhanced first-night appear to have increased cortisol response in anticipaeffect (Woodward et al., 1996b). tion of cognitive challenge (Bremner et al., 2003) and The high variability of sleep structure in PTSD may be cortisol increase as a response to the trauma script related to its clinical heterogeneity (Rotenberg, 2004). exposure (Elzinga et al., 2003), which means exaggeraPTSD displays three main categories of symptoms: tion of the normal reaction to stress. A combination of hyperresponsivity of the stress hormonal system with 1. Re-experience of the traumatic events manifested a relatively low basal cortisol level and with normal as intrusive distressing recollections (images, or augmented reaction on dexamethasone challenge thoughts, dreams, hallucinations) may indicate increased negative-feedback regulation 2. Avoidance of stimuli that may resemble these of cortisol excretion (Yehuda, 2003) as an outcome of events, like conscious avoidance and repression of active coping. thoughts, feelings, memories, and activities assoA combination of PTSD with depression abolishes ciated with trauma (with a tendency to include impairment of negative feedback in the HPA system, more and more stimuli in this category), diminished that is typical for depression (Sher et al., 2004). interest in any form of activity with a hopeless PTSD patients are characterized by increased REM view of the future sleep phasic activity (Ross et al., 1994; Mellman et al., 3. Persistently increased psychophysiological arousal 1997). Mellman et al. (2002) divided victims of psycho(irritability, hypervigilance, exaggerated startle logical trauma according to whether they developed reaction (Shalev et al., 2000), prominent orienting PTSD symptoms 1 month after trauma or not. Subjects reaction and first-night effects, difficulties falling without PTSD demonstrated greater initial REM sleep and staying asleep. Re-experiencing of the trauEM density than the control group of uninjured submatic events is accompanied by increased physiojects. PTSD patients displayed greater number of logical reactivity on exposure to internal or REM sleep periods and shorter average duration of external cues that symbolize or resemble aspects continuous REM sleep than injured subjects without of the traumatic events. PTSD. The longer the interval from the traumatic inciA feeling of helplessness is the core PTSD symptom. dent, the more fragmented the REM sleep. EM density It is possible to consider that re-exposure of traumatic was increased both in those injured subjects who events represents an attempt to revise these events and became PTSD victims and in those who did not develop to cope with feelings of helplessness. However, such PTSD. It is possible to suggest that the increased EM coping is irrelevant and fails because the object of copdensity reflects an attempt of dreams to compensate ing is illusive: the traumatic event has already passed for trauma and to prevent the development of PTSD and the subject cannot win since the event is in the past. by incorporating and integrating the traumatic experiIt is like a fight with a shadow – no matter how active ence into the patient’s “inner picture of the world.” the subject is, such a fight is doomed to failure. It is However, in coping with trauma (as in preventing nevertheless an active behavior which can explain the depression), this attempt may be successful or unsucincreased REM sleep latency, decreased REM sleep, cessful, the strain of REM sleep may be not efficient, and exaggerated first-night effect. and for this reason EM density may be equal in injured
568 V.S. ROTENBERG subjects with and without PTSD symptoms. The funcimagination of the experienced trauma in parallel with tional insufficiency of REM sleep may display itself physiological activation of brain hemispheres by using also in REM sleep disruption and decreased continuity, the intense gaze movement. Such a combination crejust as in depression. ates a condition for the integration of traumatic events PTSD patients failed to exhibit the normal differinto the broad polysemantic picture of the world based ence in the respiratory rate between REM and NREM on right-hemisphere skills. All of the above mentioned sleep. PTSD patients with trauma-related nightmares psychological methods represent true pathogenetic exhibited increased sleep respiration rates in both treatment of PTSD instead of symptomatic treatment REM and NREM sleep. Nightmare-free PTSD patients oriented towards the reduction of pathological coping. exhibited slower respiration and reduced respiratory rate variability in REM versus NREM sleep, thus disPanic disorders (PD) playing a reversal of the normal pattern of sleep respiAround two-thirds of PD patients suffer from moderration (Woodward et al., 2003). ately or severely impaired sleep, including frequent Trauma-related nightmare complaints were assoawakenings due to problems with breathing (Sheikh ciated with less efficient sleep, with more wakefulness, et al., 2003). but less movement time than those patients who denied Objective sleep variables in most investigations contrauma-related nightmares (Woodward et al., 2003). firm sleep continuity disturbances in PD patients (increased sleep latency, TST reduction, decreased SE, Pharmacological treatment stage 2 reduction) (Arriaga et al., 1996; Saletu-Zyhlarz Tricyclic antidepressants, selective serotonin reuptake et al., 2000). Data on sleep structure are more controinhibitors, and combined serotonin and norepinephversial. Some investigators found SWS reduction rine reuptake inhibitors such as nefazodone and trazo(Arriaga et al., 1996) whereas other authors even done have been successfully used in PTSD, and decrease reported increased SWS (Saletu-Zyhlarz et al., 2000), nightmares, reduce sleep latency, and improve sleep possibly a normal compensatory reaction to TST reducmaintenance (Geuze and Vermetten, 2004). Some PTSD tion. REM sleep latency was reduced in some (Lauer symptoms, for example, intrusive thoughts, repeated et al., 1992) and normal in other studies (Saletu-Zyhlarz hallucinations, and flashbacks, may resemble psychotic et al., 2000). The reasons for such contradictions are disorders, and atypical antipsychotics like olanzapine not known: they can be only partly explained by comorhave a beneficial effect on the clinical picture of bidity with depression or PTSD. PTSD, including sleep disorders (Geuze and Vermetten, Panic attacks can appear not only during the day but 2004). Anticonvulsants reduce ruminative intrusive also during night sleep. A total of 68% of PD patients memories and the number of nightmares (Berland, have a history of at least one night of panic attack 2001), presumably by balancing the activity of the (Sheikh et al., 2003). In such cases sleep is suddenly limbic system that participates in the pathogenesis interrupted by multiple somatic and psychic symptoms of PTSD. like fear, apprehension, palpitations, and sweating. Most of the psychological methods of PTSD treatChoking and smothering symptoms appear more comment are oriented towards activation of imaginative mon in sleep panic, and chest pain and nausea are more thinking and in directing it towards the integration of severe in night attacks (Sheikh et al., 2003). Patients with the traumatic experience into the global subjective nocturnal panic attacks suffer higher rates of depression picture of the world. For instance, exposure therapy and relaxation-induced panic attacks (Mellman and (Rothbaum and Mellman, 2001) requires patients to Uhde, 1989a) and report higher rates of childhood and imagine the details of traumatic experience or troubled adult trauma than PD patients without nocturnal panic dreams, to focus on these details, and to describe them attacks (Freed et al., 1999). Understandably, complaints in order to become desensitized to these details. Imagof insomnia are more prominent in PD patients with ery rehearsal therapy (Krakow et al., 2001) consists of night panic attacks. Nocturnal panic attacks arise during three steps. The subject is required: (1) to select a nightNREM sleep (stage 2/3) (Mellman and Uhde, 1989b). mare; (2) to change the nightmare any way he/she Since respiration in these stages of NREM is normally wishes; and (3) to rehearse the images of the new characterized by unsteady breathing patterns, and version for 5–20 minutes each day. Thus nightmares abnormalities in respiration are supposed to be central are displaced by new dreams, and as a result nightmare in PD, unstable breathing in sleep may provoke nocturfrequency decreases (Morin et al., 1994). EM desensitinal panic (Sheikh et al., 2003). zation and reprocessing (Rothbaum and Mellman, Sleep panic attacks and daytime panic attacks are 2001; Shapiro, 2002) also include active voluntary accompanied by different patterns of sleep movement
SLEEP AND PSYCHIATRIC DISEASES 569 activity. In general panic patients without sleep panic thinking disturbance, which confirms studies showing attacks display more sleep body movements than that psychotic exacerbation is associated with reduced patients with sleep panic and social phobic patients SE (Zarcone and Benson, 1997). (Brown and Uhde, 2003). Movements are higher in Deficits in SWS, especially in the first cycle, have nights without panic; thus Uhde (2000) suggested that been found in medication-naive patients (Keshavan increased sleep movements can protect against nocturet al., 1998). In other investigations SWS deficit was nal panic through the activation of breathing. Sheikh not confirmed (Hoffmann et al., 2000). Homeostatic et al. (2003) proposed that suppression of body moveregulation (the time course of slow-wave activity, its ments represents freezing as a response to fear, that accumulation, and dissipation over all NREM periods) is, opposite to the fight/flight reaction, and this supwas not impaired in schizophrenic in contrast to ports our assumption that both freezing and panic repdepressed patients (Hoffmann et al., 2000). resent renunciation of search in opposition to fight/ Ganguli et al. (1987), Keshavan et al. (1998), and flight reactions. Patients with sleep panic and panic in Kato et al. (1999) found an inverse correlation of delta wakefulness are not different according to sleep archiwaves with negative symptoms in both acute and tecture (Sloan et al., 1999). chronic schizophrenia. Heart QT interval variability at nighttime is higher The possible relationship between SWS deficit and in PD patients compared with controls, due to the relanegative symptoms is discussed in the literature in the tive increase in cardiac sympathetic activity (Yeragani context of the role of delta waves in normal sleep. et al., 2002). The decrease in heart rate variability as Feinberg (1989) suggested the positive correlation a response to sodium lactate was more marked in panic between delta-wave amplitude during sleep and metapatients than in a control group (Sloan et al., 1999). bolic rate of cerebral cortex, while, according to Patients with panic also display increased irregularity Wolkin et al. (1992), negative symptoms are associated of breathing during REM and increased rate of microwith hypometabolism of the prefrontal cortex. SWS apneas (Stein et al., 1995). This irregularity may be has a positive effect on the retention of information attributable to altered brainstem sensitivity to carbon in healthy subjects (Latash and Manov, 1975). In dioxide or to other unexplained factors. schizophrenia impairment of visuospatial memory is Reduced anxiety after successful treatment of panic associated with decreased SWS (Goder et al., 2004). disorder is not necessarily followed by improved sleep According to Tandon and Greden (1989), brain choparameters (Cervena et al., 2005). This means that linergic activity is involved in the production of negasleep disturbances have to be additionally treated, and tive symptoms and hyperactivity in the cholinergic also that sleep disorders may represent trait symptoms system is associated with decreased SWS. SWS reducof panic disorders. tion in schizophrenia may relate to the low concentration of serotonin, the latter being associated with an increase of negative symptoms: zopiclone treats negaSCHIZOPHRENIA tive symptoms and increases high-amplitude delta Insomnia is common in patients suffering from schizowaves in sleep (Kato et al., 1999). phrenia, but sleep complaints do not usually dominate It is possible to suggest that SWS deficiency in negthe clinical picture, in contrast to mood disorders and ative schizophrenia reflects the decreased requirement anxiety. Nevertheless, severe insomnia may appear for delta sleep due to disturbed perception and procesduring exacerbations of psychosis, and may precede sing of information in wakefulness. This can also the appearance of other symptoms of relapse (Monti explain the absence of the SWS rebound after sleep and Monti, 2004). Poor sleepers among these patients deprivation in schizophrenia (Luby and Caldwell, 1967). reported lower mean scores on quality-of-life domains, Alterations in REM sleep in schizophrenia are less were more depressed and distressed, and had more definite and consistent than alterations in SWS. In their adverse effects to medications than good sleepers substantial review, Monti and Monti (2004) showed (Ritsner et al., 2004). that in never-medicated patients REM latency was Sleep in never-medicated as well as in previously moderately decreased in three studies and normal in treated patients with schizophrenia was characterized two studies; REM sleep was moderately decreased. In by increased stage 2 latency, increased wake time after patients previously treated with neuroleptics, REM sleep onset, reduced TST and SE, and reduced stage latency was reduced more prominently than in patients 2 sleep (Monti and Monti, 2004). Decreased TST and without treatment. REM sleep time was reduced in increased sleep latency are even more prominent than most investigations, but REM% was reduced in five in patients with affective disorders (Benca et al., while increased in three studies. REM density was 1992). Sleep-onset latency correlates positively with either normal or elevated (Poulin et al., 2003).
570 V.S. ROTENBERG Hoffmann et al. (2000) found no relationship between The correlation between subjective estimation of REM sleep latency and slow-wave activity. According duration of wakefulness incorporated in sleep and to Poulin et al. (2003), REM sleep duration and EM EM density in REM sleep is similar to what has been density correlated negatively with the total score of found in major depression (see above). Estimating the positive and negative symptoms combined together. REM sleep mentation as wakefulness may represent The effects on sleep of some modern neuroleptics that a sign of the functional insufficiency of REM sleep. show high affinity for serotonin 5-HT2A receptors (in Keshavan et al. (2004) have shown decreased nonlinear addition to D2 and cholinergic receptors), contribute to complexity and diminished chaos in REM sleep of treatment of negative symptoms, and improve cognitive patients with schizophrenia, in comparison with normal functions may help to elucidate factors responsible for controls. In wakefulness decreased nonlinearity sugthis inconsistency. According to Monti and Monti (2004), gests a diminished interaction of various input paramost of the new antipsychotics improve sleep maintemeters: this means impoverishment since decreased nance (they reduce stage 2 latency, stage 1 and wake time nonlinearity corresponds to decreased complexity. after sleep onset, and increase TST, SE, and stage 2). Authors have found correlations between reduced nonOlanzapine and risperidone increase SWS and SE (Salinlinear complexity in REM sleep and deficits in neuroPascual et al., 1999; Yamashita et al., 2002; Muller et al., cognition in these patients. Kisley et al. (2003) 2004). Clozapine-treated patients show more stable showed that the sensory gating impairment that characNREM sleep and less stage 1 sleep than patients treated terizes the waking state of these patients persists also with haloperidol, while REM density was higher than in in REM sleep. the drug-naive group (Wetter et al., 1996). Clozapine The variability in sleep variables in schizophrenia improved sleep continuity, enhanced sleep stage 2, and may result from differences between rates of positive decreased plasma cortisol level (Lee et al., 2001). Olanzaand negative symptoms (Ganguli et al., 1987; Tandon pine reduced REM sleep and increased REM sleep et al., 1992). Patients with a positive/negative ratio > 1 latency (Monti and Monti, 2004) but at the same time (group I) do not display differences in SWS% or sleep increased REM density (Salin-Pascual et al., 1999). continuity, in comparison to patients with a ratio <0.5 The relationship between objective sleep variables (group II), and all differences were only in REM sleep and sleep estimation has rarely been investigated sysvariables (Rotenberg et al., 1997c, 1999a). In group I tematically in patients suffering from schizophrenia. mean REM sleep percentage was significantly lower Chronic patients with schizophrenia, in contrast to (20%) than in group II (25%) and it was the extent of healthy subjects, insomniacs (Rotenberg, 1993), and negative symptoms that correlated with the increased patients with major depression, amazingly correctly REM sleep percentage. On the other hand, positive estimate their sleep-onset latency: the correlation symptoms were twice as high in patients with low between objective sleep latency and its subjective estiEM (Table 36.3). These data are in agreement with mate was 0.83 (Rotenberg et al., 2000b). Subjective the data of Neylan et al. (1992), showing that increased estimates of sleep latency negatively correlate with severity of psychosis after neuroleptic withdrawal is objective sleep duration and objective sleep duration accompanied by a decrease in EM density, and with negatively correlates with objective sleep latency. The data of Tandon et al. (1992), indicating that 2–4 weeks estimation of sleep depth correlates moderately with after neuroleptic withdrawal (when the effect of the duration of SWS in the first and the third cycles. neuroleptics is usually still present), EM density in Patients with schizophrenia display a positive correlaschizophrenic patients is higher than after a longer tion between estimation of duration of wakefulness durperiod of neuroleptic withdrawal or in drug-naive ing the night and EM density in the fourth cycle (0.60). patients. A correct estimation of sleep delay in these patients Positive symptoms (delusions and hallucinations) may be an outcome of blunted affect in chronic schizomay be considered as a peculiar pathological search phrenia. In healthy subjects and patients with mood disactivity (Rotenberg, 2004). Negative symptoms like orders the duration of wakefulness before sleep onset is apathy, flattened affect, low social activity, inattentivein most cases overestimated due to the vivid emotional ness, and poverty of speech are similar to depression reaction to sleep delay that is presumably absent in and determine sleep structure changes similar to patients with schizophrenia who are not frustrated by depression. However, in contrast to depression, domisuch delay. At the same time, SWS determines the subnation of the negative symptoms in schizophrenia is jective estimation of sleep duration (Rotenberg, 1993) not accompanied by a prominent and constant decrease and the SWS deficiency in patients with schizophrenia in REM sleep latency – maybe because negative may be responsible for their sleep complaints, in addischizophrenia, in contrast to depression, is charactertion to the objective changes in sleep duration. ized by flattened affect.
SLEEP AND PSYCHIATRIC DISEASES Table 36.3 The relationship between eye movement (EM) density and positive and negative symptoms in schizophrenic patients
EM density All patients Subgroups
5.3 (SD 2.8) <2.5 >8.1 5.25 (SD 0.72) 4.0 (SD 1.1) 4.9 (SD 1.0) 4.3 (SD 3.8)
Positive symptoms
Negative symptoms
17.1 (SD 7.5) 25.2 (SD 3.5) 12.6 (SD 1.8) <9.5 >24.5
18.7 (SD 5.2) 33.2 (SD 4.7) 31.0 (SD 3.0)
<23.5 >34.0
(Reproduced from Rotenberg et al. (1997c).)
The absence of the first-night effect in schizophrenia (Neylan et al., 1992; Rotenberg et al., 1998) may relate also to the dominance of negative symptoms. In schizophrenic patients with predominantly positive symptoms, the first-night effect was even exaggerated (Rotenberg et al., 1998, 1999a). It is worth discussing the difference between patients with dominant positive symptoms that demonstrate first-night effect and patients with psychotic depression that do not display first-night effect. Hallucinations and delusions of patients often cause an active, although inappropriate and irrelevant, interrelationship with the environment. Delusions of depressed patients, if they are mood-congruent, are related to feelings of guilt and worthlessness, to ruminative self-annihilation, and evoke the passive behavior of giving up. Cortisol nonsuppression on the dexamethasone suppression test is more prominent in depression with mood-congruent delusions, in comparison to both nonpsychotic depression and depression with moodincongruent delusions (Ayuso-Gutierez et al., 1985). Lower rates of nonsuppression were also observed in schizophrenia (Schatzberg et al., 1985). This means that psychotic features in depression and schizophrenia may be qualitatively different. In general, sleep alterations in schizophrenia are determined by the rate of positive versus negative symptoms and, depending on the ratio existing between these symptoms, they may be quite different.
REFERENCES Agargun MY, Kara H, Solmaz M (1997). Subjective sleep quality and suicidality in patients with major depression. J Psychiatr Res 31: 377–381. Akerstedt T, Foulkard S (1995). Validation of S and C components of the three-process model of alertness regulation. Sleep 18: 1–6.
571
Akiskal HS, Lemmi H, Yerevanian B et al. (1982). The utility of the REM latency test in psychiatric diagnosis: a study of 81 depressed outpatients. Psychiatry Res 7: 101–110. Ansseau M, Kupfer DJ, Reynolds CF et al. (1985). Internight variability of REM latency in major depression: implications for the use of REM latency as a biological correlate. Biol Psychiatry 20: 489–505. Antonijevic IA, Murck H, Frieboes R-M et al. (2003). On the role of menopause for sleep-endocrine alterations associated with major depression. Psychoneuroendocrinology 28: 401–418. Armitage R, Rochlen A, Fitch T et al. (1995). Dream recall and major depression: a preliminary report. Dreaming: Journal of the Association for the Study of Dreams 5: 189–198. Arriaga F, Paiva T, Matos-Pires A et al. (1996). The sleep of non-depressed patients with panic disorder: a comparison with normal control. Acta Psychiatr Scand 93: 191–194. Ayuso-Gutierez JL, Almoguera MI, Carcia-Camba E et al. (1985). The dexamethasone suppression test in delusional depression; further findings. J Affect Disord 8: 147–151. Barbini B, Bertelli A, Colombo C et al. (1996). Sleep loss, a possible factor in augmenting manic episode. Psychiatry Res 65: 121–125. Benca RM, Obermeyer WH, Thisted RA et al. (1992). Sleep and psychiatric disorders. A meta-analysis. Arch Gen Psychiatry 49: 651–668. Benson KL, Zarcone VP (1993). Rapid eye movement sleep and eye movements in schizophrenia and depression. Arch Gen Psychiatry 50: 474–482. Berger M, Riemann D (1993). REM sleep in depression – an overview. J Sleep Res 2: 211–223. Berger M, Vollman J, Hohagen F et al. (1997). Sleep deprivation combined with consecutive sleep phase advance as a fast-acting therapy in depression: an open pilot trial in medicated and unmedicated patients. Am J Psychiatry 54: 870–872. Berland JL (2001). Topiramate in posttraumatic stress disorder: preliminary clinical observations. J Clin Psychiatry 62 (Suppl. 17): 60–63. Borbely AA (1987). The S-deficiency hypothesis of depression and the two process model of sleep regulation. Pharmacopsychiatry 20: 23–39. Bottomley A (1998). Depression in cancer patients: a literature review. Eur J Cancer Care (Engl) 7: 181–191. Bremner JD, Vythilingam M, Vermetten E et al. (2003). Cortisol response to a cognitive stress challenge in posttraumatic stress disorder (PTSD) related to childhood abuse. Psychoneuroendocrinology 28: 733–750. Brown TM, Uhde TW (2003). Sleep panic attacks: a micromovement analysis. Depress Anxiety 18: 214–220. Buysse DJ, Kupfer DJ, Frank E et al. (1994). Do electroencephalographic studies predict recurrence in depressed patients successfully treated with psychotherapy? Depression 2: 105–108. Buysse DJ, Tu XM, Cherry ChR et al. (1999). Pretreatment REM sleep and subjective sleep quality distinguish
572
V.S. ROTENBERG
depressed psychotherapy remitters and nonremitters. Biol Psychiatry 45: 205–213. Buysse DJ, Hall M, Begley A et al. (2001). Sleep and treatment response in depression: new findings using power spectral analysis. Psychiatry Res 103: 51–67. Cartwright RD, Lloyd SR (1994). Early REM sleep: a compensatory change in depression? Psychiatry Res 51: 245–252. Cartwright RD, Monroe LJ, Palmer C (1967). Individual differences in response to REM deprivation. Arch Gen Psychiatry 16: 297–302. Cartwright R, Young M, Mercer P et al. (1998a). Role of REM sleep and dream variables in the prediction of remission from depression. Psychiatry Res 80: 249–255. Cartwright R, Luten A, Young M et al. (1998b). Role of REM sleep and dream affect in overnight mood regulation: a study of normal volunteers. Psychiatry Res 81: 1–8. Cartwright R, Baehr E, Kirkby J et al. (2003). REM sleep reduction, mood regulation and remission in untreated depression. Psychiatry Res 121: 159–167. Cervena K, Matousek M, Prasko J et al. (2005). Sleep disturbances in patients treated for panic disorder. Sleep Med 6: 149–153. Clark C, Dupont R, Golshan Sh et al. (2000). Preliminary evidence of an association between increased REM density and poor antidepressant response to partial sleep deprivation. J Affect Disord 59: 77–83. Colecchia E, Berardi A, Hirschfeld U et al. (1997). Temporal variations in cognitive function measured by the Harvard Cognitive Performance Battery (HCPB). Sleepiness and mood across 40 h of continuous wakefulness. Sleep Res (Suppl.): 611. Colombo C, Benedetti F, Barbini B et al. (1999). Rate of switch from depression into mania after therapeutic sleep deprivation in bipolar depression. Psychiatry Res 86: 267–270. Dow BM, Kelsoe JR, Gillin JC (1996). Sleep and dreams in Vietnam PTSD and depression. Biol Psychiatry 39: 42–50. Elsenga S, Van den Hoofdakker RH, Dols LCW (1995). Early and late parcial sleep deprivation in depression. In: C Stefanis, C Soldatos, A Rabavilas (Eds.), Psychiatry: A World Perspective, vol. 2. Excerpta Medica, Amsterdam, pp. 374–379. Elzinga BM, Schmahl CG, Vermetten E et al. (2003). Higher cortisol levels following exposure to traumatic reminders in abuse-related PTSD. Neuropsychopharmacology 28: 1656–1665. Farina B, Marca GD, Grochocinski VJ et al. (2002). Microstructure of sleep in depressed patients according to the cyclic alternating pattern. J Affect Disord 77: 227–235. Feinberg I (1989). Effects of maturation and aging on slowwave sleep in man: implications for neurobiology. In: A Wauquier, C Dugovic, M Radulovacki (Eds.), Slow Wave Sleep: Physiological, Pathophysiological and Functional Aspects. Raven Press, New York, pp. 31–48. Feng P, Ma Y (2002). Clomipramine suppresses postnatal REM sleep without increasing wakefulness: implications for the production of depressive behaviors. Sleep 25: 177–184.
Freed S, Craske MG, Grher MR (1999). Nocturnal panic and trauma. Depress Anxiety 9: 141–145. Fuller KH, Waters WE, Binks PG et al. (1997). Generalized anxiety and sleep architecture: a polysomnographic investigation. Sleep 20: 370–376. Ganguli R, Reynolds CF III, Kupfer DJ (1987). Electroencephalographic sleep in young never medicated schizophrenics. Arch Gen Psychiatry 44: 36–44. Geuze E, Vermetten E (2004). Disordered sleep in posttraumatic stress disorder: clinical presentation, research findings and implication for treatment. In: AZ Golbin, HM Kravitz, LG Keith (Eds.), Sleep Psychiatry. Taylor & Francis, London & New York, pp. 247–270. Gillin JC, Seifritz E, Landolt HP (2000). Pharmacological studies of 5-HT and sleep in humans. In: AA Borbely, O Hayashi, TJ Sejnowski et al. (Eds.), The Regulation of Sleep. Human Frontier Science Program, Strasbourg, pp. 140–147. Goder R, Boigs M, Braun S et al. (2004). Impairment of visuospatial memory is associated with decreased slow wave sleep in schizophrenia. J Psychiatr Res 38: 591–599. Greenberg R (1977). On understanding sleep disorders and their psychopathology. McLean Hospital Journal II 3: 139–146. Greenberg R, Fingar R, Kantrowitz J et al. (1970). The effects of REM deprivation: implications for a theory of the psychological function of dreaming. Br J Med Psychol 43: 1–11. Greenberg R, Pearlman C, Campel D (1972). War neuroses and the adaptive function of REM sleep. Br J Med Psychol 45: 27–33. Grieser C, Greenberg R, Harrison R (1972). The adaptive function of sleep: the differential effects of sleep and dreaming on recall. J Abnorm Psychol 80: 280–286. Hartmann EL (1973). The Functions of Sleep. Yale University Press, New Haven. Hatzinger M, Hemmeter UM, Brand S et al. (2004). Electroencephalographic sleep profiles in treatment course and long-term outcome of major depression: association with DEX/CRH-test response. J Psychiatr Res 38: 453–465. Haug HJ (1992). Prediction of sleep deprivation outcome by diurnal variation of mood. Biol Psychiatry 31: 271–278. Hefez A, Metz L, Lavie P (1987). Long-term effects of extreme situational stress on sleep and dreaming. Am J Psychiatry 144: 344–347. Hemmeter U, Seifritz E, Hatzinger M et al. (1995). Serial partial sleep deprivation as adjuvant treatment of depressive insomnia. Prog Neuropsychopharmacol Biol Psychiatry 19: 593–602. Ho AP, Gillin JC, Buchsbaum MS et al. (1996). Brain glucose metabolism during non-rapid eye movement sleep in major depression. A positron emission tomography study. Arch Gen Psychiatry 53: 645–652. Hoffmann R, Hendricks W, Rush AJ et al. (2000). Slow-wave activity during non-REM sleep in men with schizophrenia and major depressive disorders. Psychiatry Res 95: 21–225. Hohagen F, Lis S, Krieger S et al. (1994). Sleep of patients with obsessive-compulsive disorder. Eur Arch Psychiatry Clin Neurosci 243: 273–278.
SLEEP AND PSYCHIATRIC DISEASES Holsboer-Trachsler E, Seifritz E (2000). Sleep in depression and sleep deprivation: a brief conceptual review. World J Biol Psychiatr 1: 180–186. Hong Ch, Potkin SG, Antrobus JS et al. (1997). REM sleep eye movement counts correlate with visual imagery in dreaming: a pilot study. Psychophysiology 34: 377–381. Huvig-Poppe C, Voderholzer U, Backhaus J et al. (1999). The tryptophan depletion test. Impact on sleep in healthy subjects and patients with obsessive-compulsive disorder. Adv Exp Med Biol 467: 35–42. Indursky P, Rotenberg VS (1998). Change of mood during sleep and REM sleep variables. International Journal of Psychiatry in Clinical Practice 2: 47–51. Insel TR, Gillin JC, Moore A et al. (1982). The sleep of patients with obsessive-compulsive disorder. Arch Gen Psychiatry 39: 1372–1377. Jobert M, Jahnig P, Schulz H (1999). Effect of two antidepressant drugs on REM sleep and EMG activity during sleep. Neuropsychobiology 39: 101–109. Kato M, Kajimura N, Okuma T et al. (1999). Association between delta-waves during sleep and negative symptoms in schizophrenia. PharmacoEEG studies by using structurally different hypnotics. Neuropsychobiology 39: 165–172. Kayumov L, Rotenberg V, Buttoo K et al. (2000). Interrelationships between nocturnal sleep, daytime alertness, and sleepiness: two types of alertness proposed. J Neuropsychiatry Clin Neurosci 12: 86–90. Keklund G, Ackerstedt T (1997). Objective components of individual differences in subjective sleep quality. J Sleep Res 6: 217–220. Keshavan MS, Reynolds CF 3rd, Miewald MJ et al. (1998). Delta sleep deficits in schizophrenia: evidence from automated analyses of sleep data. Arch Gen Psychiatry 55: 443–448. Keshavan MS, Cashmere JD, Miewald J et al. (2004). Decreased nonlinear complexity and chaos during sleep in first episode schizophrenia: a preliminary report. Schizophr Res 71: 263–272. Kinai T, Scerb JC (1965). Mesencephalic reticular activating system and cortical acetylcholine output. Nature 205: 80–82. Kisley MA, Olinci A, Robbins E et al. (2003). Sensory gating impairment associated with schizophrenia persists into REM sleep. Psychophysiology 40: 29–38. Koren D, Arnon I, Lavie P et al. (2002). Sleep complaints as early predictors of posttraumatic stress disorder: a oneyear prospective study of injured survivors of motor vehicle accidents. Am J Psychiatry 159: 855–857. Krakow B, Hollifield M, Johnston L et al. (2001). Imagery rehearsal therapy for chronic nightmares in sexual assault survivors with posttraumatic stress disorder: a randomized control trial. Journal of the American Medical Association 286: 537–545. Kramer M (1993). The selective mood regulatory function of dreaming: an update and revision. In: A Moffitt, M Kramer, R Hoffmann (Eds.), The Functions of Dreaming. State University of New York Press, Albany, pp. 139–196.
573
Kramer M, Roth T (1973). A comparison of dream content in dream report of schizophrenic and depressive patients groups. Compr. Psychiatry 14: 325–329. Kuhs H, Tolle R (1997). Clinical applicability of therapeutic sleep deprivation. International Journal of Psychiatry in Clinical Practice 1: 101–105. Kupfer DJ, Henninger GR (1972). REM activity as a correlate of mood changes throughout the night. Arch Gen Psychiatry 27: 368–373. Kupfer DJ, Spiker DG, Rossi A et al. (1981). Sleep treatment prediction in endogenous depression. Am J Psychiatry 138: 429–434. Kupfer DJ, Frank E, Ehlers CL (1989). EEG sleep in young depressives: first and second night effects. Biol Psychiatry 25: 87–97. Kupfer DJ, Ehlers CL, McEachran AB et al. (1990). Delta sleep ratio: a biological correlate of early recurrence in unipolar affective disorder. Arch Gen Psychiatry 47: 1100–1105. Landolt HP, de Boer LP (2001). Effect of chronic phenelzine treatment on REM sleep: report of three patients. Neuropsychopharmacology 25: 563–567. Latash LP, Manov GA (1975). The relationship between delta-sleep and REM sleep phasic components with the retention and reproduction of the verbal material learned before sleep. Fiziologia Cheloveka [Russian] 1: 262–270. Lauer CJ, Krieg JC, Garcia-Borreguero D et al. (1992). Panic disorder and major depression: a comparative electroencephalographic sleep study. Psychiatry Res 44: 41–54. Lavie P, Katz N, Pillar G et al. (1998). Elevated awakening thresholds during sleep. Characteristics of chronic warrelated posttraumatic stress disorder patients. Biol Psychiatry 44: 1060–1065. Lee JH, Reynolds CF, Hoch CC et al. (1993). Electroencephalographic sleep in recently remitted, elderly depressed patients in double-blind placebo-maintenance therapy. Neuropsychopharmacology 8: 143–150. Lee JH, Woo Ji, Meltzer HY (2001). Effects of clozapine on sleep measures and sleep-associated changes in growth hormone and cortisol in patients with schizophrenia. Psychiatry Res 103: 157–166. Luby ED, Caldwell DF (1967). Sleep deprivation and EEG slow wave activity in chronic schizophrenia. Arch Gen Psychiatry 17: 361–364. McCarley RW (1982). REM sleep and depression: common neurobiological control mechanisms. Am J Psychiatry 139: 565–570. Mellman TA, Uhde TW (1989a). Sleep panic attacks: new clinical findings and theoretical implications. Am J Psychiatry 146: 1204–1207. Mellman TA, Uhde TW (1989b). Electroencephalographic sleep in PD. A focus on sleep-related panic attacks. Arch Gen Psychiatry 46: 178–184. Mellman TA, Nolan B, Hebding J et al. (1997). A polysomnographic comparison of veterans with combat-related PTSD, depressed men, and non-ill controls. Sleep 20: 46–51. Mellman ThA, Bustamante V, Fins AI et al. (2002). REM sleep and the early development of posttraumatic stress disorder. Am J Psychiatry 159: 1696–1701.
574
V.S. ROTENBERG
Monti JM, Monti P (2004). Sleep in schizophrenia patients and the effects of antipsychotic drugs. Sleep Med Rev 2: 133–148. Morin CM, Culbert JP, Schwartz SM (1994). Nonpharmacological interventions for insomnia: a meta-analysis of treatment efficacy. Am J Psychiatry 151: 1172–1180. Muller MJ, Rossbach W, Mann J et al. (2004). Subchronic effect of olanzapine on sleep in schizophrenic patients with predominantly negative symptoms. Pharmacopsychiatry 37: 157–162. Neylan THC, van Kammen DP, Kelley ME et al. (1992). Sleep in schizophrenic patients on and off haloperidol therapy. Clinically stable vs. relapsed patients. Arch Gen Psychiatry 49: 643–649. Neylan TC, Marmar CR, Metzler TJ et al. (1998). Sleep disturbances in the Vietnam generation: findings from a nationally representative sample of male Vietnam veterans. Am J Psychiatry 155: 929–933. Nielsen TA (2000). A review of mentation in REM and NREM sleep: “covert” REM sleep as a possible reconciliation of two opposing models. Behav Brain Sci 23: 851–866. Nofzinger EA, Schwartz RM, Reynolds CF et al. (1994). Affect intensity and phasic REM sleep in depressed men before and after treatment with cognitive behavior therapy. J Consult Clin Psychol 62: 83–91. Nofzinger EA, Reynolds CF III, Thase ME et al. (1995). REM sleep enhancement by bupropion in depressed men. Am J Psychiatry 152: 274–276. Nofzinger EA, Price JC, Meltzer CC et al. (2000). Towards a neurobiology of dysfunctional arousal in depression: the relationship between beta EEG power and regional cerebral glucose metabolism during NREM sleep. Psychiatry Research 98: 71–91. Nofzinger EA, Buysse DJ, Germain A et al. (2004). Increased activation of anterior paralimbic and executive cortex from waking to rapid eye movement sleep in depression. Arch Gen Psychiatry 61: 695–702. Nowlin-Finch NL, Altshuler LL, Szuba MP et al. (1994). Rapid resolution of first episodes of mania: sleep related? J Clin Psychiatry 55: 26–29. Pasternak RE, Reynolds CF, Hoch CC et al. (1992). Sleep in spousal bereaved elders with subsyndromal depressive symptoms. Psychiatry Res 43: 43–53. Perlis ML, Giles DE, Buysse DJ et al. (1997). Which depressive symptoms are related to which sleep electroencephalographic variables? Biol Psychiatry 42: 904–913. Pivik T, Foulkes D (1966). Dream deprivation: effects on dream content. Science 153: 1232–1234. Pollmacher T, Mullington J, Lauer CJ (1997). REM sleep disinhibition at sleep onset: a comparison between narcolepsy and depression. Biol Psychiatry 42: 713–720. Poulin J, Daost AM, Forest G et al. (2003). Sleep architecture and its clinical correlates in first episode and neurolepticnaı¨ve patients with schizophrenia. Schizophr Res 62: 147–153. Rao U, McCracken JT, Lutchmansingh P et al. (1997). Electroencephalographic sleep and urinary free cortisol in adolescent depression: a preliminary report of
changes from episode to recovery. Biol Psychiatry 41: 369–373. Rao U, Lin KM, Schramm P et al. (2004). REM sleep and cortisol responses to scopolamine during depression and remission in women. Int J Neuropsychopharmacol 7: 265–274. Reynolds CF, Kupfer DJ (1988). Sleep in depression. In: RZ Williams, I Karacan, CA Moore (Eds.), Sleep Disorders, Diagnosis and Treatment. Wiley, New York, pp. 147–164. Reynolds CF III, Christiansen CL, Taska LC et al. (1983). Sleep in narcolepsy and depression – does it all look alike? J Nerv Ment Dis 171: 290–295. Reynolds CF, Hoch CC, Buysse DJ et al. (1993). Sleep after spousal bereavement: a study of recovery from stress. Biol Psychiatry 34: 791–797. Riemann D, Low H, Schredl M et al. (1990). Investigations of morning and laboratory dream recall and content in depressive patients during baseline conditions and under antidepressive treatment with trimipramine. Psychiatr J Univ Ott 15: 93–99. Riemann D, Konig A, Hohagen F et al. (1999). How to preserve the antidepressive effect of sleep deprivation: a comparison of sleep phase advance and sleep phase delay. Eur Arch Psychiatry Clin Neurosci 249: 231–237. Riemann D, Berger M, Voderholzer U (2001). Sleep and depression – results from psychobiological studies: an overview. Biol Psychol 57: 67–103. Riemann D, Voderholzer U, Berger M (2002). Sleep and sleep–wake manipulations in bipolar depression. Neuropsychobiology 45 (Suppl. 1): 7–12. Ritsner M, Kurs R, Ponizovsky A et al. (2004). Perceived quality of life in schizophrenia: relationships to sleep quality. Quality Life Res 13: 783–791. Ross RJ, Ball WA, Dinges DF et al. (1994). Motor dysfunction during sleep in posttraumatic stress disorder. Sleep 17: 723–732. Rotenberg VS (1984). Search activity in the context of psychosomatic disturbances, of brain monoamines and REM sleep function. Pavlov J Biol Sci 19: 1–15. Rotenberg VS (1988a). Functional deficiency of REM sleep and its role in the pathogenesis of neurotic and psychosomatic disturbances. Pavlov. J Biol Sci 23: 1–3. Rotenberg VS (1988b). The nature of non-linear relationship between the individual’s present state and his sleep structure. In: W Koella, F Obal, H Schulz et al. (Eds.), Sleep ’86. Gustav Fischer Verlag, Stuttgart, pp. 134–137. Rotenberg VS (1993). The estimation of sleep quality in different stages and cycles of sleep. J Sleep Res 2: 17–20. Rotenberg VS (2003). Sleep deprivation in depression: an integrative approach. International Journal of Psychiatry in Clinical Practice 7: 9–16. Rotenberg VS (2004). The psychophysiology of REM sleep in relation to mechanisms of psychiatric disorders. In: AZ Golbin, HM Kravitz, LG Keith (Eds.), Sleep Psychiatry. Taylor & Francis, London, pp. 35–64. Rotenberg VS, Arshavsky VV (1979). REM sleep, stress and search activity. Waking Sleeping 3: 235–244.
SLEEP AND PSYCHIATRIC DISEASES Rotenberg VS, Boucsein W (1993). Adaptive vs. maladaptive emotional tension. Genet Soc Gen Psychol Monogr 119: 207–232. Rotenberg VS, Cholostoy A (2004). Behavioral attitudes in major depression: a pilot investigation. Homeostasis 43: 16–18. Rotenberg VS, Michailov AN (1993). Characteristics of psychological defence mechanisms in healthy testees and in patients with somatic disorders. Homeostasis 34: 54–58. Rotenberg VS, Hadjez J, Kimhi R et al. (1997a). First night effect in depression: new data and a new approach. Biol Psychiatry 42: 267–274. Rotenberg VS, Kayumov L, Indursky P et al. (1997b). REM sleep in depressed patients: different attempts to achieve adaptation. J Psychosom Res 42: 565–575. Rotenberg VS, Hadjez J, Indursky P et al. (1997c). Eye movement density in positive and negative schizophrenia. Homeostasis 38: 97–102. Rotenberg VS, Hadjez J, Martin T et al. (1998). First night effect in different forms of schizophrenia (pilot investigation). Dynamische Psychiatrie/Dynamic Psychiatry 5/6: 421–430. Rotenberg VS, Hadjez J, Shamir E et al. (1999a). Sleep structure as a mirror of the clinical state in schizophrenic patients. Dynamische Psychiatrie/Dynamic Psychiatry 176/179: 334–340. Rotenberg VS, Kayumov L, Indursky P et al. (1999b). Slow wave sleep redistribution and REM sleep eye movement density in depression: towards the adaptive function of REM sleep. Homeostasis 39: 81–89. Rotenberg VS, Indursky P, Kayumov L et al. (2000a). The relationship between subjective sleep estimation and objective sleep variables in depressed patients. Int J Psychophysiol 37: 291–297. Rotenberg VS, Indursky P, Kimhi R et al. (2000b). The relationship between objective sleep variables and subjective sleep estimation in schizophrenia. International Journal of Psychiatry in Clinical Practice 4: 63–67. Rotenberg VS, Shamir E, Barak Y et al. (2002). REM sleep latency and wakefulness in the first sleep cycle as markers of mayor depression. A controlled study vs. schizophrenia and normal controls. Prog Neuropsychopharmacol Biol Psychiatry 26: 1211–1215. Rotenberg VS, Cholostoy A, Mark M (2003). Sleep estimation in depressed men and women. Homeostasis 42: 13–17. Rothbaum BO, Mellman TA (2001). Dreams and exposure therapy in PTSD. J Trauma Stress 14: 481–490. Rush AJ, Armitage R, Gillin JC et al. (1998). Comparative effects of nefazodone and fluoxetine on sleep in outpatients with major depressive disorder. Biol Psychiatry 44: 3–14. Saletu B, Klosch G, Gruber G et al. (1996). First-nighteffects on generalized anxiety disorder (GAD)-based insomnia: laboratory versus home sleep recording. Sleep 19: 691–697. Saletu-Zyhlarz G, Saletu B, Anderer P et al. (1997). Nonorganic insomnia in generalized anxiety disorder. 1. Controlled studies on sleep, awakening and daytime vigilance utilizing polysomnography and EEG mapping. Neuropsychobiology 36: 117–129.
575
Saletu-Zyhlarz GM, Anderer P, Berger P et al. (2000). Nonorganic insomnia in panic disorder: comparative sleep laboratory studies with normal controls and placebo controlled trials with alprazolam. Hum Psychopharmacol 15: 241–254. Saletu-Zyhlarz GM, Abu-Bakr MH, Anderer P et al. (2002). Insomnia in depression: differences in objective and subjective sleep and awakening quality in comparison to normal controls and acute effect of trazodone. Prog Neuropsychopharmacol Biolog Psychiatry 26: 249–260. Salin-Pascual RJ, Herrera-Estrella M, Galicia-Polo L et al. (1999). Olanzapine acute administration in schizophrenic patients increases delta sleep and sleep efficiency. Biol Psychiatry 46: 141–143. Schatzberg AE, Rothshild AJ, Langlais PJ et al. (1985). A corticosteroid/dopamine hypothesis for psychotic depression and related states. J Psychiatr Res 19: 57–64. Schlosberg A, Benjamin M (1978). Sleep patterns in three acute combat fatigue cases. J Clin Psychiatry 9: 546–549. Shalev AY, Peri T, Brandes D et al. (2000). Auditory startle response in trauma survivors with posttraumatic stress disorder: a prospective study. Am J Psychiatry 157: 255–261. Shapiro F (2002). EMDR 12 years after its introduction: past and future research. J Clin Psychol 58: 1–22. Sheikh JI, Woodward SH, Leskin GA (2003). Sleep in posttraumatic stress disorder and panic: convergence and divergence. Depress Anxiety 18: 187–197. Sher L, Oquendo MA, Galfalvy HC et al. (2004). Age effects on cortisol levels in depressed patients with and without comorbid post-traumatic stress disorder, and healthy volunteers. J Affect Disord 82: 53–59. Sitaram N, Gillin JC, Bunney WR (1978). The switch process in manic-depressive illness. Circadian variation in time of switch and sleep and manic ratings before and after switch. Acta Psychiatr Scand 58: 267–278. Sloan EP, Natarajan M, Baker B et al. (1999). Nocturnal and daytime panic attacks – comparison of sleep architecture, heart rate variability, and response to sodium lactate challenge. Biol Psychiatry 45: 1313–1320. Stein M, Miller AH, Trestman RL (1991). Depression, the immune system, and health and illness: findings in search of meaning. Arch Gen Psychiatry 48: 171–177. Stein MB, Millar TW, Larsen DK et al. (1995). Irregular breathing during sleep in patients with panic disorders. Am J Psychiatr 152: 1168–1173. Tandon R, Greden JF (1989). Cholinergic hyperactivity and negative schizophrenic symptoms: a model of cholinergic/dopaminegic interactions in schizophrenia. Arch Gen Psychiatry 46: 745–753. Tandon R, Shipley JE, Taylor S et al. (1992). Electroencephalographic sleep abnormalities in schizophrenia. Relationship to positive/negative symptoms and prior neuroleptic treatment. Arch Gen Psychiatry 49: 185–194. Thase ME (1998). Depression, sleep, and antidepressants. J Clin Psychiatr 59 (Suppl. 4): 55–65. Thase ME, Himmelhoch JM, Mallinger AG et al. (1989). Sleep EEG and DST findings in anergic bipolar depression. Am J Psychiatry 146: 329–333.
576
V.S. ROTENBERG
Thase ME, Kupfer DJ, Buysse DJ et al. (1995). Electroencephalographic sleep profiles in single-episode and recurrent unipolar forms of major depression. I Comparison during acute depressive states. Biol Psychiatry 38: 506–515. Uhde W (2000). Anxiety disorders. In: MH Kryger, T Roth, WC Dement (Eds.), Principles and Practice of Sleep Medicine. 3rd edn. Saunders, Philadelphia, pp. 1123–1138. Van den Hoofdakker RH (1990). Mechanisms in the clinical effect of sleep deprivation. In: CVE Syllabus and Scientific Proceeding in Summary Form. 143th Annual Meeting of the American Psychiatric Association. APA, Washington DC. van Kammen WB, Christiansen C, van Kammen DP et al. (1990). Sleep and the prisoner-of-war experience – 40 years later. In: IR Giller (Ed.), Biological Assessment and Treatment of Posttraumatic Stress Disorder. American Psychiatric Press, Washington DC, pp. 159–172. Viens M, De Koninck J, Mercier P et al. (2003). Trait anxiety and sleep-onset insomnia: evaluation of treatment using anxiety management training. J Psychosom Res 54: 31–37. Vogel GW, Thasmond A, Gibbons R (1975). REM sleep reduction effects on depressive syndromes. Arch Gen Psychiatry 32: 765–767. Wetter TC, Lauer CJ, Gillich G et al. (1996). The electroencephalographic sleep pattern in schizophrenic patients treated with clozapine or classical antipsychotic drugs. J Psychiatr Res 30: 411–419. Wiegand M, Beger M, Zulley J (1987). The influence of daytime naps on the therapeutic effect of sleep deprivation. Biol Psychiatry 22: 386–389. Williamson DE, Dahl RE, Birmaher B et al. (1995). Stressful life events and EEG sleep in depressed and normal control adolescents. Biol. Psychiatry 37: 859–865. Winocur A, DeMartines NA 3rd, McNally DP et al. (2003). Comparative effects of mirtazapine and fluoxetine on sleep physiology measures in patients with major depression and insomnia. J. Clin. Psychiatry 64: 1224–1229. Wolkin A, Sanfilipo M, Wolf AP et al. (1992). Negative symptoms and hypofrontality in chronic schizophrenia. Arch Gen Psychiatry 49: 959–965. Wong ML, Kling MA, Munson PJ et al. (2000). Pronounced and sustained central hypernoradrenergic function in major depression with melancholic features: relation to hypercorticolism and corticotropin-releasing hormone. Proc Natl Acad Sci U S A 97: 325–330.
Woodward SH, Friedman MJ, Bliwise DL (1996a). Sleep and depression in combat-related PTSD inpatients. Biol Psychiatry 39: 182–192. Woodward SH, Bliwise DL, Friedman MJ et al. (1996b). First night effects in post-traumatic stress disorder inpatients. Sleep 19: 312–317. Woodward SH, Leskin GA, Sheikh JH (2003). Sleep respiratory concomitants of comorbid panic and nightmare complaint in posttraumatic stress disorder. Depress Anxiety 18: 198–204. Wu JC, Bunney WE (1990). The biological basis of an antidepressant response to sleep deprivation and relapse: review and hypothesis. Am J Psychiatry 147: 14–21. Wu J, Buchsbaum MS, Gillin JC et al. (1999). Prediction of antidepressant effects of sleep deprivation by metabolic rates in the ventral anterior cingulated and medial prefrontal cortex. Am J Psychiatry 156: 1149–1158. Yamashita H, Morinobu S, Yamawaki S et al. (2002). Effect of risperidone on sleep in schizophrenia: a comparison with haloperidol. Psychiatry Res 109: 137–142. Yehuda R (2003). Hypothalamic-pituitary-adrenal alterations in PTSD: are they relevant to understanding cortisol alterations in cancer? Brain Behav Immun 17 (Suppl. 1): S73–S83. Yehuda R, Halligan SL, Golier JA et al. (2004). Effects of trauma exposure on the cortisol response to dexamethasone administration in PTSD and major depressive disorder. Psychoneuroendocrinology 29: 389–404. Yeragani VK, Pohl R, Balon R et al. (2002). Twenty-fourhour QT interval variability: increased QT variability during sleep in patients with panic disorder. Neuropsychobiology 46: 1–6. Young EA, Breslau N (2004). Saliva cortisol in posttraumatic stress disorder: a community epidemiologic study. Biol Psychiatry 56: 205–209. Zarcone VP, Benson KI (1983). Increased REM eye movement density in self-rated depression. Psychiatry Res 8: 65–71. Zarcone VP, Benson KL (1997). BPRS symptom factors and sleep variables in schizophrenia. Psychiatry Res 66: 111–120. Zung WW, Wilson WP, Dodson WE (1964). Effect of depressive disorders on sleep EEG response. Arch Gen Psychiatry 10: 439–445.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 37
Sleep-related eating disorder JOHN W. WINKELMAN, 1, 2 * ERIN A. JOHNSON, 2 AND LISA M. RICHARDS 2 1 Harvard Medical School, Boston, MA, USA 2
Division of Sleep Medicine, Brigham and Women’s Hospital, Boston, MA, USA
HISTORY OF NIGHT EATING AS A CLINICAL CONDITION In 1955, Stunkard et al. used the term “night-eating syndrome” (NES) to describe a particular pattern of eating seen in obese patients. This original article looked at 16 patients whose inability to lose weight in a monitored diet program confounded investigators until they discovered that the patients were consuming a substantial fraction of their daily calories at night. Since this initial publication, the topic of disordered nighttime eating has been periodically revisited in the medical literature and has appeared as a point of interest in popular print and television media. Problematic nighttime eating has been featured on television programs and illustrated in the comic strip Blondie. The dagwood sandwich, which consists of various leftovers and condiments thrown together during a raid on the refrigerator, highlights the binge-like eating and strange food combinations generally associated with nocturnal eating disorders. Interestingly, in the years following this initial publication on NES, other eating disorders such as anorexia nervosa, bulimia nervosa, and binge-eating disorder gained both popular and scientific interest while disordered nighttime eating behavior did not. Thirty years after the 1955 publication (Stunkard et al., 1955) on disordered night eating behavior, only a handful of case reports (Coates, 1978; Guirguis, 1986; Oswald and Adam, 1986) were added to the existing literature on the topic (Montgomery and Haynes, 2001). However, in the last 20 years there has been a renewed interest in the topic which has moved the investigation of nighttime eating behavior in several directions. The original criteria for NES focused on evening hyperphagia, defined as consuming a quarter or more
of daily calories after the evening meal, difficulty falling asleep, and morning anorexia (Stunkard et al., 1955). NES was also found to be associated with periods of stress and with difficulties in trying to lose weight (Birketvedt et al., 1999). To date, researchers in the field of eating disorders have continued to use the term NES to describe problematic nighttime eating behavior. Although the term has remained the same, the criteria for NES have been, and continue to be, reworked and modified in areas such as the amount of calories eaten during evening hyperphagia, the timing of the eating, the state of awareness during the eating, the effect on mood, and its distinctions from bulimia nervosa and binge-eating disorder. Though the term is frequently used in the literature, NES cannot be used as an official diagnosis as it has not been operationally defined in a diagnostic manual. For this and other reasons, the features and details of this syndrome have often been open to author interpretation. Clinicians have, however, used a clinical Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR: American Psychiatric Association, 2000) diagnosis of an eating disorder not otherwise specified for patients with these behaviors (de Zwaan et al., 2003). Much of this early investigation was performed from the perspective that night eating was a variant of a daytime eating disorder. More recently, this work has been supplemented by investigations of patients who initially presented to sleep medicine clinics. Using both polysomnography and sleep disorders classifications, distinctive patterns of sleep quality, sleep architecture, and coexistent sleep disorders in patients suffering from problematic nighttime eating behaviors have been demonstrated. The 1990 edition of
*Correspondence to: John W. Winkelman, M.D., Ph.D., 1505 Commonwealth Ave, 5th Floor, Brighton, MA 02135, USA. Tel: 617-783-1441, Fax: 617-663-6192, E-mail:
[email protected]
578
J.W. WINKELMAN ET AL.
the International Classification of Sleep Disorders (ICSD) included the diagnosis of nocturnal eating/ drinking syndrome (NEDS) which at the time was “characterized by recurrent awakenings, with the inability to return to sleep without eating or drinking” (American Academy of Sleep Medicine, 1990). The revised edition of ICSD (American Academy of Sleep Medicine, 2005), has removed NEDS and has added the term “sleep-related eating disorder” (SRED) (Table 37.1). According to the ICSD-2, the diagnostic features of SRED include “out of control” or involuntary eating during arousals from sleep, which can occur at any point along a spectrum of level of consciousness, from partial and/or confusional awakenings from sleep with subsequent partial recollection of the event to full awareness during nocturnal eating with subsequent unimpaired memory for the event. The pathological or problematic features of SRED include ingestion of abnormal combinations of food or toxic substances, complaints of nonrestorative sleep or daytime sleepiness/fatigue, sleep-related injury, morning anorexia, or weight gain (American Academy of Sleep Medicine, 2005). Finally, the nocturnal eating Table 37.1 Current International Classification of Sleep Disorders revised-2 definition and diagnostic criteria for sleep-related eating disorder A. Recurrent episodes of involuntary eating and drinking occur during the main sleep period B. One or more of the following must be present with the recurrent episodes of involuntary eating and drinking: 1. Consumption of peculiar forms or combinations of food or inedible or toxic substances 2. Insomnia related to sleep disruption from repeated episodes of eating, with a complaint of nonrestorative sleep, daytime fatigue, or somnolence 3. Sleep-related injury 4. Dangerous behaviors performed while in pursuit of food or while cooking food 5. Morning anorexia 6. Adverse health consequences from recurrent binge eating of high-caloric food C. The disturbance is not better explained by another sleep disorder, medical or neurological disorder, mental disorder, medication use, or substance use disorder (hypoglycemic states, peptic ulcer disease, reflux esophagitis, Kleine–Levin syndrome, Kluver–Bucy syndrome, and nighttime extension of daytime anorexia nervosa (binge/purge subtype), bulimia nervosa, and binge eating disorder) (Reproduced from American Academy of Sleep Medicine, 2005, pp. 174–175.)
cannot be better explained by another disorder such as hypoglycemia, peptic ulcer disease, or other sleep disorders. Pathological nighttime eating combines features of a daytime eating disorder with those of a parasomnia. There is compulsive, driven eating, with next day anorexia and undesirable weight gain, characteristic of eating disorders. In addition, patients with SRED often exhibit features of parasomnias, especially arousal disorders, such as partial arousals early in the sleep period, characterized by confusion, automatic behavior, and relative unresponsiveness to external stimuli, followed by impaired recollection of the behavior. It is this combination of behavioral features of disparate disorders which makes SRED a challenge from both pathophysiological and therapeutic perspectives.
CHARACTERISTICS OF SRED Patients with SRED generally arouse from sleep and eat roughly 2–3 hours after sleep onset. Eating episodes are characterized by rapid ingestion of food, which the patient usually reports as “out of control” or compulsive in nature. A preference for high-caloric foods is common, although the ingestion of inedible or toxic items is also reported. Patients will often deny hunger, but rather report a drive to eat. Level of consciousness during nocturnal eating ranges from full awareness to dense unawareness typical of a somnambulistic episode. Many patients report having episodes somewhere in the middle, describing themselves as “half-awake, half-asleep.” Episodes with full awareness and ones with confusion can occur on different awakenings on the same night, and level of consciousness during nocturnal eating often varies over the longitudinal course of the disorder. Next day amnesia is usually consistent with the selfreported level of consciousness during the episodes, with confusional arousals associated with more impairment of recollection. The most common daytime consequences of SRED are daytime fatigue from the repetitive nocturnal awakenings and weight gain due to the large number of calories consumed during these nighttime eating episodes. The frequency of episodes can range from once a week to 10 times in the same night. While patients may make behavioral changes to try to control their nighttime eating, such as locking cabinets or doors, compensatory behaviors, such as excessive exercise or self-induced vomiting, which are often seen in daytime eating disorders, are usually absent (Winkelman, 1998). However, morning anorexia, due to overeating throughout the night, is also common with SRED.
SLEEP-RELATED EATING DISORDER
DIFFERENTIAL DIAGNOSIS OF SRED AND NES At this time, only SRED, and not NES, is operationalized in a diagnostic nosology (ICSD-2). In addition, the diagnostic criteria generally used in the literature for NES have evolved, even over the last 10 years, making comparisons of some of the descriptive data unreliable. Nevertheless, the current research criteria for NES generally require nocturnal awakenings with ingestion of food, and greater than one-third of daily calories being consumed after the evening meal (Lundgren et al., 2006). NES is associated with periods of stress, obesity, depressed mood, and poor outcome of weight loss attempts (Rand et al., 1997). As these features are similar to those of SRED, comparing the features of the two disorders may be of clinical diagnostic or therapeutic value. The major distinctions between NES and SRED which researchers have described are: (1) the timing of nocturnal eating; (2) the state of consciousness during nocturnal eating; and (3) the rate of comorbid sleep disorders present in those with nocturnal eating (Figure 37.1). Whereas the majority of patients with SRED in the published literature (Schenck et al., 1991; Winkelman, 1998) reported being either asleep or halfasleep during nighttime eating episodes, those with NES reported being fully aware of them (O’Reardon et al., 2005). In a related finding, subsequent recall of the event is often impaired in those with SRED, whereas it is always maintained in patients with NES (O’Reardon et al., 2005). This lowered state of consciousness may also account for why some patients with SRED ingest inedible or toxic substances and patients with NES do not. The value of this distinguishing feature has been called into question by some case series of SRED patients who have variable levels of consciousness both within a single night and across the longitudinal course of the disorder. Similarly, most of the investigations
579
of patients with NES by those in the eating disorders community have not specifically addressed the level of consciousness during nighttime eating, making conclusions regarding this feature in NES unreliable. Recently an item assessing the level of awareness during nocturnal eating was added to the Night Eating Questionnaire, a psychometric scale developed to asses the severity of NES (Allison et al., 2008). The response to this item does not contribute to the severity score, but the question was included “to differentiate between NES and sleep-related eating disorder, in which nocturnal ingestions occur with little to no awareness or later recollection” (Allison et al., 2008). Although the item was included specifically for the purpose of distinguishing NES from SRED, the response choices exist along a full spectrum of awareness (“not at all [aware],” “a little,” “somewhat,” “very much so,” and “completely”) and the level at which the authors distinguished NES from SRED is not made clear. In keeping with the uncertain value of this feature of nocturnal eating as a diagnostic criterion, the revised ICSD-2 has not made reduced level of awareness, or amnesia, diagnostic features for SRED. The timing of nocturnal eating is another potential feature distinguishing SRED from NES. Whereas individuals with SRED always report awakenings from sleep to eat, those with NES may eat either before bed (as in the original cases of Stunkard) or at nighttime awakenings, the important criterion being that greater than one-third of all calories be consumed after the evening meal (O’Reardon et al., 2004). Another potential distinguishing characteristic is the common comorbidity between SRED and sleep disorders such as sleepwalking, restless-legs syndrome (RLS), periodic limb movements of sleep (PLMS), or obstructive sleep apnea (OSA). This association is not common in patients with NES. This may suggest a relationship between SRED and these sleep disorders, yet would also suggest that SRED and NES may have different etiologies. Additionally, daytime eating
Nighttime eating Amnesia for the event
Partial recall for the event
Full recall for the event
Little arousal from sleep
Half-awake, half asleep
Total arousal from sleep
SRED
Eating episodes after the onset of sleep No apparent daytime food cravings Intake of bizarre items Morning anorexia Comorbid sleep disorders common
NES
Evening hyperphagia, occasional episodes after the onset of sleep Food cravings in the evening (post evening meal) Intake of normal food items Morning anorexia
Fig. 37.1. Spectrum of nighttime eating. SRED, sleep-related eating disorder; NES, night-eating syndrome.
580
J.W. WINKELMAN ET AL.
disorders have been associated with SRED but not with NES (de Zwaan et al., 2003; Allison et al., 2005). Although NES is generally not associated with other sleep disorders, a polysomnographic study of NES subjects and controls found differences in sleep architecture between the two groups, including significantly lower sleep efficiency, total sleep time, and time in stage 2 sleep (Rogers et al., 2006). All of the NES subjects in the 2006 study by Rogers et al. showed complete electroencephalogram arousal during episodes of nighttime eating. Of course, subjects in this study were specifically excluded if they “lacked awareness of their night eating” or had amnesia for the episodes. In contrast, individuals with SRED frequently have diagnosable primary sleep disorders (see below). While SRED and NES can be described as independent disorders with distinct clinical presentations, many of the features often overlap or are not limited to one or the other. For example, a patient may report full awakenings and complete recall for half of their nighttime eating episodes while for the other half they report being asleep and remember nothing of the event. This has prompted a proposed continuum of nighttime eating behavior instead of seeing NES and SRED as totally separate. This model appears to be favorable since it is sometimes difficult to differentiate between NES and SRED in individual patients, and may facilitate diagnosis and identification of NES and SRED patients (Winkelman, 2006b). The revision of the ICSD-2 nosology, by including nighttime eating that occurs along the full spectrum of consciousness, is potentially a move toward viewing NES and SRED along a single continuum. However, the criteria still limit complete inclusion of NES under the SRED diagnosis by requiring episodes of eating to occur during the main sleep period and not prior to sleep. Diagnostic criteria for NES also appear to be in flux, making differential diagnoses with SRED more complicated. In a 2006 descriptive study of 106 individuals with a broad range of nighttime eating symptoms, de Zwaan et al. (2006) found that subjects varied in the degree to which they met sets of historical and recent diagnostic criteria for nocturnal eating disorders. Some individuals in the sample met multiple sets of diagnostic criteria, and others none at all. This may further indicate an inadequacy in the current standards to identify and diagnose all individuals suffering from nighttime eating.
subgroups of psychiatric patients, obese individuals in a weight loss program, and college students. In their sample, SRED was reported by 16.7% of individuals who were part of an inpatient eating disorders program, while 8.7% of those in an outpatient eating disorders program and 4.6% of college students reported behavior consistent with SRED (Winkelman et al., 1998). Schenck et al. (1991, 1993) reviewed a sample of patients referred to a sleep disorders clinic over a 7-year period and found that 0.5% of these patients fulfilled criteria for SRED. Although nighttime eating behavior appears to be more prevalent in some, especially disordered eating population subsets, SRED is not limited to any one subgroup. On the other hand, the prevalence of NES has been more carefully defined in the general population. When it was specifically defined as excessive evening eating, tension and/or feeling upset during the evening hours, insomnia, and morning anorexia, the prevalence was estimated at 1.5% in the general population (Rand et al., 1997). Interestingly, an obesity surgery subset of this same study found the prevalence rate of NES in postoperative gastric restriction surgery patients to be 27%, reflecting the common association of NES with the obese population. In terms of gender predominance, SRED appears to be more prevalent in women, with a reported 66–83% of patient cases. The female predominance of SRED mimics the higher prevalence rates of daytime eating disorders (anorexia nervosa and bulimia nervosa) seen in women than in men. The onset of SRED generally occurs during the late teenage years or 20s, and its course is often chronic in nature. A number of case series, starting with Winkelman (1993), have demonstrated a familial aspect to SRED (Schenck et al., 1993; Winkelman, 1997, 1998). One such series (Winkelman, 1998) found that 26.1% of the SRED sample reported having family members who also experienced nighttime eating episodes. Three other series reported familial connections in 21% (Schenck et al., 1993), 19% (Winkelman, 1997), and 27% (Provini et al., 2005) of their SRED patients. Although such data are certainly far from definitive, it would not be surprising if SRED has a genetic component as both daytime eating disorders (Hudson et al., 2006) and somnambulism (Kales et al., 1980) have genetic influences.
PREVALENCE
Weight gain and obesity are common adverse health effects associated with SRED. Consuming high-calorie foods during an “out-of-control” eating episode or, as it is in some cases, without being aware of the event can cause unwanted weight gain, which is difficult to
Currently, prevalence data on SRED in the general population are not available. Winkelman et al. (1998) reported varying prevalence rates for different
CONSEQUENCES
SLEEP-RELATED EATING DISORDER control. In one case series (Winkelman, 1998), 39% of patients presenting with SRED were overweight (body mass index (BMI) 25), while in another series (Winkelman, 1997) it was reported that 15% were overweight (30 >BMI 25) and 30% were obese (BMI 30). Psychological distress has been noted in patients with SRED due to feelings of “lack of control,” shame, guilt, and helplessness over night eating (Montgomery and Haynes, 2001). It is not uncommon for people with SRED to report either current or past episodes of anxiety and depression, especially patients who have a long history of nighttime eating behaviors (Schenck et al., 1991; Winkelman, 1997; Winkelman et al., 1999). In terms of overall diet, medically necessary dietary restrictions (e.g., for patients with diabetes or renal/liver failure) can be broken during uncontrolled nighttime eating, either leading to, or exacerbating, preexisting health problems (Montgomery and Haynes, 2001). Multiple nighttime awakening and eating episodes cause recurrent disruption of sleep which can lead to poor and nonrestorative sleep. Accidents involving falls, burns, and cuts while in search of food and during food preparation or consumption are also a concern, especially with patients who report reduced alertness during episodes. Some patients will also ingest inedible and/or toxic substances such as buttered cigarettes and cleaning supplies (Schenck et al., 1993; Schenck and Mahowald, 1994, 2000).
ASSOCIATIONS WITH OTHER DISORDERS Sleep disorders Studies using polysomnography have found that patients with SRED are more likely to have concurrent sleep disorders such as somnambulism (sleepwalking), periodic limb movement disorder (PLMD), RLS, OSA, and circadian rhythm disorders (de Zwaan et al., 2003; Winkelman, 2003). Schenck et al. (1991, 1993) found that about 84% of SRED patients in their sample also presented with somnambulism, 13% with RLS, and 10% with OSA. Another case series (Winkelman, 1998) which also used polysomnographic data found that 48% of the sample met criteria for somnambulism, 26% had periodic leg movements of sleep, and 13% had OSA. In a video-polysomnographic study of 35 patients with SRED, Vetrugno et al. (2006) demonstrated PLMS in 63% of patients, and periodic movements of facial muscles in 83% of the patients. The movements included recurrent chewing and swallowing motions that were present in all sleep stages and linked to arousal approximately 50% of the time. The characteristic comorbidity between SRED and sleep disorders has been consistent
581
throughout the literature on this topic (Schenck et al., 1991, 1993; de Zwaan et al., 2003; Winkelman, 2003). In contrast, patients presenting with NES are unlikely to have sleep disorders (de Zwaan at al., 2003).
Eating disorders There is a high rate of comorbidity between SRED and daytime eating disorders, which include anorexia and bulimia. One prevalence study (Winkelman et al., 1999) demonstrated that patients diagnosed with an eating disorder are more likely to have SRED than the other subgroups (obese, depressed, or unselected college students). Two case series showed that a high percentage of SRED patients also showed signs of daytime disordered eating. The first (Winkelman, 1998) found that 40% of those with SRED were also diagnosed with an eating disorder, while the second (Winkelman et al., 1999) found elevated scores on the Eating Attitudes Test in 40% of the SRED sample. Gupta (1991) looked at SRED in patients with bulimia nervosa and found that 30% of those with bulimia nervosa also met criteria for SRED.
Mood disorders Reports of depression and anxiety in patients with SRED have been frequent. In prevalence studies, higher rates of depression have been found in individuals with SRED than in their non-SRED counterparts (Winkelman et al., 1999). One particular case series (Winkelman, 1997) reported that 70% of respondents had a history of depression. In many cases it is unclear if the mood disturbances preceded onset of SRED or if SRED may have caused or exacerbated the problem.
PHYSIOLOGY OF SRED Clinical sleep disorders Underlying sleep disorders have been looked at as a possible cause of the behaviors associated with SRED. The sleep disorder most commonly associated with SRED is somnambulism. Partial arousals caused by OSA, RLS, PLMS, or sleepwalking have been reported to result in a nighttime eating episode sometimes (Winkelman, 1998). Even though this connection has been noted, it is unknown why this arousal initiates nighttime eating behavior in some patients. Vetrugno et al. (2006) noted that the prevalence of RLS, PLMs, and sleep-related masticatory movements in patients with SRED, as well as the findings supporting some therapeutic benefit of dopaminergic agents in the treatment of SRED (discussed in the next section), may implicate dopaminergic pathways in the pathophysiology of the disorder.
582
J.W. WINKELMAN ET AL.
The cessation of smoking, substance or alcohol abuse has triggered SRED, in addition to periods of acute stress, narcolepsy, encephalitis, autoimmune hepatitis, and strict daytime dieting (American Academy of Sleep Medicine, 2005). Prescribed medications have also been known to produce episodes of SRED. These include triazolam and various psychotropic agents such as anticholinergic medications and lithium carbonate (American Academy of Sleep Medicine, 2005). Multiple case series have described the onset of SRED with zolpidem use (Morgenthaler and Silber, 2002; Schenck et al., 2005; Najjar, 2007). Morgenthaler and Silber (2002) reported on 5 patients who developed SRED while taking zolpidem. Three of the patients had no previous history of nighttime eating episodes, while 2 had previous nighttime eating episodes which worsened in frequency and in the degree of amnesia for the event. All 5 patients discontinued zolpidem and were treated for other current sleep disorders (OSA, RLS, sleepwalking and psychophysiologic insomnia). SRED resolved in each patient. Multiple interventions (i.e., removing zolpidem and treating other presenting sleep disorders) and the naturalistic method of this report make it impossible to look at causality, yet the use of zolpidem may have been the factor which induced or aggravated the presenting SRED. Chiang and Krystal (2008) reported 2 cases in which SRED occurred while the patients were on extendedrelease zolpidem but not immediate-release zolpidem, indicating that it is possible for small variations in formulation to produce a differential effect on the potential precipitation of SRED for some patients.
Neuroendrocrine studies No physiological studies of SRED patients have been performed to date. However, researchers have found neuroendocrine differences between patients with NES and normal controls. In particular, investigators have examined levels of melatonin and leptin, which usually rise nocturnally: melatonin to support and maintain sleep (Zhdanova et al., 1996), and leptin, as suggested by Sinha et al. (1996), as an appetite suppressant. In patients with NES, Birketvedt et al. (1999) reported a reduction in the typical rise of both melatonin and leptin. Elevated plasma cortisol levels were also observed in NES patients in this study and may indicate a rise in corticotropin-releasing hormone. Corticotropinreleasing hormone acts to suppress melatonin secretion and this rise may be the origin of the observed attenuation in the melatonin levels. Another study in patients with NES also demonstrated a temporal redistribution of daily energy intake (O’Reardon et al., 2004). Though controls and subjects
with NES had similar bedtimes and waketimes, NES patients had earlier nighttime awakenings and consumption of food on nearly three-quarters of awakenings. The authors postulated that NES is a phase delay in calorie consumption with respect to the sleep–wake schedule, possibly as a result of an intrinsic abnormality in the clocks regulating these two physiological processes. However, as nocturnal awakenings or eating can influence the underlying neuroendocrine patterns themselves, it is difficult to tell if these physiological alterations are causes or effects of problematic nighttime eating.
TREATMENT Both pharmacological and nonpharmacological treatments have been employed in SRED. Pharmacological treatments for SRED are divided into those which target underlying disorders thought to produce the abnormal nocturnal eating, and those empiric therapies which have been found, usually through serendipity, to be of therapeutic value (Figure 37.2). Treatment of sleep disorders that cause fragmentation of sleep, such as RLS, PLMD, or OSA, can reduce the number of arousals from sleep, which may drive nocturnal eating episodes. RLS may particularly predispose to nocturnal eating as it produces fragmented sleep as well as the inability to stay in bed at awakenings. It is thus not surprising that Schenck et al. (1993) found that dopaminergic agents (carbidopa/ L-dopa; bromocriptine) were effective in 52% (14/27) of their cases with SRED, 5 of whom had RLS or PLMD. Similarly, 59% of their cases with reported treatment outcomes had a diagnosis of sleepwalking, and benzodiazepines were of value in 37% (10/27) of all SRED cases (Schenck et al., 1993). Nonpharmacological treatments include continuous positive airway pressure for patients with OSA. In all, Schenck et al. (1991) reported that nocturnal eating resolved in 79% of their sample after the successful treatment of the primary sleep disorder. Treatment to manage daytime eating disorders, such as selective serotonin reuptake inhibitors for bulimia nervosa, may also be beneficial in controlling nighttime eating episodes. Empiric pharmacological interventions for SRED have included various agents such as selective serotonin reuptake inhibitors, hypnotics, melatonin, D-fenfluramine (now off the market), gamma-hydroxybutyric acid, oxazepam, sertraline, sibutramine, and topiramate (American Academy of Sleep Medicine, 2005). Topiramate, an anticonvulsant approved by the US Food and Drug Administration, was originally found to produce weight loss in treatment trials for epilepsy, bipolar disorder, and migraine headaches, and reduce binge episodes
SLEEP-RELATED EATING DISORDER
583
Pharmacotherapy for SRED
Mood, anxiety or eating disorders
Binge eating disorder
Restless legs syndrome (RLS)
History of other parasomnias
SSRI
Topiramate
Dopaminergic agonist
Short to intermediateacting benzodiazepine
No effect
No effect
No effect
Topiramate as second line of treatment
Fig. 37.2. Pharmacotherapy for treating sleep-related eating disorder (SRED). SSRI, selective serotonin reuptake inhibitors.
in patients with binge-eating disorder (Shapira et al., 2000; McIntyre et al., 2002; Young et al., 2002). It was used successfully in one case series of patients with NES or SRED, with substantial reduction in nighttime eating behavior in 4 patients (Winkelman, 2003). In a more recent retrospective chart review of 25 SRED patients treated with topiramate, Winkelman (2006a) found that 68% of the patients were topiramate responders (mean dose of 135 mg) as measured by the Clinical Global Impression of Improvement. Although substantial weight loss was observed in over one-quarter of responders, nearly half of the responders discontinued topiramate after a mean of 12 months due to sideeffects. It is unclear how topiramate works to manage nighttime eating behaviors; however, it was hypothesized that topiramate may work to suppress arousals produced by underlying sleep disorders (e.g., RLS) or act as an anorexigenic (appetite suppressant), though either glutamatergic antagonism or serotonin agonism (Winkelman, 2003). In addition, topiramate stimulates insulin release (Liang et al., 2005) and increases insulin sensitivity (Wilkes et al., 2005), both of which may contribute to appetite regulation and weight loss. One randomized double-blind placebo-controlled crossover pilot study of pramipexole in 11 subjects with SRED demonstrated improvements in actigraphically monitored nocturnal activity and “the number of good nights of sleep per week,” though other outcomes related to SRED showed no improvement. In light of the current available information on the treatment of SRED, further controlled clinical trials using pharmacological agents for the treatment of SRED are warranted (Provini et al., 2005).
SUMMARY SRED combines features of sleep disorders and eating disorders, such that individuals have partial or complete arousal from sleep to eat. Those who report for clinical attention often have a chronic course, with multiple eating episodes per night, and a variety of daytime consequences of this behavior, including weight gain, daytime fatigue, and mood disorders. Currently, treatment is directed towards underlying sleep disorders, when present, or otherwise involve the empiric use of serotonergic antidepressants or topiramate.
REFERENCES Allison KC, Grilo CM, Masheb RM et al. (2005). Binge eating disorder and night eating syndrome: a comparative study of disordered eating. J Consult Clin Psychol 73 (6): 1107–1115. Allison KC, Lundgren JD, O’Reardon JP et al. (2008). The Night Eating Questionnaire (NEQ): psychometric properties of a measure of severity of the night eating syndrome. Eat Behav 9: 62–72. American Academy of Sleep Medicine (1990). The International Classification of Sleep Disorders (Revised): Diagnostic and Coding Manual. American Academy of Sleep Medicine, Rochester, MN. American Academy of Sleep Medicine (2005). The International Classification of Sleep Disorders (Revised-2): Diagnostic and Coding Manual. American Academy of Sleep Medicine, Rochester, MN. American Psychiatric Association (2000). Diagnostic and Statistical Manual of Mental Disorders. (DSM-IV-TR). American Psychiatric Association, Washington DC. Birketvedt GS, Florholmen J, Sundsfjord J et al. (1999). Behavioral and neuroendocrine characteristics of the night-eating syndrome. JAMA 282 (7): 657–663.
584
J.W. WINKELMAN ET AL.
Chiang A, Krystal A (2008). Report of two cases where sleep related eating behavior occurred with the extendedrelease formulation but not the immediate-release formulation of a sedative-hypnotic agent. J Clin Sleep Med 4: 155–156. Coates TJ (1978). Successful self-management strategies toward coping with night eating. J Behav Ther Exp Psychiatry 9: 181–183. de Zwaan M, Burgard MA, Schenck CH et al. (2003). Night time eating: a review of the literature. Eur Eat Disorders Rev 11: 7–24. de Zwaan M, Roerig DB, Crosby RD et al. (2006). Night time eating: a descriptive study. Int J Eat Disord 39: 224–232. Guirguis WR (1986). Sleepwalking as a symptom of bulimia. BMJ 293: 587–588. Gupta MA (1991). Sleep-related eating in bulimia nurovsa: and an underreported parasomnia disorder [abstract]. Sleep Res 20: 182. Hudson JI, Lalonde JK, Berry JM et al. (2006). Binge-eating disorder as a distinct familial phenotype in obese individuals. Arch Gen Psychiatry 63 (3): 313–319. Kales A, Soldatos CR, Bixler EO et al. (1980). Hereditary factors in sleepwalking and night terrors. Br J Psychiatry 137: 111–118. Liang Y, Chen X, Osborne M et al. (2005). Topiramate ameliorates hyperglycaemia and improves glucose-stimulated insulin release in ZDF rats and db/db mice. Diabetes Obes Metab 7 (4): 360–369. Lundgren JD, Allison KC, Crow S et al. (2006). Prevalence of the night eating syndrome in a psychiatric population. Am J Psychiatry 163 (1): 156–158. McIntyre RS, Mancini DA, McCann S et al. (2002). Topiramate versus bupropion SR when added to mood stabilizer therapy for the depressive phase of bipolar disorder: a preliminary single-blind study. Bipolar Disord 3: 207–213. Montgomery L, Haynes L (2001). What every nurse needs to know about nocturnal sleep-related eating disorder. J Psychosoc Nurs Ment Health Serv 39 (8): 14–20. Morgenthaler TI, Silber MH (2002). Amnestic sleep-related eating disorder associated with zolpidem. Sleep Med 3: 323–327. Najjar M (2007). Zolpidem and amnestic sleep related eating disorder. J Clin Sleep Med 3: 637–638. O’Reardon JP, Ringel BL, Dinges DF et al. (2004). Circadian eating and sleeping patterns in the night eating syndrome. Obes Res 12 (11): 1789–1796. O’Reardon JP, Peshek A, Allison KC (2005). Night eating syndrome: diagnosis, epidemiology and management. CNS Drugs 12: 997–1008. Oswald IO, Adam K (1986). Rhythmic raiding of the refrigerator related to rapid eye movement sleep. BMJ 292: 589. Provini F, Albani F, Vetrugno R et al. (2005). A pilot doubleblind placebo-controlled trial of low-dose pramipexole in sleep-related eating disorder. Eur J Neurol 6: 432–436.
Rand CS, MacGregor AM, Stunkard AJ (1997). The night eating syndrome in the general population and among postoperative obesity surgery patients. Int J Eat Disord 22: 65–69. Rogers NL, Dinges DF, Allison KC et al. (2006). Assessment of sleep in women with night eating syndrome. Sleep 29: 814–819. Schenck CH, Mahowald MW (1994). Review of nocturnal sleep-related eating disorders. Int J Eat Disord 4: 343–356. Schenck CH, Mahowald MW (2000). Parasomnias: managing bizarre sleep-related behavior among certain obese patients. Am J Med 19: 78–86. Schenck CH, Hurwitz TD, Bundlie SR et al. (1991). Sleeprelated eating disorders: polysomnographic correlates of a heterogeneous syndrome distinct from daytime eating disorders. Sleep 5: 419–431. Schenck CH, Hurwitz TD, O’Connor KA et al. (1993). Additional categories of sleep-related eating disorders and the current status of treatment. Sleep 5: 457–466. Schenck CH, Connoy DA, Castellanos M et al. (2005). Zolpidem-induced amnestic sleep-related eating disorder (SRED) in 19 patients. Sleep 28 (abstract supplement): A259. Shapira NA, Goldsmith TD, McElroy SL (2000). Treatment of binge-eating disorder with topiramate: a clinical case series. J Clin Psychiatry 5: 368–372. Sinha MK, Ohannesian JP, Heiman ML et al. (1996). Nocturnal rise in leptin in lean, obese, and non-insulindependent diabetes mellitus subjects. J Clin Invest 97: 1344–1347. Stunkard AJ, Grace WJ, Wolff HG (1955). The night-eating syndrome: a pattern of food intake among certain obese patients. Am J Med 19 (1): 78–86. Vetrugno R, Manconi M, Ferini-Strambi L et al. (2006). Nocturnal eating: sleep-related eating disorder or night eating syndrome? A videopolysomnographic study. Sleep 29: 949–954. Wilkes JJ, Nelson E, Osborne M et al. (2005). Topiramate is an insulin-sensitizing compound in vivo with direct effects on adipocytes in female ZDF rats. Am J Physiol Endocrinol Metab 288 (3): E617–E624. Winkelman JW (1993). Nocturnal binge eating is a familial disorder (abstract). Sleep Res 68. Winkelman JW (1997). Sleep-related eating disorder: the dateline dataset (abstract). Sleep Res 31. Winkelman JW (1998). Clinical and polysomnography features of sleep-related eating disorder. J Clin Psychiatry 59: 14–19. Winkelman JW (2003). Treatment of nocturnal eating syndrome and sleep-related eating disorder with topiramate. Sleep Med 4: 243–246. Winkelman JW (2006a). Efficacy and tolerability of openlabel topiramate in the treatment of sleep-related eating disorder: a retrospective case series. J Clin Psychiatry 67: 1729–1734. Winkelman JW (2006b). Sleep-related eating disorder and night eating syndrome: sleep disorders, eating disorders, or both? Sleep 29: 876–877.
SLEEP-RELATED EATING DISORDER Winkelman JW, Herzog DB, Fava M (1999). The prevalence of sleep-related eating disorder in psychiatric and non-psychiatric populations. Psychol Med 29: 1461–1466. Young WB, Hopkins MM, Shechter AL et al. (2002). Topiramate: a case series study in migraine prophylaxis. Cephalalgia 8: 659–663.
585
Zhdanova IV, Wurtman RJ, Marabito C et al. (1996). Effects of low oral dose of melatonin, given 2–4 hours before habitual bedtime, on sleep in normal young humans. Sleep 19: 423–431.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 38
Alcohol, toxins, and medications as a cause of sleep dysfunction DEIRDRE A. CONROY AND KIRK J. BROWER * University of Michigan Addiction Research Center, Ann Arbor, MI, USA
INTRODUCTION
DRUGS OF ABUSE
Numerous substances can result in sleep dysfunction by directly altering brain systems that regulate sleep (Table 38.1). Caffeine, for example, can cause insomnia via its inhibitory effects on adenosine. Substances can also cause sleep dysfunction indirectly by exacerbating an illness or disorder associated with sleep impairment (e.g., caffeine can exacerbate reflux disease causing pain and discomfort that disturb sleep). This chapter focuses predominantly on direct effects. The effects of substances on sleep are known from both preclinical studies in animals and clinical observations and research. This chapter focuses mostly on clinical studies and observations. The observed effects of a substance on sleep in clinical research are influenced by substance-related, populationrelated, and methodology-related factors. Substancerelated factors include dose, timing of dose, acute versus chronic use, withdrawal from use, pharmacokinetics, mechanism of action, and interactions with other drugs. Population-related factors include age, gender, weight, genetics, psychological traits and states, and health status. Methodological factors include sample size, study design, and type of outcome measures (e.g., nocturnal sleep versus daytime sleepiness; self-report versus polysomnography (PSG)). Very few substances are well characterized across each of these factors. Substances included in this chapter are drugs of abuse, prescription medications, substances obtained over the counter and off the shelf in stores, and toxic heavy metals.
Alcohol Alcohol has temporary soporific effects in nonalcoholics, but tolerance develops quickly and after chronic use the effects on sleep become deleterious. There is a biphasic effect of alcohol on sleep in healthy volunteers. Initially, sleep-onset latency (SOL) is shortened and there is an increase in slow-wave sleep (SWS) in the first half of the night. In the second half of the night, sleep deteriorates and there are more awakenings, there is more stage 1 (S1) sleep, less SWS (MacLean and Cairns, 1982; Williams et al., 1983), and an increased percentage of rapid eye movement (REM) sleep (Rundell et al., 1977). During this initial phase, individuals usually perceive a sleep-inducing effect from alcoholic drinks. Eleven percent of healthy Americans use alcohol specifically to help them fall asleep (National Sleep Foundation, 2005), while 15–28% of insomniacs use alcohol to aid sleep. Using a choice paradigm under controlled blinded laboratory conditions, nonalcoholic insomniacs chose and consumed alcohol as a nighttime beverage significantly more often than healthy controls, whereas healthy controls were significantly more likely to have chosen and consumed a nonalcoholic placebo beverage (Roehrs et al., 1999). Tolerance develops to the sedating effects within 1 week in both healthy volunteers (Roehrs et al., 1992) and alcoholics (Skoloda et al., 1979), requiring more alcohol to derive the same sleep-promoting effects. As the neurochemical systems of the brain adapt, sleep-generating systems, including the GABAergic system, downregulate their responses to chronic alcohol administration and
*Correspondence to: Kirk J. Brower, M.D., Professor of Psychiatry, University of Michigan Addiction Research Center, 4250 Plymouth Rd, SPC 5740, Ann Arbor, MI 48109-2700, USA. Tel: 734-232-0260, E-mail:
[email protected]
588
D.A. CONROY AND K.J. BROWER
Table 38.1 Substances associated with nocturnal sleep dysfunction
Class of substance
Insomnia
Substances of abuse Alcohol Alcohol withdrawal Nicotine Cannabis withdrawal Benzodiazepine withdrawal Barbiturates Barbiturate withdrawal Ecstasy Cocaine intoxication Amphetamines and similarly acting stimulants Anxiolytics Buspirone Stimulants Pseudoephedrine Antidepressants Monoamine oxidase inhibitors Selective serotonin reuptake inhibitors Tricyclics Antipsychotics Olanzapine Risperidone Clozapine Quetiapine Antihypertensives Beta-blockers Calcium channel blockers Alpha-2 agonists Bronchodilators Theophylline Beta-agonists Corticosteroids Dopamine agonists Levodopa Heavy-metal exposure Manganese, mercury, nickel, thallium, copper Anabolic-androgenic steroids Methyltestosterone/testosterone
sleep generation is dampened. During this time, heavy alcohol consumers may report insomnia, hypersomnia, circadian rhythm disturbances, or parasomnias (Gillin et al., 2005). Moreover, an estimated 36–91% of patients in early recovery from alcohol dependence complain of insomnia (Brower et al., 2001; Cohn et al., 2003).
ALCOHOL
WITHDRAWAL AND POLYSOMNOGRAPHY
Acute alcohol withdrawal (defined as roughly 1–10 days following last drink) is associated with sleep
þ þ þ þ þ
Sleep-related movement disorders
Sleep-disordered breathing
þ
þ þ þ
þ þ þ þ þ þ þ þ þ
þ
þ þ þ þ þ
þ þ þ þ þ þ þ þ þ þ
þ þ þ
disruption and complaints of insomnia. PSG irregularities have been well characterized. These irregularities primarily consist of an increase in SOL (Brower et al., 1998; Drummond et al., 1998), a decrease in SWS percentage (Allen et al., 1977; Brower et al., 1998; Drummond et al., 1998), and a decrease in REM sleep. Return to drinking will initially increase SWS or decrease REM sleep; however, upon repeat withdrawal, these changes will revert to baseline or below baseline levels (Brower et al., 2001).
ALCOHOL, TOXINS, AND MEDICATIONS AS A CAUSE OF SLEEP DYSFUNCTION
ALCOHOL AND SLEEP-DISORDERED BREATHING (SDB) Because alcohol is a mild respiratory suppressant it increases upper-airway resistance during sleep and can induce or worsen obstructive sleep apnea (OSA) in individuals at risk for OSA (Guilleminault, 1980). Healthy patients without OSA and only a history of snoring developed OSA following alcohol ingestion at bedtime (Mitler et al., 1988). The duration of the apneic episode has been shown to be longer and the associated oxyhemoglobin desaturation more severe following alcohol ingestion (Taasan et al., 1981). Patients with OSA and chronic obstructive pulmonary disease have a higher respiratory disturbance index and lower oxyhemoglobin saturation levels in sleep after drinking alcohol at bedtime (Issa and Sullivan, 1982). Alcoholdependent patients have an age-related increase in SDB (Aldrich et al., 1999).
SLEEP
DISTURBANCES PREDICT RELAPSE
PSG-defined sleep abnormalities during withdrawal have been associated with relapse to drinking. SOL has been found to be a strong predictor of alcohol relapse (Brower et al., 1998) as well as low total sleep time (TST) in alcoholics with and without secondary depression (Clark et al., 1999). Sleep disturbances during withdrawal can persist for up to 2 years. Drummond et al. (1998) studied patients at 16 days, 19 weeks, 14 months, and 27 months of abstinence. Sleep gradually improved across the first year of study, but even after a year of continued abstinence, REM percentage remained high and REM latency remained abbreviated (Drummond et al., 1998). In sum, several studies conducted to date have highlighted the risk to sleep that self-medication with alcohol may present. In addition, there is a relationship between both subjective and objective sleep disturbance and return to drinking (Brower, 2003).
Nicotine Most cigarettes in the US market today contain 10 mg or more of nicotine (National Institute on Drug Abuse (NIDA), 2005b). Overall, it appears that both use of and withdrawal from nicotine have been associated with sleep complaints.
EPIDEMIOLOGICAL
STUDIES OF SMOKING
AND SLEEP DISORDERS
The relationship between smoking and sleep was analyzed in a study that controlled for demographic, health, behavioral, and psychological variables (Riedel et al., 2004). Most people (39%) who described themselves as having chronic insomnia were light smokers
589
(<15 cigarettes/day), followed by 33% of heavy smokers (>15 cigarettes/day) and 31% of nonsmokers. Regression analyses showed that heavy smoking predicted chronic insomnia only in females. Phillips and Danner (1995) questioned students in grades 9–12 (38% of whom smoked) and adults between ages 20 and 84 years (20% of whom smoked) about problems going to sleep, sleep disturbance, and daytime sleepiness. Results consistently showed that smoking was associated with poor sleep habits, poor sleep quality, and impairment of daytime functioning across a wide age range (Phillips and Danner, 1995). Another study found that smoking, particularly in females, was related to both frequent and infrequent difficulty getting to sleep (Wetter and Young, 1994).
SMOKING
AND SLEEP-DISORDERED BREATHING
Nicotine has been associated with improving SDB while smoking has been shown to be a risk factor for SDB. Two studies have suggested that nicotine improves SDB. Eight male patients with OSA who chewed nicotine gum (containing a total of 14 mg nicotine) had a reduced number of apneas in the first 2 hours of sleep (Gothe et al., 1985; Young et al., 2002). A later study found that nonsmoking participants with a history of habitual snoring who slept with a nicotine patch containing 11 mg nicotine had shorter SDB event durations and increased SpO2 nadir. However, snoring intensity and frequency of SDB events were not changed (Davila et al., 1994). A positive correlation between smoking and OSA has been reported (Young et al., 2002). Wetter and colleagues (1994) reported a relationship between current smoking and moderate or worse SDB after controlling for sex, age, body mass index, and alcohol use. Heavy smokers (>40 cigarettes per day) had the greatest risk of SDB while never smoking was unrelated to SDB. However, former smokers in that study were not more likely to have OSA than those who had never smoked.
ACUTE
EXPOSURE TO NICOTINE ON
PSG
Acute exposure to nicotine has been associated with mild sedation and relaxation at low doses and arousal at high doses. In nonsmokers, nicotine prolonged SOL, reduced TST, and slightly changed REM sleep (Gillin et al., 2005). A group of eight smokers (mean age 30 years) were compared to a group of age- and sex-matched nonsmoking controls across four consecutive nights in the sleep laboratory. On the first two nights in the laboratory, smoking participants demonstrated longer SOL and spent more time in bed than did nonsmoking control subjects (Soldatos et al., 1980). There were no sleep stage differences between
590
D.A. CONROY AND K.J. BROWER
the smoking group and the control group. These findings were supported by a separate study (Davila et al., 1994). Three studies have reported that non-REM sleep stages are relatively unaffected by nicotine (Soldatos et al., 1980; Davila et al., 1994; Salin-Pascual et al., 1995) and two have found that nicotine reduces REM sleep (Davila et al., 1994; Salin-Pascual et al., 1995).
NICOTINE
WITHDRAWAL ON
PSG
Soldatos et al. (1980) found initial improvements in SE parameters and then a decline in sleep quality on the third and fourth nights of withdrawal. Prosise et al. (1994) used a larger age range (35–49 years of age) and revealed a greater number of arousals, stage changes, and awakenings during smoking abstinence (Prosise et al., 1994). A multiple sleep latency test (MSLT) was associated with an insignificant reduction in mean sleep latency values. In depressed versus nondepressed women sleep fragmentation initially peaked but then decreased. Only REM sleep discriminated between withdrawal trajectories of the depressed group. Nondepressed women had a prolonged REM onset latency (ROL) at day 3 and 5, but then both depressed and nondepressed were equal by 10 days postcessation (Wetter et al., 2000). The short- and long-term effects of nicotine on sleep may vary, due to differences in age, smoking history, and time of last cigarette with respect to bedtime. Alcohol and caffeine may also play a role (Borsato et al., 2000). Nevertheless, both subjective (Wetter and Young, 1994) and objective data (Wetter et al., 2000) suggest that sleep quality may improve after prolonged abstinence from smoking.
Caffeine Caffeine is a phosphodiesterase inhibitor that blocks adenosine receptors and therefore promotes wakefulness. A number of recent studies have highlighted caffeine’s ability to attenuate the progressive increase in sleepiness across the day and the quality of recovery sleep following sleep deprivation. In one randomized controlled trial (RCT), 200 mg caffeine administered twice during 40 hours of sleep deprivation reduced the slow component of electroencephalogram (EEG) power (0.75–2.0 Hz) and enhanced faster components (11.25–20.0 Hz) compared to placebo during recovery sleep (Landolt et al., 2004). Wyatt et al. (2004) found that, although caffeine kept subjects alert across an extended 28.57-hour “day” on a forced desynchrony protocol, cognitive performance suffered at the circadian nadir (Wyatt et al., 2004).
High doses of caffeine affect recovery sleep more than low doses. An RCT of 0 (placebo), 100, or 300 mg caffeine during 27 hours of sleep deprivation revealed that the low dose increased S1 sleep only, but the high dose reduced TST, increased S1 sleep, and reduced SWS in the first third of the night. Caffeine dose and participant’s history of high or low caffeine use did not affect performance on a neurocognitve test battery (LaJambe et al., 2005). Excessive caffeine may affect cardiac sympathetic function during sleep. Bonnet and colleagues (2005) examined electrocardiograms (ECGs) of 15 healthy volunteers who took 400 mg caffeine a half-hour before bedtime. R-R intervals in the ECG traces were examined before sleep, in S2 sleep, and REM sleep in caffeine and placebo conditions. The heart rate variability, defined as the integration of the lowfrequency/high-frequency ratio band, was significantly higher during REM sleep in the caffeine group than in the placebo group. There was no difference between low-frequency/high-frequency ratios for wake time and S2 sleep in the caffeine condition. These results have implications for patients with heart disease and who consume excessive amounts of caffeine (Bonnet et al., 2005).
Marijuana The active ingredient in marijuana is delta-9-tetrahydrocannabinol (THC). Cannabidiol is an extract of THC that can be measured along with THC in laboratory research settings. The effects of acute exposure of marijuana on sleep are similar to some hypnotics because they can induce sleep (Hollister, 2001), slightly decrease REM sleep (Pivik et al., 1972), and adversely affect sleep upon withdrawal (Wiesbeck et al., 1996). Doses of 10, 20, and 30 mg THC prior to sleep have decreased SOL after subjects reported achieving a “high” subjectively (Cousens and Dimascio, 1973). There is an initial increase in S4 sleep with THC (Pivik et al., 1972; Feinberg et al., 1975, 1976), but more recent studies have found that 15 mg THC and 5 mg cannabidiol before bed decreased S3 sleep (Nicholson et al., 2004). Prolonged ROL (Nicholson et al., 2004), reduced eye movements, and reduced REM sleep duration have also been noted (Pivik et al., 1972). Sleep disturbance is a common side-effect of marijuana withdrawal. Among 1735 frequent users of marijuana (>21 occasions in a single year), 235 (13.5%) reported difficulty sleeping during withdrawal (Wiesbeck et al., 1996). Difficulty falling asleep and decreased SWS% have been documented during the
ALCOHOL, TOXINS, AND MEDICATIONS AS A CAUSE OF SLEEP DYSFUNCTION first two nights (Freemon, 1982) of withdrawal. While acute exposure to low doses (2 mg) of THC decreases REM sleep (Pivik et al., 1972), there is no REM sleep rebound during the withdrawal period (Freemon, 1974). Higher doses (70–210 mg), on the other hand, resulted in REM sleep rebound during withdrawal (Feinberg et al., 1976). Daytime consequences are reported following higher doses of THC, including mild hangovers (Cousens and Dimascio, 1973), increased sleepiness, mood changes, and impaired memory (Nicholson et al., 2004). Objective methods of assessing sleepiness, such as the MSLT, have not been utilized to assess daytime consequences of THC.
Ecstasy 3,4-methylenedioxymethamphetamine (MDMA) or “ecstasy” is a stimulant with hallucinogenic properties. It stimulates the release and inhibits the reuptake of serotonin (5-HT) and, to a lesser extent, other neurotransmitters, which can generate feelings of elation and pleasure (Parrott, 2001; Ricaurte and McCann, 2001). This abrupt surge in neurotransmitters affects regulation of mood, aggression, sexual activity, sleep, and sensitivity to pain. Two studies have shown that persistent use of ecstasy shortens TST and impairs non-REM sleep, particularly S2 sleep (Jansen, 1999; Parrott, 2001). Allen and colleagues (1993) examined the effects of MDMA on the sleep of 23 MDMA-abstinent users compared to age- and sex-matched controls with no history of use (Allen et al., 1993). The MDMA users had a 19-minute reduction of TST. The MDMA users also had a slightly shorter ROL than controls (60 versus 75 minutes), but this finding was not significant.
Ketamine and phencyclidine Ketamine is a general anesthetic used primarily in veterinary medicine and as a pediatric anesthetic. Ketamine is molecularly similar to phencyclidine (PCP or “angel dust”) and has a similar mechanism of action. Ketamine has been referred to as a “dissociative anesthetic” (Lydic and Baghdoyan, 2002) because it can produce analgesia and amnesia without a loss of consciousness. Long-term effects include tolerance and possible physical and/or psychological dependence. The sleep effects of ketamine are better studied than PCP. Ketamine, dizocilpine maleate (MK-801), and PCP all block noncompetitively the cation channel of the N-methyl-D-aspartate subset of glutamate receptors. Ketamine’s use as an anesthetic in humans has been associated primarily with reports of excessive dreaming. The experience can range from reports of
591
nightmares in children (median age 2.25 years), which may last for months to even years following exposure (Valentin and Bech, 1996), to pleasant dreaming experiences in adult patients (Grace, 2003). In a study of awake EEG recordings in patients with neuropathic pain, subanesthetic doses of ketamine caused a significant decrease in alpha-wave amplitude without increasing the absolute amplitude of slow-wave activity (Rangaswamy et al., 2004). This reduction was associated with subjective pain relief. In addition, ketamine significantly decreased REMs, but did not increase slow eye movements, which indicate drowsiness. These results suggest that ketamine produced a conscious state that was neither alert nor drowsy (Oga et al., 2002).
Gamma-hydroxybutyrate Although gamma-hydroxybutyrate (GHB), also called sodium oxybate, can be a drug of abuse, in the clinical setting it is a highly effective treatment of narcolepsy with cataplexy (Xyrem International Study Group, 2005; Lemon et al., 2006). It has a dual action on sleeping and waking. It controls cataplexy, enhances sleep quality, and improves daytime sleepiness (Lammers et al., 1993; Mamelak et al., 2004). The mechanisms by which it controls the symptoms of narcolepsy or cataplectic attacks are still unknown (for review, see Xyrem (Sodium Oxybate) Oral Solution, 2002; Scammell, 2003), but it is an endogenous metabolite of gamma-aminobutyric acid (GABA) that likely binds to GHB and GABAB receptors. In adults with narcolepsy–cataplexy, nightly administration of sodium oxybate produced dose-related increases in SWS and delta power. REM sleep increased initially, and then decreased in a dose-related way. Awakenings decreased on the nocturnal PSG. The ability to maintain wakefulness was also improved on maintenance of wakefulness tests the next day (Mamelak et al., 2004). Sodium oxybate is administered in liquid form at bedtime with a second dose halfway through the night. Adverse effects include nocturnal incontinence and sleepwalking, and it is cautioned for patients with a history of drug abuse.
Inhalants Inhalants are breathable chemical vapors or gases that produce psychoactive effects when abused. They include, but are not limited to, the following: volatile organic solvents, fuel gases, nitrites, anesthetic gases, and aerosols (US Department of Health and Human Services, 2003). To our knowledge, there are no studies examining the effects of inhalants on the sleep EEG.
592
D.A. CONROY AND K.J. BROWER
Central nervous system (CNS) stimulants CNS stimulants constitute a diverse group of drugs, all of which are alerting and disruptive to sleep, and subject to abuse because of their actions on monoamine neurotransmitter systems (dopamine (DA), norepinephrine (NE), and/or 5-HT). Typically, CNS stimulants such as amphetamines, methylphenidate, and modafinil are used clinically to treat daytime sleepiness or attention deficit disorders. Cocaine is used clinically as a topical anesthetic. Another drug in this category, pemoline, was removed from the US market in 2005 because of the risk of liver failure. In general, stimulants impair the quality of sleep by increasing the amount of S1 sleep, decreasing S2 sleep, SWS, and REM sleep, and by increasing ROL (Foral et al., 2003). The one exception is modafinil, which has not been found to affect sleep architecture. Withdrawal from stimulants typically results in REM rebound, which is an important consideration in the sleep laboratory when evaluating MSLT results from individuals discontinuing their stimulant medications.
AMPHETAMINES Amphetamines enhance the release of DA and block the reuptake of NE and DA. The effects of amphetamines on sleep may be prolonged even after they are discontinued. Across 20 nights following withdrawal, amphetamine-dependent subjects in one study showed an initial increase in TST followed by reduced sleep time and more disturbed sleep (Gossop et al., 1982) than controls. Another study utilized a thorough sleep questionnaire in 21 patients across the first 3 weeks of methamphetamine withdrawal. Compared to healthy controls, the patients’ total hours of sleep (day and night) peaked on the fifth day of abstinence and, unlike Gossop et al. (1982), was higher at the study’s completion than when the study began. SOL, number of awakenings in the night, quality of sleep, clearheadedness on awakening, satisfaction with sleep, and depth of sleep all improved significantly across the 3 weeks (McGregor et al., 2005).
PSEUDOEPHEDRINE
AND PHENYLPROPANOLAMINE
Pseudoephedrine and phenylpropanolamine are orally effective nasal decongestants and sympathomimetics. An RCT comparing the efficacy and safety of cetirizine (5 mg), pseudoephedrine (120 mg bid), and their combination found that insomnia was the most common complaint in patients taking pseudoephedrine (Bertrand et al., 1996). Phenylpropanolamine is structurally similar to amphetamine. Used both as a nasal decongestant and
as a weight control medication, it can increase plasma caffeine levels when taken in combination (Lake et al., 1990). Phenylpropanolamine’s reported role in causing hemorrhagic strokes (Kernan et al., 2000) led the Food and Drug Administration to propose its removal from the US market (Sorelle, 2000; Food and Drug Administration, 2005).
MODAFINIL Although initially approved to treat excessive daytime sleepiness (EDS) secondary to narcolepsy, modafinil is now being prescribed for daytime sleepiness due to sleep apnea syndrome and shift work sleep disorder (Schwartz, 2005). Modafinil works in part by blocking reuptake of DA, but its full mechanism of action is unknown. Modafinil 400 mg is as alerting as caffeine 600 mg (Wesensten et al., 2005), but it does not affect sleep architecture and there is no rebound hypersomnolence or potential for abuse (Scammell and Matheson, 1998).
COCAINE Cocaine blocks reuptake of DA, NE, and 5-HT. People initially enjoy the effects of cocaine because they feel energized for extended periods of time without the need for food or sleep. Tolerance quickly develops to its reinforcing and stimulatory effects and chronic cocaine use has been associated with heart attacks, respiratory failure, strokes, and seizures (National Institute on Drug Abuse (NIDA), 2005a). Acute administration of cocaine to three abstinent abusers increased SOL by several hours, decreased SE, and decreased REM sleep percentage (Johanson et al., 1999; Foral et al., 2003). Subjective reports of sleep problems are a common side-effect of cocaine withdrawal, including hypersomnia and increased dreaming (Brower et al., 1988). These complaints are reflected in PSG changes during withdrawal, including an initial increase in TST, shortened ROL, increased REM sleep percentage, and increased REM density (Kowatch et al., 1992; Johanson et al., 1999). After withdrawal, sleep quality worsens. After a 3-day binge period of smoked cocaine among dependent patients and 15 subsequent days of abstinence, TST, SE, and SOL deteriorated (Pace-Schott et al., 2005). Other studies have shown that SOL and wake time in the night remain elevated and SE continues to be low in the 3 weeks postabstinence (Kowatch et al., 1992; Thompson et al., 1995). Subjective reports of sleep quality, however, remained unchanged across the first 2 weeks of abstinence (Pace-Schott et al., 2005), while selfreported sleep parameters worsened 1 month after abstinence (Weddington et al., 1990). In sum, sleep is
ALCOHOL, TOXINS, AND MEDICATIONS AS A CAUSE OF SLEEP DYSFUNCTION considerably disrupted objectively and subjectively for weeks after withdrawal from cocaine.
Opioids Opioids are typically used for their analgesic effects, mediated by agonistic action at opioid receptors. They also cause sedation. Opioids with short half-lives (2–7 hours) are more prone to abuse than ones with a longer half-life (8–12 hours) (Gillin et al., 2005). Adverse effects can include apathy, poor concentration, mood changes, nausea, and vomiting. Tolerance can develop quickly following repeated administration. Opioids can affect sleep differently depending on whether the user has pain or not. Pain patients have increases in TST, presumably because of fewer painrelated arousals and awakenings (Gillin et al., 2005). Abstinent morphine addicts showed a dose-related effect of morphine on sleep, with decreases in TST, SWS, and REM sleep (Kay et al., 1969). Methadonedependent patients taking methadone have more awakenings (Staedt et al., 1996a) and clinically significant periods of central sleep apnea, and lower SE and SWS (Teichtahl et al., 2001). Increases in slow-wave activity and decreased fast activity have also been reported (Kay, 1975). Over prolonged methadone abstinence, REM sleep and SWS may increase (Kay, 1975), but the integrity of sleep can be disrupted indefinitely (Gillin et al., 2005).
PRESCRIBED MEDICATIONS Antidepressants The effects of antidepressants on sleep have been well reviewed (Thase, 1999; Winokur et al., 2001; Mayers and Baldwin, 2005; Wilson and Argyropoulos, 2005). Most antidepressants suppress REM sleep and prolong REM sleep latency, but nefazodone (Rush et al., 1989; Sharpley et al., 1996), trimipramine (Sonntag et al., 1996; Wolf et al., 2001; Riemann et al., 2002a), and perhaps bupropion (Nofzinger et al., 1995, 2001; Ott et al., 2004) are exceptions.
TRICYCLICS
AND TETRACYCLICS
The tricyclic and tetracyclic antidepressants are 5-HT and NE reuptake inhibitors that also have antihistaminergic, anticholinergic, and anti-alpha-adrenergic effects (alpha-1 and alpha-2 receptors). All of these neurotransmitter systems are involved in regulating sleep. Tricyclics are traditionally divided into secondary amines (desipramine, nortriptyline, protriptyline) that predominantly inhibit NE reuptake and tertiary amines (amitriptyline, clomipramine, doxepin, imipramine, trimipramine), some of which preferentially
593
inhibit 5-HT reuptake (amitriptyline, clomipramine, imipramine, trimipramine). The tertiary amines are generally more sedating than the secondary amines, which may be a combined effect of histamine type 1 (H1) receptor blockade and less noradrenergic stimulation. Among the tertiary tricylic antidepressants, amytriptyline, doxepin, and trimipramine are the most sedating, whereas clomipramine and imipramine are the least sedating (Winokur et al., 2001; Mayers and Baldwin, 2005; Wilson and Argyropoulos, 2005). The tetracyclic antidepressants (maprotriline and amoxapine) are also secondary amines and preferentially inhibit NE reuptake. Cyclic antidepressants in healthy or depressed patients. In general, tricyclic antidepressants reduce REM sleep and prolong ROL. Upon abrupt withdrawal, REM sleep rebound may occur (Wilson and Argyropoulos, 2005). By contrast, trimipramine leaves REM sleep unchanged or may even enhance REM sleep (Sonntag et al., 1996). Trimipramine can also increase SWS (Sonntag et al., 1996). The sedating tricyclics (amitriptyline, doxepin, trimipramine) decrease SOL and wake time after sleep onset (WASO), and increase SE and TST (Wilson et al., 2005), whereas other cyclic antidepressants may do the opposite (Winokur et al., 2001). Cyclic antidepressants in primary insomnia. Doxepin (25–50 mg at bedtime) significantly increased SE and patient-rated sleep quality compared to placebo in an RCT with 47 patients (Hajak et al., 2001). Likewise, trimipramine increased SE and patient sleep ratings in an RCT with 55 patients (Riemann et al., 2002b).
MONOAMINE
OXIDASE INHIBITORS
(MAOIS)
Phenelzine and tranylcypromine irreversibly and nonselectively inhibit both type A and type B monoamine oxidase. Isoniazid is another irreversible and nonselective MAOI that is used to treat tuberculosis. Nonselective MAOIs reduce the degradation of DA, 5-HT, and NE. Selegiline is a type B-selective MAOI, marketed in the USA as an antiparkinsonian agent, that will be discussed below in the section with other antiparkinsonian drugs. A transdermal form of selegiline for treating depression is available. Type B-selective MAOIs reduce degradation of DA but not 5-HT and NE in usual therapeutic doses. Phenelzine and tranylcypromine profoundly suppress REM sleep in depressed patients (Landolt et al., 2001; Wilson and Argyropoulos, 2005) with REM rebound reported during withdrawal from the medications (Mayers and Baldwin, 2005). All of the MAOIs have been associated with insomnia, and tranylcypromine,
594 D.A. CONROY AND K.J. BROWER which bears some resemblance to amphetamine structurHealthy volunteer subjects. Ware and Pittard (1990) ally, is considered more stimulating than phenelzine. studied 6 males aged 18–32 years using a double-blind, Tranylcypromine also decreased S4 sleep in depressed placebo-controlled crossover design during 4 nights of patients (Nolen et al., 1993). trazodone doses increasing from 50 to 200 mg (Ware and Pittard, 1990). The only significant finding was SELECTIVE SEROTONIN REUPTAKE INHIBITORS an increase in S4%. Ware et al. (1994) studied 12 males (SSRIS) aged 20–34 years in a double-blind, placebo-controlled study. Trazodone significantly decreased awakenings, SSRIs are activating and disruptive to sleep as measured movement/arousals and REM sleep; it prolonged by PSG, resulting in increased arousals and S1 sleep, and ROL, but it did not change SOL, TST, SE, or SWS decreased TST and SE. SSRIs prolong ROL, decrease compared to placebo. Yamadera et al. (1999) studied REM sleep, and REM sleep rebound has been reported 12 males aged 21–28 years after 2 days of either sinfollowing cessation of SSRIs (Wilson and Argyropoulos, gle-blind trazodone 25 mg qid or placebo and found 2005). In general, SSRIs do not affect SWS, although a significant increase in SWS (Yamadera et al., 1999). one study revealed increased SWS with paroxetine Patients with primary insomnia. Montgomery et al. when taken in the morning (Oswald and Adam, 1986). (1983) administered 150 mg trazodone nightly for Paradoxically, SSRIs may improve insomnia in depressed 3 weeks to 9 volunteers with insomnia, aged 50–70 years, patients as compared to placebo, because the depressionfollowed by 1 week of placebo in a single-blind study related insomnia improves when the depression responds (Montgomery et al., 1983). Trazodone increased SWS to medication. Thus, the alerting effect measured by PSG and enhanced subjectively reported sleep compared to is not necessarily reflected in self-reported sleep quality placebo, while decreasing nocturnal arousals, REM (Staner et al., 1995). sleep, and S1 sleep. SOL and TST were unchanged. WithSome investigators have tried to distinguish whether drawal effects were maximal on night 2 and consisted of some SSRIs are more sleep-enhancing or less disruprebound insomnia and REM sleep, and a negative tive to sleep than others. In this regard, paroxetine rebound in SWS. was noted to improve sleep in depressed patients early Patients with depression. Mouret et al. (1988) admiin treatment (Montgomery, 1992), improve selfnistered 400–600 mg trazodone daily in open-label fashreported sleep quality in an open-label trial in nonion to inpatients with major depression. Compared to a depressed patients with insomnia (Nowell et al., 1999), 3-night control period before starting trazodone, TST and increase SWS when given in the morning to and SE were significantly increased and SOL and numhealthy controls (Oswald and Adam, 1986). When given ber of awakenings were significantly decreased on all at night in this latter study, however, paroxetine caused treatment nights. SWS was significantly increased and more frequent awakenings and reduced total sleep S1 significantly decreased during week 4, but REM (Oswald and Adam, 1986). Moreover, self-reported sleep was unchanged during treatment (Mouret et al., relief of insomnia in the study by Nowell et al. (1999) 1988). In an 8-week single-blind study, trazodone at did not correlate with PSG improvements in sleep 150–400 mg in divided doses (with most of the dose in quantity and paroxetine decreased power within the the evening), 5 of 6 depressed patients with insomnia delta frequency range (Nowell et al., 1999). Finally, demonstrated improvements in SOL, SE, TST, and another study employing a randomized, double-blind, S4% when compared to a baseline placebo period placebo-controlled design found that paroxetine (Scharf and Sachais, 1990). In a double-blind trial in (20 mg) was more disruptive to sleep than citalopram which depressed patients were randomized to tid admin(20 mg) in healthy subjects (Wilson et al., 2004). istration of trazodone, venlafaxine, or placebo, trazoThe SSRIs have also been associated with increased done significantly improved intrerviewer-rated sleep periodic limb movements (PLMs), (Yang et al., 2005), scores versus venlafaxine or placebo (Cunningham although one study failed to find an association et al., 1994). In a 6-week single-blind study of patients (Brown et al., 2005). with dysthymia and insomnia, trazodone significantly increased SWS and decreased S2%, but had no effect TRAZODONE on sleep continuity, when compared to placebo (Parrino Trazodone strongly blocks postsynaptic 5-HT2A recepet al., 1994). In a 6-week double-blind trial in which tors and weakly blocks presynaptic reuptake of 5-HT; depressed outpatients were randomized to trazodone it also has H1 antagonist and weak alpha-1-adrenergic or fluoxetine, trazodone significantly improved subjecproperties. Sedation has been attributed to its antihistative sleep as reported by patients to their clinicians mine properties while increased SWS is attributed to (Debus et al., 1988). Two single-blind trials reported by 5-HT2A receptor blockade. Van Bemmel et al. (1992, 1995) showed that trazodone
ALCOHOL, TOXINS, AND MEDICATIONS AS A CAUSE OF SLEEP DYSFUNCTION decreased REM sleep and increased ROL without affecting SWS or sleep continuity. Power density analyses showed significant reductions in the 13–14-Hz frequency band. Insomnia associated with MAOIs responded to openlabel trazodone at doses of 50–75 mg at night (Jacobsen, 1990). Nierenberg et al. (1994) treated insomnia associated with fluoxetine or bupropion in patients with major depression using an RCT, and reported improved subjective ratings of sleep compared to placebo at doses of 50–100 mg nightly (Nierenberg et al., 1994). Kaynak et al. (2004) gave 12 females 7 days of either trazodone 100 mg or placebo in a double-blind controlled trial. All patients had been treated for at least 3 weeks on SSRIs and had complaints of insomnia. Subjective sleep improved significantly across both conditions. In contrast to placebo, however, trazodone significantly increased TST, SE, and SWS and significantly decreased S1 and number of awakenings (Kaynak et al., 2004). Patients with substance use disorders. Karam-Hage and Brower (2003) described the use of nightly trazodone in abstinent alcohol-dependent patients with insomnia. Morning sedation was a problem, as has also been reported when trazodone was given to fluoxetinetreated depressed patients (Metz and Shader, 1990). Le Bon et al. (2003) conducted an RCT of 16 alcoholdependent patients following acute alcohol withdrawal and reported that trazodone significantly increased SE and decreased WASO when compared to placebo (Le Bon et al., 2003). Patients with other disorders. Trazodone increased SWS and decreased the number of awakenings in 11 patients with chronic pain compared to placebo in a single-blind nonrandomized trial, but increased SOL (Saletu et al., 2005). One case report suggested that trazodone at increasing doses of 25–100 mg nightly successfully treated restless-legs syndrome (RLS) and insomnia when added to a combination of sedative hypnotics (Hasegawa et al., 2004).
NEFAZODONE Nefazodone is infrequently used since a black-box warning was added for life-threatening hepatic failure. In a double-blind placebo-controlled study of 22 healthy nondepressed subjects, the only nocturnal sleep parameter altered by nefazodone was a decrease in S1 sleep (Vogel et al., 1998). Ware et al. (1994) found few PSG changes in their randomized, double-blind trial in 12 healthy subjects, although nefazodone increased REM sleep (Ware et al., 1994). Similarly, another study reported no significant effects on sleep continuity and architecture in 37 healthy controls in an RCT (Sharpley et al., 1996).
595
Lastly, among 125 depressed patients randomized to either nefazodone or fluoxetine, nefazodone significantly increased SE and decreased awakenings whereas fluoxetine had the opposite effect (Rush et al., 1998). Compared to baseline, nefazodone significantly increased REM sleep percentage and decreased S1 percentage, SWS percentage, and ROL. Nefazodone is one of a few antidepressants that do not suppress REM sleep. Compared to fluoxetine, nefazodone also significantly increased subjective sleep quality during weeks 2 through 8 of the 8-week trial. Compared to paroxetine, nefazodone significantly increased SE (Hicks et al., 2002).
BUPROPION Unlike most other antidepressants, bupropion does not reliably suppress REM sleep (Nofzinger et al., 2001; Ott et al., 2004). It even enhanced REM sleep and shortened REM latency in some depressed patients (Nofzinger et al., 1995). Nightmares and vivid dreaming might be associated with bupropion’s REM enhancement effects (Balon, 1996). Consistent with its DA reuptake inhibitor effects, bupropion decreased PLMs in depressed patients with PLM disorder (Nofzinger et al., 2000). Another study reported that bupropion was less likely than either SSRIs or venlafaxine to increase PLMs (Yang et al., 2005).
MIRTAZAPINE Mirtazapine blocks 5-HT2 and 5-HT3 receptors, alpha2-noradrenergic receptors, and H1 receptors (Stimmel et al., 1997). Alpha-2-blockade increases both 5-HT and NE release. Ruigt et al. (1990) conducted a randomized, placebo-controlled study with healthy subjects and reported decreased SOL and S1 sleep and increased SWS (Ruigt et al., 1990). Similarly, Aslan et al. (2002) randomly assigned healthy subjects to mirtazapine or placebo and reported decreased S1 sleep, increased SWS, and improvements in SE and awakenings (Aslan et al., 2002). Another RCT with healthy subjects found that mirtazapine improved subjective sleep quality versus placebo (Ridout et al., 2003). Among depressed patients, an open-label study found increased TST and SE and decreased SOL without any changes in sleep architecture over 2 weeks of study compared to baseline (Winokur et al., 2000). When compared to paroxetine in older adults with major depression (Schatzberg et al., 2002) or venlafaxine among inpatients with severe major depression (Guelfi et al., 2001), mirtazapine was associated with significantly more improved interviewer-rated sleep scores.
596
SEROTONIN
D.A. CONROY AND K.J. BROWER NOREPINEPHRINE REUPTAKE INHIBITORS
Venlafaxine. In healthy subjects, venlafaxine increased wake time, S1 sleep, and PLMs, and it decreased stages 2 and 3 sleep, and REM sleep (Salin-Pascual et al., 1997). Among inpatients with major depression, venlafaxine decreased TST and REM sleep and increased wake time and REM sleep latency compared to placebo (Luthringer et al., 1996). In another randomized, double-blind study of patients with major depression, venlafaxine and placebo did not differ on the Hamilton Depression sleep factor score over a 6-week period (Cunningham et al., 1994). Venlafaxine has also been associated with increased PLMs (Yang et al., 2005). Duloxetine. In healthy subjects, duloxetine decreased REM sleep and increased REM sleep latency compared to placebo (Chalon et al., 2005). Subjectively, duloxetine at 80 mg daily improved getting to sleep when compared to placebo in healthy subjects (Chalon et al., 2005), although 20% of subjects with major depression reported insomnia as an adverse event with duloxetine 80 mg daily in another randomized, double-blind, placebo-controlled trial (Goldstein et al., 2004).
LITHIUM (LI) In healthy subjects, Li increased SWS (Friston et al., 1989) and ROL, decreased REM sleep, and had no effect on TST (Billiard, 1987). Similar effects have been observed in depressed patients who took Li (Billiard, 1987). A study in patients with mood disorders reported that Li increased cerebrospinal fluid levels of delta sleep-inducing peptide, which might explain its effect on SWS (Regnell et al., 1988). In patients with bipolar disorder, Li decreased REM sleep and prolonged ROL (Campbell et al., 1989). Discontinuation effects following Li therapy in bipolar patients appear to be related to manic relapse, rather than Li withdrawal per se (Balon et al., 1988; Klein et al., 1991). Li has also been associated with somnambulism in psychiatric patients, particularly when combined with other psychotropic medication such as antipsychotic agents (Charney et al., 1979; Landry et al., 1999).
Antiepileptic drugs Many antiepileptic drugs have sedative effects and have been investigated for their effects on sleep both in patients with and without epilepsy (Placidi et al., 2000; Bazil, 2003; Legros and Bazil, 2003; Vaughn and D’Cruz, 2004). In addition to epilepsy, common uses of antiepileptic drugs include neuropathic pain, psychiatric disorders, and some sleep disorders.
TRADITIONAL
ANTIEPILEPTIC DRUGS
Carbamazepine increases SE and SWS while decreasing REM percentage in healthy subjects (Placidi et al., 2000). It also increases daytime somnolence. In epileptics, it decreases REM sleep as well and increases the number of stage shifts, but these effects may be reversible with chronic administration. Legros and Bazil (2003) found no sleep EEG effects in 10 epileptics treated chronically with carbamazepine, whereas Bell et al. (2002) found that SWS and ROL were increased and S2 sleep was decreased with stable carbamazepine monotherapy. Phenobarbital increases S2 sleep and reduces SOL, the number of awakenings, and REM sleep (Placidi et al., 2000; Bazil, 2003). It has little effect on SWS. Barbiturates can also worsen OSA. Phenytoin has yielded inconsistent effects in sleep EEG studies (Legros and Bazil, 2003). In general, it reduces SOL, decreases REM sleep, and increases daytime drowsiness (Bazil, 2003). It can also decrease SWS and increase S1 sleep (Legros and Bazil, 2003). Finally, phenytoin can decrease SE and worsen symptoms of RLS (Vaughn and D’Cruz, 2004). Valproate can increase SWS and decrease REM sleep in healthy subjects (Vaughn and D’Cruz, 2004), but has minimal effects on sleep architecture in patients with epilepsy (Placidi et al., 2000). In patients with PLM disorder, an open-label trial reported increased SE and SWS, decreased S1 sleep, and no effect on REM sleep (Ehrenberg et al., 2000). In an RCT, it significantly decreased PLMs and RLS symptoms (Eisensehr et al., 2004).
NEWER
ANTIEPILEPTIC DRUGS
Felbamate has stimulant-like effects in epileptics (Ketter et al., 1996) and has been associated with insomnia (Leppik, 1995). Gabapentin increases SWS in healthy controls (Rao et al., 1988; Foldvary-Schaefer et al., 2002), including those who consumed alcohol prior to bedtime (Bazil et al., 2005). The most common side-effect of gabapentin when given three times daily in placebo-controlled trials as an adjunctive anticonvulsant was somnolence (19% versus 9% on placebo) (Beydoun et al., 1995). Gabapentin has been shown to treat RLS effectively in randomized, double-blind placebo-controlled studies (Thorp et al., 2001; Garcia-Borreguero et al., 2002). When used to treat peripheral neuropathy, sleep subjectively improves, although this may be due to decreased nocturnal pain (Backonja, 1999). Gabapentin may also improve subjective sleep and decrease nightmares in patients with posttraumatic stress disorder (Hamner et al., 2001). Finally, gabapentin enhances subjectively
ALCOHOL, TOXINS, AND MEDICATIONS AS A CAUSE OF SLEEP DYSFUNCTION reported sleep in alcoholics when treated in open-label trials (Chouinard et al., 1998; Karam-Hage and Brower, 2000, 2003; Rosenberg, 2003). Lamotrigine has been associated with insomnia and may increase REM sleep in patients with epilepsy (Placidi et al., 2000; Vaughn and D’Cruz, 2004). Although it has minimal effects on sleep EEG in general (Legros and Bazil, 2003; Vaughn and D’Cruz, 2004), it can also decrease SWS (Placidi et al., 2000). Levetiracetam was evaluated in normal volunteers and patients with epilepsy in a double-blind placebocontrolled study (Bell et al., 2002). In epileptics, it was added to stable carbamazepine therapy. Levetiracetam increased S2 sleep in both groups of subjects, increased REM sleep latency only in healthy volunteers, and decreased S4 sleep only in patients. Subjectively, both subject groups reported fewer periods of wakefulness. Oxcarbazepine has not been well-studied (Bazil, 2003). According to its Food and Drug Administration label, 19% of epileptic patients on monotherapy reported somnolence compared to 5% on placebo among patients who had previously been treated with other antiepileptic drugs. Pregabalin has been studied in 24 healthy subjects in an RCT, and significantly increased SWS, and decreased SOL and REM sleep percentage (Hindmarch et al., 2005). Subjectively, it improved time to sleep onset and sleep quality, but impaired behavior after awakening. Tiagabine is a GABA reuptake inhibitor. In a double-blind placebo-controlled study with 10 healthy older adults (age 59–78 years), 5 mg tiagabine increased sleep efficiency, SWS, and slow-wave activity (Rangaswamy et al., 2004) but had no significant effect on subjective sleep quality (Mathias et al., 2001). Another RCT by Walsh et al. (2006) of 24 healthy older adults revealed no differences between 2 mg and placebo, but the 4- and 8-mg doses consistently increased SWS (Walsh et al., 2006). In 207 older adults with primary insomnia, tiagabine (at 4, 6, or 8 mg before bedtime) significantly increased SWS and decreased S1 sleep; and the 6- and 8-mg doses significantly decreased the number of awakenings (Roth et al., 2006). Subjectively, however, the 8-mg dose significantly decreased TST and sleep quality, while the other doses had no effect. In 58 adult patients with primary insomnia, tiagabine significantly increased SWS in a dose-related manner from 4 to 16 mg daily (Walsh et al., 2006). Topiramate has been associated with somnolence in clinical trials with epileptic patients, but is otherwise not well studied. In one open-label trial with 14 patients (Bonanni et al., 2004), no differences before and after
597
treatment with 200 mg daily were found for either sleep EEG parameters or daytime sleepiness as measured both subjectively and objectively (MSLT). At even smaller doses, topiramate may reduce symptoms of RLS, although additional studies are needed (Perez-Bravo, 2004).
Antiparkinsonian agents Antiparkinsonian agents are used in the treatment of Parkinson’s disease (PD), RLS, and PLM disorder. PD is a neurodegenerative movement disorder that results from a depletion of dopaminergic neurons in the substantia nigra. Approximately 74–98% of patients with PD experience some form of a sleep disorder (Bhatt et al., 2005), including insomnia, OSA, parasomnias, PLM disorder, RLS, REM sleep behavior disorder, EDS, and circadian rhythm disturbances. Difficulty falling asleep may be due to parkinsonian tremors or RLS symptoms. Problems staying asleep may also be due to tremors, which can also occur during light S1 sleep but rarely in S3 or S4 sleep (Hening et al., 1999), nocturnal akinesia, PLMs, OSA, or REM sleep behavior disorder. It is not known if these sleep disorders are a consequence of the disease pathology itself, the medications used to treat PD, or from other psychiatric complications such as depression. A combination of all of these factors is likely (Trenkwalder, 2005).
LEVODOPA/CARBIDOPA Sleep complaints occur in up to 75% of PD patients on levodopa therapy (Nausieda et al., 1984). Evening administration of levodopa can be sedating at low doses, but sleep-disruptive at high doses (Askenasy and Yahr, 1985; Leeman et al., 1987; van Hilten et al., 1994). Vivid dreams or nightmares have also been reported (van Hilten et al., 1994). PSG studies of levodopa/carbidopa have shown both increased and decreased REM sleep and decreased SWS (Schweitzer, 2005). In general, sleep tends to improve overall with levodopa/carbidopa therapy because it relieves the symptoms of PD which can outweigh other sleep disturbances (van Hilten et al., 1994). In patients with RLS, levodopa with or without carbidopa has been associated with augmentation (Trenkwalder, 2005).
DOPAMINE
RECEPTOR AGONISTS
DA receptor agonists (e.g., apomorphine, bromocriptine, pergolide, pramipexole, ropinirole) improve mobility in PD and reduce the number of PLMs and restless-legs symptoms in patients both with and without PD. Like levodopa/carbidopa, low doses of DA receptor agonists can increase sleepiness while high
598
D.A. CONROY AND K.J. BROWER
doses can cause insomnia (Rye et al., 2000; Larsen and Tanberg, 2001). The mechanisms for this effect may be related to the DA neurons in the ventral tegmental area, where wake-promoting projections lead to the cerebral cortex. Evening dosing of DA agonists may help decrease nocturnal rigidity across the night, which might have been the initial precipitating factor in the sleep disturbance (Bhatt et al., 2005). Augmentation may require a dose earlier in the day, lowering the evening dosage, or stopping the medication altogether (Trenkwalder, 2005).
OTHER
ANTIPARKINSONIAN DRUGS
Monoamine oxidase-B inhibitors (MAOI-Bs) prevent the breakdown of DA, thereby increasing nigrostriatal DA levels. Selegiline, a highly selective MAOI-B, also inhibits DA reuptake from the synaptic cleft and is rapidly metabolized into amphetamine, which further increases DA availability. Insomnia has been reported in 10–32% of PD patients taking selegiline (Chrisp et al., 1991). Benztropine and trihexyphenidyl, anticholinergic drugs, have been found to suppress REM sleep, decrease sleep continuity, and slightly increase SWS (Novak and Shapiro, 1997; Cender et al., 1998). Amantadine, a presynaptic releasing agent that enhances DA activity, is associated with insomnia and nightmares (Novak and Shapiro, 1997) in patients taking it for RLS. PD patients are 25% more sleepy than individuals without PD (O’Suilleabhain and Dewey, 2002). It is not known what percentage of the EDS is due to direct contributions, i.e., the PD itself, or indirect contributions, i.e., the medications used to treat PD. Sleepiness in patients with PD became widely known in 1999 when 8 consecutive patients taking the nonergot DA receptor agonists pramipexole or ropinirole experienced “sleep attacks” (sudden irresistible attacks of sleep) while driving, which caused motor vehicle crashes (Frucht et al., 1999; Olanow et al., 2000). The attacks stopped after pramipexole and ropinirole were discontinued. Frucht et al. (2000) later reported that those patients who were switched from pramipexole to pergolide had a resolution of these events. Another study (Paus et al., 2003) found the lowest risk of sleep attacks was with L-dopa monotherapy (3%), the second was with DA receptor agonist monotherapy (5%), and the highest risk was a combination of L-dopa and DA receptor agonist (7%). DA receptor agonists and the duration of PD were significant influences for the occurrence of the sleep attacks (Paus et al., 2003). PD patients taking levodopa medications report greater sleepiness on the Epworth Sleepiness Scale than those who are not. Higher doses of levodopa produced some sedation, with 25 mg carbidopa/100 mg
levodopa increasing the Epworth Sleepiness Scale 1 point (indicating a greater likelihood of dozing off) (O’Suilleabhain and Dewey, 2002). Sleepiness could be predicted by three factors: (1) levodopa dose; (2) use of a DA receptor agonist; and (3) PD severity. However, data collected from MSLTs have not found a relationship between objective sleepiness and medications in PD (Arnulf et al., 2002; Rye and Jankovic, 2002).
Antipsychotic drugs MECHANISMS
OF ACTION
Both the old- and new-generation antipsychotics tend to improve sleep induction and maintenance in both schizophrenic patients and healthy controls. The main effects of first-generation (typical) drugs are to block D2 receptors, whereas second-generation (atypical) drugs block both D2 and 5-HT2A receptors. Some antipsychotics also have effects on other receptors, including alpha-adrenergic-1 and -2 receptor blockade, H1 receptor blockade, and acetylcholine receptor blockade as well as other subtypes of 5-HT and DA receptors (Monti and Monti, 2004). Low-potency typical agents (e.g., chlorpromazine) are more sedating than the higher-potency typical agents (e.g., haloperidol and fluphenazine). 5-HT2 receptor blockade may cause the increase in SWS that has been reported with atypical antipsychotic agents (Yamashita et al., 2005). Open-label studies of inpatients with schizophrenia have demonstrated improved sleep continuity (e.g., decreased SOL and increased SE) with the typical antipsychotic medications haloperidol and thiothixene (Taylor et al., 1991; Maixner et al., 1998). Patients with schizophrenia who were switched from typical to atypical antipsychotic drugs (i.e., olanzapine, risperidone, and quetiapine) had subjective sleep quality improvements (Yamashita et al., 2004), with greater improvement in patients who were older versus younger than age 65 years (Yamashita et al., 2005).
SPECIFIC
AGENTS
Clozapine is an atypical antipsychotic medication. Monti and Monti (2004) summarized three studies. All were single-blind trials, two of them included PSG, two involved schizophrenic subjects only, and one involved healthy controls only. Touyz et al. (1977) administered 12.5 mg to healthy controls (n ¼ 6) in a crossover design, and reported that S1 and REM sleep decreased, but other PSG parameters were unchanged (Touyz et al., 1977). Among schizophrenia patients treated with 170–275 mg daily on average for 2 weeks, TST, SE, and S2 increased, while WASO and SWS
ALCOHOL, TOXINS, AND MEDICATIONS AS A CAUSE OF SLEEP DYSFUNCTION decreased (Hinze-Selch et al., 1997). Schizophrenia inpatients treated with an average of 348 mg daily for 2 weeks reported overlapping findings of increased TST, SE, and stage 2 sleep (Wetter et al., 1996). In an uncontrolled trial with bipolar and schizoaffective patients, clozapine prolonged SOL and the number of awakenings without any significant changes in sleep stages (Armitage et al., 2004). Patients also reported feeling significantly more rested upon awakening. Although none of these studies evaluated the effects of withdrawal, a single case report of rebound insomnia was noted after abrupt clozapine withdrawal in a schizophrenic patient (Staedt et al., 1996b). Haloperidol is a typical antipsychotic agent. Four single-blind studies in patients with schizophrenia studies were summarized by Monti and Monti (2004, p. 145). The most consistent findings across studies include increases in SE (Taylor et al., 1991; Wetter et al., 1996; Maixner et al., 1998) and ROL (Taylor et al., 1991; Nofzinger et al., 1993; Maixner et al., 1998) and a decrease in SOL (Taylor et al., 1991; Wetter et al., 1996; Maixner et al., 1998). TST and S1 were increased in two of four studies (Nofzinger et al., 1993; Wetter et al., 1996) and one study found increased REM sleep and decreased REM density and S2 sleep at a mean dose of 11 mg daily for 6 weeks (Nofzinger et al., 1993). No significant changes in SWS were seen across the four studies, although S3 sleep increased in one study at a mean dose of 11 mg daily for 3 weeks (Maixner et al., 1998). Haloperidol has also been reported to disrupt nocturnal rest–activity circadian rhythms (Wirz-Justice et al., 2000). Olanzapine. In healthy subjects, olanzapine (5–10 mg) also improved sleep continuity by PSG and increased SWS (Sharpley et al., 2000). REM sleep, however, was decreased and ROL was prolonged. In an openlabel trial with SSRI-treated depressed patients, olanzapine increased both SE and SWS (Sharpley et al., 2005). Increased SE and SWS have also been reported in patients with schizophrenia (Salin-Pascual et al., 1999; Muller et al., 2004): 10 mg olanzapine was administered nightly to 20 inpatients with schizophrenia. The authors reported decreased WASO and increased TST, as measured by PSG, as well as increased S2 sleep and SWS and decreased S1 sleep. No significant changes were observed for REM sleep parameters. Heart rate variability during sleep was unaffected in olanzapine-treated patients with schizophrenia (Mann et al., 2004). Although olanzapine generally improves sleep in healthy subjects and patients with depression or schizophrenia, case reports of restless legs, PLMs, and sleep-related eating disorder have also been reported (Kraus et al., 1999; Paquet et al., 2002).
599
Risperidone. In a double-blind trial of patients with schizophrenia, awakenings were significantly decreased, although both TST and stage 3 sleep were increased (reviewed by Monti and Monti, 2004). An open-label comparison of 5 patients treated with risperidone revealed significantly increased SWS when compared to 5 demographically similar patients treated with haloperidol (Yamashita et al., 2002). The third study, also open-label, found that risperidone-treated patients with schizophrenia reported significantly better sleep quality than age- and sex-matched patients treated with typical antipsychotic agents, but a higher movement index as recorded by actigraphy than nontreated age- and sexmatched healthy subjects (Dursun et al., 1999). In an open-label trial in patients with dementia, both caregivers and patients rated patients’ sleep as improved in terms of TST and decreased wake time (Duran et al., 2005). Risperidone also improved sleep in SSRI-unresponsive patients with major depression (Ostroff and Nelson, 1999). As with olanzapine, case reports of RLS (Wetter et al., 2002) and sleep-related eating disorder (Lu and Shen, 2004) have been reported. Quetiapine is a new-generation atypical antipsychotic medication that promotes sleep in healthy subjects (Cohrs et al., 2004). In particular, a double-blind placebo-controlled trial (n ¼ 14 men) of acutely administered doses of either 25 or 100 mg taken 1 hour before bedtime significantly increased, when compared to placebo PSG parameters of TST, sleep efficiency, and S2 sleep percentage, while decreasing SOL. Quetiapine also significantly increased subjectively reported sleep time and sleep quality. The 100-mg dose also significantly increased PLMs, but a single case report suggested that quetiapine may be less likely than risperidone and haloperidol to induce PLMs and RLS (Wetter et al., 2002). Open-label trials, case reports, and retrospective reviews of quetiapine treatment without PSG have reported improved sleep in patients with secondary insomnia associated with PD (Juri et al., 2005), schizophrenia (Yamashita et al., 2005), posttraumatic stress disorder (Robert et al., 2005), antidepressant use (Sokolski and Brown, 2006), and chronic pain (Fernando and Chew, 2005).
Anxiolytics (not classified elsewhere) Traditional antianxiety medications (benzodiazepines, barbiturates) are taken to aid sleep and are covered elsewhere in this book as part of the pharmacotherapy of insomnia. Buspirone is a medication indicated for the treatment of generalized anxiety disorder that works through a serotonergic mechanism as a partial agonist
600
D.A. CONROY AND K.J. BROWER
of 5-HT1A receptors. In randomized, double-blind placebo-controlled trials with healthy subjects, buspirone suppressed REM sleep (Ware et al., 1994; Wilson et al., 2005) and increased sleep fragmentation (Wilson et al., 2005). Another study in healthy subjects reported a significant increase in ROL when compared to placebo in adolescents but not adults (Rao et al., 2000). In a single-blind study of anxious patients, buspirone improved subjective sleep quality compared to baseline placebo but had no clinically significant effect on sleep macroarchitecture (De Roeck et al., 1989). In patients with insomnia, buspirone significantly increased WASO on the first of 3 nights and decreased REM percentage in the first third of the night on nights 5–11 when compared to baseline placebo nights (Manfredi et al., 1991).
body temperature in 8 healthy male volunteers. Atenolol (100 mg) alone increased awake time in the night, and decreased SWS and REM sleep when compared to placebo. Atenolol 3 hours before bedtime and then divided doses of melatonin (up to 3 mg) taken across the night reversed these changes (Van den Heuvel et al., 1997). Sedation is a common complaint in patients taking beta-blockers (Obermeyer and Benca, 1996; Novak and Shapiro, 1997; Schweitzer, 2005). To date, no study has quantified the level of daytime sleepiness by using the MSLT. Several studies have investigated psychomotor performance resulting from beta-blockers and found few consistent deficits (Schweitzer, 2005).
Cardiovascular medications
Alpha2 agonists are antihypertensive agents and are sedating in 30–75% of patients (Paykel et al., 1982). Nightmares are also a common complaint in patients taking clonidine and methyldopa (Foral et al., 2003; Schweitzer, 2005). The sedative hypnotic effects of alpha2 agonists are thought to result from inhibition of NE release after binding presynaptic noradrenergic receptors (autoreceptors) in the locus coeruleus section of the brainstem. Clonidine improves subjective sleep in healthy patients. In older hypertensive patients there is an increase in SWS (Foral et al., 2003), S2 sleep (Huynh et al., 2006), and TST (Kanno and Clarenbach, 1985), and a decrease in REM sleep (Foral et al., 2003). A double-blind placebo-controlled study comparing propranolol (20–80 mg bid) and clonidine (0.1–0.3 mg bid) showed that in younger (31–59 years) male hypertensive patients there was decreased TST, prolonged REM latency, and reduced total REM sleep (%) after treatment. In the older (60–78 years) patients, there were no significant effects of clonidine on sleep. Nocturnal penile tumescence was significantly decreased in both groups of patients with each of the study drugs (Kostis et al., 1990). Clonidine has also been associated with objective daytime sleepiness in the day (Carskadon et al., 1989). Clonidine significantly reduced sleep bruxism in affected patients while increasing S2 sleep and decreasing REM sleep (Huynh et al., 2006). Methyldopa is both an alpha-2-agonist and an amino acid decarboxylase enzyme inhibitor that blocks the transformation of DOPA to DA and NE, causing a net decrease in central monoamine neurotransmitter levels. Two studies have shown an increase in TST and SE (Bartel et al., 1997; Foral et al., 2003) on methyldopa and others have found decreased SWS and REM sleep (Foral et al., 2003). No effects on SDB have
ANTIADRENERGIC
MEDICATIONS
Beta-blockers. Beta-blockers primarily act peripherally by blocking adrenergic beta-receptors. Sleep disturbances have been reported in 2.0–4.3% of patients taking beta-blockers (Schweitzer, 2005), likely due to some CNS penetration. These side-effects typically include insomnia, nightmares, vivid dreams, tiredness, and fatigue (McAinsh and Cruickshank, 1990; Foral et al., 2003). Side-effects are more common among lipophilic beta-blockers (e.g., propanolol, timolol), which more easily cross the blood–brain barrier than hydrophilic types (e.g., atenolol, nadolol, carvedilol, and sotalol) (McAinsh and Cruickshank, 1990). The level of affinity for 5-HT receptors (e.g., pindolol), degree of melatonin suppression (e.g., atenolol) and the age of the patient may affect CNS side-effects. The most common PSG finding in patients taking beta-blockers is a suppression of REM sleep (Foral et al., 2003). Metoprolol, pindolol, and atenolol have been shown to decrease sleep continuity (Foral et al., 2003; Schweitzer, 2005). Pindolol is a moderately lipophilic beta-blocker that has a high affinity for 5-HT1A receptors, which are involved in the sleep/ wake-generating system. Healthy, nondepressed males taking pindolol (2.5 mg) were studied with and without paroxetine (20 mg/day). Pindolol alone produced more awake time in the night, a prolonged ROL, and decreased SWS and REM sleep compared to the placebo. Both pindolol and paroxetine reduced REM sleep and SWS more than with either medication alone or placebo (Bell et al., 2003). Atenolol, which is highly hydrophilic and suppresses endogenous melatonin levels, was studied in a partial RCT. Van den Heuvel and colleagues (1997) assessed the effects of atenolol and exogenous melatonin on sleep architecture and
ALPHA2
AGONISTS
ALCOHOL, TOXINS, AND MEDICATIONS AS A CAUSE OF SLEEP DYSFUNCTION been found when combined with a diuretic in hypertensive patients (Bartel et al., 1997). Beta-blockers or alpha-2-agonists may cause some sleep disruption and daytime somnolence. Discontinuation of any one of these medications may not resolve sleep complaints completely and may lead to rebound hypertension and nightmares (Novak and Shapiro, 1997; Cender et al., 1998).
CALCIUM
CHANNEL BLOCKERS
Calcium channel blockers affect the movement of calcium into the cells of the heart and blood vessels which relax blood vessels to increase the supply of blood and oxygen to the heart. While sleep effects of these medications are rare, insomnia has been reported in patients taking felodipine (Foral et al., 2003). Few reports of daytime sleepiness have been reported. To date, no PSG studies have been conducted on calcium channel blockers.
Bronchodilators THEOPHYLLINE As a xanthine, theophylline is related to caffeine and blocks adenosine receptors, but it is used primarily as a respiratory stimulant for the treatment of pulmonary disorders. In healthy subjects, theophylline increases arousals, decreases TST, and worsens sleep quality as compared to placebo (Kaplan et al., 1993), although the effect is dose-related (Roehrs et al., 1995). Theophylline also increases daytime SOL and alertness in healthy subjects. In SDB related to high altitude, an RCT found that theophylline effectively normalized the number of central apneas and hypopneas (Fischer et al., 2004). In mild OSA, theophylline significantly decreased the apnea–hypopnea index compared to placebo, but the authors concluded that the mean decrease was not clinically significant (Hein et al., 2000). Another study of OSA patients demonstrated a significant decrease in apnea–hypopnea index compared to placebo, as well as poorer sleep quality (Mulloy and McNicholas, 1992). After the decrease in apnea– hypopnea index was adjusted for poorer sleep quality, the significant effect remained but was blunted, suggesting that part of the improvement in apnea– hypopnea index was due to poorer sleep quality. In patients with severe chronic obstructive pulmonary disease, theophylline significantly increases arterial oxygen saturation during sleep, but worsens sleep quality (Mulloy and McNicholas, 1993). In patients with nocturnal asthma, theophylline worsened subjectively reported sleep quality compared to placebo, but did not affect sleep architecture or continuity by PSG
601
(Wiegand et al., 1999). In stabilized patients with chronic congestive heart failure, theophylline significantly decreased central (but not obstructive) sleep apneas and hypopneas as well as arousals, and also shortened arterial oxygen desaturation episodes (Hu et al., 2003).
BETA-AGONISTS Beta-2-adrenergic receptor stimulation is associated with wakefulness in animals (Berridge et al., 2005). Most human studies are in patients with asthma. These patients have disturbed sleep when compared to healthy controls even when they are clinically stable (Vir et al., 1997), which may reflect in part the sleepdisrupting effects of bronchodilators. Nevertheless, randomized double-blind trials suggest that the beta2-adrenergic agonists improve the subjective sleep of patients with nocturnal asthma when compared to placebo, due to the reduction of breathing disturbances (Petrie et al., 1993; Kraft et al., 1997; Wiegand et al., 1999; Sears, 2001). In addition, they appear to have minimal effects on sleep architecture (Stewart et al., 1987; Veale et al., 1994; Man et al., 1996; Wiegand et al., 1999); one study reported beneficial effects, including decreased light sleep and increased S4 sleep when patients were treated with salmeterol versus placebo (Fitzpatrick et al., 1990). In female depressed inpatients, clenbuterol had no consistent effects on sleep EEG (Wiegand et al., 1991).
Antihistamines First-generation type 1 histamine receptor antagonists (e.g., diphenhydramine, promethazine, hydroxyzine, and cyproheptadine) easily cross the blood–brain barrier and are associated with CNS side-effects, including drowsiness and EDS. However, second-generation type 1 histamine receptor antagonists (e.g., loratadine and cetirizine), which less easily enter the brain, can also cause EDS and other CNS effects. Diphenhydramine, loratadine, promethazine, and cyproheptadine have all been shown to increase non-REM sleep and to decrease REM sleep (Foral et al., 2003). Diphenhydramine decreases SOL (Cender et al., 1998) and may cause EDS (Schweitzer et al., 1994). Morin et al. (2005) reported on an RCT of diphenhydramine versus a combination of valerian hops. Diphenhydramine (50 mg) significantly increased SE, as measured by sleep diary, and improved sleep, as measured by the Insomnia Severity Index versus placebo. No significant changes in PSG-measured sleep continuity, S1–S4 sleep, and REM sleep were noted. Significant rebound was not observed with diphenhydramine (Morin et al., 2005). Cetirizine decreases SOL, but is not likely to produce EDS (Hutchison et al., 2001). In an RCT,
602
D.A. CONROY AND K.J. BROWER
cetirizine 5–20 mg or hydroxyzine 25 mg was administered to 60 healthy volunteers without sleep complaints. MSLT results and vigilance performance tasks in patients taking cetirizine 5–20 mg did not differ from placebo. Patients taking hydroxyzine were significantly more sedated and had slower reaction times when compared to the placebo group for at least 4 hours after treatment (Seidel et al., 1987). Another study comparing cetirizine (10 mg), diphenhydramine (50 mg tid), and placebo showed that on the first day diphenhydramine (taken at 8:00 a.m., 3:00 p.m., and 10:00 p.m.) caused performance impairments and sleepiness on the MSLT, while cetirizine (taken at 8 a.m.) and placebo did not (Schweitzer et al., 1994). On day 3, performance in the diphenhydramine group matched that of the other groups, suggesting tolerance to the sedating effects of diphenhydramine over time. Likewise, lipophilic antihistamines such as diphenhydramine may cause short-term improvements in sleep. Type 2 histamine receptor antagonists do not easily cross the blood–brain barrier, but insomnia and EDS have been reported in patients taking these medications. A double-blind placebo-controlled crossover study on 12 healthy participants on cimetidine (400 mg bid), famotidine (20 mg bid), or ranitidine (150 mg bid) for 1 week showed a significant reduction in SOL with famotidine, but no significant difference in any sleep stages. MSLT revealed no differences in sleepiness among any of the medications. Patients taking cimetidine were subjectively sleepier than patients taking the other medications (Orr et al., 1994).
Nonsteroidal anti-inflammatory drugs and acetaminophen Nonsteroidal anti-inflamatory drugs (NSAIDs) include both prescription and over-the-counter medications, e.g., ibuprofen and aspirin (acetylsalicylic acid), which block the production of prostaglandins. Prostaglandin D2 is thought to play a role in sleep homeostasis because, when it is administered into the third ventricle in rat brains (Ueno et al., 1983) and the cerebral ventricle of conscious monkeys (Hayaishi et al., 1987), it promotes sleep. Sleep-deprived rats have an increased level of prostaglandin D2 in their cerebrospinal fluid (Ram et al., 1997). Prostaglandins may also interact with the circadian system by mediating the rise in core body temperature, which is governed by the threshold hypothalamic temperature (Horne and Shackell, 1987). When prostaglandins are blocked by aspirin, there is a reduction in the circadian rise of core body temperature (Horne and Shackell, 1987) and therefore there is a reduction in the resultant SWS and S2 sleep (Cender et al., 1998).
In an RCT of the effects of aspirin, ibuprofen, and acetaminophen on sleep, Murphy and colleagues (1994) demonstrated that aspirin and ibuprofen increased the number of awakenings and wake time, and decreased SE. Ibuprofen also decreased SWS and delayed the onset of SWS in the night. Acetaminophen did not significantly disrupt sleep compared to placebo (Murphy et al., 1994). In conclusion, NSAIDs disrupt sleep architecture via their mechanism of inhibition of prostaglandin and reduction of prostaglandin D2 levels. In patients with mild to moderate levels of pain or fever, however, NSAIDs may improve sleep indirectly by reducing the sleep disruption associated with pain and elevated body temperature.
Hormones and synthetic substitutes THYROID-STIMULATING
HORMONE
(TSH)
Endogenous TSH shows a circadian pattern of secretion, with increasing levels across the day and low levels at night. TSH levels decline during sleep, with the greatest inhibition during SWS. During sleep deprivation, TSH levels can be up to double their normal values. Exogenous TSH, liothyronine (T3) or levothyroxine (T4) can be taken orally to treat hypothyroid disease. Thyroxine (150 or 300 mg/kg) does not change the TST or the rate of cycling through sleep stages (Eastman and Rechtschaffen, 1979) in rats. In humans, treatment with oral levothyroxine 50 mg/day increased SWS in hypothyroid males (Jha et al., 2006) and thyroid hormones reversed a marked reduction in SWS in patients with primary myxedema (Ruiz-Primo et al., 1982). Data on the effects of thyroid replacement therapy (TRT) on other objective sleep measures are lacking. The majority of studies over the past several decades in humans have focused on TRT in improving SDB that is associated with hypothyroidism (Strollo et al., 2005). Study findings on TRT to treat SDB have been mixed. OSA patients treated with thyroxine did not demonstrate improvement in SDB in a clinical case report and a controlled clinical trial (Grunstein and Sullivan, 1988; Resta et al., 2005). A more recent study found declines in the apnea–hypopnea index after 7–11 months of treatment with TRT (Jha et al., 2006). In sum, there are few data to suggest that TRT significantly affects objective or subjective sleep. The majority of research to date focuses on the potential benefit of TRT on SDB. Nevertheless, clinicians and patients should be mindful of insomnia related to thyroid hormone (i.e., hyperthyroidism) in the event of an accidental double-dosing or overdose of thyroid replacement medication.
ALCOHOL, TOXINS, AND MEDICATIONS AS A CAUSE OF SLEEP DYSFUNCTION
Anabolic androgenic steroids Anabolic androgenic steroids are used by bodybuilders and athletes in supraphysiological doses, leading to a variety of adverse medical and psychiatric effects (Pope and Brower, 2005). High-dose anabolic androgenic steroids have been associated with both mania and depression, with mania most common during episodes of use, and depression most common during withdrawal. Manic-like symptoms of increased energy and sexual arousal and diminished sleep were observed in a double-blind placebo-controlled study of high-dose methyltestosterone administration to healthy men who did not lift weights; they correlated with increased levels of the 5-HT metabolite, 5-hydroxyindoleacetic acid, in cerebrospinal fluid (Daly et al., 2001). Insomnia during anabolic androgenic steroid withdrawal occurred in 20% of male weightlifters in one study (Brower et al., 1991), although only 4% of users were affected in another study using similar methodology (Midgley et al., 1999). Testosterone can also induce or worsen OSA and increase REM sleep (Sandblom et al., 1983; Matsumoto et al., 1985).
Hormone replacement therapy ESTROGEN
REPLACEMENT THERAPY
(ERT)
Several studies have examined the effects of ERT on sleep in postmenopausal women because sleep disturbance is such a pervasive complaint in this population. PSG studies have revealed overall improvements in sleep continuity and quality of sleep with ERT. Scharf and colleagues (1997) studied PSG in 7 postmenopausal women (ages 45–60 years) before and after taking nightly estrogen (0.625 mg). After 4 weeks, the women showed a decrease in WASO, an increase in SE, a decrease in S1 sleep, an increase in REM sleep, and a decrease in the number of cyclic alternating patterns (a pattern in the EEG correlated to reports of sleep disturbance). Subjective sleep quality improved, as did the number of reported nightly hot flashes (Scharf et al., 1997). These findings, however, were not supported by a later study which showed no significant treatment effects on sleep parameters across the entire night with an estrogen patch (50 mg) (Antonijevic et al., 2000). ERT decreases SOL and number of awakenings associated with restlessness after 3 months of ERT in postmenopausal women (Polo-Kantola et al., 1998). A later study by the same group (Polo-Kantola et al., 1999) found decreases in the frequency of movement-related arousals, but no differences in SOL, SE, or TST in the ERT group when compared to placebo. The alleviation of hot flashes and sweating and the possible reductions in muscle pain, heart palpitations, and anxiety related
603
to the ERT may have led to the sleep improvement (Purdie et al., 1995; Polo-Kantola et al., 1998, 1999).
PROGESTERONE There is little evidence for objective improvements of sleep quality with progesterone and sedation is a common side-effect. In a double-blind, placebo-controlled crossover study, 9 healthy males took micronized progesterone 300 mg 1.5 hours before bedtime. Only male participants were selected for this study to rule out variations in endogenous progesterone secretion. Participants showed a decrease in S2 sleep, latency to SWS, and insignificant decreases in S4 and REM sleep. Power spectral analysis of the EEG revealed a reduction in delta power and an increase in sigma in the first hour of the night (Friess et al., 1997).
COMBINATION
THERAPY
ERT plus progesterone have both beneficial and negligible effects on sleep over time. Postmenopausal women taking estrogen plus oral micronized progesterone 200 mg (Prometrium) for 6 months had significantly greater improvements in SE (from 81% to 89%) and lower WASO (from 86 to 47 minutes) than patients taking estrogen plus medroxyprogesterone acetate 5 mg (Provera). Both groups had improvements in their subjective sleep (Montplaisir et al., 2001). The effects of estrogen plus progestin (0.625 mg) on sleep disturbance were examined in the Women’s Health Initiative clinical trial of 17 000 postmenopausal women. Combination treatment on sleep over 3 years yielded a very small effect size (0.11). However, a subgroup of patients made up of 260 women aged 50–54 years old with moderate to severe vasomotor symptoms at baseline showed significant improvements in sleep disturbance scores compared to the 216 women in the placebo group (Hays et al., 2003). In conclusion, hormone replacement therapy may improve sleep primarily through indirect mechanisms, i.e., through the resolution of hot flashes and sweating rather than through direct effects on the sleep architecture itself. The improvements in the subjective assessment of sleep in postmenopausal women may be more clinically meaningful.
HEAVY METALS Welding fumes are associated with manganese neurotoxicity (Bowler et al., 1999; Josephs et al., 2005). Bowler et al. (1999) grouped fatigue, lack of vigor, and sleep disturbance into one domain, and found that, although only 11 of 15 studies published from 1938 to 1994 assessed this domain, all 11 found disturbances
604
D.A. CONROY AND K.J. BROWER
in this domain, including both insomnia and hypersomnia. A more recent case series of 8 patients with manganese neurotoxicity revealed insomnia, daytime sleepiness, and/or sleep apnea in 2 patients (Josephs et al., 2005). Mercury has also been associated with subjective complaints of sleeplessness (Bose-O’Reilly et al., 2003; Cordeiro et al., 2003). Copper smelters expose people to lead, cadmium, and arsenic (Lilis et al., 1985). A study of 680 copper smelter workers found that sleep disturbances were related to the magnitude of lead absorption as measured by zinc protoporphyrin levels (Lilis et al., 1985). Unfortunately, the nature of the sleep disturbances was not characterized, nor was a control group of unexposed subjects included. A smaller study of 96 lead smelting workers found no difference between lead workers and control subjects in terms of sleeping patterns (Kirkby et al., 1983). Two men who fought a nickel cadmium battery fire and sustained heavy smoke inhalation developed insomnia and other neurotoxic symptoms such as anosmia (Kilburn and McKinley, 1996), associated with elevated urine cadmium and nickel concentrations. Thallium has been used to manufacture some types of cement, resulting in the exposure of cement plant workers and members of the surrounding community. In a study of over 1000 potentially exposed individuals, increasing thallium levels in both urine and hair samples were associated with increasing frequencies of sleep disturbances (Brockhaus et al., 1981). Copper-associated toxicity, as occurs in patients with Wilson’s disease, has been associated with hypersomnia in one case report (Firneisz et al., 2000) and insomnia in one case report (Walter and Lyndon, 1997). In the first case, hypersomnia resolved with chelating agent therapy. In the second case, depressed mood resolved within 3 weeks of chelating agent therapy, but insomnia persisted for up to 3 years.
REFERENCES Aldrich MS, Brower KJ, Hall JM (1999). Sleep-disordered breathing in alcoholics. Alcohol Clin Exp Res 23: 134–140. Allen R, Wagman A, Funderburk F (1977). Slow wave sleep changes: alcohol tolerance and treatment implications. Adv Exp Med Biol 85A: 629–640. Allen R, McCann U, Ricaurte G (1993). Persistent effects of 3,4-methylenedioxymethamphetamine (MDMA, “ecstasy”) on human sleep. Sleep 16: 560–564. Antonijevic I, Stalla G, Steiger A (2000). Modulation of the sleep electroencephalogram by estrogen replacement in postmenopausal women. Am J Obstet Gynecol 182: 277–282. Armitage R, Cole D, Suppes T et al. (2004). Effects of clozapine on sleep in bipolar and schizoaffective disorders. Prog Neuropsychopharmacol Biol Psychiatry 28: 1065–1070.
Arnulf I, Konofal E, Merino-Andreu M et al. (2002). Parkinson’s disease and sleepiness. Neurology 58: 1019–1024. Askenasy J, Yahr M (1985). Reversal of sleep disturbance in Parkinson’s disease by antiparkinsonian therapy. Neurology 35: 527–532. Aslan S, Isik E, Cosar B (2002). The effects of mirtazapine on sleep: a placebo controlled, double-blind study in young healthy volunteers. Sleep 25: 677–679. Backonja MM (1999). Gabapentin monotherapy for the symptomatic treatment of painful neuropathy: a multicenter, double-blind, placebo-controlled trial in patients with diabetes mellitus. Epilepsia 40 (Suppl 6): S57–S59; discussion S73–S74. Balon R (1996). Bupropion and nightmares. Am J Psychiatry 153: 579–580. Balon R, Yeragani VK, Pohl RB et al. (1988). Lithium discontinuation: withdrawal or relapse? Compr Psychiatry 29: 330–334. Bartel P, Loock M, Becker P et al. (1997). Short-term antihypertensive medication does not exacerbate sleepdisordered breathing in newly diagnosed hypertensive patients. Am J Hypertens 10: 640–645. Bazil CW (2003). Effects of antiepileptic drugs on sleep structure: are all drugs equal? CNS Drugs 17: 719–728. Bazil CW, Battista J, Basner RC (2005). Gabapentin improves sleep in the presence of alcohol. J Clin Sleep Med 1: 284–287. Bell C, Vanderlinden H, Hiersemenzel R et al. (2002). The effects of levetiracetam on objective and subjective sleep parameters in healthy volunteers and patients with partial epilepsy. J Sleep Res 11: 255–263. Bell C, Wilson S, Rich A et al. (2003). Effects on sleep architecture of pindolol, paroxetine and their combination in healthy volunteers. Psychopharmacology 166: 102–110. Berridge CW, Stellick RL, Schmeichel BE (2005). Wakepromoting actions of medial basal forebrain beta2 receptor stimulation. Behav Neurosci 119: 743–751. Bertrand B, Jamart J, Marchal J et al. (1996). Cetirizine and pseudoephedrine retard alone and in combination in the treatment of perennial allergic rhinitis: a double-blind multicentre study. Rhinology 34: 91–96. Beydoun A, Uthman BM, Sackellares JC (1995). Gabapentin: pharmacokinetics, efficacy, and safety. Clin Neuropharmacol 18: 469–481. Bhatt M, Podder N, Chokroverty S (2005). Sleep and neurodegenerative diseases. In: K Roos, A Avidan (Eds.), Sleep in Neurological Practice. Thieme Medical Publishers, New York. Billiard M (1987). Lithium carbonate: effects on sleep patterns of normal and depressed subjects and its use in sleep–wake pathology. Pharmacopsychiatry 20: 195–196. Bonanni E, Galli R, Maestri M et al. (2004). Daytime sleepiness in epilepsy patients receiving topiramate monotherapy. Epilepsia 45: 333–337. Bonnet M, Tancer M, Uhde T et al. (2005). Effects of caffeine on heart rate and QT variability during sleep. Depress Anxiety 22: 150–155.
ALCOHOL, TOXINS, AND MEDICATIONS AS A CAUSE OF SLEEP DYSFUNCTION Borsato G, Madrid G, Hicks R (2000). Cigarette Smoking and Sleep Disturbance. Associated Professional Sleep Societies. Sleep, Las Vegas, NV. Bose-O’Reilly S, Drasch G, Beinhoff C et al. (2003). The Mt. Diwata study on the Philippines 2000-treatment of mercury intoxicated inhabitants of a gold mining area with DMPS (2,3-dimercapto-1-propane-sulfonic acid, Dimaval). Sci Total Environ 307: 71–82. Bowler RM, Mergler D, Sassine MP et al. (1999). Neuropsychiatric effects of manganese on mood. Neurotoxicology 20: 367–378. Brockhaus A, Dolgner R, Ewers U et al. (1981). Intake and health effects of thallium among a population living in the vicinity of a cement plant emitting thallium containing dust. Int Arch Occup Environ Health 48: 375–389. Brower KJ (2003). Insomnia, alcoholism and relapse. Sleep Med Rev 7: 523–539. Brower K, Maddahian E, Blow F et al. (1988). A comparison of self reported symptoms and DSM-III-R criteria for cocaine withdrawal. Am J Drug Alcohol Abuse 14: 347–356. Brower K, Blow F, Young J et al. (1991). Symptoms and correlates of anabolic-androgenic steroid dependence. Br J Addict 86: 759–768. Brower KJ, Aldrich MS, Hall JM (1998). Polysomnographic and subjective sleep predictors of alcoholic relapse. Alcohol Clin Exp Res 22: 1864–1871. Brower KJ, Aldrich M, Robinson EAR et al. (2001). Insomnia, self-medication, and relapse to alcoholism. Am J Psychiatry 158: 399–404. Brown LK, Dedrick DL, Doggett JW et al. (2005). Antidepressant medication use and restless legs syndrome in patients presenting with insomnia. Sleep Med 6: 443–450. Campbell SS, Gillin JC, Kripke DF et al. (1989). Lithium delays circadian phase of temperature and REM sleep in a bipolar depressive: a case report. Psychiatry Res 27: 23–29. Carskadon M, Cavallo A, Rosekind M (1989). Sleepiness and nap sleep following a morning dose of clonidine. Sleep 12: 338–344. Cender D, Gelhot A, Phillips B et al. (1998). Daytime drowsiness: is a drug to blame? J Respir Dis 19: 617–629. Chalon S, Pereira A, Lainey E et al. (2005). Comparative effects of duloxetine and desipramine on sleep EEG in healthy subjects. Psychopharmacology (Berl) 177: 357–365. Charney DS, Kales A, Soldatos CR et al. (1979). Somnambulistic-like episodes secondary to combined lithiumneuroleptic treatment. Br J Psychiatry 135: 418–424. Chouinard G, Beauclair L, Belanger MC (1998). Gabapentin: long-term antianxiety and hypnotic effects in psychiatric patients with comorbid anxiety-related disorders [letter]. Can J Psychiatry 43: 305. Chrisp P, Mammen G, Sorkin E (1991). Selegiline. A review of its pharmacology, symptomatic benefits and protective potential in Parkinson’s disease. Drugs Aging 1: 228–248. Clark C, Gillin J, Golshan S et al. (1999). Polysomnography and depressive symptoms in primary alcoholics with and
605
without a lifetime diagnosis of secondary depression and in patients with primary major depression. J Affective Disord 52: 177–185. Cohn T, Foster J, Peters T (2003). Sequential studies of sleep disturbance and quality of life in abstaining alcoholics. Addict Biol 8: 455–462. Cohrs S, Rodenbeck A, Guan Z et al. (2004). Sleep-promoting properties of quetiapine in healthy subjects. Psychopharmacology (Berl) 174: 421–429. Cordeiro QJ, Araujo Medrado DE, Faria M et al. (2003). Depression, insomnia, and memory loss in a patient with chronic intoxication by inorganic mercury. J Neuropsychiatry Clin Neurosci 15: 457–458. Cousens K, Dimascio A (1973). Delta-9-THC as an hypnotic. An experimental study of 3 dose levels. Psychopharmacologia 33: 355–364. Cunningham LA, Borison RL, Carman JS et al. (1994). A comparison of venlafaxine, trazodone, and placebo in major depression. J Clin Psychopharmacol 14: 99–106. Daly R, Su T, Schmidt P et al. (2001). Cerebrospinal fluid and behavioral changes after methyltestosterone administration: preliminary findings. Arch Gen Psychiatry 58: 172–177. Davila D, Hurt R, Offord K et al. (1994). Acute effects of transdermal nicotine on sleep architecture, snoring, and sleep disordered breathing in nonsmokers. Am J Respir Crit Care Med 150: 469–474. Debus JR, Rush AJ, Himmel C et al. (1988). Fluoxetine versus trazodone in the treatment of outpatients with major depression. J Clin Psychiatry 49: 422–426. De Roeck J, Cluydts R, Schotte C et al. (1989). Explorative single-blind study on the sedative and hypnotic effects of buspirone in anxiety patients. Acta Psychiatr Scand 79: 129–135. Drummond S, Gillin J, Smith T et al. (1998). The sleep of abstinent pure primary alcoholic patients: natural course and relationship to relapse. Alcohol Clin Exp Res 22: 1796–1802. Duran JC, Greenspan A, Diago JI et al. (2005). Evaluation of risperidone in the treatment of behavioral and psychological symptoms and sleep disturbances associated with dementia. Int Psychogeriatr 1–14. Dursun SM, Patel JK, Burke JG et al. (1999). Effects of typical antipsychotic drugs and risperidone on the quality of sleep in patients with schizophrenia: a pilot study. J Psychiatry Neurosci 24: 333–337. Eastman C, Rechtschaffen A (1979). Effect of thyroxine on sleep in the rat. Sleep 2: 215–232. Ehrenberg BL, Eisensehr I, Corbett KE et al. (2000). Valproate for sleep consolidation in periodic limb movement disorder. J Clin Psychopharmacol 20: 574–578. Eisensehr I, Ehrenberg BL, Rogge Solti S et al. (2004). Treatment of idiopathic restless legs syndrome (RLS) with slow-release valproic acid compared with slow-release levodopa/benserazid. J Neurol 251: 579–583. Feinberg I, Jones R, Walker J et al. (1975). Effects of high dosage delta-9-tetrahydrocannabinol on sleep patterns in man. Clin Pharmacol Ther 17: 458–466.
606
D.A. CONROY AND K.J. BROWER
Feinberg I, Jones R, Walker J et al. (1976). Effects of marijuana extract and tetrahydrocannabinol on electroencephalographic sleep patterns. Clin Pharmacol Ther 19: 782–794. Fernando A, Chew G (2005). Chronic insomnia secondary to chronic pain responding to quetiapine. Australas Psychiatry 13: 86. Firneisz G, Szalay F, Halasz P et al. (2000). Hypersomnia in Wilson’s disease: an unusual symptom in an unusual case. Acta Neurol Scand 101: 286–288. Fischer R, Lang SM, Leitl M et al. (2004). Theophylline and acetazolamide reduce sleep-disordered breathing at high altitude. Eur Respir J 23: 47–52. Fitzpatrick MF, Mackay T, Driver H et al. (1990). Salmeterol in nocturnal asthma: a double blind, placebo controlled trial of a long acting inhaled beta 2 agonist. BMJ 301: 1365–1368. Foldvary-Schaefer N, De Leon Sanchez I, Karafa M et al. (2002). Gabapentin increases slow-wave sleep in normal adults. Epilepsia 43: 1493–1497. Food and Drug Administration (2005). PhenylpropanolamineContaining Drug Products for Over-the-Counter Human Use; Tentative and Final Monographs. Department of Health and Human Services. National Archives and Records Administration NARA, Washington DC. Foral PA, Malesker MA, Hopkins H (2003). Medication effects on sleep. In: TJ Bowman (Ed.), Review of Sleep Medicine. Butterworth Heinemann, Burlington, MA. Freemon F (1974). The effect of delta-9-tetrahydrocannabinol on sleep. Psychopharmacology 35: 39–44. Freemon F (1982). The effect of chronically administered delta-9-tetrahydrocannabinol upon the polygraphically monitored sleep of normal volunteers. Drug Alcohol Depend 10: 345–353. Friess E, Tagaya H, Trachsel L et al. (1997). Progesteroneinduced changes in sleep in male subjects. Am J Physiol Endocrinol Metab 272: E885–E891. Friston KJ, Sharpley AL, Solomon RA et al. (1989). Lithium increases slow wave sleep: possible mediation by brain 5-HT2 receptors? Psychopharmacology (Berl) 98: 139–140. Frucht S, Rogers J, Greene P (1999). Falling asleep at the wheel: motor vehicle mishaps in persons taking pramipexole and ropinirole. Neurology 52: 1908–1910. Frucht S, Greene P, Fahn S (2000). Sleep episodes in Parkinson’s disease: a wake-up call. Mov Disord 15: 601–603. Garcia-Borreguero D, Larrosa O, De La Llave Y et al. (2002). Treatment of restless legs syndrome with gabapentin. A double-blind, cross-over study. Neurology 59: 1573–1579. Gillin J, Drummond S, Clark C et al. (2005). Medication and substance abuse. In: M Kryger, T Roth, WC Dement (Eds.), Principles and Practice of Sleep Medicine. 4th edn. Elsevier Saunders, Philadelphia. Goldstein DJ, Lu Y, Detke MJ et al. (2004). Duloxetine in the treatment of depression: a double-blind placebocontrolled comparison with paroxetine. J Clin Psychopharmacol 24: 389–399. Gossop M, Bradley B, Brewis R (1982). Amphetamine withdrawal and sleep disturbance. Drug Alcohol Depend 10: 177–183.
Gothe B, Strohl K, Levin S et al. (1985). Nicotine: a different approach to treatment of obstructive sleep apnea. Chest 87: 11–17. Grace R (2003). The effects of variable-dose diazepam on dreaming and emergence phenomena in 400 cases of ketamine-fentanyl anaesthesia. Anaesthesia 58: 904–910. Grunstein R, Sullivan C (1988). Sleep apnea and hypothyroidism: mechanisms and management. Am J Med 85: 775–779. Guelfi JD, Ansseau M, Timmerman L et al. (2001). Mirtazapine versus venlafaxine in hospitalized severely depressed patients with melancholic features. J Clin Psychopharmacol 21: 425–431. Guilleminault C (1980). Sleep apnea syndromes: impact of sleep and sleep states. Sleep 3: 227–234. Hajak G, Rodenbeck A, Voderholzer U et al. (2001). Doxepin in the treatment of primary insomnia: a placebo-controlled, double-blind, polysomnographic study. J Clin Psychiatry 62: 453–463. Hamner MB, Brodrick PS, Labbate LA (2001). Gabapentin in PTSD: a retrospective, clinical series of adjunctive therapy. Ann Clin Psychiatry 13: 141–146. Hasegawa Y, Emori K, Suzuki M et al. (2004). Restless legs syndrome successfully treated with trazodone. Sleep and Biological Rhythms 2: 65–66. Hayaishi O, Ueno R, Onoe H et al. (1987). Prostaglandin D2 induces sleep when infused into the cerebral ventricle of conscious monkeys. Adv Prostaglandin Thromboxane Leukot Res 17B: 946–948. Hays J, Ockene J, Brunner R et al. (2003). Effects of estrogen plus progestin on health-related quality of life. N Engl J Med 348: 1839–1854. Hein H, Behnke G, Jorres RA et al. (2000). The therapeutic effect of theophylline in mild obstructive sleep apnea/ hypopnea syndrome: results of repeated measurements with portable recording devices at home. Eur J Med Res 5: 391–399. Hening W, Allen R, Walters A et al. (1999). Motor functions and dysfunctions of sleep. In: S Chokroverty, R Daroff (Eds.), Sleep Disorders Medicine: Basic Science, Technical Considerations, and Clinical Aspects. ButterworthHeinemann, Woburn. Hicks JA, Argyropoulos SV, Rich AS et al. (2002). Randomised controlled study of sleep after nefazodone or paroxetine treatment in out-patients with depression. Br J Psychiatry 180: 528–535. Hindmarch I, Dawson J, Stanley N (2005). A double-blind study in healthy volunteers to assess the effects on sleep of pregabalin compared with alprazolam and placebo. Sleep 28: 187–193. Hinze-Selch D, Mullington J, Orth A et al. (1997). Effects of clozapine on sleep: a longitudinal study. Biol Psychiatry 42: 260–266. Hollister LE (2001). Marijuana (cannabis) as medicine. Journal of Cannabis Therapeutics 1: 5–27. Horne J, Shackell B (1987). Slow wave sleep elevations after body heating: proximity to sleep and effects of aspirin. Sleep 10: 383–392.
ALCOHOL, TOXINS, AND MEDICATIONS AS A CAUSE OF SLEEP DYSFUNCTION Hu K, Li Q, Yang J et al. (2003). The effect of theophylline on sleep-disordered breathing in patients with stable chronic congestive heart failure. Chin Med J (Engl) 116: 1711–1716. Hutchison T, Shahan D, Anderson M (2001). Drugdex System. Micromedex, Englewood, CO. Huynh N, Lavigne G, Lanfranchi P et al. (2006). The effect of 2 sympatholytic medications – propranolol and clonidine – on sleep bruxism: experimental randomized controlled studies. Sleep 29: 307–316. Issa F, Sullivan C (1982). Alcohol, snoring and sleep apnea. J Neurol Neurosurg Psychiatry 45: 353–359. Jacobsen FM (1990). Low-dose trazodone as a hypnotic in patients treated with MAOIs and other psychotropics: a pilot study. J Clin Psychiatry 51: 298–302. Jansen K (1999). Ecstasy (MDMA) dependence. Drug Alcohol Depend 53: 121–124. Jha A, Sharma S, Tandon N et al. (2006). Thyroxine replacement therapy reverses sleep-disordered breathing in patients with primary hypothyroidism. Sleep Med 55–61. Johanson C, Roehrs T, Schuh K et al. (1999). The effects of cocaine on mood and sleep in cocaine-dependent males. Exp Clin Psychopharmacol 7: 338–346. Josephs KA, Ahlskog JE, Klos KJ et al. (2005). Neurologic manifestations in welders with pallidal MRI T1 hyperintensity. Neurology 64: 2033–2039. Juri C, Chana P, Tapia J et al. (2005). Quetiapine for insomnia in Parkinson disease: results from an open-label trial. Clin Neuropharmacol 28: 185–187. Kanno O, Clarenbach P (1985). Effects of clinidine and yohimbine on sleep in man: polygraphic study and EEG analysis by normalized slope descriptors. Electroencephalogr Clin Neurophysiol 60: 478–484. Kaplan J, Fredrickson PA, Renaux SA et al. (1993). Theophylline effect on sleep in normal subjects. Chest 103: 193–195. Karam-Hage M, Brower KJ (2000). Gabapentin treatment for insomnia associated with alcohol dependence [letter]. Am J Psychiatry 157: 151. Karam-Hage M, Brower KJ (2003). Open pilot study of gabapentin versus trazodone to treat insomnia in alcoholic outpatients. Psychiatry Clin Neurosci 57: 542–544. Kay D (1975). Human sleep and EEG through a cycle of methadone dependence. Electroencephalogr Clin Neurophysiol 38: 35–43. Kay D, Einstein R, Jasinski D (1969). Morphine effects on human REM state, waking state and NREM sleep. Psychopharmacologia 14. Kaynak H, Kaynak D, Gozukirmizi E et al. (2004). The effects of trazodone on sleep in patients treated with stimulant antidepressants. Sleep Med 5: 15–20. Kernan W, Viscoli C, Brass L et al. (2000). Phenylpropanolamine and the risk of hemorrhagic stroke. N Engl J Med 343: 1826–1832. Ketter TA, Malow BA, Flamini R et al. (1996). Felbamate monotherapy has stimulant-like effects in patients with epilepsy. Epilepsy Res 23: 129–137. Kilburn KH, Mckinley KL (1996). Persistent neurotoxicity from a battery fire: is cadmium the culprit? South Med J 89: 693–698.
607
Kirkby H, Nielsen CJ, Nielsen VK et al. (1983). Subjective symptoms after long term lead exposure in secondary lead smelting workers. Br J Ind Med 40: 314–317. Klein E, Mairaz R, Pascal M et al. (1991). Discontinuation of lithium treatment in remitted bipolar patients: relationship between clinical outcome and changes in sleep–wake cycles. J Nerv Ment Dis 179: 499–501. Kostis J, Rosen R, Holzer B et al. (1990). CNS side effects of centrally-active antihypertensive agents: a prospective, placebo-controlled study of sleep, mood state, and cognitive and sexual function in hypertensive males. Psychopharmacology 102: 163–170. Kowatch R, Schnoll S, Knisely J et al. (1992). Electroencephalographic sleep and mood during cocaine withdrawal. Journal of Addictive Disorders 11: 21–45. Kraft M, Wenzel SE, Bettinger CM et al. (1997). The effect of salmeterol on nocturnal symptoms, airway function, and inflammation in asthma. Chest 111: 1249–1254. Kraus T, Schuld A, Pollmacher T (1999). Periodic leg movements in sleep and restless legs syndrome probably caused by olanzapine. J Clin Psychopharmacol 19: 478–479. LaJambe C, Kamimori G, Belenky G et al. (2005). Caffeine effects on recovery sleep following 27 h total sleep deprviation. Aviat Space Environ Med 76: 108–113. Lake C, Rosenberg D, Gallant S et al. (1990). Phenylpropanolamine increases plasma caffeine levels. Clin Pharmacol Ther 47: 675–685. Lammers G, Arends J, Declereck A et al. (1993). Gammahydroxybutyrate and narcolepsy: a double-blind placebo controlled study. Sleep 16. Landolt HP, Raimo EB, Schnierow BJ et al. (2001). Sleep and sleep electroencephalogram in depressed patients treated with phenelzine. Arch Gen Psychiatry 58: 268–276. Landolt H, Retey J, Tonz K et al. (2004). Caffeine attenuates waking and sleep electroencephalographic markers of sleep homeostasis in humans. Neuropsychopharmacology 29: 1933–1939. Landry P, Warnes H, Nielsen T et al. (1999). Somnambulisticlike behaviour in patients attending a lithium clinic. Int Clin Psychopharmacol 14: 173–175. Larsen J, Tanberg E (2001). Sleep disorders in patients with Parkinson’s disease: epidemiology and management. CNS Drugs 15: 267–275. Le Bon O, Murphy JR, Staner L et al. (2003). Double-blind, placebo-controlled study of the efficacy of trazodone in alcohol post-withdrawal syndrome: polysomnographic and clinical evaluations. J Clin Psychopharmacol 23: 377–383. Leeman A, O’Neill C, Nicholson P (1987). Parkinson’s disease in the elderly: response to and optimal spacing of night time dosing with levodopa. Br J Pharmacol 24. Legros B, Bazil CW (2003). Effects of antiepileptic drugs on sleep architecture: a pilot study. Sleep Med 4: 51–55. Lemon M, Strain J, Farver D (2006). Sodium oxybate for cataplexy. Ann Pharmacother 40: 433–440. Leppik IE (1995). Felbamate. Epilepsia 36 (Suppl 2): S66–S72. Lilis R, Valciukas JA, Weber JP et al. (1985). Effects of lowlevel lead and arsenic exposure on copper smelter workers. Arch Environ Health 40: 38–47.
608
D.A. CONROY AND K.J. BROWER
Lu ML, Shen WW (2004). Sleep-related eating disorder induced by risperidone. J Clin Psychiatry 65: 273–274. Luthringer R, Toussaint M, Schaltenbrand N et al. (1996). A double-blind, placebo-controlled evaluation of the effects of orally administered venlafaxine on sleep in inpatients with major depression. Psychopharmacol Bull 32: 637–646. Lydic R, Baghdoyan H (2002). Ketamine and MK-801 decrease acetylcholine release in the pontine reticular formation, slow breathing, and disrupt sleep. Sleep 25: 615–620. MacLean A, Cairns J (1982). Dose response effects on ethanol on the sleep of young men. J Stud Alcohol 43: 434–444. Maixner S, Tandon R, Eiser A et al. (1998). Effects of antipsychotic treatment on polysomnographic measures in schizophrenia: a replication and extension. Am J Psychiatry 155: 1600–1602. Mamelak M, Black J, Montplaisir J et al. (2004). A pilot study on the effects of sodium oxybate on sleep architecture and daytime alertness in narcolepsy. Sleep 27: 1327–1334. Man GC, Champman KR, Ali SH et al. (1996). Sleep quality and nocturnal respiratory function with once-daily theophylline (Uniphyl) and inhaled salbutamol in patients with COPD. Chest 110: 648–653. Manfredi RL, Kales A, Vgontzas AN et al. (1991). Buspirone: sedative or stimulant effect? Am J Psychiatry 148: 1213–1217. Mann K, Rossbach W, Muller MJ et al. (2004). Heart rate variability during sleep in patients with schizophrenia treated with olanzapine. Int Clin Psychopharmacol 19: 325–330. Mathias S, Wetter TC, Steiger A et al. (2001). The GABA uptake inhibitor tiagabine promotes slow wave sleep in normal elderly subjects. Neurobiol Aging 22: 247–253. Matsumoto AM, Sandblom RE, Schoene RB et al. (1985). Testosterone replacement in hypogonadal men: effects on obstructive sleep apnoea, respiratory drives, and sleep. Clin Endocrinol (Oxf) 22: 713–721. Mayers AG, Baldwin DS (2005). Antidepressants and their effect on sleep. Hum Psychopharmacol 20: 533–559. McAinsh J, Cruickshank J (1990). Beta-blockers and central nervous system side effects. Pharmacol Ther 46: 163–197. McGregor C, Srisurapanont M, Jittiwutikarn J et al. (2005). The nature, time course and severity of methamphetamine withdrawal. Addiction 100: 1320–1329. Metz A, Shader R (1990). Adverse interactions encountered when using trazodone to treat insomnia associated with fluoxetine. Int Clin Psychopharmacol 5: 191–194. Midgley SJ, Heather N, Davies JB (1999). Dependence producing potential of anabolic-androgenic steroids. Addict Res 7: 539–550. Mitler M, Dawson A, Henriksen S et al. (1988). Bedtime ethanol increases resistance of upper airways and produces sleep apneas in asymptomatic snorers. Alcohol Clin Exp Res 12: 801–805. Montgomery SA (1992). The advantages of paroxetine in different subgroups of depression. Int Clin Psychopharmacol 6 (Suppl 4): 91–100.
Montgomery I, Oswald I, Morgan K et al. (1983). Trazodone enhances sleep in subjective quality but not in objective duration. Br J Clin Pharmacol 16: 139–144. Monti JM, Monti D (2004). Sleep in schizophrenia patients and the effects of antipsychotic drugs. Sleep Med Rev 8: 133–148. Montplaisir J, Lorrain J, Denesle R et al. (2001). Sleep in menopause: differential effects of two forms of hormone replacement therapy. Menopause 8: 10–16. Morin C, Koetter U, Bastien C et al. (2005). Valerian-hops and diphenhydramine for treating insomnia: a randomized placebo-controlled clinical trial. Sleep 28: 1465–1471. Mouret J, Lemoine P, Minuit MP et al. (1988). Effects of trazodone on the sleep of depressed subjects – a polygraphic study. Psychopharmacology 95: S37–S43. Muller MJ, Rossbach W, Mann K et al. (2004). Subchronic effects of olanzapine on sleep EEG in schizophrenic patients with predominantly negative symptoms. Pharmacopsychiatry 37: 157–162. Mulloy E, McNicholas WT (1992). Theophylline in obstructive sleep apnea. A double-blind evaluation. Chest 101: 753–757. Mulloy E, McNicholas WT (1993). Theophylline improves gas exchange during rest, exercise, and sleep in severe chronic obstructive pulmonary disease. Am Rev Respir Dis 148: 1030–1036. Murphy P, Badia P, Myers B et al. (1994). Nonsteroidal antiinflammatory drugs affect normal sleep patterns in humans. Physiol Behav 55: 1063–1066. National Institute on Drug Abuse (NIDA) (2005a). Cocaine Effects. National Institutes of Health, Bethesda, MD. National Institute on Drug Abuse (NIDA) (2005b). What is nicotine? Research Report Series – Nicotine Addiction. National Institutes of Health, Bethesda, MD. National Sleep Foundation (2005). Sleep in America Poll. National Sleep Foundation, Washington DC. Nausieda P, Glantz R, Weber S (1984). Psychiatric complications of levodopa therapy of Parkinson’s disease. Adv Neurol 40: 271–277. Nicholson A, Turner C, Stone B et al. (2004). Effect of delta-9-tetrahydrocannabinol and cannabidiol on nocturnal sleep and early morning behavior in young adults. J Clin Psychopharmacol 24: 305–313. Nierenberg AA, Adler LA, Peselow E et al. (1994). Trazodone for antidepressant-associated insomnia. Am J Psychiatry 151: 1069–1072. Nofzinger E, Van Kammen D, Gilbertson M et al. (1993). Electroencephalographic sleep in clinically stable schizophrenic patients: two-weeks versus six-weeks neurolepticfree. Biol Psychiatry 33: 829–835. Nofzinger EA, Reynolds CFR, Thase ME et al. (1995). REM sleep enhancement by bupropion in depressed men. Am J Psychiatry 152: 274–276. Nofzinger EA, Fasiczka A, Berman S et al. (2000). Bupropion SR reduces periodic limb movements associated with arousals from sleep in depressed patients with periodic limb movement disorder. J Clin Psychiatry 61: 858–862.
ALCOHOL, TOXINS, AND MEDICATIONS AS A CAUSE OF SLEEP DYSFUNCTION Nofzinger EA, Berman S, Fasiczka A et al. (2001). Effects of bupropion SR on anterior paralimbic function during waking and REM sleep in depression: preliminary findings using. Psychiatry Res 106: 95–111. Nolen WA, Haffmans PM, Bouvy PF et al. (1993). Monoamine oxidase inhibitors in resistant major depression. A double-blind comparison of brofaromine and tranylcypromine in patients resistant to tricyclic antidepressants. J Affect Disord 28: 189–197. Novak M, Shapiro C (1997). Drug induced sleep disturbances. Drug Safety 16: 133–148. Nowell PD, Reynolds CFR, Buysse DJ et al. (1999). Paroxetine in the treatment of primary insomnia: preliminary clinical and electroencephalogram sleep data. J Clin Psychiatry 60: 89–95. Obermeyer W, Benca R (1996). Effects of drugs on sleep. Neurol Clin 14: 827–840. Oga K, Kojima T, Matsuura M et al. (2002). Effects of low-dose ketamine on neuropathic pain: an electroencephalogramelectrooculogram/behavioral study. Psychiatry Clin Neurosci 56: 355–363. Olanow C, Schapira A, Roth T (2000). Falling asleep at the wheel: motor vehicle mishaps in people taking pramipexole and ropinirole [letter]. Neurology 54: 274–277. Orr W, Duke J, Imes N et al. (1994). Comparative effects of H2-receptor antagonists on subjective and objective assessment of sleep. Aliment Pharmacol Ther 8: 203–207. Ostroff RB, Nelson JC (1999). Risperidone augmentation of selective serotonin reuptake inhibitors in major depression. J Clin Psychiatry 60: 256–259. O’Suilleabhain P, Dewey RJ (2002). Contributions of dopaminergic drugs and disease severity to daytime sleepiness in Parkinson’s disease. Arch Neurol 59: 986–989. Oswald I, Adam K (1986). Effects of paroxetine on human sleep. Br J Clin Pharmacol 22: 97–99. Ott GE, Rao U, Lin KM et al. (2004). Effect of treatment with bupropion on EEG sleep: relationship to antidepressant response. Int J Neuropsychopharmacol 7: 275–281. Pace-Schott E, Stickgold R, Mazur A et al. (2005). Sleep quality deteriorates over a binge–abstinence cycle in chronic smoked cocaine users. Psychopharmacology 179: 873–883. Paquet V, Strul J, Servais L et al. (2002). Sleep-related eating disorder induced by olanzapine. J Clin Psychiatry 63: 597. Parrino L, Spaggiari MC, Boselli M et al. (1994). Clinical and polysomnographic effects of trazodone CR in chronic insomnia associated with dysthymia. Psychopharmacology 116: 389–395. Parrott A (2001). Human psychopharmacology of ecstasy (MDMA): a review of 15 years of empirical research. Hum Psychopharmacol 16: 557–577. Paus S, Brecht H, Koster J et al. (2003). Sleep attacks, daytime sleepiness, and dopamine agonists in Parkinson’s disease. Mov Disord 18. Paykel E, Fleminger R, Watson J (1982). Psychiatric side effects of antihypertensive drugs other than reserpine. J Clin Psychopharmacology 2: 14–39.
609
Perez Bravo A (2004). [Topiramate use as treatment in restless legs syndrome.]. Actas Esp Psiquiatr 32: 132–137. Petrie GR, Chookang JY, Hassan WU et al. (1993). Bambuterol: effective in nocturnal asthma. Respir Med 87: 581–585. Phillips B, Danner F (1995). Cigarette smoking and sleep disturbance. Arch Intern Med 155: 734–737. Pivik R, Zarcone V, Dement W et al. (1972). Delta-9-tetrahydrocannabinol and synhexyl; effects on human sleep patterns. Clin Pharmacol Ther 13: 426–435. Placidi F, Scalise A, Marciani MG et al. (2000). Effect of antiepileptic drugs on sleep. Clin Neurophysiol 111 (Suppl 2): S115–S119. Polo-Kantola P, Erkkola R, Helenius H et al. (1998). When does estrogen replacement therapy improve sleep quality? Am J Obstet Gynecol 178: 1002–1009. Polo-Kantola P, Erkkola R, Irjala K et al. (1999). Effect of short-term transdermal estrogen replacement therapy on sleep: a randomized, double-blind crossover trial in postmenopausal women. Fertil Steril 71: 873–880. Pope HJ, Brower K (2005). Anabolic-Androgenic Steroid Abuse. Williams & Wilkins, Baltimore. Prosise G, Bonnet M, Berry R et al. (1994). Effects of abstinence from smoking on sleep and daytime sleepiness. Chest 105: 1136–1141. Purdie D, Empson J, Crichton C et al. (1995). Hormone replacement therapy, sleep quality and psychological wellbeing. Br J Obstet Gynaecol 102: 735–739. Ram A, Pandey H, Matsumura H et al. (1997). CSF levels of prostaglandins, especially level of prostaglandin D2, are correlated with increasing propensity towards sleep in rats. Brain Res 1997: 81–89. Rangaswamy M, Porjesz B, Chorlian D et al. (2004). Resting EEG in offspring of male alcoholics: beta frequencies. Int J Psychophysiol 51: 239–251. Rao ML, Clarenbach P, Vahlensieck M et al. (1988). Gabapentin augments whole blood serotonin in healthy young men. J Neural Transm 73: 129–134. Rao U, Lutchmansingh P, Poland RE (2000). Contribution of development to buspirone effects on REM sleep: a preliminary report. Neuropsychopharmacology 22: 440–446. Regnell G, Widerlov E, Ekman R (1988). Delta sleepinducing peptide in CSF of patients with affective illness is elevated by lithium treatment. Biol Psychiatry 24: 112–116. Resta O, Carratu P, Carpagnano G et al. (2005). Influence of subclinical hypothyroidism and T4 treatment on the prevalence and severity of obstructive sleep apnea syndrome (OSAS). J Endocrinol Invest 28: 893–898. Ricaurte G, McCann U (2001). Experimental studies on 3, 4-methylenedioxymethamphetamine (MDA, “ectasy”) and its potential to damage brain serotonin neurons. Neurotox Res 3: 85–99. Ridout F, Meadows R, Johnsen S et al. (2003). A placebo controlled investigation into the effects of paroxetine and mirtazapine on measures related to car driving performance. Hum Psychopharmacol 18: 261–269. Riedel B, Durrence H, Lichstein K et al. (2004). The relation between smoking and sleep: the influence of smoking
610
D.A. CONROY AND K.J. BROWER
level, health, and psychological variables. Behav Sleep Med 2: 63–78. Riemann D, Voderholzer U, Cohrs S et al. (2002a). Trimipramine in primary insomnia: results of a polysomnographic double-blind controlled study. Pharmacopsychiatry 35: 165–174. Riemann DW, Feige B, Weske G et al. (2002b). Sleep in alcohol dependent patients during acute and subacute withdrawal. Sleep 25 (Abstract Suppl): A267. Robert S, Hamner MB, Kose S et al. (2005). Quetiapine improves sleep disturbances in combat veterans with PTSD: sleep data from a prospective, open-label study. J Clin Psychopharmacol 25: 387–388. Roehrs T, Zwyghuizen-Doorenbos A, Knox M et al. (1992). Sedating effects of ethanol and time of drinking. Alcohol Clin Exp Res 16: 553–557. Roehrs T, Merlotti L, Haplin D et al. (1995). Effects of theophylline on nocturnal sleep and daytime sleepiness/alertness. Chest 108: 382–387. Roehrs T, Papineau K, Rosenthal L et al. (1999). Ethanol as a hypnotic in insomniacs: self administration and effects on sleep and mood. Neuropsychopharmacology. 20: 279–286. Rosenberg KP (2003). Gabapentin for chronic insomnia. Am J Addict 12: 273–274. Roth T, Wright KPJ, Walsh J (2006). Effect of tiagabine on sleep in elderly subjects with primary insomnia: a randomized, double-blind, placebo-controlled study. Sleep 29: 335–341. Ruigt GS, Kemp B, Groenhout CM et al. (1990). Effect of the antidepressant Org 3770 on human sleep. Eur J Clin Pharmacol 38: 551–554. Ruiz-Primo E, Jurado J, Solis H et al. (1982). Polysomnographic effects of thyroid hormones primary myxedema. Electroencephalogr Clin Neurophysiol 53: 559–564. Rundell OH, Williams HL, Lester BK (1977). Sleep in alcoholic patients: longitudinal findings. Adv Exp Med Biol 85B: 389–402. Rush AJ, Giles D, Jarrett R et al. (1989). Reduced REM latency predicts response to tricyclic medication in depressed outpatients. Biol Psychiatry 26: 61–72. Rush A, Armitage R, Gillin J et al. (1998). Comparative effects of nefazodone and fluoxetine on sleep in outpatients with major depressive disorder. Biol Psychiatry 44: 3–14. Rye D, Jankovic J (2002). Emerging views of dopamine in modulating sleep/wake state from an unlikely source: PD. Neurology 58: 341–346. Rye D, Bliwise D, Dihenia B et al. (2000). Daytime sleepiness in Parkinson’s disease. J Sleep Res 9: 63–69. Saletu B, Prause W, Anderer P et al. (2005). Insomnia in somatoform pain disorder: sleep laboratory studies on differences to controls and acute effects of trazodone, evaluated by the Somnolyzer 24 7 and the Siesta database. Neuropsychobiology 51: 148–163. Salin-Pascual R, De La Fuente J, Galicia-Polo L et al. (1995). Effects of transdermal nicotine on mood and sleep in nonsmoking major depressed patients. Psychopharmacology (Berl) 121: 476–479.
Salin-Pascual RJ, Galicia-Polo L, Drucker-Colin R (1997). Sleep changes after 4 consecutive days of venlafaxine administration in normal volunteers. J Clin Psychiatry 58: 348–350. Salin-Pascual RJ, Herrera-Estrella M, Galicia-Polo L et al. (1999). Olanzapine acute administration in schizophrenic patients increases delta sleep and sleep efficiency. Biol Psychiatry 46: 141–143. Sandblom RE, Matsumoto AM, Schoene RB et al. (1983). Obstructive sleep apnea syndrome induced by testosterone administration. N Engl J Med 308: 508–510. Scammell TE (2003). The neurobiology, diagnosis, and treatment of narcolepsy. Ann Neurol 53: 154–166. Scammell TE, Matheson J (1998). Modafinil: a novel stimulant for the treatment of narcolepsy. Expert Opin Investig Drugs 7: 99–112. Scharf MB, Sachais BA (1990). Sleep laboratory evaluation of the effects and efficacy of trazodone in depressed insomniac patients. J Clin Psychiatry 51: 13–17. Scharf M, Mcdannold M, Stover R et al. (1997). Effects of estrogen replacement therapy on rates of cyclic alternating patterns and hot-flush events during sleep in postmenopausal women: a pilot study. Clin Ther 19: 304–311. Schatzberg AF, Kremer C, Rodrigues HE et al. (2002). Double-blind, randomized comparison of mirtazapine and paroxetine in elderly depressed patients. Am J Geriatr Psychiatry 10: 541–550. Schwartz J (2005). Modafinil: new indications for wake promotion. Expert Opin Pharmacother 6: 115–129. Schweitzer P (2005). Drugs that disturb sleep and wakefulness. In: M Kryger, T Roth, W Dement (Eds.), Principles and Practice of Sleep Medicine. Elsevier Saunders, Philadelphia. Schweitzer P, Muehlbach M, Walsh J (1994). Sleepiness and performance during three -day administration of certirizine or diphenhydramine. J Allergy Clin Immunol 94: 716–724. Sears MR (2001). The evolution of beta2-agonists. Respir Med 95 (Suppl B): S2–S6. Seidel W, Cohen S, Bliwise N et al. (1987). Cetirizine effects on objective measures of daytime sleepiness and performance. Ann Allergy 59: 58–62. Sharpley AL, Williamson DJ, Attenburrow MEJ et al. (1996). The effects of paroxetine and nefazodone on sleep: a placebo controlled trial. Psychopharmacology 126: 50–54. Sharpley AL, Vassallo CM, Cowen PJ (2000). Olanzapine increases slow-wave sleep: evidence for blockade of central 5-HT(2C) receptors in vivo. Biol Psychiatry 47: 468–470. Sharpley AL, Attenburrow ME, Hafizi S et al. (2005). Olanzapine increases slow wave sleep and sleep continuity in SSRI-resistant depressed patients. J Clin Psychiatry 66: 450–454. Skoloda T, Alterman A, Gottheil E (1979). Sleep Quality Reported by Drinking and Non-Drinking Alcoholics. Pergamon Press, Elmsford, NY. Sokolski KN, Brown BJ (2006). Quetiapine for insomnia associated with refractory depression exacerbated by phenelzine. Ann Pharmacother 40: 567–570.
ALCOHOL, TOXINS, AND MEDICATIONS AS A CAUSE OF SLEEP DYSFUNCTION Soldatos C, Kales J, Scharf M et al. (1980). Cigarette smoking associated with sleep difficulties. Science 207: 551–552. Sonntag A, Rothe B, Guldner J et al. (1996). Trimipramine and imipramine exert different effects on the sleep EEG and on nocturnal hormone secretion during treatment of major depression. Depression 4: 1–13. Sorelle R (2000). FDA warns of stroke risk associated with phenylpropanolamine: cold remedies and drugs removed from store shelves. Circulation 102: e9041. Staedt J, Wassmuth F, Stoppe G (1996a). Effects of chronic treatment with methadone and naltrexone on sleep in addicts. Eur Arch Psychiatry Clin Neurosci 246: 305–309. Staedt J, Stoppe G, Hajak G et al. (1996b). Rebound insomnia after abrupt clozapine withdrawal. Eur Arch Psychiatry Clin Neurosci 246: 79–82. Staner L, Kerkhofs M, Detroux D et al. (1995). Acute, subchronic and withdrawal sleep EEG changes during treatment with paroxetine and amitriptyline: a double-blind randomized trial in major depression. Sleep 18: 470–477. Stewart IC, Rhind GB, Power JT et al. (1987). Effect of sustained release terbutaline on symptoms and sleep quality in patients with nocturnal asthma. Thorax 42: 797–800. Stimmel G, Dopheide J, Stahl S (1997). Mirtazapine: an antidepressant with noradrenergic and specific serotonergic effects. Pharmacotherapy 17: 10–21. Strollo P, Atwood C, Sanders M (2005). Medical therapy for obstructive sleep apnea-hypopnea syndrome. In: M Kryger, T Roth, W Dement (Eds.), Principles and Practice of Sleep Medicine. Elsevier, Philadelphia. Taasan V, Block A, Boysen B et al. (1981). Alcohol increases sleep apnea and oxygen desaturation in asymptomatic men. Am J Med 71: 240–245. Taylor SF, Tandon R, Shipley JE et al. (1991). Effect of neuroleptic treatment on polysomnographic measures in schizophrenia. Biol Psychiatry 30: 904–912. Teichtahl H, Prodromidis A, Miller B et al. (2001). Sleepdisordered breathing in stable methadone programme patients: a pilot study. Addiction 96: 395–403. Thase ME (1999). Antidepressant treatment of the depressed patient with insomnia. J Clin Psychiatry 60 (Suppl 17): 28–31. Thompson P, Gillin J, Golshan S et al. (1995). Polygraphic sleep measures differentiate alcoholics and stimulant abusers during short term abstinence. Biol Psychiatry 38: 831–836. Thorp ML, Morris CD, Bagby SP (2001). A crossover study of gabapentin in treatment of restless legs syndrome among hemodialysis patients. Am J Kidney Dis 38: 104–108. Touyz SW, Beumont PJ, Saayman GS et al. (1977). A psychophysiological investigation of the short-term effects of clozapine upon sleep parameters of normal young adults. Biol Psychiatry 12: 801–822. Trenkwalder C (2005). Parkinsonism. In: M Kryger, T Roth, W Dement (Eds.), Principles and Practice of Sleep Medicine. 4th edn. Elsevier Saunders, Philadelphia. Ueno R, Honda K, Inouse S et al. (1983). Prostaglandin D2, a cerebral sleep inducing substance in rats. Proc Natl Acad Sci 80: 1735.
611
US Department of Health and Human Services (2003). Inhalants. Substance Abuse Treatment Advisory - Breaking News for the Treatment Field, vol. 3. National Institutes of Health, Bethesda, MD, pp. 1–8. Valentin N, Bech B (1996). Ketamine anaesthesia for electrocochleography in children. Are psychic side effects really rare? Scand Audiol 25: 39–43. Van Bemmel AL, Havermans RG, Van Diest R (1992). Effects of trazodone on EEG sleep and clinical state in major depression. Psychopharmacology 107: 569–574. Van Bemmel AL, Beersma DG, Van Den Hoofdakker RH (1995). Changes in EEG power density of non-REM sleep in depressed patients during treatment with trazodone. J Affect Disord 35: 11–19. Van Den Heuvel C, Reid K, Dawson D (1997). Effect of atenolol on nocturnal sleep and temperature in young men: reversal by pharmacological doses of melatonin. Physiol Behav 61: 795–802. Van Hilten B, Hoff J, Middlekoop M (1994). Sleep disruption in Parkinson’s disease. Arch Neurol 51: 922–928. Vaughn BV, D’Cruz OF (2004). Sleep and epilepsy. Semin Neurol 24: 301–313. Veale D, Cooper BG, Griffiths CJ et al. (1994). The effect of controlled-release salbutamol on sleep and nocturnal oxygenation in patients with asthma and chronic obstructive pulmonary disease. Respir Med 88: 121–124. Vir R, Bhagat R, Shah A (1997). Sleep disturbances in clinically stable young asthmatic adults. Ann Allergy Asthma Immunol 79: 251–255. Vogel G, Cohen J, Mullis D et al. (1998). Nefazodone and REM sleep: how do antidepressant drugs decrease REM sleep? Sleep 21: 70–77. Walsh JK, Zammit G, Schweitzer PK et al. (2006). Tiagabine enhances slow wave sleep and sleep maintenance in primary insomnia. Sleep Med 7: 155–161. Walter G, Lyndon B (1997). Depression in hepatolenticular degeneration (Wilson’s disease). Aust N Z J Psychiatry 31: 880–882. Ware JC, Pittard JT (1990). Increased deep sleep after trazodone use: a double-blind placebo-controlled study in healthy young adults. J Clin Psychiatry 51 (9 Suppl): 18–22. Ware JC, Rose FV, Mcbrayer RH (1994). The acute effects of nefazodone, trazodone and buspirone on sleep and sleep-related penile tumescence in normal subjects. Sleep 17: 544–550. Weddington W, Brown B, Haertzen C et al. (1990). Changes in mood, craving, and sleep during short term abstinence reported by male cocaine addicts. A controlled, residential study. Arch Gen Psychiatry 47: 861–868. Wesensten N, Killgore W, Balkin T (2005). Performance and alertness effects of caffeine, dextroamphetamine, and modafinil during sleep deprivation. J Sleep Res 14: 255–266. Wetter DW, Young TB (1994). The relation between cigarette smoking and sleep disturbance. Prev Med 23: 328–334.
612
D.A. CONROY AND K.J. BROWER
Wetter DW, Young TB, Bidwell T et al. (1994). Smoking as a risk factor for sleep disordered breathing. Arch Intern Med 154: 2219–2224. Wetter TC, Lauer CJ, Gillich G et al. (1996). The electroencephalographic sleep pattern in schizophrenic patients treated with clozapine or classical antipsychotic drugs. J Psychiatr Res 30: 411–419. Wetter DW, Carmack C, Anderson C et al. (2000). Tobacco withdrawal signs and symptoms among women with and without a history of depression. Exp Clin Psychopharmacol 8: 88–96. Wetter TC, Brunner J, Bronisch T (2002). Restless legs syndrome probably induced by risperidone treatment. Pharmacopsychiatry 35: 109–111. Wiegand M, Schreiber W, Lauer C et al. (1991). The action of clenbuterol on sleep and symptomatology in depressives. Pharmacopsychiatry 24: 89–92. Wiegand L, Mende CN, Zaidel G et al. (1999). Salmeterol vs theophylline: sleep and efficacy outcomes in patients with nocturnal asthma. Chest 115: 1525–1532. Wiesbeck G, Schuckit M, Kalmijn J et al. (1996). An evaluation of the history of marijuana withdrawal syndrome in a large population. Addiction 91: 1469–1478. Williams D, Maclean A, Cairns J (1983). Dose–response effects of ethanol on the sleep of young women. J Stud Alcohol 44: 515–523. Wilson S, Argyropoulos S (2005). Antidepressants and sleep: a qualitative review of the literature. Drugs 65: 927–947. Wilson SJ, Bailey JE, Rich AS et al. (2004). Using sleep to evaluate comparative serotonergic effects of paroxetine and citalopram. Eur Neuropsychopharmacol 14: 367–372. Wilson S, Bailey JE, Rich AS et al. (2005). The use of sleep measures to compare a new 5HT1A agonist with buspirone in humans. J Psychopharmacol 19: 609–613. Winokur A, Sateia MJ, Hayes B et al. (2000). Acute effects of mirtazapine on sleep continuity and sleep architacture in depressed patients: a pilot study. Biol Psychiatry 48: 75–78. Winokur A, Gary KA, Rodner S et al. (2001). Depression, sleep physiology, and antidepressant drugs. Depress Anxiety 14: 19–28.
Wirz-Justice A, Werth E, Savaskan E et al. (2000). Haloperidol disrupts, clozapine reinstates the circadian rest– activity cycle in a patient with early-onset Alzheimer disease. Alzheimer Dis Assoc Disord 14: 212–215. Wolf R, Dykierek P, Gattaz WF et al. (2001). Differential effects of trimipramine and fluoxetine on sleep in geriatric depression. Pharmacopsychiatry 34: 60–65. Wyatt J, Cajochen C, Ritz-De Cecco A et al. (2004). Lowdose repeated caffeine administration for circadian-phase dependent performance degredation during extended wakefulness. Sleep 27: 374–381. Xyrem (Sodium Oxybate) Oral Solution, P. I. (2002). Xyrem. Orphan Medical, Minnetonka, MN. Xyrem International Study Group (2005). Further evidence supporting the use of sodium oxybate for the treatment of cataplexy: a double-blind, placebo controlled study in 228 patients. Sleep Med 6: 415–421. Yamadera H, Suzuki H, Nakamura S et al. (1999). Effects of trazodone on polysomnography, blood concentration and core body temperature in healthy volunteers. Psychiatry Clin Neurosci 53: 189–191. Yamashita H, Morinobu S, Yamawaki S et al. (2002). Effect of risperidone on sleep in schizophrenia: a comparison with haloperidol. Psychiatry Res 109: 137–142. Yamashita H, Mori K, Nagao M et al. (2004). Effects of changing from typical to atypical antipsychotic drugs on subjective sleep quality in patients with schizophrenia in a Japanese population. J Clin Psychiatry 65: 1525–1530. Yamashita H, Mori K, Nagao M et al. (2005). Influence of aging on the improvement of subjective sleep quality by atypical antipsychotic drugs in patients with schizophrenia: comparison of middle-aged and older adults. Am J Geriatr Psychiatry 13: 377–384. Yang CM, Spielman AJ, Huang YS (2005). Insomnia. Curr Treat Options Neurol 7: 373–386. Young TB, Peppard P, Gottlieb D (2002). Epidemiology of obstructive sleep apnea: a population health perspective. Am J Respir Crit Care Med 165: 1217–1239.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 39
Sleep, pain, fibromyalgia, and chronic fatigue syndrome CAROL A. LANDIS * Department of Biobehavioral Nursing and Health Systems, University of Washington, Seattle, WA, USA
INTRODUCTION: THE PROBLEM OF SLEEP DISTURBANCE AND PAIN Sleep disturbance and pain are complex and multidimensional interrelated phenomena. Pain-related poor sleep complaints are common, affect a large number of people worldwide, and have serious consequences for daytime functioning, health outcomes, and quality of life. In the USA, a survey sponsored by the National Sleep Foundation (1996) reported that > 50% of respondents from a representative sample (2000 adults (18 years of age) had nighttime pain sometime during the previous year; nearly half of them reported pain 10 nights/month and 6 hours of habitual nocturnal sleep. Compared to individuals without nighttime pain, those with pain were more likely female, and less likely to report excellent physical health, vigor, ability to concentrate, general mood, and ability to handle stress. A community-based survey of sleep and mental health disorders (18 980 participants 18 years of age) from five European countries found a 17.1% prevalence of one chronic painful physical condition and a 10.3% prevalence of one insomnia symptom (e.g., delayed sleep onset, disrupted nighttime sleep, early-morning awakening, or nonrestorative sleep) (Ohayon, 2005). In those individuals with chronic pain, 23.3% reported insomnia, but surprisingly, 40.2% of those individuals with insomnia symptoms reported chronic pain. Anxious and depressed mood, irritability, and fatigue were higher in those with insomnia and chronic pain compared to those with only insomnia. In both of these surveys, back pain, headaches, and musculoskeletal types of pain were reported most often. Compared to the general population, estimates of sleep disturbances range from 40% to 70% in patients with various types of chronic pain conditions drawn
from clinic populations (Pilowsky et al., 1985; Becker et al., 1997; Morin et al., 1998). Pain-related sleep disturbances are often associated with an exacerbation of pain the next day (Affleck et al., 1996; Edwards et al., 2008), with increased fatigue, depressed mood, and reduced daytime and social functioning (Menefee et al., 2000; Moldofsky, 2001; Smith and Haythorthwaite, 2004; Roehrs and Roth, 2005). Most of the available clinical research literature about chronic pain-related sleep disturbance focuses on patients with some type of nonmalignant pain, or pain associated with medical illnesses; there have been few studies of patients with neurological disorders or with neuropathic pain (Menefee et al., 2000; Drewes and Arendt-Nielsen, 2001; Roehrs and Roth, 2005). Perhaps from common experience it seems obvious that pain, as occurs with acute tissue injury from physical trauma or surgery, should interfere with being able to fall and stay asleep, but the relation between acute pain and sleep disturbance is complex and not so straightforward. Trauma and surgery evoke tissue inflammation and activate pain mechanisms of peripheral and central sensitization (Wolfe and Chong, 1993), and disturb sleep (Raymond et al., 2001; Redeker et al., 2004; Griffins and Peerson, 2005; see references in Roehrs and Roth, 2005). However, in addition to pain, older age, preoperative medical status, preexisting insomnia, anesthesia, analgesics, psychological and physiological responses to surgery, and many aspects of the hospital environment are likely sources of disturbed sleep. Chronic pain has well-recognized disturbing effects on self-reports of sleep quality, but clinical pain severity has not been correlated consistently with disturbed sleep as measured by objective methods of polysomnography (PSG) or actigraphy (Carette et al., 1995;
*Correspondence to: Carol A. Landis, D.N.Sc., R.N., F.A.A.N., Professor, Department of Biobehavioral Nursing and Health Systems, Box 357266, University of Washington, Seattle, WA 98195-7266, USA. Tel: 206-616-1908, Fax: 206-543-4771, E-mail: calandis@ u.washington.edu
614
C.A. LANDIS
Leventhal et al., 1995; Menefee et al., 2000; Landis et al., 2004b; Majer et al., 2007). Often the self-report of poor sleep quality is out of proportion to modest changes in PSG indicators of sleep, especially when patients are compared to sedentary control subjects of similar age (Landis et al., 2004b; Majer et al., 2007). For many chronic musculoskeletal conditions or back pain, pain may disappear or become much less intense when individuals are not moving around or lie down to go to sleep. Clearly the report of one symptom (pain) may be biased by the report of another (poor sleep, or fatigue) (Roehrs and Roth, 2005). Alternatively, subjective complaints of sleep disturbance, fatigue, and altered mood in patients with persistent pain may be manifestations of an undiagnosed sleep disorder (Mahowald and Mahowald, 2000a; Reeves et al., 2006), of sustained attention and arousal (Ursin and Eriksen, 2001), or of activation of the stress system (Pacak and Palkovits, 2001; Clauw and Crofford, 2003). There is increased interest in the problem of sleep and chronic pain, as evidenced by several reviews that focused, in part, on neurobiological links between sleep disturbance and chronic pain (Menefee et al., 2000; Smith and Haythornthwaite, 2004; Roehrs and Roth, 2005). Data from a population-based sample provide evidence for a bidirectional association between sleep and pain (Edwards et al., 2008). The first part of this chapter critically reviews research evidence of this bidirectional relation. Several questions guided the organization of this chapter. What is the experimental evidence for an interaction between sleep and pain? How might the transmission of pain be modulated or gated in the central nervous system (CNS) during sleep? Does sleep loss affect pain processing? What is the evidence from the experimental animal literature for pain-related sleep disturbance? Current models of pain processing and modulation are briefly discussed as background for a subsequent review of the research evidence about possible gating of pain signals during sleep and about sleep loss effects on pain perception. Research findings from experimental animal and human studies have revealed that sleep probably exerts minimal sensory gating of physiological pain stimuli, yet perception and motor responses to pain stimuli are reduced during sleep by mechanisms that are poorly understood (Foo and Mason, 2003). Lower pain thresholds and tolerance are common after sleep loss, but the mechanisms or alterations in pain processing that underlie these changes are not known. Electroencephalographic (EEG) studies of sleep in animal models of chronic pain can be attributable to pain processing in the CNS and provide insights into painrelated sleep disturbance.
The second part of this chapter describes what is known from research studies in adults with fibromyalgia (FM) and chronic fatigue syndrome (CFS), two disorders that illustrate the complexity, surrounding the problem of sleep disturbance and pain in chronic conditions. Pain, sleep disturbance and fatigue are the most common symptoms of FM and CFS and sleep has been the most extensively studied using both subjective and objective measures in these disorders (Mahowald and Mahowald, 2000a, b; Drewes and Arendt-Nielsen, 2001). The pioneering work of Moldofsky and colleagues (1975) provided evidence of disturbed sleep in patients with FM (also called fibrositis syndrome). These investigators showed that depriving young healthy male subjects of stage 4 sleep induced FM-like symptoms (Moldofsky and Scarisbrick, 1976), and these results have been replicated in a small sample of middleaged women (Lentz et al., 1999b). The pathogenesis of FM is still unknown, but is thought to involve altered CNS processing or modulation of pain, and/or dysregulation of the neuroendocrine stress response (Clauw and Chrousos, 1997; Pillemer et al., 1997; Staud and Rodriguez, 2006; Abeles et al., 2007). Many patients with FM also suffer from CFS. In recent years, some researchers have suggested that FM and CFS are different expressions of the same underlying disease or pathogenic mechanisms in the CNS that lead to widespread pain and fatigue (Buchwald, 1996; Clauw and Chrousos, 1997; Komaroff and Buchwald, 1998; Goldenberg, 1999; Aaron and Buchwald, 2001; Friedberg and Jason, 2001). Pain and sleep disturbance in FM and CFS may contribute independently to altered fatigue, mood disturbance, and cognitive impairments or they may act synergistically to impact these symptoms and health outcomes. The case definitions, prevalence, models of pathogenesis and pathophysiology, as well as diagnosis and current treatment recommendations are discussed. Sleep disturbance in FM and CFS is considered secondary to abnormalities of pain processing or stress system responses, but may be better conceptualized as a comorbid condition that requires specific assessment and treatment. Improvement in sleep quality is an important therapeutic goal and success often enables patients with these disorders to cope more effectively and improve their quality of life.
SLEEPAND PAIN INTERACTION Background and definitions SLEEP Sleep is defined as a reversible behavioral state characterized by decreased responsiveness to arousing stimuli and disengagement from environmental surroundings.
SLEEP, PAIN, FIBROMYALGIA, AND CHRONIC FATIGUE SYNDROME It is a complex physiological and behavioral process orchestrated by distinct neuronal networks and is uniquely distinct from resting. Sleep physiology in humans is assessed with PSG recordings of brain waves, eye movements, and muscle tone and PSG is the most sensitive method for the assessment of painrelated sleep disturbance. Standard criteria exist for recording and scoring PSG recordings into stages of sleep and events that occur during sleep, e.g., arousals, breathing patterns, and leg movements (American Academy of Sleep Medicine, 2007). Various methods of quantitative analysis of EEG waveforms and microelements have been used in studies of patients with chronic pain. For example, evidence of increased alpha activity during nonrapid eye movement (NREM) sleep and reduced delta and spindle activity have been identified and linked to pain in patients with chronic pain (Moldofsky et al., 1975; Drewes, 1999; Roizenblatt et al., 2001; Landis et al., 2004a; Rizzi et al., 2004). Sleep behavior in patients with chronic pain has been assessed with daily logs (Menefee et al., 2000; Smith and Haythornthwaite, 2004) and with the use of actigraphy recordings of body movements (Lavie et al., 1992; Wilson et al., 1998; Korszum et al., 2002; Landis et al., 2003; Kop et al., 2005). The perception of sleep duration and quality, sleepiness, sleep disturbance, or feeling rested from sleep has been assessed in patients with pain using a variety of instruments and questionnaires. The perception of sleep duration and quality will always be a retrospective appraisal of usual sleep or of a previous night’s sleep. Yet, self-reported sleep quality provides important information related to an individual’s interpretation and evaluation of the significance of his or her sleep experience that is influenced by many personal (physical and psychological) and environmental factors.
PAIN Pain is a unique, personal, and subjective unpleasant experience with a combination of sensory, affective, and behavioral dimensions most often associated with actual or potential tissue damage (Basbaum and Jessell, 2000) (Table 39.1). Pain as a perception requires a certain level of consciousness to judge intensity, unpleasant aspects, and relevance. Physiological pain refers to activation of nociceptors and pain pathways in response to noxious stimuli—a type of pain that serves a protective function and considered an earlywarning signal of potential tissue damage (Wolfe and Chong, 1993; Wolfe and Salter, 2000). Nociceptive pain is a term used to describe activation of nociceptors and pain pathways in response to tissue inflammation and injury. Neuropathic pain refers to pain associated
615
Table 39.1 Pain: glossary of terms Allodynia
Hyperalgesia
Nociceptive pain
Neuropathic pain
Pain
Physiological pain
Pain evoked by a stimulus, e.g. light touch, that does not usually elicit pain An increased or exaggerated response to a noxious stimulus that evokes pain Pain associated with activation of nociceptors and pain pathways from tissue inflammation or injury Pain associated with injury to or a lesion of the nervous system or arising from the nervous system An unpleasant sensory and emotional experience associated with actual or potential tissue damage or described in terms of such damage* Activation of nociceptors and pain pathways warning of potential tissue damage
*Mersky and Bogduk (1994).
with damage to the peripheral or central nervous system. Allodynia and hyperalgesia are terms used to describe pain pathology associated with either nociceptive or neuropathic pain. Allodynia refers to the ability of nonnoxious stimuli such as light touch or slight movement to evoke pain reports or behavioral responses indicative of pain. Hyperalgesia refers to exaggerated responses to noxious stimuli and has been used to describe heightened sensitivity surrounding tissue injury and reports of spontaneous pain (Basbaum and Jessell, 2000). The affective dimension of pain is associated with its unpleasant qualities and with emotions associated with fear, dread, and suffering (Price, 2000). Pain is also viewed as motivated behavior influenced by many personal, social, cultural, and environmental factors (Fordyce, 1976; Price, 2000).
Pain processing and modulation The classic description of the perception of pain involves the activation of peripheral nociceptors in response to noxious (thermal, mechanical, chemical) stimuli and the transmission of afferent impulses by primary afferents (A delta (fast) and C (slow) fibers) to the spinal cord and cortex via a relay in the thalamus. Nociceptor inputs also activate spinal withdrawal reflexes, and increase emotional, autonomic, and neurohormonal arousal responses (Price, 2000; Wolfe and Salter, 2000). Over the last 50 years, much has been learned about the adaptability of the CNS and mechanisms involved in neuronal plasticity that underlie the
616 C.A. LANDIS transduction, transmission, and modulation of pain. (Wolfe and Salter, 2000; Staud and Rodriguez, 2006). The gate control theory (Melzack and Wall, 1965), When nociceptive afferent inputs to the spinal cord which postulated that large-diameter myelinated afferare prolonged, as occurs with tissue inflammation, ents provided sensory inputs to spinal cord inhibitory functional changes occur in the connectivity of neuinterneurons to cause inhibition of the transmission rons in the spinal cord. Activation-dependent plasticity of noxious inputs from primary afferents, provided is considered the basic process underlying sensitizaan explanation for behaviors, such as rubbing the site tion of peripheral nociceptors and the sustained activaof an injury, that reduced pain. The theory also tion of cells in the CNS in response to tissue or nerve provided a dynamic view of pain processing in the injury. Sensitization of nociceptors and primary afferCNS. Subsequent studies led to the identification of ents (decreased activation threshold) occurs through stimulus-evoked descending neural inhibitory (opioid changes intrinsic to nociceptors or from mediators and nonopioid) systems that modulate pain at the level (bradykinin, serotonin, prostaglandins, epinephrine, of the spinal cord (Willis, 1988; Basbaum and Jessell, adenosine) and neurotropic factors (nerve growth fac2000) and under extraordinary circumstances permit tor) released by damaged tissues that alter functioning individuals to withstand considerable physical injury of voltage-gated and ligand-gated ion channels in priwithout reporting or manifesting pain (Melzack and mary afferents (Levine, 1998; Wolfe and Salter, 2000; Wall, 1965). Staud and Rodriguez, 2006). Sustained activation By the late 1980s, pain scientists were well aware (wind-up) of dorsal horn cells is dependent upon prithat neural activity associated with processing of noxmary afferent inputs and the release of neuropeptides ious stimuli involved changes in the sensitivity of (e.g., substance P) and glutamate, with subsequent actiperipheral terminals (peripheral sensitization) (Raja vation of N-methyl-D-aspartate (NMDA) receptors. Non-NMDA and NMDA receptor activation at multiet al., 1988) as well as both facilitation and inhibition ple synapses forms the basis of sustained hyperexcitof cells and fibers in the CNS that were time- and conability of cells in the spinal cord, called central text-dependent (Wall, 1988; Willis, 1988). In more sensitization (Levine, 1998; Wolfe and Salter, 2000). recent decades, pain scientists have studied the Central sensitization involves altered response propermechanisms and neuropeptides involved with ongoing ties of cells in the spinal cord, activation of cellular tissue inflammation or lesions of peripheral nerves signaling cascades with long-term changes in gene (Treede et al., 1992; Levine et al., 1993), and those expression and upregulation of neuropeptides, transinvolved with modifications in cells of the dorsal horn mitters, and receptors (Coderre et al., 1993; Basbaum of the spinal cord that enable pain to persist long after and Jessell, 2000; Wolfe and Salter, 2000). Taken tissues have healed, a phenomenon called central sensitogether, sensitization of peripheral afferents and cells tization (Coderre et al., 1993; Wolfe and Chong, 1993; in the spinal cord forms the basis for hypersensitivity Wolfe and Salter, 2000). A brief summary of pain prosurrounding inflamed tissue, and for the ability of light cessing is provided based on selected reviews from the touch and other nonnoxious stimuli to elicit pain pain literature (Basbaum and Jessell, 2000; Price, 2000; responses at the site of injury and in adjacent normal Wolfe and Salter, 2000; Staud and Rodriguez, 2006) tissue. as background information for the review of sleep These changes in the sensitivity and responses of modulation of nociception and pain-related sleep nociceptors and dorsal horn cells can be reversed as tisdisturbance. sues heal and inflammation subsides. However, pain pathways can undergo modification in the form of PAIN PROCESSING IN PERIPHERAL AFFERENTS long-lasting changes in the expression of receptors, AND SPINAL CORD transmitters, channels, or even cell death (Wolfe and Pain processing involves rapid, slow and sometimes Salter, 2000). These changes alter the structure and prolonged, reversible and potentially irreversible connectivity of neurons such that usual stimulus– changes in peripheral afferents and in cells and synapresponse characteristics of the system are permanently tic connections in the spinal cord (Wolfe and Salter, changed. The gain of the system is enhanced and pain 2000). Noxious stimuli activate specific peripheral sensitivity is amplified so that even mild nociceptive nociceptors (e.g., heat, vanilloid receptors) located on stimulation that might occur with sore muscles elicits free nerve endings of primary afferents. With suffipain. cient signal strength action potentials are generated in Nerve injury is sometimes associated with the death primary afferents and invade the spinal cord to actiof cells in the dorsal horn, which leads to permanent vate fast excitatory glutamate-mediated transmission loss of inhibitory controls and sustained facilitation and the immediate activation of dorsal horn cells (Wolfe and Salter, 2000). The mechanisms involved
SLEEP, PAIN, FIBROMYALGIA, AND CHRONIC FATIGUE SYNDROME in central sensitization and amplification of pain at the spinal cord level affect the processing of pain at higher levels in the CNS. Sustained central sensitization is considered the most parsimonious explanation for the heightened pain perception in patients with FM, but whether this is attributable to ongoing or intermittent peripheral sources, pain amplification in the spinal cord, altered CNS pain processing, or stress system dysregulation is a matter of ongoing debate (Yunus, 1992; McDermid et al, 1996; Pillemer et al., 1997; Bennett, 1998; Weigent et al., 1998; Carli et al., 2002; Okifuji and Turk, 2002; Clauw and Crofford, 2003; Staud and Rodriguez, 2006).
PAIN
PROCESSING IN THE BRAIN
Pain processing in the brain is far more complicated than in peripheral nerves or the spinal cord. Pain and information about tissue injury are transmitted from the spinal cord via ascending pathways to regions of the brain including the thalamus, reticular formation, periaqueductal gray, and hypothalamus, with relays to the limbic system and cortical regions involved in somatosensory and affective dimensions of pain (Basbaum and Jessell, 2000; Price, 2000; Pacak and Palkovits, 2001; Craig, 2003b). In addition to specific areas implicated in pain processing, these structures regulate arousal, autonomic responses, motor integration, and descending motor and sensory inhibition. Imaging studies in humans using positron emission tomography and functional magnetic resonance imaging (fMRI) have identified cortical and subcortical regions of the brain implicated in pain processing. Certain regions, including the anterior cingulate cortex, the insular cortex, cerebellum, thalamus, and premotor cortex, show consistent activation patterns in response to various noxious stimuli (Casey, 1999). Models have been proposed that divide selected brain regions into a sensory-perceptual system and an affectiveemotional system (Price, 2000; Chen, 2001). For example, specific nuclei in the sensory-perceptual system such as the ventroposterior thalamus and regions of somatosensory cortex mediate spatial localization and discriminate aspects of nociception. The anterior cingulate cortex is believed to be an important component of the affective-emotional system involved in mediating the unpleasant aspects of pain (Price, 2000). Activity in the anterior cingulate cortex can also be elicited by noxious as well as nonnoxious warm and cold stimulation (Craig, 2003b) and subdivisions responsive to noxious stimuli partially overlap those involved in attention mechanisms (Peyron et al., 2000). The insular cortex is considered the cortical location that integrates so-called interoceptive modalities associated with
617
bodily feelings, including pain (e.g., temperature, hunger, thirst, itch) (Craig, 2003a). In patients with chronic pain, decreased resting blood flow patterns in the thalamus associated with spontaneous pain can be altered with analgesics, suggesting that regions responsive to pain stimuli are also involved in pain control. Craig (2003a, b) has proposed a new model that integrates pain processing in the CNS within a framework of other homeostatic drives that function to maintain body integrity. Pain is viewed as an integral part of a homeostatic emotional behavioral network of “feelings” that also includes temperature, itch, muscle ache, hunger, thirst, “air hunger,” and sensual touch (Craig, 2003a, b). Pain as a homeostatic emotion is both a distinct sensation associated with an adverse condition of the body and a motivated behavioral response. This model of pain processing is based on evidence that pain, temperature, itch, muscle ache, and other bodily feelings share a common anatomical pathway in the lateral spinothalamic tract from lamina 1 of the spinal cord to structures in the brainstem, thalamus, anterior cingulate, and insular cortex, that is highly developed in primates. A homeostatic model of pain processing may have particular relevance for understanding altered perception of pain and the pathophysiological basis of other bodily feelings and symptoms in FM and CFS.
SICKNESS-INDUCED
HYPERALGESIA
In addition to peripheral and central sensitization, illness-causing agents (e.g., endotoxin) induce hyperalgesia through activation of peripheral and vagal afferents with subsequent activation of both ascending and descending systems involved in pain processing and modulation (Watkins et al., 1994). It has been shown that proinflammatory cytokines released from circulating lymphocytes lead to release of cytokines by glia in the spinal cord and an increase in chemical mediators (e.g., excitatory amino acids, prostaglandins, nerve growth factors, and nitric oxide) that facilitate nociception and pain processing in the CNS (Watkins and Maier, 2005). It has been suggested that glia, rather than neurons, may be the biological basis of sickness behavior and therapies directed toward the upregulation of antiinflammatory cytokines have been shown to reduce pain in animal studies (Watkins and Maier, 2005).
Experimental studies of sleep modulation of pain-related sensation Sleep is characterized by reduced responsiveness to sensory and environmental stimuli, yet processing of sensory inputs occurs in the sleeping brain. An
618 C.A. LANDIS imaging study has shown that regional brain activation or REM sleep in the cat (Cairns et al., 1996), or in to auditory stimuli occurs in the auditory cortex, thalacortical evoked responses after trigeminal nerve stimumus, and caudate during both wakefulness and NREM lation during NREM sleep even after 12 hours of sleep sleep, yet regions of the parietal and cingulate cortices deprivation in the rat (Frederickson and Rechtschaffen, were less activated during NREM sleep compared to 1978). Decreased sensory-evoked discharge rates in the wakefulness (Portas et al., 2000). Arousal thresholds trigeminal complex have been recorded during REM during sleep are based on the stimulus strength necessleep compared to wakefulness and NREM sleep sary to produce a change in the EEG recording from (Satoh et al., 1980a, b), but responses to air puff stione stage of sleep to wakefulness (i.e., an arousal) or muli applied to the face were actually increased during on the time it takes to perform a motor task in REM sleep in the cat (Cairns et al., 1996). Further eviresponse to the stimulus (i.e., response latency). Finddence of a REM sleep-gating mechanism is shown by ings from human studies indicate that arousals and reduced spontaneous spike activity in spinoreticular response latencies to auditory tones are highly variable tract neurons in lamina 3 of the spinal cord (Soja between subjects and in the same subject during differet al., 2001b) and reduced responses of these neurons ent times of a night (Rechtschaffen et al., 1966). Comto antidromic stimulation of the ventrolateral reticular pared to NREM stage 1 sleep, arousal thresholds are formation or to spinal cord glutamate-evoked activity diminished considerably in stage 2 and in REM sleep; during REM sleep compared to wakefulness and they are highest in NREM stages 3 and 4, especially NREM sleep (Soja et al., 2001a). These findings sugafter sleep deprivation. Given that arousal thresholds gest that afferent input is gated during REM sleep vary as a function of behavioral state, the transduction through descending pathways that can exert inhibitory of and/or transmission of sensory stimuli, including or facilitatory influences depending upon different pain, may be gated at primary, secondary, or tertiary types of sensory input (Soja et al., 2001a). Alternalevels of the CNS during sleep. tively, these changes may be secondary to the descending inhibitory mechanisms from the brainstem associated with muscle atonia during REM sleep. GATING OF SENSORY TRANSMISSION DURING SLEEP Brainstem neurons in the region of the ventromedial FROM ANIMAL STUDIES reticular formation involved in mediating descending There is evidence that the transmission of sensory stipain modulation and facilitation show distinct patterns muli in the brainstem and spinal cord is affected to of spontaneous activity during waking, NREM, and some extent by behavioral state. Sensory gating in the REM sleep in rats (Leung and Mason, 1999). Cells that trigeminal nucleus or in spinal cord neurons that give are activated by morphine, called off cells (i.e., inhibit rise to ascending somatosensory tracts has been pain), are continuously active during NREM sleep, addressed in a few animal studies. In most cases the sporadically active in wakefulness, and silent during intensity of electrical nerve stimulus was lower than REM sleep. Cells that are inhibited by morphine, called that of the nociceptive threshold (Hernandez-Peon on cells (i.e., facilitate pain), are active during waking, et al., 1965; Soja et al., 2001b), or was capable of elicitvirtually silent during NREM sleep, and most active ing a slight burning sensation when applied to the during REM sleep. Based on these response properties, investigator’s hand (Mason et al., 2001). Hernandezone would expect that behavioral responses to noxious Peon and colleagues (1965) conducted one of the first stimuli would be increased during NREM sleep comphysiological recordings of evoked potentials in the tripared to wakefulness and REM sleep (Mason et al., geminal nucleus during sleep in cats and found that 2001). However, this was not the case. Paw withdrawal responses to stimulation of the skin of the face were latencies to a thermal stimulus were increased during stable during quiet wakefulness and reduced during NREM sleep compared to wakefulness, and behavioral behavioral alertness and REM sleep. However, during responses (e.g., licking the paw, moving about the synchronized sleep (analogous to NREM stages in cage) were suppressed during NREM sleep and exaghumans) there was an increase in the amplitude of gerated during waking. the response, which was similar to that observed after Foo and Mason (2003) suggest that off cells (i.e., lesions in the midbrain tegmentum. This observation inhibit pain), which are continually active during was interpreted as a release of the trigeminal nucleus NREM sleep, may dampen sensory inputs, and on cells from tonic descending inhibition (or disinhibition) during (i.e., facilitate pain), which are active during waking NREM sleep. and REM, may augment inputs to neuronal circuits Results from other studies have shown no differthat mediate arousal. The enhanced rate of response ences in the spontaneous discharge rates in trigeminal during NREM sleep is similar to the increased amplisensory complex neurons during wakefulness, NREM tude of evoked responses in the trigeminal nucleus
SLEEP, PAIN, FIBROMYALGIA, AND CHRONIC FATIGUE SYNDROME reviewed above (Satoh et al., 1980a) and could also reflect reduced descending inhibition of spinal reflexes during sleep (Mason et al., 2001). Thus, responses to nociceptive stimuli are preserved during NREM sleep, yet gated at the level of the first synapse in the transmission pathway during REM sleep.
MODULATION
OF AROUSAL RESPONSES TO NOXIOUS
STIMULI FROM HUMAN STUDIES
Experimental studies of the interaction of sleep and pain have been conducted in healthy human subjects. It is difficult to compare results across studies, because the type, duration, and intensity of stimuli and protocols used in each study were quite different (Drewes, 1999; Lavigne et al., 2000, 2004; Bentley et al., 2003). Nevertheless, in all of the studies, noxious stimuli (e.g., saline infusions into muscle, finger joint pressure, cutaneous laser, heat) were shown to evoke reports of physiological pain when subjects were awake. Collectively, these studies show that cortical arousal responses to noxious stimuli lead to transient disruptions of sleep and only brief awakenings. For example, in one study after an arousal to heat stimulus, subjects returned to sleep within 40 seconds and a behavioral response was observed in only 2.5% of the stimulations (Lavigne et al., 2000). Cutaneous heat of moderate (Lavigne et al., 2000) or high intensity (Bentley et al., 2003) led to more frequent cortical arousals from NREM stage 2 compared to slow-wave (SW) and REM sleep, yet subjects reported minimal awareness of having been aroused or awakened during sleep. In a recent study, more arousals from SW and REM sleep were evident in response to noxious stimulation (hypertonic – isotonic saline muscle infusions) compared to innocuous stimulation (vibration/tactile þ auditory – auditory), but both noxious and nonnoxious stimulation led to a similar number of awakening responses from NREM stage 2 sleep and to reductions in the amounts of SWS and REM sleep obtained on experimental nights (Lavigne et al., 2004). Studies of EEG activity in response to noxious stimulation during sleep and during wakefulness are not the same. Drewes and colleagues (1997), using a unique autoregressive modeling technique to quantify EEG spectral power, showed that three types of noxious stimuli were associated with different patterns of EEG activity during sleep. Saline infusions into muscle and pressure applied to a finger joint reduced delta (0.5–3.5 Hz) and increased alpha (8–12 Hz) and beta (14.5–25Hz) activity, but had differential effects on sigma (12–14.5 Hz) activity; muscle pain was associated with reduced sigma activity, while joint pain
619
was associated with increased sigma activity. EEG studies of cortical activity in awake subjects using induced tonic muscle pain (e.g., intramuscular injections of hypertonic saline) have shown a characteristic pattern of reduced delta and alpha activity and increased beta (fast) activity (Chen, 2001) compared to control subjects, and reduced alpha activity in the low alpha range (8.0–10.8 Hz) was correlated with increased pain intensity (Chang et al., 2002). Although responses to mild physiological pain stimuli of short duration are reduced during sleep in healthy humans, this inhibition is limited and can be easily reversed in all stages of sleep. During sleep, patients with chronic pain may be more sensitive and responsive to sensory stimuli, but to our knowledge this has not been reported. However, sleep patterns were nearly the same in women with and without chronic pain of FM during a night when an intravenous catheter was inserted and blood samples were obtained frequently (Landis et al., 2001). Further studies are warranted in order to determine whether patients with chronic pain are more susceptible to sensory and nociceptive stimuli during sleep.
Experimental studies of sleep loss on pain-related sensations Sleep loss is associated with changes in pain perception or sensitivity. A progressive decrease in the threshold to noxious stimuli (application of Von Frey hairs), but not nonnoxious stimuli, was a consistent finding from an early study of prolonged sleeplessness of 60 hours’ duration in humans (Cooperman et al., 1934). However, the basis for this change in the physiological pain threshold following total sleep loss remains unknown. Although the literature on sleep deprivation-induced changes in pain perception is not extensive, most of the studies have focused on the selective deprivation of REM sleep in animals and of SW or total sleep in humans. Whether the reported changes in pain sensitivity are related to the loss of specific stages or the loss of sleep per se remains unclear (Kunderman et al., 2004; Roehrs and Roth, 2005).
REM
SLEEP DEPRIVATION EFFECTS ON NOCICEPTION
IN ANIMALS
Most studies of sleep loss effects on pain sensitivity in animals have been done using the relatively selective classic platform method REM sleep deprivation (REMSD) (Hicks et al., 1978, 1979; Onen et al., 2001b; May et al., 2005). In this method an animal is placed on a small platform (e.g., an inverted flower pot) surrounded by water. The animal can obtain NREM sleep, but with the onset of REM sleep and
620
C.A. LANDIS
muscle atonia, it loses its balance and falls forward, causing an arousal. REMSD is associated with a reduction in the threshold to noxious stimuli during (Onen et al., 2001a), immediately after several days of deprivation (Hicks et al., 1978), and after several days of recovery sleep (Hicks et al., 1979). Some evidence exists for reduced efficacy of opioid-mediated descending pain modulation in REMSD (Ukponmwan et al., 1984). A study by May and colleagues (2005) showed more robust increases in paw withdrawal latencies at a lower thermal level of stimulation (44oC) than at suprathreshold levels (52oC) and suggested that REMSD is associated with preferential activation of small C-fiber afferents rather than A-delta afferents. Satinoff and colleagues (1970) reported increased amplitude of evoked responses in the cortex and simultaneously reduced amplitude in the trigeminal nucleus and reticular formation to direct nerve stimulation in REM sleep-deprived cats. These results suggest that some types of sensory stimuli are subject to CNS modulation even during sleep deprivation. It is important to note that REMSD is associated with a progressive and substantial increased sleep drive, especially for REM sleep, as the deprivation episode is continued. There is considerable instability in behavioral state as the animals are frequently aroused from attempts to fall asleep. REMSD is also associated with activation of the stress response (Landis, 2005), which has potential to inhibit or facilitate processing of noxious stimuli (Terman et al., 1984; Sapolsky et al., 2000).
SLEEP
Pressure, but not thermal, pain tolerance thresholds were reduced significantly after 1 night of sleep deprivation and remained lower after both SW and REM sleep interruption nights, although the scores were not statistically different compared to baseline. After recovery sleep, there was a large increase in pressure pain tolerance scores, which was correlated with the amount of SW sleep during recovery. In a more recent study, Kunderman and colleagues (2004) showed that the threshold to heat pain, but not the detection of warm temperature, was reduced after each of 2 individual nights of total sleep deprivation compared to control subjects permitted usual sleep. However, the sleep-deprived subjects reported no pain or discomfort. Roehrs and Roth (2005) suggest that sleepiness, which usually ensues following total or partial sleep deprivation, rather than the loss of sleep, is responsible for lower pain thresholds. Based on the results of these few heterogeneous studies, it is not clear whether changes in the nociceptive threshold are due to SW sleep loss, sleep disruption, total sleep loss, or to sleepiness. In addition, mood disturbance is a reliable outcome of partial and total sleep deprivation (Pilcher and Huffcutt, 1996) and higher depression scores and more sleep disturbance have been independently associated with a low pain threshold (Chiu et al., 2005).
Experimental studies of pain-related sleep disturbance INFLAMMATORY
DEPRIVATION EFFECTS ON NOCICEPTION
IN HUMANS
Unlike animal studies, most studies in humans have focused on selective SW or total sleep deprivation. Selective SW sleep deprivation for 3 nights by auditory stimuli has been shown to increase muscle tenderness in response to pressure stimuli (dolorimeter) and reports of pain symptoms compared to baseline in young and middle-aged subjects (Moldofsky et al., 1975; Lentz et al., 1999b). However, these changes were not observed in another study that compared SW sleepdeprived and control subjects (Older et al., 1999). Subjects in all these studies reported increased fatigue, tiredness, and reduced vigor. Onen and colleagues (2001a) studied pressure pain tolerance threshold after 1 night of total sleep deprivation followed by 2 consecutive nights of selective interruption of SW or REM sleep in counterbalanced order and a night of recovery sleep. One night of total sleep deprivation was used in order to increase sleep pressure such that auditory stimuli would not lead to increased waking or light sleep on the subsequent nights of sleep interruption.
MODELS
Experimental studies of sleep in animal models of chronic pain provide insights into relations between pain and sleep disturbance. Adjuvant arthritis in the rat is a systemic disease model of chronic pain with similar features to polyarthritis in humans and is associated with hyperalgesia and pain-related behaviors that are most apparent during the acute inflammatory phase of the disease (Calvino et al., 1987; Colpaert, 1987). Inflammation and nerve injury activate pain mechanisms and pathways discussed previously, leading to hyperalgesia and allodynia with the potential to disrupt sleep. During the acute phase of the disease, arthritic rats showed highly fragmented sleep, increased wakefulness, large reductions in NREM sleep with high amplitude (analogous to SW sleep) and in REM sleep compared to nonarthritic rats (Landis et al., 1988, 1989). Rats with more severe arthritis, and presumably more pain, were sleepier, as evidenced by increased delta activity during the dark hours (when normal rats are most awake), loss of the diurnal variation in sleep and wake stages, and positive correlations between arthritis severity and amounts of lighter stages of
SLEEP, PAIN, FIBROMYALGIA, AND CHRONIC FATIGUE SYNDROME NREM sleep (Landis et al., 1989). A similar fragmented sleep pattern was found in another study of adjuvant arthritis, and although hyperalgesic responses were evident in the injected paw for as long as 8 weeks, sleep patterns were only recorded during the initial weeks of the disease (Anderson and Tufik, 2000). Whether disrupted sleep patterns persist beyond the acute phase of the disease is not known.
NEUROPATHIC
MODELS
Neuropathic pain is associated with pathology of the nervous system and with pain that persists long after peripheral tissues have healed (Wall, 1988; Wolfe and Salter, 2000). Patients with neuropathic pain often complain of sleep disturbances (Bennett, 1999). Spontaneous neural activity has been recorded during waking and during sleep from cells in the medial and intralaminar thalamic nuclei of patients with chronic deafferentation pain that could reflect central sensitization and altered pain processing (Rinaldi et al., 1991). However, no difference in spontaneous bursting activity of thalamic neurons has been observed in patients with and without chronic pain, suggesting that thalamic bursting is not specific to pain (Radhakrishnan et al., 1999). Following constriction of the sciatic nerve to induce peripheral nerve injury in rats, allodynia and hyperalgesic responses to nonnoxious and noxious stimuli have been observed to persist for long periods of time (Bennett and Xie, 1988). In studies using this model, altered sleep patterns with increased awakenings were found during days 2–10 immediately following surgery (Anderson and Tufik, 2003), but no changes in sleep and wake patterns or in EEG spectral power were observed in rats with nerve injury compared to shamoperated controls for as long as 146 days (Kontinen et al., 2003). In a separate study, increased wakefulness and reduced SW sleep were found only in a small subgroup of animals with peripheral nerve injury and reduced dominant behaviors during a resident–intruder paradigm of social interaction (Monassi et al., 2003). The investigators interpreted these findings in light of previous reports that linked sleep disturbance with social dysfunction in patients with neuropathic pain.
Summary of sleep–pain interaction Physiological pain stimuli are processed in the CNS during sleep and capable of transient disruptions in sleep. Presumably sleep processes, principally those related to spindle activity and cortical slow waves, gate responses to nociceptive stimulation in thalamocortical networks (Steriade et al., 1993; Steriade, 2000). Gating of nociceptive stimuli at the first synapse in sensory transmission pathways is limited and occurs during
621
REM sleep, possibly in conjunction with the activation of the mechanisms responsible for descending inhibition of muscle tone. Loss of particular stages and of total sleep lowers the nociceptive threshold, but the mechanisms underlying this type of hyperalgesia are not known. Sleep loss could augment hyperalgesia and amplify the perception of pain in patients with chronic pain (Wittig et al., 1982), but perhaps for ethical reasons, to our knowledge results from experimental sleep deprivation studies in patients with chronic pain have not been reported. Experimental studies of altered sleep patterns in animal models of chronic pain reveal that sleep is most disturbed during the immediate postoperative period following peripheral nerve injury and during the acute inflammatory phase of arthritis. Altered sleep patterns may be attributable, at least in part, to peripheral and central sensitization mechanisms in situations of acute tissue injury or inflammation.
FIBROMYALGIA AND CHRONIC FATIGUE SYNDROME Background The perception of poor-quality and unrefreshing sleep is common in FM and CFS. FM and CFS are complex, chronic illnesses of unknown etiology characterized primarily by symptoms of pain, fatigue, and sleep disturbance. The purpose of this section is to summarize what is known about these disorders with emphasis on disturbed sleep and its relation to pain, and on strategies that may be helpful in symptom management to improve health outcomes. Improvement in sleep quality is an important therapeutic goal and success often enables patients to cope more effectively and improve quality of life (Valente, 1998). Considerable controversies surround FM and CFS. The diagnosis is made on the basis of symptom presentation due to absence of any valid diagnostic laboratory test for either disorder. Patients with FM or CFS often have a variety of coexisting medical or psychiatric conditions that complicate diagnosis and effective management. There has been a tendency to label patients with these diagnoses without using standardized criteria. As more information is now available about FM and CFS to the public from a variety of sources, individuals are also more likely today to selfdiagnose and patient complaints are often not taken seriously due to a climate of increased skepticism and disbelief about the pathologic nature of these conditions. Patients may also be dismissed as chronic complainers, as seeking drugs or a disability claim. Since FM and CFS are thought primarily to affect women, the failure to identify a physical basis for
622
C.A. LANDIS
these disorders has led some researchers and clinicians to embrace psychiatric or sociocultural explanations that can bias care (Richman et al., 2000). There is a very large literature about FM and CFS and recent reviews provide more information about the management of these disorders (Bennett, 1998, 2004; Whiting et al., 2001; Afari and Buchwald, 2003; Clauw and Crofford, 2003; Goldenberg et al., 2004; Staud and Rodriguez, 2006; Abeles et al., 2007; Clauw, 2007).
Definitions of FM and CFS FM and CFS are heterogeneous disorders. The case definitions for FM and for CFS were originally developed as criteria for sample selection to enable better comparison across research studies and over time they have become used as the basis for making clinical diagnosis. However, investigators and clinicians may not adhere rigidly to the criteria in subject selection or in making a diagnosis. The case definition for FM was based on data derived from a multicenter study (Wolfe et al., 1990). The case definition for CFS is based on an expert panel consensus about clustering of symptoms (Fukuda et al., 1994). Sleep studies of patients conducted prior to the adoption of these definitions probably reflect a larger population of individuals with widespread pain and fatigue.
Table 39.2 Diagnostic criteria for fibromyalgia and chronic fatigue syndrome Fibromyalgia Widespread pain (bilateral above and below the waist) for at least 3 months’ duration in combination with: Tenderness at 11 or more of 18 specific bilateral tender point sites* Digital palpation is performed with approximately 4 kg force The presence of a second clinical disorder does not exclude the diagnosis of fibromyalgia Chronic fatigue/chronic fatigue syndrome (CFS) Chronic severe fatigue persists or relapses for 6 months{ Classify as CFS if four or more of the following symptoms are present for 6 months and developed after the onset of fatigue: impaired memory or concentration, sore throat, tender cervical or axillary lymph nodes, muscle pain, multijoint pain, new headaches, unrefreshing sleep, and postexertion exercise Classify as idiopathic chronic fatigue if the above criteria for CFS are not met *Tenderness was defined as mild or greater pain (Wolfe et al., 1990) at the occiput, low cervical, trapezius, supraspinatus, second rib, lateral epicondyle, gluteal, greater trochanter, and knee. { Fatigue is new or of defined onset, not substantially alleviated by rest, and results in substantial reduction in previous levels of social and personal activities (Fukuda et al., 1994; Komaroff and Buchwald, 1998).
FIBROMYALGIA The case definition of FM is a history of chronic, generalized aching of 3 months’ duration and the finding of pain (tenderness), during physical examination, in at least 11 out of 18 discrete musculoskeletal points in nine paired regions of the body (Wolfe et al., 1990). The most characteristic symptoms are widespread pain, fatigue, sleep disturbance, and morning stiffness. Although sleep disturbance is not part of the case definition for FM, insomnia is common and has been associated with intense pain, fatigue, sleepiness, and cognitive difficulties in patients (Wolfe et al., 1990; Affleck et al., 1996; Cote and Moldofsky, 1997; Nicassio et al., 2002; Landis et al., 2003). Specific diagnostic criteria for FM are listed in Table 39.2. Some investigators use the tender point criterion as a measure of illness severity because the significance of 11 out of 18 positive tender points in relation to the case definition has been criticized. Tenderness at the nine paired body sites is not unique to FM; many healthy individuals without widespread pain have 11 or more tender points (White et al., 1999). The definition biases the assessment of individuals with chronic widespread pain in favor of women because healthy women have lower pain thresholds compared to men (Wolfe et al., 1995; Clauw and Crofford, 2003).
Women are only 1.5 times more likely to complain of widespread pain compared to men, but are 11 times more likely than men to have 11 out of 18 painful tender points (Clauw, 2007). Further, tender points may not accurately reflect pain thresholds or tolerance because of expectancy, novelty, or the unwillingness to experience pain (Clauw and Crofford, 2003) and the number of them is correlated with distress (Wolfe et al., 1995; White et al., 2002). Sophisticated methods exist for applying nociceptive stimuli in random fashion in experimental studies, but these are not practical to use in clinical assessments or as part of screening procedures for sample selection (Gracely et al., 2002). One group of investigators has suggested that the tender point criterion be abandoned in favor of using a complaint of chronic widespread pain in the clinical assessment of FM or that subgroups be identified based on evoked pain characteristics not confounded with distress or other behavioral or psychological factors (Clauw and Crofford, 2003; Clauw, 2007).
CHRONIC
FATIGUE SYNDROME
The case definition for CFS most often used by researchers and clinicians was developed from a consensus among experts (Fukuda et al., 1994). CFS is
SLEEP, PAIN, FIBROMYALGIA, AND CHRONIC FATIGUE SYNDROME characterized by severe disabling fatigue that reduces an individual’s level of activity for at least 6 months. This fatigue cannot be attributed to another medical or psychiatric cause and must coexist with a combination of symptoms, including impaired cognition, sleep disturbance, and musculoskeletal pain. Investigators consider patients to have idiopathic chronic fatigue if the criteria for CFS are not met (Table 39.2). Similar to FM, controversy surrounds the case definition of CFS because it is based on symptoms that overlap with, and are difficult to distinguish from, other conditions and because it is based on a consensus of experts rather than empirically derived (Tan et al., 2002; Afari and Buchwald, 2003). The diagnosis of CFS requires that certain conditions associated with fatigue be excluded. These conditions include hypothyroidism, sleep apnea, narcolepsy, side-effects of medications, malignancies, hepatitis B or C virus infection, past or current diagnosis of major depression with melancholia, bipolar affective disorder, schizophrenia, dementias, eating disorders, and alcohol or substance abuse within 2 years of the onset of fatigue (Fukuda et al., 1994). However, the case definition for chronic fatigue does not exclude conditions such as FM, anxiety, somatoform disorders, subsyndromal depression, or multiple chemical sensitivity disorder, and other medical conditions, such as Lyme disease, that were treated prior to the development of severe fatigue. Because of the heterogeneity of CFS, a proposal has been developed to classify the case definition into subgroups based on whether symptoms are predominantly related to the nervous, endocrine, musculoskeletal, or immune systems (Tan et al., 2002). Others suggest that CFS occurs along a continuum and is best studied under the umbrella of “unexplained chronic fatigue” (Schmaling et al., 2003).
Prevalence and risk factors of FM and CFS FIBROMYALGIA FM is a common cause of chronic, primarily musculoskeletal, widespread pain and the second most common disorder diagnosed in rheumatology practice. Its prevalence in the general adult population in the USA is estimated at 2–4 % (Wolfe et al., 1995), and also occurs in children and adolescents (Siegel et al., 1998). The prevalence of FM is much higher in women, with an odds ratio of 9.1. The incidence of FM increases with age and affects nearly 7% of women over 60 years (Wolfe et al., 1995). Greater sensitivity to pain may place women at higher risk for developing FM (Pillemer et al., 1997). FM has been described as an illness predominantly of “middle-aged white women” (Buchwald, 1996), but this observation probably reflects
623
better access to medical care services by white women than a racial or ethnic predisposition to the disorder. It may also reflect the population density of people in localities where a preponderance of research studies on FM have been conducted in the USA and Europe (Croft et al., 1993; Henriksson and Burckhardt, 1996; Wolfe et al., 1997). Higher prevalence rates have been found among female offspring (Buskila et al., 1996) and relatives (Buskila and Neumann, 1997) of individuals with FM (see references in Ablin et al., 2006). A specific polymorphism in the 5-HT2A receptor gene (Bondy et al., 1999) and the promoter region of the serotonin transporter gene (Offenbaecher et al., 1999) have been linked to FM, and may predispose individuals with FM to develop psychiatric symptoms (Gurosy et al., 2001), particularly anxiety (Ablin et al., 2006). Polymorphisms have also been evaluated in genes controlling catecholamine catabolism and dopamine receptors in FM (Ablin et al., 2006) and several of these have been identified in disorders that are often comorbid with FM and associated with psychological distress (e.g. depression, irritable-bowel syndrome, CFS). These observations support the idea that FM exists along a spectrum of affective disorders (Ablin et al., 2006).
CHRONIC
FATIGUE SYNDROME
CFS occurs in women and men of all ages, including children and the elderly, but women are at greater risk. Among individuals seeking medical care in primary care practices, CFS affects 1 in 100 individuals (Komaroff and Buchwald, 1998), but the prevalence in the general population varies considerably in different regions of the USA. The prevalence of CFS was 0.42% from a community-based urban sample in Chicago, Illinois, and women and minority groups with lower socioeconomic status were most affected (Jason et al., 1999). The prevalence was estimated to be 0.24% in the general population in Wichita, Kansas (Reyes et al., 2003), and more recently estimated to be 2.5% in Georgia (Reeves et al., 2007). All of these studies showed higher prevalence in women compared to men, but, in contrast to earlier studies, both Latino and African American women showed equal prevalence with white women (Jason et al., 1999; Reeves et al., 2007). There is evidence for a familial aggregation of CFS based on higher concordance rates in monozygotic compared to dizygotic twins (Buchwald et al., 2001; Afari and Buchwald, 2003) and for greater exposure to childhood trauma in a population-based sample (Heim et al., 2006). Individuals with CFS often describe themselves as being healthy and quite active until the onset of a flu-like syndrome (Buchwald, 1996).
624
PSYCHIATRIC
C.A. LANDIS DISORDERS
Depression and history of psychiatric disorders place individuals at higher risk for developing FM and CFS (Goldenberg, 1999). Some of the so-called vegetative or atypical signs of depression, especially fatigue, sleep disturbance, and malaise, are quite similar to FM and CFS symptoms, but classic symptoms of major depression, including anhedonia, guilt, and lack of motivation, are not characteristic of FM or CFS patients. In fact, psychiatric interviews indicate that as many as 60% of patients with CFS did not have and never had evidence of major depression at the time of symptom onset (Komaroff and Buchwald, 1998). Nevertheless, lifetime prevalence of psychiatric disorders, in particular posttraumatic stress disorder, and depression is high (e.g., 50–75%) in patients with FM and CFS (Goldenberg, 1999; Sherman et al., 2000; Afari and Buchwald, 2003; Roy-Byrne et al., 2004). Psychiatric conditions are considered comorbid, but whether they precede or follow FM or CFS onset is not clear. Psychological distress is also common in FM and CFS and often attributed to health-seeking behaviors in patients seen in tertiary care centers (Buchwald, 1996). However, high levels of psychological distress were found in people with FM in a large community study in which anxiety and depression scores were the same as those reported in clinic populations (Wolfe et al., 1995). Psychological distress, anxiety, and depressed mood are common in patients with chronic pain and medical illnesses.
Associated conditions CONDITIONS
WITH OVERLAPPING SYMPTOMS
Individuals with FM and CFS are likely to suffer from comorbid conditions such as irritable bowel syndrome, multiple chemical sensitivity, temporomandibular joint disorder, myofascial pain syndrome, tension headache, autonomic nervous system disorders (e.g., dysautonomias), Gulf War illness, chronic sinusitis, and interstitial cystitis (Clauw and Chrousos, 1997; Aaron and Buchwald, 2001; Clauw and Crofford, 2003). In a twin control study of comorbid conditions in CFS, the twin with chronic fatigue had much higher rates of FM, irritable-bowel syndrome, temporomandibular joint disorder, tension headache, and chronic low-back pain compared to the nonfatigued twin (Aaron et al., 2001), but did not show evidence of neurally mediated hypotension (Poole et al., 2000). A female predominance is suggested for the cooccurrence of many of these disorders. Not unexpectedly, decreased pain threshold and a higher number of tender points were the most consistent objective
findings in a review of published literature (Aaron and Buchwald, 2001). Individuals with both FM and CFS are likely to report worse symptoms, see multiple health care providers, and have worse overall health status, greater impairment, and disability (Aaron and Buchwald, 2003).
SLEEP
DISORDERS
Individuals with FM and CFS may have comorbid sleep disorders, such as sleep-disordered breathing (SDB) (Jennum et al., 1993; Buchwald et al., 1994; LeBon et al., 2000; Fossey et al., 2004; Gold et al., 2004; Reeves et al., 2006), restless-legs syndrome (RLS) (Yunus and Aldag, 1996), and periodic leg movement disorder (PLMD) (Moldofsky et al., 1986). Patients with SDB, FM, and daytime sleepiness showed a greater number of oxygen desaturations/hour of sleep compared to FM patients without sleepiness in one study (Sarzi-Puttini et al., 2002), but not in another (Lario et al., 1996). Interestingly, a greater number of men with FM have shown evidence of sleep apnea compared to women with FM (May et al., 1993). Based on a single night of PSG, among patients with a diagnosis of CFS or a current psychiatric disorder, 41% had an abnormal Multiple Sleep Latency Test (MSLT) indicative of daytime sleepiness, 44% had sleep apnea, and 41% had idiopathic hypersomnia (Buchwald et al., 1994). LeBon and colleagues (2000) reported an incidence of 46% with an apnea–hypopnea index (AHI) > 5 in a sample of patients with CFS who were predominantly female (74%) with a mean age of 36.5 years, but 69% reported no daytime sleepiness. A clinic-based PSG study showed that > 50% of patients with CFS had SDB or PLMD (Fossey et al., 2004) and a population-based sample showed a significantly higher AHI index, but mean levels were not > 5, the threshold for the definition of obstructive sleep apnea (Reeves et al., 2006). Gold and colleagues (2004) reported that 3 weeks of continuous positive airway pressure treatment for women with FM and upper-airway resistance syndrome significantly reduced fatigue, pain, distress, gastrointestinal symptoms, and disability scores. Fatigue and sleepiness can be difficult to distinguish. The prevalence of excessive daytime sleepiness and primary sleep disorders such as SDB, RLS, and PLMD in patients with chronic widespread pain has not been determined in large population-based studies. A population-based study of unexplained fatigue showed increased odds ratio for nonrestorative sleep and restlessness, but not sleep apnea or excessive daytime sleepiness factors of the Sleep Assessment
SLEEP, PAIN, FIBROMYALGIA, AND CHRONIC FATIGUE SYNDROME 625 Questionnaire (Unger et al., 2004). Excessive daytime circadian rhythms in CFS is mixed; the circadian sleepiness in FM and CFS is controversial, with positive rhythm of core body temperature was not different in reports of self-reported sleepiness in some (Buchwald CFS patients from controls in one study (Hamilos et al., 1994; Morriss et al., 1997; Watson et al., 2004) et al., 2001), but core body temperature and melatobut not all studies (Moldofsky et al., 1988; Whelton nin secretion rhythms were dissociated in another et al., 1992). Subjective complaints have been verified (Williams et al., 1996). In a population-based sample, by MSLT in a recent co-twin control study (Watson lower morning and higher evening levels of salivary et al., 2004) but only 26% of a population-based sample cortisol were found in a very small number of indivishowed evidence of physiological sleepiness on MSLT duals with CFS compared to those with generalized (Reeves et al., 2006). fatigue not meeting critieria for CFS and nonfatigued controls and provides some evidence of altered diurnal cortisol rhythm (Nater et al., 2008).
Sleep disturbance in FM and CFS
Given complaints of widespread pain and distress in patients with FM or CFS and comorbid psychiatric disorders, it is not surprising that insomnia symptoms of difficulty falling and staying asleep and early-morning awakening are quite common. Self-report of sleep disturbance is one of eight possible symptoms in the case definition of CFS (Fukuda et al., 1994) and occurs in 78% of individuals with FM (Wolfe et al., 1990). Sleep disturbance is viewed as perpetuating FM and CFS symptoms of pain and fatigue, rather than as predisposing or precipitating factors in illness onset. Sleep disturbance precedes the development of CFS in only about 20% of patients but appears associated with relapse (Morriss et al., 1997). Yet, 50% of patients associate the onset of FM or CFS symptoms after trauma, surgery, or an infectious illness when sleep is likely to have been disturbed. Griffins and Peerson (2005) reported nearly a doubling of insomnia symptoms 3 months after elective surgery and hospitalization that was associated with preexisting insomnia (predisposing factor) and dysfunctional beliefs and attitudes about disturbed sleep (perpetuating factor). Whether persistent insomnia after trauma or an infectious illness plays a role in the development of FM or CFS has not been reported in prospective studies. Once the disorders are established, poor self-reported sleep quality adversely affects pain (Affleck et al., 1996) and mediates the relation between pain and fatigue in FM (Schaefer, 2003). In one study of sleep and pain in women with and without FM, fatigue was directly correlated with actigraphy-derived wake after sleep onset (WASO) and inversely correlated with sleep efficiency (SE) in the women with FM (Landis et al., 2003). Moldofsky (1995) suggested that altered circadian rhythms might explain the disturbed sleep patterns in FM and CFS. However, in a constant routine study no differences in circadian phase or amplitude were found in self-reported sleepiness, melatonin, cortisol, or core body temperature between women with and without FM (Klerman et al., 2001). The issue of altered
OBJECTIVE
MEASURES OF SLEEP IN FIBROMYALGIA
PSG has been studied extensively in FM (Moldofsky, 1995; Drewes, 1999; Mahowald and Mahowald, 2000b). Compared to control subjects of similar age, the most consistent findings from PSG studies show slightly longer sleep latencies, more wakefulness, and NREM stage 1 with reduced SE, most evident in the first half of the night in FM (Cote and Moldofsky, 1997; Shaver et al., 1997; Drewes, 1999; Landis et al., 2004b; Rizzi et al., 2004). Branco and colleagues (1994) reported reduced amounts of SW sleep, but the control subjects were nearly two decades younger than the FM patients. The most striking feature of sleep patterns in FM is the perception of poor sleep quality that is out of proportion to modest changes in objective measures of sleep. These findings are most evident when subjects are carefully selected on the basis of appropriate case definitions, compared to women of similar age, and screened for psychiatric disorders, particularly depression (Carette et al., 1995; Leventhal et al., 1995; Landis et al., 2004b). Insomnia in FM is considered secondary to pain or central sensitization, but no differences have been observed in sleep patterns in patients with primary insomnia compared to patients with chronic pain (Schneider-Helmert et al., 2001). Compared to controls, Rizzi and colleagues (2004) reported reduced SE, a higher arousal index, and significantly increased cyclic alternating pattern in FM. Finally, Burns and colleagues (2008) recently found an increased number of sleep stage shifts in patients with FM compared to controls and shorter duration of NREM stage 2 episodes that predicted higher pain intensity. Actigraphy has been used to measure sleep in FM (Korszum et al., 2002; Landis et al., 2003) and CFS (Kop et al., 2005), but the findings are not consistent. Patients with FM had similar levels of activity during the day but showed higher levels of activity at night compared to controls studied for 5–7 days (Korszum et al., 2002). No differences were found between
626 C.A. LANDIS patients and controls in actigraphy-derived WASO, SE, (Hauri and Hawkins, 1973), is not correlated with total sleep time, or fragmentation index studied over 3 symptom severity in all studies (Carette et al., 1995; days (Landis et al., 2003), but in another study sleep Leventhal et al., 1995), and is present with primary latency was longer and SE reduced compared to coninsomnia (Schneider-Helmert et al., 2001). Experimentrols (Kop et al., 2005). It could be argued that actigratal disruptions of SW sleep, as described previously, phy is not sensitive enough to quantify disturbed sleep have been associated with the emergence of lower pain in women with FM, but it has the distinct advantage of thresholds and with symptoms of fatigue and reduced enabling description of sleep and wake behavior couvigor (Moldofsky and Scarisbrick, 1976; Lentz et al., pled with activity levels and symptom reports for lon1999b), but the induction of alpha activity was only ger periods of time. observed in the initial study of Moldofsky and Scarisbrick (1976) and not replicated in two other studies OBJECTIVE MEASURES OF SLEEP IN CFS (Lentz et al., 1999b; Older et al., 1999). Roizenblatt and colleagues (2001) differentiated phasic versus Compared to FM, there are far fewer PSG studies in tonic alpha activity in an assessment of sleep physiolpatients with CFS. The findings of disturbed sleep in ogy and correlated this activity with pain in FM, but clinic studies are not consistent and, similar to FM, the analysis was biased in favor of analyzing only epiobjective findings are modest in comparison to patient sodes of NREM sleep that contained alpha activity complaints (Togo et al., 2008). Longer sleep onset and based on visual inspection. Phasic versus tonic alpha REM sleep latencies and lower amounts of REM sleep activity as the basis for symptoms in FM and CFS but no evidence of sleep fragmentation have been has been criticized because musculoskeletal symptoms reported compared to healthy controls (Moldofsky are reported in only a few patients with SDB who typiet al., 1988; Whelton et al., 1992). However, other studcally experience high rates of sleep fragmentation and ies have found evidence of sleep fragmentation and nonrestorative sleep (Mahowald and Mahowald, reduced SW sleep (Fischler et al., 1997). A significant 2000b). Further, EEG alpha activity during sleep varies first-night effect has been described in patients with considerably in recordings from multiple sites over the CFS with and without a psychiatric comorbidity (LeBon cortex that suggests different functional characteriset al., 2003). Perhaps because of the need to rule out a tics, including sleep maintenance, not necessarily sleep sleep disorder or depression as a basis of fatigue in disruption (Pivik and Harmon, 1995). CFS, most studies in clinic populations included only Observations of reduced delta power in FM provide a single night of PSG and focused on the identification additional information about altered sleep physiology of a primary sleep disorder or comparisons with and implicate supraspinal corticothalamic structures depressed patients (see references in Ball et al., in the mechanisms of sleep disturbances (Drewes, 2004). In a study of monozygotic twins discordant 1999). Because we and others have been unable to for CFS, the ill twins showed a higher AHI and more find evidence for alpha–delta sleep in FM patients NREM stage 3 and REM sleep, but other sleep variwith moderate levels of pain (Carette et al., 1995; ables were not different compared to the well twins Leventhal et al., 1995), we chose to quantify sleep (Ball et al., 2004). Only one previous study had spindle activity, an EEG indicator, considered imporreported increased stage 4 sleep in CFS (Zubieta tant for the induction and maintenance of NREM et al., 1993) and a higher stage 4 to stage 2 ratio was sleep (Steriade, 2000). We found that women with found in patients with CFS compared to those with FM had more pain and fewer mean spindles per minsleep apnea or healthy controls (LeBon et al., 2007). ute and per epoch of NREM stage 2 compared to age-matched, sedentary controls (Landis et al., NONRESTORATIVE SLEEP IN FM AND CFS 2004a). We also reported that pain pressure threshold Patients with FM and CFS often complain of nonrespredicted spindle incidence and time per NREM stage torative sleep and this pattern has been linked to alpha 2 epoch, after controlling for age and depression, two activity in NREM sleep (Moldofsky et al., 1975, 1988; variables associated with fewer sleep spindles. Moldofsky, 1990; Anch et al., 1991; Whelton et al., Reduced spindle activity also has been reported in 1992; Drewes, 1999). The alpha–delta hypothesis of nondepressed patients with chronic low-back pain nonrestorative sleep assumes that increased alpha (Harmon et al., 2002). It is plausible that reduced activity represents pain or nociception during sleep. spindle activity could reflect altered pain processing However, this pattern is not necessary or sufficient to and central sensitization at the level of thalamocortiexplain complaints of nonrestorative sleep in FM and cal networks that are important in sleep induction CFS. It was first described in psychiatric disorders and maintenance.
SLEEP, PAIN, FIBROMYALGIA, AND CHRONIC FATIGUE SYNDROME
Pathogenesis and pathophysiology The etiology and pathogenesis of FM and CFS are not known. In about 50% of those diagnosed, symptoms develop in the absence of any prior medical condition. However, the onset of symptoms in both FM and CFS often follows an infection or traumatic psychological or physical event in which sleep disturbances and pain are likely to co-occur. A general conceptual model of the pathogenesis of these disorders hypothesizes that susceptible individuals have a predisposition or genetic background that renders them highly sensitive to triggering events, such as an illness or a psychological or physical trauma. This event or series of events activates mediators involving CNS networks related to pain processing and modulation, along with neuroendocrine, autonomic, and immune systems such that symptoms of the primary illness persist, never completely resolve, or new symptoms develop (Clauw and Chrousos, 1997; Klimas, 1998; Clauw and Crofford, 2003; Abeles et al., 2007). The triggering event in FM is most often psychological or physical trauma; in CFS it is an infectious illness such as the flu. Sleep disturbances are considered secondary to abnormalities of pain processing with the induction of central sensitization and to dysregulation of the stress response system. Nevertheless, findings from a 4-hour sleep delay challenge study showed a blunted SW (delta) activity response in twins with CFS compared to their healthy cotwins, suggesting that the basic sleep drive was impaired (Armitage et al., 2007).
CENTRAL
SENSITIZATION IN
FM
AND
CFS
Considerable evidence exists to support the hypothesis that central sensitization is the basis for abnormal pain processing in FM, and possibly in CFS. Heightened pain perception in response to light touch (allodynia) and reduced pressure pain threshold (hyperalgesia) is consistent with central sensitization (Lautenbacher et al., 1994; McDermid et al., 1996; Bendsten et al., 1997; Pillemer et al., 1997; Carli et al., 2002; Okifuji and Turk, 2002; Staud and Rodriguez, 2006). Compared to patients with other types of chronic pain, patients with FM consistently report higher levels of pain in response to pressure applied at tender points, and heightened responses to thermal and ischemic pain stimuli (Carli et al., 2002). Patients with FM also show evidence of hyperalgesia regardless of whether pain stimuli are presented randomly or in a predictable manner (as with tender point assessment by dolorimetry) (Petske et al., 2000). In one fMRI study considerably more brain areas were activated and perceptions of pain intensity were increased in response to light
627
pressure in patients with FM compared to controls (Gracely et al., 2002). These findings were interpreted as evidence of cortical and subcortical augmented pain processing, indicative of a chronic hyperalgesic state and central sensitization. Imaging studies in FM have shown reduced resting blood flow patterns in the cerebral cortex and thalamus (Mountz et al., 1995; Kwiatek et al., 2000) that is consistent with imaging studies of patients with chronic neuropathic pain and thought to reflect a potential neuronal deficit during quiet wakefulness (Peyron et al., 2000). Additional evidence for central sensitization includes increased cerebrospinal fluid levels of substance P (Russell, 1998) and the ability of ketamine, an NMDA receptor antagonist, to relieve pain for extended periods of time in a subset of patients with FM (Sorensen et al., 1997). In addition to central sensitization, possible deficiencies in pain-inhibitory mechanisms have been found in FM (Lautenbacher and Rollman, 1997) and mechanisms associated with illness-induced hyperalgesia could play a role (Watkins and Maier, 2005). It has been established that cytokines alter CNS processing of pain, autonomic, neuroendocrine, and behavioral responses (Watkins and Maier, 2005), but the mechanisms are considered distinct from those involved with central sensitization. In addition, the role of cytokines in the pathogenesis and pathophysiology of FM and CFS has yet to be established (Staud and Rodriguez, 2006). Psychosocial factors, beliefs, and coping responses, in particular catastrophizing, have been shown to augment pain in FM, possibly by activating brain circuitry involved in mediating attentional, anticipatory, and emotional responses to nociceptive stimuli (Gracely et al., 2004).
DYSREGULATION OF IN FM AND CFS
THE STRESS SYSTEM
Dysregulation of the stress system has been hypothesized to lead to fatigue and to augment pain in FM and CFS (Clauw and Chrousos, 1997; Pillemer et al., 1997; Okifuji and Turk, 1999; Ursin and Eriksen, 2001; Clauw and Crofford, 2003; Van Houdenhove and Egle, 2004). The hypothalamic–pituitary–adrenal (HPA) and the locus coeruleus–norepinephrine systems are the main components of the stress system responses that are activated by pain, psychosocial (e.g., fear, novelty, anticipation of threat), and physical (e.g., heat, cold, restraint, surgery, trauma) stimuli (Sapolsky et al., 2000; Pacak and Palkovits, 2001). Corticotropin-releasing hormone and arginine vasopressin regulate the output of adrenocorticotropic hormone (ACTH), with subsequent activation of the
628
C.A. LANDIS
adrenal gland to secrete cortisol. Initial observations of basal HPA axis function suggested that patients with FM and CFS had abnormally low levels of plasma glucocorticoids (Demitrack and Crofford, 1998), but this has not been observed in subsequent studies (Parker et al., 2001). There is evidence for dysregulation of the HPA axis, but both exaggerated and blunted responses of ACTH and cortisol to pharmacologic challenge have been observed in FM and CFS, and the clinical significance of these observations in relation to symptoms remains unclear (Parker et al., 2001). Two reports support previous findings of blunted responses to challenge of ACTH and cortisol in FM (Calis et al., 2004) and CFS (Roberts et al., 2004) and suggest that subtle abnormalities in the responsiveness of the HPA axis could impact symptom severity. Depression, which is associated with abnormalities of the HPA axis, is a serious confound in many of these studies. Autonomic dysregulation has been observed in FM and CFS, but the nature of this dysregulation remains unclear. Nocturnal exaggerated sympathetic activity has been suggested as one pathway to disturbed sleep based on observations of increased low-frequency activity and reduced heart rate variability in FM (Martinez-Lavin et al., 1998) and during waking and sleep in CFS (Boneva et al., 2007). Patients with FM and CFS often have increased heart rates at rest compared to controls and sometimes show hypofunction of autonomic responses to challenge (e.g., exercise, cold pressor test, tilt table testing, and pharmacologic challenge) that could be indicative of impaired sympathetic nervous system responses (Okifuji and Turk, 2002; Timmers et al., 2002; Van Houdenhove and Egle, 2004). Neurally mediated hypotension manifested by hypotension with bradycardia (vasovagal reaction) or with tachycardia (vasodepressor reaction) and symptoms (e.g., light-headedness, dizziness, and nausea) has been reported in FM and CFS (Okifuji and Turk, 1999; Afari and Buchwald, 2003). However, a population-based study (Jones et al., 2005) and a controlled twin study (Poole et al., 2000) failed to find evidence of abnormal responses to tilt table testing in patients with CFS compared to controls. Physical deconditioning, which is very common in CFS and FM, and hydration status are important variables that could explain abnormal autonomic responses in some studies. Activation of the stress response is usually considered to lead to sleep disturbance, but disturbed sleep with altered neuroendocrine or autonomic function during sleep could contribute to altered regulation of the stress response in FM and CFS. Compared to controls, reduced levels of nocturnal prolactin and growth hormone have been observed in FM (Landis et al.,
2001), but no group differences were found in 24-hour measures of cortisol (Landis et al., 2004b). The clinical significance of lower levels of these sleep-related hormones is not known. However, prolactin has anxiolytic behavioral effects and has been shown to attenuate HPA responsiveness to stress activation (Torner et al., 2001). These observations suggest that lower nocturnal levels of prolactin could contribute to dysregulation of the stress system in FM and CFS.
DIAGNOSIS OF FM AND CFS Clinical presentation HISTORY FM and CFS are diagnosed on the basis of history and symptom report. Patients with severe fatigue, sleep disturbance, and pain should have a thorough history that includes assessment of medical and psychosocial circumstances, as well as changes in sleep patterns, surrounding the onset of symptoms. Careful history of prior illnesses, psychiatric disorders, alcohol or substance abuse, allergies, current prescription, overthe-counter medications, and herbal supplements should be ascertained. Making a diagnosis of either FM or CFS requires careful assessment to rule out underlying disorders that could account for symptoms, including other sleep disorders. Patients with complaints of daytime sleepiness should be evaluated for SDB, RLS, PLMD, and narcolepsy. In particular, a sleep history, beliefs about sleep, and an appraisal of the role sleep disturbances play in the exacerbation of symptoms needs to be assessed. This information will be important in the establishment of therapeutic goals.
PHYSICAL
FINDINGS
There have been no validated physical findings that are indicative of FM or of CFS (Fukuda et al., 1994). Many of the physical findings reported in the literature of subtle changes in immune, neuroendocrine, and autonomic abnormalities are not consistent across studies. This may reflect the heterogeneity of the samples or differences in the use or interpretation of case definitions among studies. Most pathologic evaluations of muscle tissue have revealed minor abnormalities and changes consistent with a sedentary lifestyle but no abnormalities in muscle function in FM (Geel, 1994). Subtle abnormalities of immune indicators have been described in some reports in both FM and CFS, but these are difficult to interpret and are of unknown clinical significance (Wallace et al., 1990; Moldofsky, 1995; Clauw and Chrousos, 1997; Landis et al., 2004b). Neurologic examination is usually unremarkable, although patients often have reduced pain thresholds, photophobia, paresthesias,
SLEEP, PAIN, FIBROMYALGIA, AND CHRONIC FATIGUE SYNDROME and signs of cognitive impairment, e.g., difficulty with concentration, attention, and memory. Substance P levels are elevated in cerebrospinal fluid and are considered a trait marker of FM (Russell, 1998) but spinal taps are not a routine aspect of a clinical examination in FM and CFS. All patients with symptoms consistent with FM or CFS should have a thorough physical examination, including a mental status examination and laboratory tests in order to rule out a specific treatable cause of the symptoms. Laboratory tests should include a complete blood count with differential, urinalysis, sedimentation rate, blood sugar, serum creatinine, and thyroid hormone (Fukuda et al., 1994; Salit et al., 1996).
FM and CFS treatment strategies FM and CFS are chronic disabling disorders that tend neither to progress nor to improve over time. Although some individuals do report overall improvement with pharmacological and behavioral therapies (Buchwald, 1996; Wolfe et al., 1997; Rossy et al., 1999; Whiting et al., 2001), many continue to have significant complaints of pain and fatigue (Kennedy and Felson, 1996). An overall approach to treatment of FM and CFS requires understanding and patience on the part of the physician and other health care providers. Symptoms are likely to wax and wane over time. Therapies need to be planned taking into account individual patient expectations related to potential outcomes and patients’ willingness to participate and adhere to the interventions (Mease, 2005). No one therapy will relieve all symptoms. Most intervention studies have used a wide variety of interventions and change in pain is the most common outcome measure in FM and a wide variety of physical, psychological, and qualityof-life outcome measures have been used in CFS. Despite a large literature on therapies for managing symptoms in FM and CFS, evidence-based guidelines have not been reported (Whiting et al., 2001; Goldenberg et al., 2004). In addition, patients with FM and CFS are likely to use a variety of complementary and alternative therapies and most of them have not been adequately studied (Holdcraft et al., 2003; Wahner-Roedler et al., 2005).
Nonpharmacologic and pharmacologic symptom management In general, combinations of nonpharmacologic/behavioral and pharmacologic therapies are most effective for relieving symptoms of FM and CFS, although there is evidence that intensive education alone will improve symptoms (Goldenberg et al., 2004). Low-intensity exercise and cognitive-behavioral therapies are both
629
quite effective for improving self-reported symptoms in FM (Rossy et al., 1999; Goldenberg et al., 2004) and hold promise in the treatment of CFS, particularly in the improvement of physical status and quality-oflife outcomes (Whiting et al., 2001). Low-intensity exercise needs to be carefully graded to avoid straining muscles and producing pain and also aggravating fatigue. Antidepressants, analgesics, and other medications with a CNS site of action are used in combination with cognitive-behavioral therapies, massage, muscle stretching/strengthening, and low-intensity exercise. In a meta-analysis of randomized, placebo-controlled trials antidepressants were found to improve sleep, fatigue, pain, and well-being, but not tender point pain (O’Malley et al., 2000). Although tricyclic antidepressants and selective serotonin reuptake inhibitors have been used to treat FM, amitriptyline is the antidepressant that has been the most studied and has the best efficacy for improving sleep and overall general well-being (see Goldenberg et al., 2004, for comparisons among various medications). Among analgesic medications, nonsteroidal antiinflammatory drugs are not particularly helpful for relieving pain in FM and CFS unless there is evidence of an underlying inflammatory process. Tramadol with acetaminophen is effective for reducing pain and stiffness (Goldenberg et al., 2004) and has been shown to improve quality of life (Bennett et al., 2005). Medications used in the treatment of neuropathic pain syndromes may be useful therapy. Gabapentin is used in the clinical management of pain in patients with FM and clinical trials are currently underway. Pregabalin, a second-generation anticonvulsant, is effective for neuropathic types of pain and has been shown in randomized clinical trials to reduce pain, disturbed sleep, and fatigue in FM compared to placebo (Crofford et al., 2005; Arnold et al., 2008). Patients with FM and CFS may be sensitive to medications and hence require carefully individualized dosing so as to avoid side-effects. In terms of dietary supplements, magnesium and S-adenosyl-L-methionine are effective in relieving symptoms (Holdcraft et al., 2003).
Management of sleep disturbance One therapeutic goal in the management of FM or CFS is to improve sleep. Presumably, improved sleep affects the perception of other symptoms and the ability of individuals with these disorders to carry out usual daytime activities better. A combination of pharmacological and nonpharmacological therapies is recommended. A low dose of antidepressant taken at bedtime is useful for enhancing sleep and analgesics taken during the day may relieve pain. Although
630 C.A. LANDIS selective serotonin reuptake inhibitors are commonly with complex interactions. Diagnosis of these disorders prescribed for patients with FM and CFS, they have depends on self-reported symptoms and their clinical documented adverse effects on sleep (Menefee et al., management is challenging for both the health care pro2000). The use of hypnotics in the treatment of sleep vider and the patient. Disturbed sleep is a common disturbance in patients with chronic pain is controversymptom and careful assessment is necessary to distinsial. Benzodiazepines may improve sleep, but they guish insomnia from a comorbid condition that may antagonize opioid analgesia (Levine et al., 1993; Gear require specific treatment, including psychiatric disoret al., 1997), and nonbenzodiazepine hypnotic drugs der, hypothyroidism, or other primary sleep disorder. (zaleplon, zolpidem, and eszopiclone) may be more Symptoms of FM and CFS persist but are not considered effective and safer with few daytime side-effects to get progressively worse over time. A combination (Menefee et al., 2000). Low-dose antidepressants of pharmacological, graded exercise and cognitivehave antihistaminergic and anticholinergic properties, behavioral therapy is the therapeutic approach which although their efficacy in treating sleep disturbances appears to be the most effective for symptom relief. in FM and CFS has not been evaluated, and they are SUMMARY AND RECOMMENDATIONS questionable for use with older women. Hypnotics are recommended only when insomnia is severe and There is no rational approach to the treatment of painnot on a routine basis, but patients with FM or CFS related sleep disturbance. This is not surprising given often find it difficult to refrain from their use. In a that so little research has been done on the nature of small sample of midlife women with FM, mean insompain-related sleep disturbance in patients with various nia scores increased substantially more than pain types of chronic pain. Further, it is not clear that pain scores during a 2-week drug washout period in prepaactually is the cause of disrupted sleep in patients with ration for a sleep laboratory study (Lentz et al., 1999a). chronic pain. Nociceptive stimuli lead to transient Patients should be encouraged to follow good sleep changes in the EEG and shifts to lighter stages of sleep hygiene practices: avoid caffeine and other stimulants and brief arousals, but these changes probably do not in the afternoon and evening; avoid alcohol, heavy reflect pain-related disturbed sleep in chronic condimeals, and exercise within a few hours of sleep; keep tions. Nociceptive stimuli have distinct effects on a regular sleep/wake schedule and get up at the same EEG activity and behavioral responses that are differtime every day; and sleep in a quiet, dark, cool environent during wakefulness and sleep, but these effects ment. As a basis for designing a sleep improvement have not been studied in the same people during plan, patients should keep a 2-week sleep diary to waking and sleep. It has long been postulated that a inform them about their sleep habits and to assist the vicious cycle of pain–poor sleep–pain occurs in health care provider in assessing insomnia severity. This patients with chronic pain (Moldofsky et al., 1975) assessment is essential for developing a more specific and daily diary data support this hypothesis (Affleck intervention plan. Cognitive-behavioral therapy strateet al., 1996), but data from objective measures of sleep gies for treating primary insomnia hold promise as a are less convincing. More research is required to eluciway to improve sleep, also potentially reducing pain date the nature of pain-related sleep disturbance using and fatigue, and their efficacy has been evaluated in a both self-report and objective measures of sleep and pilot study of patients with FM (Edinger et al., 2005). baseline and evoked measures of pain. The complaint of nonrestorative sleep and insomnia FM is a model of chronic widespread pain and CFS does not necessarily require a sleep center evaluation, is a model of widespread fatigue. Complaints of poor but may be necessary to rule out PLMD or SDB. The sleep far exceed modest changes in objective measures primary indication for referral to a sleep center is excesof sleep and are similar to individuals with some types sive daytime sleepiness, which could be indicative of of insomnia. Few comparative studies of patients with sleep apnea, narcolepsy, or PLMD. The recent finding these disorders have been done and could provide of reduced symptoms in patients with FM treated with insights into the nature of pain-related poor sleep. CPAP suggests that PSG evaluation and standard treatStudies comparing individuals with different levels of ment even for mild SDB may be helpful. illness severity or those in flare versus relapse and not taking CNS active medications that alter either Summary sleep or pain would enhance understanding about FM and CFS are complex chronic conditions that primardisturbed sleep and its relation to symptoms of the ily affect women. The etiology and pathogenesis of these disorders. Nonrestorative sleep is the most common disorders are unknown. The pathophysiology is likewise complaint in patients with pain yet the physiological poorly understood and involves multiple body systems basis of this symptom is unclear. Similar to current
SLEEP, PAIN, FIBROMYALGIA, AND CHRONIC FATIGUE SYNDROME models of the neurobiology of insomnia, altered activity in neuroendocrine and autonomic systems could be pathways to nonrestorative sleep in FM and CFS. Experimental manipulations, such as sleep delay or presleep stressors, which challenge sleep, neuroendocrine, and autonomic mechanisms, have the potential to reveal alterations during sleep not evident on baseline. From a theoretical perspective sleep quality may well mediate the relation between symptoms of pain and fatigue and quality of life, depressed mood, or other health outcomes. Intervention studies are needed that test the efficacy of interventions such as insomnia cognitivebehavioral therapy and its effects on relieving symptoms and improving health outcomes with the potential to prevent relapse.
ACKNOWLEDGMENT This study was supported by grants from the Center for Women’s Health and Gender Research, NR04001, NR081346, AT002108, and NR01118.
REFERENCES Aaron LA, Buchwald D (2001). A review of the evidence for overlap among unexplained clinical conditions. Ann Intern Med 134: 868–881. Aaron LA, Buchwald D (2003). Chronic diffuse musculoskeletal pain, fibromyalgia and co-morbid unexplained clinical conditions. Best Prac Res Clin Rheumatol 17: 563–574. Aaron LA, Herrell R, Ashton S et al. (2001). Comorbid clinical conditions in chronic fatigue. J Gen Intern Med 16: 24–31. Abeles AM, Pillinger MH, Solitar BM et al. (2007). Narrative review: the pathophysiology of fibromyalgia. Ann Intern Med 146: 726–734. Ablin JN, Cohen H, Buskila D (2006). Mechanisms of disease: genetics of fibromyalgia. Nat Clin Prac Rheum 2: 671–678. Afari N, Buchwald D (2003). Chronic fatigue syndrome: a review. Am J Psychiatry 160: 221–236. Affleck G, Urrows S, Tennen H et al. (1996). Sequential daily relations of sleep, pain intensity, and attention to pain among women with fibromyalgia. Pain 68: 363–368. American Academy of Sleep Medicine H (2007). Manual for the scoring of sleep and associated events: rules, terminology and technical specifications. American Academy of Sleep Medicine, Westchester, IL. Anch AM, Lue FA, MacLean AW et al. (1991). Sleep physiology and psychological aspects of the fibrositis (fibromyalgia) syndrome. Can J Psychol 45 (2): 179–184. Anderson ML, Tufik S (2000). Altered sleep and behavioral patterns of arthritic rats. Sleep Res Online 34: 161–167. Anderson ML, Tufik S (2003). Sleep patterns over 21-day period in rats with chronic constriction of sciatic nerve. Brain Res 984: 84–92.
631
Armitage R, Landis C, Hoffman R et al. (2007). The impact of a 4-hour delay on slow wave activity in twins discordant for chronic fatigue syndrome. Sleep 30: 657–662. Arnold LM, Russell IJ, Diri EW et al. (2008). A 14-week, randomized double-blinded, placebo-controlled monotherapy trial of pregabalin in patients with fibromyalgia. J Pain 9: 792–805. Ball N, Buchwald DS, Schmidt D et al. (2004). Monozygotic twins discordant for chronic fatigue syndrome. Objective measures of sleep. J Psychosom Res 56: 207–212. Basbaum AI, Jessell TM (2000). The perception of pain. In: ER Kandel, JA Schwartz, TM Jessell (Eds.), Principles of Neural Science. 4th edn. McGraw-Hill, New York, pp. 474–491. Becker N, Thomsen AB, Olsen AK et al. (1997). Pain epidemiology and health related quality of life in chronic non-malignant pain patients referred to a Danish multidisciplinary pain center. Pain 73: 393–400. Bendsten L, Norregaard J, Jensen R et al. (1997). Evidence of qualitatively altered nociception in patients with fibromyalgia. Arthritis Rheum 40: 98–102. Bennett GJ (1999). Opioids and painful peripheral neuropathy. In: E Kalso, HJ McQuay, EZ Wiesenfeld-Hallin (Eds.), Opioid Sensitivity of Chronic Noncancer Pain. IASP Press, Seattle, pp. 319–326. Bennett RM (1998). Disordered growth hormone secretion in fibromyalgia: a review of recent findings and a hypothesized etiology. Z Rheumatol 57 (Suppl 2): 72–76. Bennett RM (2004). In: The Fibromyalgia Construct – From Past to Future. Fibromyalgia Workshop: The Next Advances, November 11–12, Washington DC, pp. 21–35. Bennett GJ, Xie YK (1988). A peripheral mononeuropathy in rat that produces disorders of pain sensation like those seen in man. Pain 33: 87–107. Bennett RM, Schein J, Kosinski MR et al. (2005). Impact of fibromyalgia pain on health-related quality of life before and after treatment with tramadol/acetaminophen. Arthritis Rheum 53: 519–527. Bentley AJ, Newton S, Zio CD (2003). Sensitivity of sleep stages to painful thermal stimuli. J Sleep Res 12: 143–147. Bondy B, Spaeth M, Offenbaecher M et al. (1999). The T102C polymorphism of the 5-HT2A-receptor gene in fibromyalgia. Neurobiol Dis 6: 433–439. Boneva R, Decker MJ, Maloney EM et al. (2007). Higher heart rate and reduced heart rate variability persist during sleep in chronic fatigue syndrome: a population-based study. Auton Neurosci 137: 94–101. Branco J, Atalaia A, Pavia T (1994). Sleep cycles and alphadelta sleep in fibromyalgia syndrome. J Rheumatol 21: 1113–1117. Buchwald D (1996). Fibromyalgia and chronic fatigue syndrome. Similarities and differences. Rheum Clin North Am 22: 219–243. Buchwald D, Pascualy R, Bombardier C et al. (1994). Sleep disorders in patients with chronic fatigue. Clin Infect Dis Suppl 1: S68–S72. Buchwald D, Herrell R, Ashton S et al. (2001). A twin study of chronic fatigue. Psychosom Med 63: 936–943.
632
C.A. LANDIS
Burns JW, Crofford LJ, Chervin RD (2008). Sleep stage dynamics in fibromyalgia patients and controls. Sleep Med 9: 689–696. Buskila D, Neumann L (1997). Fibromyalgia syndrome (FM) and norarticular tenderness in relatives of patients with FM. J Rheumatol 24: 941–944. Buskila D, Neumann L, Hazanov I et al. (1996). Familial aggregation in the fibromyalgia syndrome. Semin Arthritis Rheum 26 (3): 605–611. Cairns BE, McErlane SA, Fragoso MC et al. (1996). Spontaneous discharge and peripherally evoked orofacial responses of trigemino-thalamic tract neurons during wakefulness and sleep. J Neurosci 16: 8149–8159. Calis M, Gokee C, Ates F et al. (2004). Investigation of the hypothalamic-pituitary-adrenal axis (HPA) by 1 microg ACTH test and metyrapone test in patients with primary fibromyalgia syndrome. J Endocrinol Invest 27: 42–46. Calvino B, Crepon-Bernard M, LeBars D (1987). Parallel clinical and behavioral studies of adjuvant arthritis in the rat: possible relationship with ‘chronic pain’. Behav Brain Res 24: 11–29. Carette S, Oakson G, Guimont C et al. (1995). Sleep electroencephalography and the clinical response to amitriptyline in patients with fibromyalgia. Arthritis Rheum 38 (9): 1211–1217. Carli G, Suman AL, Biasi G et al. (2002). Reactivity to superficial and deep stimuli in patients with chronic musculoskeletal pain. Pain 100: 259–269. Casey KL (1999). Forebrain mechanisms of nociception and pain: analysis through imaging. Proc Natl Acad Sci U S A 96: 7668–7674. Chang P-F, Arendt-Nielsen L, Graven-Nielsen T et al. (2002). Psychophysical and EEG response to repeated experimental muscle pain in humans: pain intensity encodes EEG activity. Brain Res Bull 59: 533–543. Chen ACN (2001). New perspectives in EEG/MEG brain mapping and PET/fMRI neuroimaging of human pain. Inter J Psychophysiol 42: 147–159. Chiu YH, Silman AJ, Macfarlane GJ et al. (2005). Poor sleep and depression are independently associated with a reduced pain threshold. Results of a population based study. Pain 115: 316–321. Clauw DJ (2007). Fibromyalgia: update on mechanisms and management. JCR 13: 102–109. Clauw DJ, Chrousos GP (1997). Chronic pain and fatigue syndromes: overlapping clinical and neuroendocrine feaures and potential pathogenic mechanisms. Neuroimmunomodulation 4: 134–153. Clauw DJ, Crofford LJ (2003). Chronic widespread pain and fibromyalgia: what we know, and what we need to know. Best Prac Res Clin Rheum 17: 685–701. Coderre TJ, Katz J, Vaccarino AL et al. (1993). Contribution of central neuroplasticity to pathological pain: review of clinical and experimental evidence. Pain 52: 259–285. Colpaert FC (1987). Evidence that adjuvant arthritis in the rat is associated with chronic pain. Pain 28: 201–222. Cooperman NR, Mullin FJ, Kleitman N (1934). Studies of the physiology of sleep XI. Further observations on the
effects of prolonged sleeplessness. Am J Physiol 107: 589–593. Cote KA, Moldofsky H (1997). Sleep, daytime symptoms, and cognitive performance in patients with fibromyalgia. J Rheumatol 24: 2014–2023. Craig AD (2003a). A new view of pain as a homeostatic emotion. Trends Neurosci 26: 303–307. Craig AD (2003b). Pain mechanisms: labeled lines versus convergence in central processing. Ann Rev Neurosci 26: 1–30. Crofford LJ, Rowbotham MC, Mease PJ et al. (2005). Pregabalin for the treatment of fibromyalgia syndrome. Arthritis Rheum 52: 1264–1273. Croft P, Rigby AS, Boswell R et al. (1993). The prevalence of chronic widespread pain in the general population. J Rheumatol 20 (4): 710–713. Demitrack MA, Crofford L (1998). Evidence for and pathophysiologic implications of hypothalamic-pituitaryadrenal axis dysregulation in fibromyalgia and chronic fatigue syndrome. Ann N Y Acad Sci 840: 684–697. Drewes AM (1999). Pain and Sleep Disturbances. Aalborg University, Aalborg, Denmark. Drewes AM, Arendt-Nielsen L (2001). Pain and sleep in medical diseases: interactions and treatment possibilities, a review. Sleep Res Online 4: 67–76. Drewes AM, Nielsen KD, Arendt-Nielsen L et al. (1997). The effect of cutaneous and deep pain on the electroencephalogram during sleep – an experimental study. Sleep 20: 632–640. Edinger JD, Wohlgemuth WK, Krystal AD et al. (2005). Behavioral insomia treatment of fibromyalgia: final report. Sleep 28 (Suppl A): 224. Edwards RR, Almeida DM, Klick B et al. (2008). Duration of sleep contributes to next-day pain report in the general population. Pain 37: 202–207. Fischler B, Le Bon O, Hoffmann G et al. (1997). Sleep anomalies in chronic fatigue syndrome. A comorbidity study. Neuropsychobiol 35: 115–122. Foo H, Mason P (2003). Brainstem modulation of pain during sleep and waking. Sleep Med Rev 7: 145–154. Fordyce WE (1976). Behavioral Methods for Chronic Pain and Illness. CV Mosby, St Louis. Fossey M, Libman E, Bailes S et al. (2004). Sleep quality and psychological adjustment in chronic fatigue syndrome. J Behav Med 27: 581–605. Frederickson CJ, Rechtschaffen A (1978). Effects of sleep deprivation on awakening thresholds and sensory evoked potentials in the rat. Sleep 1: 69–82. Friedberg F, Jason LA (2001). Chronic fatigue syndrome and fibromyalgia: clinical assessment and treatment. J Clin Psychol 57: 433–455. Fukuda K, Straus SE, Hickie I et al. (1994). The chronic fatigue syndrome: a comprehensive approach to its definition and study. Ann Intern Med 121: 953–959. Gear RW, Miaskowski C, Heller PH et al. (1997). Benzodiazepine mediated antagonism of opioid analgesia. Pain 71: 25–29. Geel SE (1994). The fibromyalgia syndrome: musculoskeletal pathophysiology. Semin Arthritis Rheum 23 (5): 347–353.
SLEEP, PAIN, FIBROMYALGIA, AND CHRONIC FATIGUE SYNDROME Gold AR, Dipalo F, Gold MS et al. (2004). Inspiratory airflow dynamics during sleep in women with fibromyalgia. Sleep 27: 459–466. Goldenberg DL (1999). Fibromyalgia syndrome a decade later. Arch Intern Med 159: 777–785. Goldenberg DL, Bruckhardt C, Crofford L (2004). Management of fibromyalgia syndrome. JAMA 292: 2388–2395. Gracely RH, Petzke F, Wolf JM et al. (2002). Functional magnetic resonance imaging evidence of augmented pain processing in fibromyalgia. Arthritis Rheum 46: 1333–1343. Gracely RH, Geisser ME, Giesecke T et al. (2004). Pain catastrophizing and neural responses to pain among persons with fibromyalgia. Brain 127: 835–843. Griffins MF, Peerson A (2005). Risk factors for insomnia after hospitalization. J Adv Nurs 49: 245–253. Gurosy S, Erdal E, Herken H et al. (2001). Association of T102C polymorphism of the 5-HT2A receptor gene with psychiatric status in fibromyalgia syndrome. Rheumatol Int 21: 58–61. Hamilos DL, Nutter D, Gershtenson J et al. (2001). Circadian rhythm of core body temperature in subjects with chronic fatigue syndrome. Clin Physiol 21: 184–195. Harmon K, Pivik RT, D’Eon JL et al. (2002). Sleep in depressed and nondepressed participants with low back pain: electroencephalographic and behavior findings. Sleep 25: 775–783. Hauri P, Hawkins DR (1973). Alpha-delta sleep. Electroencephal Clin Neurophysiol 34: 233–237. Heim C, Wagner D, Maloney E et al. (2006). Early adverse experience and risk for chronic fatigue syndrome. Arch Gen Psychiatry 63: 1258–1266. Henriksson C, Burckhardt CS (1996). Impact of fibromyalgia on everyday life: a study of women in the USA and Sweden. Disabil Rehabil 18 (5): 241–248. Hernandez-Peon R, O’Flaherty JJ, Mazzuchelli-O’Flaherty AL (1965). Modifications of tactile evoked potentials at the spinal trigeminal sensory nucleus during wakefulness and sleep. Exp Neurol 13: 40–57. Hicks RA, Moore JD, Findley P et al. (1978). REM sleep deprivation and pain thresholds in rats. Percept Mot Skills 47: 848–850. Hicks RA, Coleman DD, Ferrante F et al. (1979). Pain thresholds in rats during recovery from REM sleep deprivation. Percep Motor Skills 48: 687–690. Holdcraft LC, Assefi N, Buchwald D (2003). Complementary and alternative medicine in fibromyalgia and related syndromes. Best Prac Res Clin Rheum 17: 667–683. Jason LA, Richman JA, Rademaker AW et al. (1999). A community-based study of chronic fatigue syndrome. Arch Intern Med 159: 2129–2137. Jennum P, Drewes AM, Andreasen A et al. (1993). Sleep and other symptoms in primary fibromyalgia and in healthy controls. J Rheumatol 20: 1756–1759. Jones JF, Nicholson A, Nisenbaum R et al. (2005). Orthostatic instability in a population-based study of chronic fatigue syndrome. Am J Med 118: 1415.e19–1415.e28. Kennedy M, Felson D (1996). A prospective long-term study of fibromyalgia syndrome. Arthritis Rheum 39 (4): 682–685.
633
Klerman EB, Goldenberg DL, Brown EN et al. (2001). Circadian rhythms of women with fibromyalgia. J Clin Endocrinol Metab 86: 1034–1039. Klimas N (1998). Pathogenesis of chronic fatigue syndrome and fibromyalgia. Growth Horm IGF Res 8: 123–126. Komaroff AL, Buchwald D (1998). Chronic fatigue syndrome: an update. Annu Rev Med 49: 1–13. Kontinen VK, Ahnaou A, Drinkenberg WHIM et al. (2003). Sleep and EEG patterns in the chronic constriction injury model of neuropathic pain. Physiol Behav 78: 241–246. Kop WJ, Lyden A, Berlin AA et al. (2005). Ambulatory monitoring of physical activity and symptoms in fibromyalgia and chronic fatigue syndrome. Arthritis Rheum 52: 296–303. Korszum A, Young EA, Englegerg NC et al. (2002). Use of actigraphy for monitoring sleep and activity levels in patients with fibromyalgia and depression. J Psychosom Res 52: 439–443. Kunderman B, Spernal J, Huber MT et al. (2004). Sleep deprivation affects thermal pain thresholds but not somatosensory thresholds in healthy volunteers. Psychosom Med 66: 932–937. Kwiatek R, Barnden L, Tedman R et al. (2000). Regional cerebral blood flow in fibromyalgia. Arthritis Rheum 43: 2823–2833. Landis CA (2005). Partial and sleep state selective deprivation. In: CA Kushida (Ed.), Sleep Deprivation Basic Science, Physiology, and Behavior, Lung Biology in Health and Disease, vol. 192. Marcel Dekker, New York, pp. 81–102. Landis CA, Robinson CR, Levine JD (1988). Sleep fragmentation in the arthritic rat. Pain 34: 93–99. Landis CA, Levine JD, Robinson CR (1989). Decreased slow-wave and paradoxical sleep in a rat model of chronic pain. Sleep 12: 167–177. Landis CA, Lentz MJ, Rothermel J et al. (2001). Decreased nocturnal levels of prolactin and growth hormone in women with fibromyalgia. J Clin Endocrin Metab 86: 1672–1678. Landis CA, Frey CA, Lentz MJ et al. (2003). Self-reported sleep quality and fatigue correlates with actigraphy sleep indicators in midlife women with fibromyalgia. Nurs Res 54: 140–147. Landis CA, Lentz MJ, Rothermel J et al. (2004a). Decreased sleep spindles and spindle activity in midlife women with fibromyalgia. Sleep 741–750. Landis CA, Lentz MJ, Tsuji J et al. (2004b). Pain, psychological variables, sleep quality and natural killer cell activity in midlife women with and without fibromyalgia. Brain Behav Immun 18: 304–313. Lario BA, Valdivielso JLA, Lopez JA et al. (1996). Fibromyalgia syndrome: overnight falls in arterial oxygen saturation. Am J Med 101: 54–60. Lautenbacher S, Rollman GB (1997). Possible deficiencies of pain modulation in fibromyalgia. Clin J Pain 13: 189–196. Lautenbacher S, Rollman GB, McCain GA (1994). Multimethod assessment of experimental and clinical pain in patients with fibromyalgia. Pain 59: 45–53.
634
C.A. LANDIS
Lavie P, Epstein R, Tzischinsky O et al. (1992). Actigraphic measurements of sleep in rheumatoid arthritis: comparison of patients with low back pain and health controls. J Rheumatol 19: 362–365. Lavigne G, Zucconi M, Castronovo C et al. (2000). Sleep arousal response to experimental thermal stimulation during sleep in human subjects free of pain and sleep problems. Pain 84: 283–290. Lavigne GJ, Brousseau M, Kato T et al. (2004). Experimental pain perception remains equally active over all sleep stages. Pain 110: 646–655. LeBon O, Fischler B, Hoffman JR et al. (2000). How significant are primary sleep disorders and sleepiness in the chronic fatigue syndrome? Sleep Res Online 3: 43–48. LeBon O, Minner P, Moorsel CV et al. (2003). First-night effect in the chronic sleep syndrome. Psychiatry Res 120: 191–199. LeBon O, Neu D, Valente F et al. (2007). Paradoxical NREMS distribution in ‘pure’ chronic fatigue patients: a comparison with sleep apnea-hypopnea patients and healthy control subjects. J Chronic Fatigue Syndr 14: 45–59. Lentz M, Hao J, Buchwald D et al. (1999a). Sleep and pain symptoms in women with fibromyalgia, on and off medication. Commun Nurs Res 32: 183. Lentz MJ, Landis CA, Rothermer J et al. (1999b). Effects of selective slow wave sleep disruption on musculoskeletal pain and fatigue in middle aged women. J Rheumatol 26 (7): 1586–1592. Leung CG, Mason P (1999). Physiological properties of medullary raphe neurons during sleep and waking. J Neurophysiol 81: 584–595. Leventhal L, Freundlich B, Lewis J et al. (1995). Controlled study of sleep parameters in patients with fibromyalgia. J Clin Rheumatol 1 (2): 110–113. Levine JD (1998). New directions in pain research: molecules to maladies. Neuron 20: 649–654. Levine JD, Fields HL, Basbaum AI (1993). Peptides and the primary afferent nociceptor. J Neurosci 13: 2273–2286. McDermid AJ, Rollman GB, McCain GA (1996). Generalized hypervigilance in fibromyalgia: evidence of perceptual amplification. Pain 66: 133–144. Mahowald ML, Mahowald MW (2000a). Nighttime sleep and daytime functioning (sleepiness and fatigue) in well-defined chronic rheumatic diseases. Sleep Med 1: 179–193. Mahowald ML, Mahowald MW (2000b). Nighttime sleep and daytime functioning (sleepiness and fatigue) in less well-defined chronic rheumatic diseases with particular reference to the ‘alpha-delta NREM sleep anomaly’. Sleep Med 1: 195–207. Majer M, Jones JF, Unger ER et al. (2007). Perception versus polysomnographic assessment of sleep in CFS and non-fatigued control subjects: results from a populationbased study. BMC Neurol 7: 40. Martinez-Lavin M, Hermosillo AG, Rosas M et al. (1998). Circadian studies of autonomic nervous balance in patients with fibromyalgia. Arthritis Rheum 41: 1966–1971.
Mason P, Escobebo I, Gurgin C et al. (2001). Nociceptive responsiveness during slow-wave sleep and waking in the rat. Sleep 24: 32–38. May KP, West SG, Baker MR et al. (1993). Sleep apnea in male patients with the fibromyalgia syndrome. Am J Med 94: 505–508. May ME, Harvey MT, Valdovinos MG et al. (2005). Nociceptor and age specific effects on REM sleep deprivation induced hyperalgesia. Behav Brain Res 159: 89–94. Mease P (2005). Fibromyalgia syndrome: review of clinical presentation, pathogenesis, outcome measures and treatment. J Rheumatol Suppl 75: 6–21. Melzack R, Wall PD (1965). Pain mechanisms: a new theory. Science 150: 971–979. Menefee LA, Cohen MJM, Anderson WR et al. (2000). Sleep disturbance and nonmalignant chronic pain: a comprehensive review of the literature. Pain Med 1: 156–172. Mersky H, Bogduk N (Eds.), (1994). Classification of Chronic pain: Description of Chronic Pain Syndromes and Definition of Pain Terms. International Association for the Study of Pain Press, Seattle. Moldofsky H (1990). The contribution of sleep–wake physiology to fibromyalgia. Adv Pain Res Ther 17: 227–240. Moldofsky H (1995). Sleep, neuroimmune and neuroendocrine functions in fibromyaglia and chronic fatigue. Adv Neuroimmunol 9: 35–96. Moldofsky H (2001). Sleep and pain. Sleep Med Rev 5: 385–396. Moldofsky H, Scarisbrick P (1976). Induction of neurasthenic musculoskeletal pain syndrome by selective sleep stage deprivation. Psychosom Med 38 (1): 35–43. Moldofsky H, Scarisbrick P, England R et al. (1975). Musculoskeletal symptoms and non-REM sleep disturbance in patients with fibrositis syndrome and healthy subjects. Psychosom Med 37: 341–351. Moldofsky H, Tullis C, Lue FA (1986). Sleep related myoclonus in rheumatic pain modulation disorder (Fibrositis Syndrome). J Rheumatol 13: 614–617. Moldofsky H, Saskin P, Lue FA (1988). Sleep and symptoms in fibrositis syndrome after a febrile illness. J Rheumatol 15: 1701–1704. Monassi CR, Bandler R, Keay KA (2003). A subpopulation of rats show social and sleep–waking changes typical of chronic neuropathic pain following peripheral nerve injury. Eur J Neurosci 17: 1907–1920. Morin CM, Gibson D, Wade J (1998). Self-reported sleep and mood disturbance in chronic pain patients. Clin J Pain 14: 311–314. Morriss RK, Wearden AJ, Battersby L (1997). The relation of sleep difficulties to fatigue, mood and disability in chronic fatigue syndrome. J Psychosom Res 42: 597–605. Mountz JM, Bradley LA, Modell JG et al. (1995). Fibromyalgia in women. Arthritis Rheum 38: 926–938. Nater UM, Youngblood LS, Jones JF et al. (2008). Alternations in diurnal salivary cortisol rhythm in a populationbased sample of cases with chronic fatigue syndrome. Psychosomatic Med 70: 298–305.
SLEEP, PAIN, FIBROMYALGIA, AND CHRONIC FATIGUE SYNDROME National Sleep Foundation JF (1996). Adult Public’s Experiences with Nighttime Pain. Gallup Organization, Princeton. Nicassio PM, Moxham EG, Schuman CE et al. (2002). The contribution of pain, reported sleep quality, and depressive symptoms to fatigue in fibromyalgia. Pain 100: 271–279. Offenbaecher M, Bondy B, de Jonge S et al. (1999). Possible association of fibromyalgia with a polymorphism in the serotonin transporter gene regulatory region. Arthritis Rheum 42: 2482–2488. Ohayon MA (2005). Relationship between chronic painful physical condition and insomnia. J Psychiatr Res 39: 151–159. Okifuji A, Turk DC (1999). Fibromyalgia search for mechanisms and effective treatment. In: RJ Gatchel, DC Turk (Eds.), Psychosocial Factors in Pain: Clinical Perspectives. Guildford, New York, chapter 15. Okifuji A, Turk DC (2002). Stress and psychophysiological dysregulation in patients with fibromyalgia syndrome. Appl Psychophysiol Biofeedback 27: 129–141. Older SA, Battafarano DF, Canning CA et al. (1999). The effects of delta wave sleep interruption on pain thresholds and fibromyalgia-like symptoms on healthy subjects: correlations with insulin-like growth factor I. J Rheumatol 25 (6): 1180–1186. O’Malley PG, Balden E, Tomkins G et al. (2000). Treatment of fibromyalgia with antidepressants – a meta-analysis. J Gen Intern Med 15: 656–666. Onen S, Alloui A, Gross A et al. (2001a). The effects of total sleep deprivation, selective sleep interruption and sleep recovery on pain tolerance thresholds in healthy subjects. J Sleep Res 10: 35–42. Onen S, Alloui A, Jourcan D et al. (2001b). Effects of rapid eye movement (REM) sleep deprivation on pain sensitivity in the rat. Brain Res 900: 261–267. Pacak K, Palkovits M (2001). Stressor specificity of central neuroendocrine responses: implications for stress-related disorders. Endocrine Rev 22: 502–548. Parker AJR, Wessely S, Cleare AJ (2001). The neuroendocrinology of chronic fatigue syndrome and fibromyalgia. Psychol Med 31: 1331–1345. Petske F, Clauw DJ, Khine A et al. (2000). Increased pain sensitivity in fibromyalgia: effect of two types of stimuli and ascending versus random modes of presentation. Arthritis Rheum 43 (Suppl 9): S173. Peyron R, Laurent B, Garcia-Larrea L (2000). Functional imaging of brain responses to pain. A review and metaanalyses. Neurophysiol Clin 30: 263–288. Pilcher JJ, Huffcutt AI (1996). Effects of sleep deprivation on performance: a meta-analysis. Sleep 19: 318–326. Pillemer SR, Bradley LA, Crofford LJ et al. (1997). The neuroscience and endocrinology of fibromyalgia. Arthritis Rheum 40 (11): 1928–1939. Pilowsky I, Crettenden I, Townley M (1985). Sleep disturbance in pain clinic patients. Pain 23: 27–33. Pivik RT, Harmon K (1995). A reconceptualization of EEG alpha activity as an index of arousal during sleep: all alpha activity is not equal. J Sleep Res 4: 131–137.
635
Poole J, Herrell R, Ashton S et al. (2000). Results of isoproterenol tilt table testing in monozygotic twins discordant for chronic fatigue syndrome. Arch Intern Med 160: 3461–3468. Portas CM, Krakow K, Allen P et al. (2000). Auditory processing across the sleep–wake cycle: simultaneous EEG and fMRI monitoring in humans. Neuron 28: 991–999. Price DD (2000). Psychological and neural mechanisms of the affective dimension of pain. Science 288: 1769–1772. Radhakrishnan V, Tsoukatos J, Davis KD et al. (1999). A comparison of the burst activity of lateral thalamic neurons in chronic pain and non-pain patients. Pain 80: 567–575. Raja SN, Meyer RA, Campbell JN (1988). Peripheral mechanisms of somatic pain. Anesthesiology 68: 571–590. Raymond I, Nielsen TA, Lavigne G et al. (2001). Quality of sleep and its daily relationship to pain intensity in hospitalized adult burn patients. Pain 92: 381–388. Rechtschaffen A, Hauri P, Zeitlin M (1966). Auditory awakening thresholds in REM and NREM sleep stages. Percept Mot Skills 22: 927–942. Redeker NS, Ruggerio J, Hedgers C (2004). Patterns and predictors of sleep pattern disturbance after cardiac surgery. Res Nurs Health 27: 217–224. Reeves WC, Heim C, Maloney EM et al. (2006). Sleep characteristics of persons with chronic fatigue syndrome and non-fatigued controls: results from a population-based study. BMC Neurol 6: 41. Reeves WC, Jones JF, Maloney EM et al. (2007). Prevalence of chronic fatigue syndrome in metropolitan, urban, and rural Georgia. Popul Health Metr 5: 5. Reyes M, Nisenbaum R, Hoaglin DC et al. (2003). Prevalence and indicence of chronic fatigue syndrome in Wichita, Kansas. Arch Intern Med 163: 1530–1536. Richman JA, Jason LA, Taylor RR et al. (2000). Feminist perspectives on the social construction of chronic fatigue syndrome. Health Care Women Intern 21: 173–185. Rinaldi PC, Young RF, Albe-Fessard D et al. (1991). Spontaneous neuronal hyperactivity in the medial and intralaminar thalamic nuclei of patients with deafferentiation pain. J Neurosurg 74: 415–421. Rizzi M, Sarzi-Puttini P, Atzeni F et al. (2004). Cyclic alternating pattern: a new marker of sleep alteration in patients with fibromyalgia? J Rheumatol 31: 1193–1199. Roberts AD, Wessely S, Chalder T et al. (2004). Salivary cortisol responses to awakening in chronic fatigue syndrome. Br J Psychiatry 184: 136–141. Roehrs T, Roth T (2005). Sleep and pain: interaction of two vital functions. Semin Neurol 25: 106–116. Roizenblatt S, Moldofsky H, Benedito-Silva AA et al. (2001). Alpha sleep characteristics in fibromyalgia. Arthritis Rheum 44: 222–230. Rossy LA, Buckelew SP, Dorr N et al. (1999). A meta-analysis of fibromyalgia treatment interventions. Ann Behav Med 21 (2): 180–191. Roy-Byrne P, Smith WR, Golderg J et al. (2004). Posttraumatic stress disorder among patients with chronic pain and chronic fatigue. Psychol Med 34: 363–368.
636
C.A. LANDIS
Russell IJ (1998). Advances in fibromyalgia: possible role for central neurochemicals. Am J Med Sci 315 (6): 377–384. Salit IE, Vancouver Chronic Fatigue Syndrome Consensus Group (1996). The chronic fatigue syndrome: a position paper. J Rheumatol 23: 540–544. Sapolsky RM, Romero M, Munck AU (2000). How do glucocorticoids influence stress responses? Integrating permissive, suppressive, stimulatory, and preparative actions. Endocrine Rev 21: 55–89. Sarzi-Puttini P, Rizzi M, Andreoli A et al. (2002). Hypersomnolence in fibromyalgia syndrome. Clin Exp Rheumatol 20: 69–72. Satinoff E, Drucker-Colin RR, Hernandez-Peon R (1970). Paleocortical excitability and sensory filtering during REM sleep deprivation. Physiol Behav 7: 103–106. Satoh T, Eguchi K, Watabe K et al. (1980a). Attenuation during paradoxical sleep of signals from tooth pulp to thalamus. Brain Res Bull 5: 547–551. Satoh T, Harada Y, Watabe K et al. (1980b). Presynaptic inhibition of tooth pulp afferents in the trigeminal nucleus during REM sleep. Sleep 2: 363–366. Schaefer KM (2003). Sleep disturbances linked to fibromyalgia. Holist Nurs Pract 17: 120–127. Schmaling KB, Fiedelak JI, Katon WJ et al. (2003). Prospective study of the prognosis of unexplained chronic fatigue in a clinic-based cohort. Psychosom Med 65: 1047–1054. Schneider-Helmert D, Whitehouse I, Kumar A et al. (2001). Insomnia and alpha sleep in chronic non-organic pain as compared to primary insomia. Neuropsycholobiology 43: 54–58. Shaver JLF, Lentz M, Landis CA et al. (1997). Sleep, psychological distress, and stress arousal in women with fibromyalgia. Res Nurs Health 20: 247–257. Sherman JJ, Turk DC, Okifuji A (2000). Prevalence and impact of posttraumatic stress disorder-like symptoms on patients with fibromyalgia syndrome. Clin J Pain 16: 127–134. Siegel DM, Janeway D, Baum J (1998). Fibromyalgia syndrome in children and adolescents: clinical features at presentation and status at follow-up. Pediatrics 101: 377–382. Smith MT, Haythornthwaite JA (2004). How do sleep disturbance and chronic pain inter-relate? Insights from the longitudinal and cognitive-behavioral clinical trials literature. Sleep Med Rev 8: 119–132. Soja PJ, Pang W, Taepavarapruk N et al. (2001a). On the reduction of spontaneous and glutamate-driven spinocerebellar and spinoreticular tract neuronal activity during active sleep. Neuroscience 104: 199–206. Soja PJ, Pang W, Taepavarapruk N et al. (2001b). Spontaneous spike activity of spinoreticular tract neurons during sleep and wakefulness. Sleep 24: 18–25. Sorensen J, Bengtsson A, Ahlner J et al. (1997). Fibromyalgia – are there different mechanisms in the processing of pain? A double blind crossover comparison of analgesic drugs. J Rheumatol 24: 1615–1621. Staud R, Rodriguez ME (2006). Mechanisms of disease: pain in fibromyalgia syndrome. Nat Clin Prac Rheum 2: 90–98.
Steriade M (2000). Corticothalamic resonance, states of vigilance and mentation. Neuroscience 101: 243–276. Steriade M, McCormick DA, Sejnowski TJ (1993). Thalamocortical oscillations in the sleeping and aroused brain. Science 262: 679–685. Tan EM, Sugiura K, Gupta S (2002). The case definition of chronic fatigue syndrome. J Clin Immunol 22: 8–12. Terman GM, Shavit Y, Lewis JW et al. (1984). Intrinsic mechanisms of pain inhibition: activation of the stress response. Science 226: 1270–1277. Timmers HJ, Wieling W, Soetekouw PM et al. (2002). Hemodynamic and neurohormonal responses to head-up tilt in patients with chronic fatigue syndrome. Clin Auton Res 12: 273–280. Togo F, Natelson BH, Cherniack NS et al. (2008). Sleep structure and sleepiness in chronic fatigue syndrome with or without coexisting fibromyalgia. Arthritis Res Ther 10: R56. Torner L, Toschi N, Pohlinger A et al. (2001). Anxiolytic and anti-stress effects of brain prolactin: improved efficacy of antisense targeting of the prolactin receptor by molecular modeling. J Neurosci 21: 3207–3214. Treede RD, Meyer RA, Raja SN et al. (1992). Peripheral and central mechanisms of cutaneous hyperalgesia. Prog Neurobiol 38: 397–421. Ukponmwan OE, Rupreht J, Dzoljic MR (1984). REM sleep deprivation decreases the antiniciceptive property of enkephalinase-inhibition, morphine, and cold-water swim. Gen Pharmacol 15: 255–258. Unger ER, Nisenbaum R, Moldofsky H et al. (2004). Sleep assessment in a population-based study of chronic fatigue syndrome. BMC Neurol 4: 1–9. Ursin H, Eriksen HR (2001). Sensitization, subjective health complaints, and sustained arousal. Ann N Y Acad Sci 933: 119–129. Valente RM (1998). Comment. Fibromyalgia: wizards at odds? Clin J Pain 14: 79–82. Van Houdenhove B, Egle UT (2004). Fibromyalgia: a stress disorder? Psychother Psychosom 73: 267–275. Wahner-Roedler DL, Elkin PL, Vincent A et al. (2005). Use of complmentary and alternative medical therapies by patients referred to a fibromyalgia treatment program at a tertiary care center. Mayo Clin Proc 80: 55–60. Wall PD (1988). Stability and instability of central pain mechanisms. In: R Dubner, GF Gebhart, MR Bond (Eds.), Proceedings of the Vth World Congress on Pain. Elsevier Science, Amsterdam p. 24.13. Wallace DJ, Peter JB, Bowman RL et al. (1990). Fibromyalgia, Cytokines, Fatigue Syndromes, and Immune Regulation. Advances in Pain Research and Therapy, vol. 17, Raven Press, New York, pp. 277–287. Watkins LR, Maier S (2005). Immune regulation of central nervous system functions: from sickness responses to pathological pain. J Intern Med 257: 139–155. Watkins LR, Wiertelak EP, Goehler LE et al. (1994). Neurocircuitry of illness-induced hyperalgesia. Brain Res 639: 283–299.
SLEEP, PAIN, FIBROMYALGIA, AND CHRONIC FATIGUE SYNDROME Watson NF, Jacobsen C, Goldberg J et al. (2004). Subjective and objective sleepiness in monozygotic twins discordant for chronic fatigue syndrome. Sleep 27: 973–977. Weigent DA, Bradley LA, Blalock JE et al. (1998). Current concepts in the pathophysiology of abnormal pain perception in fibromyalgia. Am J Med Sci 315: 405–412. Whelton CL, Salit I, Moldofsky H (1992). Sleep, Epstein– Barr virus infection, musculoskeletal pain, and depressive symptoms in chronic fatigue syndrome. J Rheumatol 19: 939–943. White KP, Speechley M, Harth M et al. (1999). The London fibromyalgia epidemiology study: comparing the deographic and clinical characteristics in 100 random community cases of fibromyalgia versus controls. J Rheumatol 26: 1577–1585. White KP, Nielson WR, Harth M et al. (2002). Chronic widespread musculoskeletal pain with or without fibromyalgia: psychological distress in a representative community adult sample. J Rheumatol 29: 588–594. Whiting P, Bagnall A, Sowden AJ et al. (2001). Interventions for the treatment and management of chronic fatigue syndrome. JAMA 286: 1360–1368. Williams G, Pirmohamed J, Minors D et al. (1996). Dissociation of body-temperature and melatonin secretion circadian rhythms in patients with chronic fatigue syndrome. Clin Physiol 16: 327–337. Willis WD (1988). Anatomy and physiology of descending control of nociceptive responses of dorsal horn neurons: comprehensive review. In: HL Fields, JM Besson (Eds.), Progress in Brain Research, vol. 77. Elsevier, Amsterdam, pp. 1–29.
637
Wilson KG, Watson ST, Currie SR (1998). Daily diary and ambulatory monitoring of sleep in patients with insomnia associated with chronic musculoskeletal pain. Pain 75: 75–84. Wittig RM, Zorick FJ, Blumer D et al. (1982). Disturbed sleep in patients complaining of chronic pain. J Nerv Ment Dis 170: 429–431. Wolfe C, Chong M-S (1993). Preemptive analgesia – treating postoperative ain by preventing the establishment of central sensitization. Anesth Analg 77: 362–379. Wolfe C, Salter MW (2000). Neuronal plasticity: increasing the gain in pain. Science 288: 1765–1768. Wolfe F, Smythe H, Yunus M et al. (1990). The American College of Rheumatology 1990 criteria for the classification of fibromyalgia. Report of the multicenter criteria committee. Arthritis Rheum 33: 160–172. Wolfe F, Ross K, Anderson J et al. (1995). The prevalence and characteristics of fibromyalgia in the general population. Arthritis Rheum 38 (1): 19–28. Wolfe F, Anderson J, Harkness D et al. (1997). A prospective, longitudinal, multicenter study of service utilization and costs in fibromyalgia. Arthritis Rheum 40 (9): 1560–1570. Yunus M (1992). Towards a model of pathophysiology of fibromyalgia: aberrant central pain mechanisms with peripheral modulation. J Rheumatol 19: 846–849. Yunus M, Aldag JC (1996). Restless legs syndrome and leg cramps in fibromyalgia syndrome: a controlled study. BMJ 312: 1339. Zubieta JK, Demitrack MA, Shipley JE et al. (1993). Sleep EEG in chronic fatigue syndrome: comparison with major depression. Biol Psychiatry 33: 73A–74A.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 40
Women and sleep JOYCE A. WALSLEBEN * Division of Pulmonary, Critical Care and Sleep Medicine, New York University School of Medicine, New York, NY, USA
Differences in the sleep of males and females have been documented across multiple studies. Humans begin to form various stages of sleep around the fourth month of life. Sleep architecture continues to evolve throughout childhood and adolescence and subtle differences of architecture between sexes may exist at times during this period. Sleep then reaches a fairly stable period until midlife when gender differences begin to be more noticeable and suggest a female advantage. Objective tests would tend to indicate that women sleep “better” than men. However, subjective studies tend to show that women complain of more insomnia and more pain and stress-related interference of sleep than men (Table 40.1). This chapter will discuss differences in women’s sleep compared to men, reasons why differences occur, and how this may affect clinical decisions.
OBJECTIVE DIFFERENCES IN FEMALES’ SLEEP A seminal work examining sleep in normal subjects was reported by Williams et al. (1974) and shows sleep architectural changes across ages and between genders. Noncomplaining sleepers, categorized by decade and gender, were studied with full laboratory-based polysomnography. While not all variables that could influence sleep were controlled for at this early time in our history, this work did attempt to control for the influence of the menstrual cycle by only studying adult women in their follicular phase. Sleep differences between males and females were seen to begin around 9–10 months of age, with female babies sleeping longer. Around age 3 years males showed greater time in bed (TIB), total sleep time (TST), longer rapid eye movement (REM) cycle length and higher percentage
of stage 2 sleep. Females demonstrated a trend toward increased slow-wave sleep (SWS) which continued throughout most of their lives. Teenage females tended to show less TIB and in the later teens females slept less than males. In their 20s females demonstrated more TST than men and continued to do so throughout life. Additionally they showed more stage 2 sleep. Males began to show increased levels of arousals and decreased SWS toward the end of the second decade. The decline of SWS continued throughout their life but did not begin in females until the fourth or fifth decade. Females began to show less SWS in their 50s and began to look like males did in their 30s. Females continued to show decreased levels of arousal (compared to men) into their fourth decade. Sleep became fragmented with increased arousals during predicted perimenopausal years. During the sixth decade larger differences were seen in the amount of SWS; only 10% of males showed any SWS while 50% of females did. By the age of 70, few males showed appreciable amounts of SWS. In their seventh decade, females showed more stage changes than males, perhaps simply because they continued to show all stages of sleep. Males tended to show shorter REM cycles than females. More recently, Walsleben et al. (2004) demonstrated similar findings in a large cohort of adults over age 40 (n ¼ 470) using home-based polysomnography. This cohort was well defined as “normative” in that subjects with possible causes of sleep disruption were excluded. Females continued to show “better” sleep. They had longer TST, lower arousal rates, more SWS and less stage 1 and 2 sleep compared to males. Importantly, the data also demonstrated significant subjective excessive daytime sleepiness (EDS) in subjects despite a TST of > 7.2 hours per night.
*Correspondence to: Joyce A. Walsleben, R.N., Ph.D., Sleep Medicine Associates of NYC, 11 East 26th St, New York, NY 10010. Tel: 212-481-1818, Fax: 212-523-0498, E-mail:
[email protected]
640
J.A. WALSLEBEN
Table 40.1 Sleep disorders that are more common in women compared to men Women
Men
Insomnia: 1.4 more than men Restless-legs syndrome: 2 more than men Sleep-related headaches: 4 more in women Fibromyalgia: 80% women Nocturnal sleep-related eating disorders: 65% women Nightmares Familial sleep paralysis
Obstructive sleep apnea: 2 more in men Primary snoring: 2 more in men Rapid eye movement behavior disorder: 88% men Delayed sleep phase syndrome Sleep enuresis: 3:2 male/female Sleep terrors Sudden unexplained nocturnal death
Smaller objective studies of gender differences in sleep have shown few significant differences between men’s and women’s sleep when studies are visually scored. With more advanced electroencephalogram (EEG) scoring techniques, the finding of increased delta power among women has been confirmed and other differences noted. Dijk et al. (1989) studied gender differences in young adults aged 19–28 years (13 males/15 females) using computer-quantified spectral analysis of EEG. These authors noted an increase of delta power in the EEG (0.25–4 Hz) of females during non-REM (NREM) sleep and higher power densities in women during REM sleep that was consistent across the night. Armitage (1995) studied young adults (mean age 25 years, 11 males/11 females) using visually scored staging and period analysis algorithms, to examine EEG frequencies during sleep. Her analysis evaluated EEG in five conventional frequency categories: (1) delta (0.5–4 Hz), seen in SWS; (2) theta (4–8 Hz), predominantly seen in other stages of sleep; (3) alpha (8–12 Hz), found in quiet wakefulness; (4) sigma (12–16 Hz), seen in spindle activity of stage 2; and (5) beta (16–32 Hz), seen in lighter stages of sleep and wake. When global delta power of NREM was examined, females again showed significantly more delta across the sleep period. Unfortunately, most of the females in these two studies took oral or injectable contraceptives that may have influenced the findings. Ehlers and Kupfer (1997) studied young adults aged 20–40 years using visually scored sleep staging and spectral analysis of EEG characteristics to examine the effects of aging on the EEG. Both sexes had a decline in spectral power of spindles with age. No gender differences in SWS or delta wave activity were seen among subjects in their 20s. However, significant reductions of delta activity and percentage SWS were noted for males in their 30s. Additionally, males showed significant reductions of REM time, REM density, activity, and intensity with an increase of stage
2 sleep. These authors suggested this might reflect that males and females age differently over the second and third decade. Laboratory findings studying 10 older men and 10 postmenopausal women demonstrated a novel measurement technique for polysomnographically recorded sleep. When NREM delta and alpha spectral activity was normalized for the amount of delta in REM sleep, women were shown to have less delta activity and more alpha activity in NREM than men, an objective finding which may reconcile women’s subjective complaints of poor sleep (Latta et al., 2006). To avoid confounds of the laboratory environment, other small studies have objectively evaluated sleep in the subject’s home with full polysomnography. Kobayashi et al. (1998) studied 18 older subjects (8 males/10 females, mean aged 60.6 and 61.7 respectively) during two 36-hour sleep/wake periods. Females napped less frequently, had higher sleep efficiency, less stage 1 sleep, more SWS, more REM and fewer state changes than males. However, no mention was made of concomitant sleep disorders such as apnea that could be expected to influence sleep negatively. Fukuda et al. (1999) evaluated sleep in older subjects (8 males and 8 females aged 54–72 years). Visually scored sleep staging and spectral analysis of two frequency bands (0.5–2 Hz and 2–4 Hz) were analyzed. Visually scored sleep parameters showed that females continued to have higher percentages of SWS. With spectral analysis, females showed larger amounts of delta power and maintained clearer periodicity of delta power across the night. The authors suggest that the SWS generator is better conserved in middle-aged and elderly females compared to same-aged males. Using sleep logs and actigraphy at home, Reyner and Horne (1995) studied 400 adults (211 female and 189 males) aged 20–70 years for 15 consecutive nights. Actigraphy provided objective confirmation of sleep length and timing as well as sleep continuity. Subjects were divided into three age groups: (1) young, aged
WOMEN AND SLEEP 641 20–34 years; (2) middle-aged, 35–49 years; and (3) years). All subjects had a screen/adaptation night in older, 50–70 years. Home environmental factors were the laboratory. Females were alternately studied in not controlled in this field study. Overall, there their mid follicular and mid luteal phases over a 3appeared to be minimal effects of aging in both subjecmonth period. Polysomnography and continuous core tive and objective parameters. Females reported longer body temperature were measured along with levels of sleep latency (time to fall asleep). Although both males estradiol and progesterone in the females. Rectal temand females awoke earlier as they aged, there was a peratures of the normally cycling females were elesignificant difference in rise time between middle-aged vated, as expected, in the luteal phase of the subjects, with females rising later than males. Young menstrual cycle compared to that in their follicular males slept longer than both their middle-aged and cycle and documented blunted nocturnal drops of temolder counterparts and middle-aged females slept lonperature compared to males. Both groups of females ger than middle-aged males. Actigraphy confirmed attained temperature minima earlier than males, sugsubjective complaints that females, particularly the gesting a gender effect. Temperatures of the females older ones, had more TIB with more frequent awakenon exogenous hormones were similar to that of the ings. Many of these awakenings were noted to be enviluteal phase in normally cycling females. ronmental (children’s needs). This begins to suggest There was no significant difference in the sleep that women’s sleep is also dependent on social issues. architecture (macrostructure) of males and females; however, more SWS was seen in the luteal phase of normally cycling females. Those on exogenous horObjective studies of gender differences mones demonstrated less SWS than normally cycling in circadian rhythmicity females, suggesting that, as hormonal supplementation The circadian rhythm of body temperature, oscillating alters the temperature phase, it may also influence between a nadir at night and maxima in the afternoons, sleep. Buysse et al. (1993) studied 17 healthy 20–30is thought to influence sleep onset and offset. Quesyear-old males (n ¼ 9) and females (n ¼ 8) and 18 tions have been posed as to the impact of ovulatory healthy 80-year-olds (11 males and 7 females) during changes in body temperature on females’ sleep. Ito a 36-hour constant routine paradigm to evaluate temet al. (1995) studied the plasma melatonin circadian poral patterns of unintended sleep episodes. During pattern under controlled conditions with measurements the constant routine, which followed a 24-hour normal every hour for 24 hours on the third day of each week routine adaptation period, balanced nutrition was supin 7 females aged 18–19 who spent 3 consecutive days plied every hour. Online core body temperatures were in each of 5 successive weeks in the laboratory. The tracked and cortisol and melatonin levels were sampled menstrual cycle was divided into four phases. Plasma over the entire period. All subjects had continuous EEG melatonin increased in the late luteal phase and rise with measurement of mood and sleepiness every hour. time was delayed on the first of the 3 days in the laboFemales showed stronger rhythmic trends for sleep ratory. Additionally, SWS was increased in the follicuthan males. Although all temperature measurements lar phase, as was TIB and TST, suggesting that the of the younger females were taken during their follicmenstrual cycle did affect melatonin and sleep/wake ular menstrual phase, older females in this study rhythm. showed higher temperature amplitudes than the younSimilarly, Parry et al. (1997) studied the nocturnal ger females. Unfortunately, 3 of the younger females patterns of melatonin in females with premenstrual were taking oral contraceptives which could have dysphoric disorder (PMDD) and controls and noted a blunted their temperature curves. Still, the findings delay in the secretion of melatonin and a decrease in may suggest that changes occur with increasing age. melatonin secretion during the luteal menstrual phase In a study designed to examine the relationship as compared to the follicular phase in females with between age-related changes in sleep and the circadian PMDD. The authors suggest that the circadian pacetiming system, Campbell and Murphy (1998) studied 60 maker of females with PMDD is more responsive to subjects (32 females and 28 males) between the ages of the hormonal changes of the menstrual cycle. Further 40 and 84 years. For some analyses, the group was they postulate that this sensitivity may render these divided by age and sleep history. One middle-aged females more subject to mood, cognitive, and sleep group (40–60 years) and two older groups aged 65–81 disturbances as a result of endogenous and exogenous years (one a subset who had experienced sleep difficulstimuli (Parry et al., 2006a). ties for at least 1 year prior to the study) were studied. Baker et al. (2001) studied subjective and objective Polysomnography and measures of core body temperasleep variables in 8 normally cycling women, 8 women ture were performed at an adaptation and baseline on birth control pills, and 8 males (all aged 21–22 night. There was no difference between the sleep
642
J.A. WALSLEBEN
quality of noncomplaining older subjects when compared to middle-aged subjects; however there was an advance in minimum body temperature in older subjects. Although complaining older subjects had decreased TST, sleep efficiency and REM with increased wake after sleep onset compared to noncomplaining older subjects, there was no difference in the rhythm of body temperature. With age controlled for, females again showed significantly higher temperature amplitude than males. In addition, there was a significant age effect on amplitude in females, not males. The authors suggest that these findings argue that a stronger circadian rhythmicity, as measured by temperature curve amplitude, is maintained by older females and that age-related sleep disturbances may have multiple causes. In addition to the homeostatic and circadian rhythms, an interval timing clock which measures the duration of a period of time, much like a stopwatch, is thought to exist (Virginia, 1996). How this may have an impact on sleep is not yet known. However, work by Morofushi et al. (2001) tends to indicate that estrogen may control the mechanism of the interval clock, affecting time-keeping across the menstrual cycle. Further, Kruijver and Swaab (2002) have shown estrogen and progesterone receptors located in the human SCN with a significantly stronger nuclear estrogen receptoralpha expression pattern in females compared to males.
SUBJECTIVE DIFFERENCES IN WOMEN’S SLEEP Despite objective proof that sleep is good, many women continue to complain of poor sleep. A 1997 poll of just over 1000 women by the National Sleep Foundation (1998) found that 50% of women polled complained about insomnia. Seventy percent of menstruating women lost 2.5 nights of sleep per month and 80% of pregnant women complained about disrupted sleep. Forty-four percent of women napped every weekend. Almost a third took over-the-counter or prescription sleep aids. Similarly, 38% of 12 603 women polled, as part of the Study of Woman’s Health Across the Nation, reported difficulty sleeping. This sample studied women between the ages of 40 and 55 years. Those reporting the most sleep difficulty were in the late perimenopausal group or had been oophorectomized. Caucasian women had the highest percentage of complaints and Japanese and Chinese women the least. When compared to Caucasian women, African American women had fewer complaints (Kravitz et al., 2003). It is unclear why the discrepancy between objective and subjective findings exists. Perhaps we are not
looking closely enough when objectively monitoring sleep. Clearly the use of standardized visual scoring (Rechtschaffen and Kales (R&K), 1968) may not adequately mark the subtle disruption, which may have an impact on sleep in women. O’Malley et al. (2003) have shown that approximately 20% more arousals are noted when frontal EEG leads were added to typical R&K montages. Latta et al. (2006) studied healthy nonobese older subjects (10 males and 10 postmenopausal females) and found that women actually had lower delta activity than males when NREM delta activity was normalized for the delta activity in REM sleep, and higher absolute alpha activity. This important finding coincides with women’s subjective complaints of poor sleep. Finally, women may be assessing other aspects of their sleep when complaining of difficulty (Vitiello et al., 2004). For instance, both Cartwright and Knight (1987) and Ultberg et al. (2000) have described the negative impact of a spouse’s sleep disorder on one’s sleep. When studying partners of apneics, Cartwright & Knight saw poor adjustment on the Marital Satisfaction Inventory and Ultberg et al. noted more insomnia and daytime fatigue/sleepiness among the spouses. Spouses noted improvement of their own sleep when treatment of the apnea occurred (Strawbridge et al., 2004). Other hormonal and physiological factors as well as psychological and sociological factors are thought to affect women’s sleep.
HORMONAL FACTORS Estrogen level Limited data suggest that secretions of gonadal hormones influence or modulate sleep physiology in animals and both the physiology and pathology of sleep and its disorders in humans. Neuroendocrine function is influenced by gonadal hormones at both pre- and postsynaptic levels. Animal studies show that neurosteroids (estrogen, progesterone, and testosterone) play a pivotal role in the mediation of stress and the effect on brain functions. Furthermore affects are noted in brain regions related to the control of sleep and wake (medial preoptic nuclei, medial hypothalamus) and limbic areas such as the hippocampus and amgydala (McEwen, 2001). Estrogen has been shown to increase the turnover of norepinephrine in the brainstem, hypothalamus, nucleus accumbens, and locus coeruleus as well as alter expression of c-fos proteins in a2-adrenergic neurons (for review, see Manber and Armitage, 1999). These effects act to decrease REM sleep but the action appears to depend on the phase of the circadian cycle. Temperature phase may be altered, suggesting that
WOMEN AND SLEEP estrogen may weaken the coupling between the core body temperature and the sleep–wake cycle or otherwise modulate circadian rhythms (Dijk et al., 1989). Estrogen acts as an excitatory stimulus by increasing the production of and receptor concentrations of neurotransmitters such as serotonin, norepinephrine, and dopamine as well as b-endorphins, and increasing the availability of glutamate, which stimulates the excitatory N-methyl-D-aspartate system (Arpels, 1996). Estrogen also regulates the flow of other key hormones that are secreted during sleep, among them growth hormone, prolactin, cortisol, and melatonin. Estrogen can act as an antidepressant, decreasing monoamine oxidase activity while increasing availability of serotonin and norephinephrine, and is a necessary cofactor for memory (Joffe and Cohen, 1998; McEwen, 2001). In theory, increased levels of estrogen occurring as a consequence of hormone replacement therapy (HRT) could increase activity and irritability and lessen sleep. However, studies evaluating HRT in postmenopausal women demonstrate increased sleep times; there was less fragmentation and enhanced REM sleep compared to baseline and placebo controls (Giampiero et al., 1997; Leproult et al., 1998; Moe et al., 2001; Montplaisir et al., 2001; Gambacciani et al., 2005).
643
progesterone is high. During the follicular phase women’s natural killer responses are the same as in men. This suggests that progesterone may modify immune function, perhaps having an impact on women’s risk of lupus and rheumatoid diseases that may also alter their ability to sleep.
Hormones: testosterone Animal work also suggests that androgens (testosterone) play a role in the sexual dimorphism of REM sleep during a critical period of brain development around the perinatal time (Manber and Armitage, 1999). Testosterone, excreted by the adrenals in women and converted into estrogen in the brain, has variable effects on sleep. In men testosterone decreases REM sleep but the addition of exogenous testosterone to adult animals has been shown to have little effect on sleep. For women, as estrogen is waning, the ratio of estrogen to testosterone changes such that there appears to be more testosterone. Those sensitive to the effects of androgens will feel symptoms of irritability, sleeplessness, and depression similar to that of estrogen loss. The lessening of progesterone as well as the change in this ratio of estrogen to testosterone may influence the sleep changes around the perimenopause.
Hormones: progesterone Progesterone has a hypnotic and anxiolytic effect on sleep similar to that of the benzodiazepines. Progesterone and its metabolites act directly on the GABAA receptor and, through a complex mechanism, result in either a hyperpolarization and decrease in neuronal excitability (allopregnanolone and pregnanolone) or an antagonistic reaction which limits GABA-induced chloride transport (pregnenolone sulfate) (Mellon, 1994). The sedating action of progesterone is comparable to that of the benzodiazepines and acts in a dosedependent fashion (Lancel et al., 1997). Progesterone has been shown to decrease latency to sleep, decrease wakefulness, and increase EEG spindle activity in both REM and NREM sleep in both animal and human studies. Furthermore the progesterone antagonist mifepristone (RU-486) has been shown to produce increased wake time, longer sleep latencies, and decreased REM and SWS when administered to healthy men (Wiedemann et al., 1998). Progesterone also acts as an antiestrogen and downregulates the estrogen receptors. Researchers also see changes in cellular immune function across the menstrual cycle that appear to be associated with fluctuations of progesterone. Moldofsky et al. (1995) have shown that there is less natural killer cell activity during the luteal phase when
PHYSIOLOGIC CHANGES OVER THE LIFESPAN In addition to women’s cyclic sex hormones, there are changing life stages such as menarche, pregnancy, lactation, and menopause which also affect sleep (Parry et al., 2006a, b).
Sleep and the menstrual cycle Numerous studies and surveys of subjective complaints of sleep disturbance demonstrate large numbers of women with occasional menstrual-related sleep difficulty (National Sleep Foundation, 1998). This includes complaints of bloating, cramping, and pain such that women lose up to two nights of sleep per month. However, few objective studies have confirmed these complaints, perhaps because few studies accurately measured hormonal levels, many dividing the menstrual cycle into a variety of phases which could not be matched for meta-analysis. Furthermore, most studies have few subjects. In studies of sleep, the menstrual cycle has been divided into two to eight phases. If two phases are studied, they are the follicular (preovulation) and luteal (postovulation) phases. If more than two phases are discussed, authors separate the follicular and luteal phases into early or late. They
644 J.A. WALSLEBEN may also include menstruation and ovulation as Pregnancy and the postpartum period phases. This complicates the comparison and interpreBeing pregnant and caring for an infant also have an tation of studies. impact on sleep. Due to the rapid rise of progesterone Although the findings are not always consistent, during the first trimester, many women are unable to generally in the follicular phase, as increased estrogen stay awake during the day. Progesterone also inhibits is triggered by follicule-stimulating hormone (FSH), smooth-muscle contraction and may be responsible many women will experience an increased depth of for frequent trips to the bathroom during the night. sleep if not actual increased sleep time, increased By 11 weeks of pregnancy, sleep becomes disrupted SWS and TST. At midcycle, after ovulation, the corpus with increased awakenings, a shorter time to fall luteum produces progesterone. This increase in progesasleep, and less efficient sleep. Some studies show a terone acts to increase body temperature and can blunt slight decline in REM and SWS, perhaps due to more circadian rhythm. Additional estrogen is secreted in the awakenings. Some women may also be bothered at early luteal phase, perhaps modulating some of these night by nausea (which is hormonally related), and by effects. Over the course of the next 14 days, there is backaches. increasing wakefulness and increased sleep disturbance By the second trimester, sleep is the most stable it as levels of estrogen and progesterone decline. Less will be, although less REM and SWS is noted (Lee, REM sleep occurs but an increase of stage 2 sleep is 1998). Women are bothered by fetal movements and noted with higher spindle activity (Driver et al., 1996). the emergence of pregnancy-related heartburn. RestThere is a significant decrease in SWS premenstrually, less-leg activity may also start during the second tridecreased sleep efficiency, an increase in the time it mester and may be due to an imbalance of ferritin in takes to fall asleep, and decreased sleep quality the brain and folate deficiency (Lee et al., 2001) or (Driver, 2008). Because of the blunting in melatonin indirect interference with dopaminergic transmission rhythm, some women tend to advance their circadian as a result of an estrogen-driven increased turnover phase, getting sleepier early in the evening and awakof norepinephrine (Manconi et al., 2004). Despite the ening early in the morning. The metabolic rate normal serum level, brain ferritin may be low. Addiincreases across the cycle as well. Sixty-eight percent tional iron in supplement form is frequently helpful of menstruating women surveyed felt sleepiest during (Earley and Connor, 1999). the week before or the first few days of their periods, During the third trimester, there is increasing sleep compared to the rest of the month. In rare cases, difficulty, in part because of the physical girth of the women can suffer debilitating hypersomnia or EDS body and the inability to be comfortable and in part that begins premenstrually and resolves after menses because of changing hormones prior to delivery. Less begins. This may be due to sensitivity to progesterone’s TST is noted and sleep becomes lighter with more sedating effects or the lessening of estrogen secretion frequent awakenings (Brunner et al., 1994). Women and metabolic rate during the menses (Parry et al., will tend to dream of the impending birth and care 2006a). of the baby (Hall et al., 1982). Sleep deprivation and Women who experience premenstrual syndrome fatigue are major issues late in the third trimester. (PMS) may experience these symptoms to a greater Women also suffer from shortness of breath, frequent degree. PMS varies from woman to woman. Cliniurination, cramps, itching, and frequent nightmares. cally, PMS symptoms arise in the period between ovuHeartburn increases along with the size of the belly. lation and menstruation. There may be daytime Additionally, the growing uterus can press on the scisleepiness and increased sleep disturbances. Some atic nerve, causing pain. Each of these problems interresearchers have likened PMS to jet lag. Both are temferes with sleep continuity. However, REM sleep porary conditions involving nighttime sleep disturreturns to almost normal levels during the last month bance and daytime sleepiness, with mood changes of pregnancy. and difficulty concentrating. Both also involve shifts Of interesting clinical note, Lee and Gay (2004) also in the secretion of melatonin. Melatonin has been reported that TST is associated with length of labor found to be higher premenstrually and during menand type of delivery such that women who sleep less struation. Low serotonin may also contribute to than 6 hours per night were more likely to have longer PMS-related mood swings, depression, and anxiety. labors and 4.5 times more likely to have cesarean delivFor women who suffer PMDD, sleep problems are eries. Those whose sleep was even more fragmented common and objective differences are more prohad an even higher rate of cesarean births. nounced (Parry, 1989). Despite these general findings, In addition to the hormonal aspects of pregnancy it is important to note the vast individuality of and childbirth, there are the physical stresses of responses among women.
WOMEN AND SLEEP pregnancy and the demands of taking care of a newborn who needs to be fed on a schedule (day or night). In striving to do their best, parents often put their own sleep needs on the back burner. Sleep issues continue into the postpartum phase for many women. Lee and Zaffke (1999) followed 24 primiparous and 18 multiparous women to evaluate perceived levels of fatigue and energy before, during, and after pregnancy. Studies that were carried out in the subjects’ homes during the follicular and luteal phase of menstruation prior to conception served as baseline data. Studies were repeated during each trimester and again at months 1 and 3 of the postpartum period. Measures included polysomnography, scales including: Lee Fatigue Scale, Profile of Mood States and Dupuy General Wellbeing, Vitality subscale. Serum chemistries included iron (hemoglobin, hematocrit, ferritin, B12, and folic acid) progesterone and thyroid serum triiodothyronine (T3), serum thyroxine (T4), T3 resin uptake, free T4 index, and thyroid antimicrosomal antibody titer. Complaints of fatigue during the first trimester correlated to subject’s younger age and lower levels of iron, hemoglobin, and ferritin. Hemoglobin levels remained at low normal throughout the pregnancy whereas ferritin levels dipped more slowly across trimesters. During the third trimester, fatigue was related to decreased TST. Postpartum fatigue was related to decreased sleep, ferritin, and hemoglobin. Even at 3 months postpartum these women still perceived less energy than their baseline levels. The perception of energy appeared to be influenced by parity, with multiparae having less energy throughout pregnancy. This suggests that pregnancy takes a significant toll on the sleep patterns and energy levels of women. Lee suggests that poor sleep may set women up for profound mood changes and depression during the postpartum period. She suggests that the “baby blues” may be a consequence of prolonged sleep deprivation (Lee et al., 2000). Postpartum depression or anxiety may be overlooked as a cause of sleep problems because we expect disrupted sleep at this time of life. Furthermore, the sleep systems of women with a history of depression may be more sensitive to the psychobiological changes of childbearing. Those women may have an earlier onset or more severe sleep disruption. Clinicians should be alert to the issues of sleep and pregnancy and educate their patients regarding expectations and solutions to improve outcomes.
Pregnancy and apnea During pregnancy changes in respiration and airway mechanics also occur. Snoring and apnea are not uncommon. To evaluate the extent of this problem
645
Loube et al. (1996) carried out a large survey of pregnant women, asking about snoring status, and compared infant outcomes to examine the impact of self-reported snoring on infant health. A total of 350 pregnant women and 110 age-matched women as controls answered a survey about snoring and daytime sleepiness. Those with reported daytime sleepiness and snoring were given full sleep evaluations. Fourteen percent of pregnant women snored versus 4% of the nonpregnant women. Eleven women reported anecdotal apnea (cessation of airflow). Of these, only four were recorded. Two of them met the criteria for mild apnea, one had positional apnea, and the other only snored. There were no significant differences between infants from either group, perhaps due to inadequate power. In contrast, Franklin et al. (2000) noted in a study of 500 Swedish women that habitual snoring was a sign of pregnancy-induced high blood pressure (preeclampsia), and was associated with lower birth weights and lower Apgar scores. The study also noted that women started to snore before any sign of hypertension appeared and that snoring was related to sleep apnea. While it may seem reasonable to suppose that the increased abdominal girth of pregnancy (with or without excessive weight gain) underlies the increase in apnea, there is little evidence to support this. A more likely explanation is that the frequent nasal congestion experienced by pregnant women predisposes to upper-airway collapse due to the large negative pressure in the airway needed to overcome the nasal obstruction. Fortunately, for many this is countered by the increase in minute ventilation and the fact that most pregnant women sleep in the lateral position during the later trimesters (Pien and Schwab, 2004). That position and the lessening of REM sleep may be protective as REM and supine positions may predispose to developing increased upperairway resistance syndrome and sleep apnea. Clearly, care must be taken to assess the important aspect of snoring during late pregnancy whether or not women complain of disrupted sleep.
Perimenopause and menopause Menopause, marked by a permanent cessation of menstruation (>12 months), elevation of luteinizing hormone and FSH, and decrease of androgens, is preceded by many years of hormonal changes. This period has been called the perimenopause and can stretch 5–10 years before the onset of menopause. Perimenopausal women frequently note mood changes and sleep disruption during this time. Physical and psychological symptoms such as hot flashes and depression can take their toll on sleep.
646 J.A. WALSLEBEN The hot flash typically is characterized by peripheral DIFFERENCES IN FEMALE vasodilatation, profuse sweating beginning on the face PSYCHOSOCIAL ISSUES AND THE and upper body, and subsequent chilling. The flash is IMPACT ON SLEEP thought to be a disorder of thermoregulation. They Psychosocial issues, particularly at the midlife period, may occur 2–20 times a day and last 3–5 minutes, with are different for women and men and affect them in a peak acrophase around 6 p.m. When flashes occur at significant ways. Part of this effect may be due to hornight they are accompanied by wake either preceding monal influence. It is known that oxytocin, a neurohoror following the event (Freedman and Krell, 1999). mone stimulated by estrogen, acts to enhance bonding, Alterations in central catecholamines occur. Levels of particularly in new mothers when the amount of oxytoplasma 3-methoxy-4-hydroxyphenylglycol are higher in cin increases. This also influences aspects of women’s women who experience hot flashes (Woodward and “tend and befriend” psychology, perhaps making it difFreedman, 1994). In a sense the hot flash is a general ficult to “let it go” when nighttime falls. Additionally, alerting mechanism which interrupts sleep and requires part of the midlife woman’s stress may be due to the time to settle before sleep can comfortably recur. The different roles women may be expected to play in sociphenomenon results in sleep loss and daytime conseety. Women are typically the caregivers to the extended quences, such as mood changes and loss of concentrafamily as well as the main caregiver to the immediate tion and memory (Baker et al., 1997). The addition of family. More women now work outside the home and estrogen and estrogen replacement therapy (ERT/ may be single mothers attempting to survive on HRT) reduces the hot flash and has been seen to lower-paying jobs than men, with few social supports. increase SWS in postmenopausal women (Leproult Many work the night shift, suffering the effects of ciret al., 1998). Despite findings from the Women’s cadian misalignment and sleep deprivation. Most work Health Initiative (Writing Group for the Women’s “the second shift” of home and family. There are just Health Initiative Investigators, 2002) and subsequent so many hours in the day and something has to give. warnings about the risks involved with supplemental That something is usually sleep. These phenomena hormones, they still remain an effective treatment for beg for education so that women understand the menopausal symptoms. Patients are encouraged to importance of adequate sleep time and the conseuse the lowest doses for the shortest amount of time quences of poor sleep. to relieve symptoms. Stressors are also different between the sexes. What Menopause is also a stage of life-altering changes may profoundly affect a woman will have little to no which can produce stress and mood changes (Parry effect on a man. In a study of 1179 working individuals et al., 2006b). Children are leaving, parents are requir(623 women), Nordin et al. (2005) note that “women’s ing more care, marriages are being renegotiated, and sleep may be more vulnerable to poor emotional supwomen may be redefining their roles. These stresses port and poor social integration than men’s sleep.” In add to a hormonally volatile time in women’s lives this study matrixes were developed to measure netand may take a toll. Shaver and Paulsen (1993) work (number of helpful friends), emotional support reported on subjective and objective studies of 135 (perception of closeness of friends/relatives), work healthy women aged 37–59 years. Women were control, and work demand indexes. Subjective quality grouped as premenopausal and menopausal, each with of sleep was determined. Twenty-five percent of the and without poor sleep. The authors noted that women women compared to 16% of the men rated their sleep with objectively documented poor sleep had higher quality to be poor. Women with low scores of network psychological distress rather than active menopausal and emotional support but with high scores on work symptoms. This suggests that the sleep disruption in demand index complained of poorer-quality sleep. the menopausal years may not be totally due to horNone of the indexes were associated with poor sleep monal changes. Women’s perception of poor sleep in the men. Although stressors have been shown to during the pre-, peri-, and postmenopausal years is affect sleep differentially, this paper points out the not always consistent with objective data. Examining unique associations between stress and sleep in data on 589 women from her Wisconsin Sleep Cohort women. Study, Young et al. (2003a) found that menopausal Further, literature has again taken up the issues of a status was not associated with diminished sleep quality midlife crisis for women which involves significant life as measured by polysomnography. In fact, postmenochanges, which had previously been economically pausal women slept better than premenopausal unavailable to them. More women who question their women. Postmenopausal women showed 3.4% more happiness or position during the midlife years (generSWS and 13.4 minutes more TST with less wake after ally 40–60 years) are now able to afford changes which sleep onset.
WOMEN AND SLEEP 647 may have an impact on the entire family as well as the flashes (Scharf et al., 1997; Schmidt et al., 1997) and woman herself. This issue has been well described in may continue to be helpful in postmenopausal women The Breaking Point: How Female Midlife Crisis is (Giampiero et al., 1997; Hays et al., 2003; Gambacciani Transforming Today’s Women (Shellenbarger, 2005). et al., 2005). Caution should be exercised when considHow these changes will affect women’s sense of ering this treatment, especially in women >60 years of power, well-being, and sleep remains to be seen. age (Board of the North American Menopause Society Awareness of the impact of these and other psychoso(NAMS), 2003). cial variables such as simple safety may help clinicians in their attempt to improve women’s sleep.
Sleep disorders common in women Far more women than men complain of insomnia – difficulty falling or staying asleep (Leger et al., 2000). This increase may be related to the increase in depression in women or at least the reporting of somatic symptoms related to sleep difficulties, which is increased among depressed women both acutely (Angst and Dobler-Mikola, 1984) and chronically (Kornstein et al., 2000). While it is still unclear as to the causation of symptoms, i.e., whether sleep difficulties precede mood symptoms or not, studies suggest a strong association (Joffe and Cohen, 1998). Furthermore, women may be more subjected to the entrainment of poor sleep habits first developed during years of parenting. Clearly, insomnia may also be caused by physical syndromes such as fibromyalgia and pain. Medications may affect one’s ability to sleep. Simple environmental issues such as safety may also play important causative roles. Because insomnia is so multifactorial, care should be taken to evaluate women for all the possible causative factors. The increase of reports of insomnia among women is especially true during the perimenopausal years when hormone levels are rapidly shifting and continue to be prominent as women age. Maggi et al. (1998) evaluated 2398 (867 males and 1531 females) community-living older (>65 years) subjects with questionnaires. The prevalence of insomnia was 54% in women compared to 36% in men. There was an increased odds ratio for insomnia (1.69) and depression (1.93) in women even when results were controlled for potential risk factors such as health status and smoking and alcohol habits. Night waking was the most common complaint.
DIFFERENCES
IN TREATMENT OF WOMEN’S INSOMNIA
As we know, the pathophysiology of insomnia is multifactorial. Treatments should be designed to alleviate the cause when possible. In addition to behavioral changes and medications, studies have also shown that ERT/HRT improves the sleep of perimenopausal depressed women irrespective of the presence of hot
Obstructive sleep apnea (OSA) and sleep-disordered breathing (SDB)
Once thought to be a man’s disease, OSA is also common among women and frequently overlooked as a possible cause for poor sleep. The estimated prevalence of SDB, which is defined as an apnea–hypopnea score over 5/hour of sleep, is 24% in men and 9% in adult women. Four percent of men and 2% of women will have the apnea–hypopnea syndrome, which includes daytime sleepiness (Young et al., 1993). There is an increased likelihood of developing OSA/SDB postmenopausally. Young et al. (2003b) reported an increased odds ratio (2.6 (1.4, 4.8)) of developing five or more apnea episodes per hour and an increased odds ratio of 3.5 (1.4, 8.8) of developing an apnea–hypopnea index of 15 events per hour in postmenopausal women. Symptoms of OSA in both men and women include dramatic snoring (although many women do not know if they snore and may not report it), gasping during sleep, restlessness, and daytime sleepiness. Unfortunately, despite giving the classic symptoms of OSA to their health care provider, many women go undiagnosed. It is not clear whether this results from a bias of the health care worker or the concurrent reporting of psychologically oriented symptoms such as insomnia, depression, and anxiety, which attract more attention in women (Young et al., 1996). Women with OSA do report far more symptoms of depression and anxiety as measured with the Symptom Check List-90 than men, regardless of the severity of their OSA. Furthermore, Pillar and Lavie (1998) note that complaints of depression and anxiety were higher in women with severe OSA compared to women with mild OSA/SDB. There has been much speculation as to why there is a sexual dimorphism in this disorder. Popovic and White (1998) suggested it is due to an increase in pharyngeal dilator muscle activity, probably related to levels of progesterone in awake females, such that genioglossus tone is increased in the luteal menstrual phase as well as in those postmenopausal women taking ERT. During sleep, Thurnheer et al. (2001) noted no such difference. They did note an increase in total respiratory resistance at sleep onset in men compared to women. The authors suggested that the waking
648
J.A. WALSLEBEN
increase in upper-airway resistance previously seen in women reflected the narrower size of their airway. Vgontzas et al. (2001) note that SDB is more common among women with polycystic ovarian disease, perhaps reflecting the role of hormones. Obesity tends to be a large factor in the development of obstructive apnea. However, for equal degrees of obesity, a man would probably have more sleep apnea than the woman, perhaps because of the placement of male fat in the midtorso area. Buyse et al. (2003) also notes that obese women < 55 years of age (presumably premenopausal) had a positive effect of weight gain on chemosensitivity, which may have been protective. However, women who are severely overweight are in jeopardy at any age. They may not have apnea from airway obstruction but may suffer hypoventilation, a decreased effort to breathe, particularly in REM, allowing significant hypoxia to develop (O’Connor et al., 2000). As previously mentioned, women can also develop a temporary form of OSA during pregnancy. Unfortunately the consequences of OSA are the same, if not worse, for women compared to men (Peppard et al., 2000). Snoring alone increases the likelihood of the metabolic syndrome in women (Leinweber et al., 2003). Treatment options are the same for both sexes; however, several studies have indicated that HRT may be a useful treatment of sleep apnea (Pickett et al., 1989; Bixler et al., 2001; Polo-Kantola et al., 2003; Shahar et al., 2003; Wesstrom et al., 2005). Given the recent controversy over the risk factors of HRT, it may be premature to consider HRT as a treatment option for SDB.
Restless-legs syndrome Restless-legs syndrome, described as crawly sensations in the legs which cause the sufferer to move them constantly, is more common in women than men and may have an impact on one’s ability to fall asleep (Lavigne and Montplaisir, 1994). Restless-legs syndrome has a circadian rhythm which worsens the symptoms in the evening hours, just as one tries to settle down. Symptoms generally increase with age but are two to three times more common in pregnancy (Manconi et al., 2004). A National Sleep Foundation poll (2005) showed that restless-legs syndrome is “significantly associated with medical and psychiatric conditions, other sleep disorders, unfavorable life style behaviors and adverse effects on daytime function.” Clinicians should explore symptoms of restlessness with their patients. Treatments include supplemental iron with vitamin C (when serum iron levels are low) and dopaminergic agents/ agonists.
CONCLUSIONS In summary, subtle differences in sleep architecture exist between males and females, particularly as they age. Most of these differences appear to be influenced by the gonadal hormones estrogen and progesterone in females and changes in the ratio of estrogen to testosterone as menopause approaches. Females’ cyclic hormonal nature and physiologic changes significantly influence sleep architecture across their reproductive lifetime. Estrogen seems to increase REM sleep in humans and improve sleep continuity in menopause. Progesterone is known to be sedating and similar to the benzodiazepines in that it decreases REM sleep and increases spindling and stage 2 sleep in humans. This effect is most notable in the first trimester of pregnancy. Although data suggest that women have a propensity for “better/deeper” sleep, subjective reports do not agree. Recent work demonstrating a novel measurement technique for sleep shows that women have less delta activity and more alpha activity in NREM, an objective finding which may reconcile subjective complaints. Furthermore, certain sleep disorders appear to favor one sex over the other. Sleep disorders are common in women and have a negative impact on their quality of life. Insomnia, restless legs, and apnea all act to disrupt sleep. Women have a risk of depression that is twice that of men. This may influence the prevalence of insomnia in women. Other sleep disorders such as apnea appear frequently in women, yet are still underdiagnosed, leaving women subjected to the significant health outcomes of hypertension, diabetes, and profound daytime sleepiness. Awareness of these issues and attention to incorporating questions about sleep and daytime alertness into a woman’s care will optimize treatment. Treatment of sleep complaints and disorders in women will need to consider their unique physiology and psychology. Attention to stressors and life stage is necessary. While HRT can improve sleep in many women, individual risk/benefit ratios should be considered before incorporating this therapy.
REFERENCES Angst J, Dobler-Mikola A (1984). Do the diagnostic criteria determine the sex ratio in depression? J Affect Dis 7: 189–198. Armitage R (1995). The distribution of EEG frequencies in REM and NREM sleep stages in healthy young adults. Sleep 18 (5): 334–341. Arpels JC (1996). The female brain hypoestrogenic continuum from the premenstrual syndrome to menopause. J Reprod Med 41: 633–639.
WOMEN AND SLEEP Baker A, Simpson S, Dawson D (1997). Sleep disruption and mood changes associated with menopause. J Psychosom Res 43 (4): 359–369. Baker FC, Waner JI, Vieira EF et al. (2001). Sleep and 24 hour body temperatures: a comparison in young men, naturally cycling women and women taking hormonal contraceptives. J Physiol 530 (3): 565–574. Bixler EO, Vgontzas AN, Lin HM et al. (2001). Prevalence of sleep-disordered breathing in women: effects of gender. Am J Resp Crit Care Med 163: 608–613. Board of the North American Menopause Society (NAMS) HM (2003). Treatment of menopause-associated vasomotor symptoms: position statement of the North American Menopause Society. Menopause 11 (1): 11–33. Brunner DP, Munch M, Biedermann K et al. (1994). Changes in sleep and sleep electroencephalogram during pregnancy. Sleep 17 (7): 576–582. Buyse B, Markous N, Cauberghs M et al. (2003). Effect of obesity and/or sleep apnea on chemosensitivity: differences between men and women. Respir Physiol Neurobiol 134: 13–22. Buysse DJ, Monk TH, Reynolds CFIII et al. (1993). Patterns of sleep episodes in young and elderly adults during a 36-hour constant routine. Sleep 16 (7): 632–637. Campbell SS, Murphy PJ (1998). Relationships between sleep and body temperature in middle-aged and older subjects. J Am Geriatr Soc 46 (4): 458–462. Cartwright RD, Knight S (1987). Silent partners: the wives of sleep apnea patients. Sleep 10: 244–248. Dijk D-J, Beersma DGM, Bloem GM (1989). Sex differences in sleep EEG of young adults: visual scoring and spectral analysis. Sleep 12 (6): 500–507. Driver H. (Ed.), (2008). Sleep and Disorders of Sleep in Women: Sleep Medicine Clinics 3. WB Saunders, Philadelphia. Driver HS, Dijk DJ, Werth E et al. (1996). Sleep and the sleep electroencephalogram across the menstrual cycle in young healthy women. J Clin Endocrinol Metab 81 (2): 728–735. Earley CJ, Connor JR (1999). RLS patients have abnormally reduced CSF ferritin compared to both normals and patient controls. Sleep 22: S156. Ehlers CL, Kupfer DJ (1997). Slow-wave sleep: do young adult men and women age differently? J Sleep Res 6: 211–215. Franklin KA, Holmgren PA, Jonsson F et al. (2000). Snoring, pregnancy-induced hypertension and growth retardation of the fetus. Chest 117: 137–141. Freedman RR, Krell W (1999). Reduced thermoregulatory null zone in postmenopausal women with hot flashes. Am J Obstet Gynecol 181: 66–70. Fukuda N, Nonma H, Kohsaka M et al. (1999). Gender differences of slow wave sleep in middle aged and elderly subjects. Psychiatry Clin Neurosci 539 (2): 151–153. Gambacciani M, Ciaponi M, Cappagli B et al. (2005). Effects of low-dose, continuous combined hormone replacement therapy on sleep in symptomatic postmenopausal women. Maturitas 50: 91–97.
649
Giampiero P, Toro G, Carta G et al. (1997). HRT as a first step treatment of insomnia in post menopausal women. European Menopause Journal 4 (4): 145–146. Hall CS, Domhoff GW, Blick KA et al. (1982). The dream of college men and women in 1950 and 1980: a comparison of dream content and sex differences. Sleep 5: 188–194. Hays J, Ockene JK, Brunner RL et al. (2003). Effects of estrogen plus progestin on health-related quality of life. Nejm 348: 1839–1854. Ito M, Kohsaka M, Honma K et al. (1995). Changes in biological rhythm and sleep structure during the menstrual cycle in healthy women. Seishin Shinkeigaku Zasshi 97 (3): 155–164. Joffe H, Cohen LS (1998). Estrogen, serotonin and mood disturbance: where is the bridge? Biol Psychol 44: 798–811. Kobayashi R, Kohsaka M, Fukuda N et al. (1998). Gender differences in sleep of middle aged individuals. Psychiatry Clin Neurosci 52 (2): 861–867. Kornstein SG, Schatzberg AF, Thase ME et al. (2000). Gender differences in chronic major and double depression. J Affect Dis 60: 1–11. Kravitz HM, Ganz PA, Bromberg J et al. (2003). Sleep difficulty in women at midlife: a community survey of sleep and the menopausal transition. Menopause 10 (1): 41–50. Kruijver FP, Swaab DF (2002). Sex hormone receptors are present in the human suprachiasmatic nucleus. Neuroendocrinology 75: 296–305. Lancel M, Faulhaber J, Schiffelholz T et al. (1997). Allopregnanolone affects sleep in a benzodiazepine-like fashion. J Pharmacol Exp Ther 282 (3): 1213–1218. Latta F, Leproult R, Tasali E et al. (2006). Sex differences in delta and alpha EEG activity in healthy older adults. Sleep 28 (12): 1525–1534. Lavigne GJ, Montplaisir JY (1994). Restless legs syndrome and sleep bruxism, prevalence and association among Canadians. Sleep 17: 739–743. Lee KA (1998). Alterations in sleep during pregnancy and postpartum: a review of 30 years of research. Sleep Med Rev 2 (4): 231–242. Lee KA, Gay CL (2004). Sleep in late pregnancy predicts length of labor and type of delivery. Am J Obstet Gynecol 191 (6): 2041–2046. Lee KA, Zaffke ME (1999). Longitudinal changes in fatigue and energy during pregnancy and the postpartum period. J Obstet Gynecol Neonatal Nurs 28 (2): 183–191. Lee KA, McEnany G, Zaffke E (2000). REM sleep and mood state in childbearing women: sleepy or weepy? Sleep 23 (7): 877–885. Lee KA, Zaffke ME, Baratte-Beeke K (2001). Restless legs syndrome and sleep disturbance during pregnancy: the role of folate and iron. J Womens Health Gend Based Med 10 (4): 335–341. Leger D, Guilleminault C, Dreyfus JP et al. (2000). Prevalence of insomnia in a survey of 12,778 adults in France. J Sleep Res 9: 35–42.
650
J.A. WALSLEBEN
Leinweber C, Kecklund G, Akerstadt T et al. (2003). Snoring and the metabolic syndrome in women. Sleep Med 4: 531–536. Leproult R, Hofmann E, Van Cauter E (1998). Slow wave activity: effects of gender and estrogen replacement therapy. Sleep 21 (Suppl): 590H. Loube DI, Poceta JS, Morales MC et al. (1996). Selfreported snoring in pregnancy. Association with fetal outcome. Chest 109 (4): 885–889. McEwen BS (2001). Genome and hormones: gender differences in physiology. Invited Review. Estrogens effect on the brain: multiple sites and molecular mechanisms. J Appl Physiol 91 (Dec): 2785–2801. Maggi S, Langlois JA, Minicuci N et al. (1998). Sleep complaints in community dwelling older persons: prevalence, associated factors and reported causes. J Am Geriatr Soc 46 (2): 161–168. Manber R, Armitage R (1999). Sex, steroids and sleep: a review. Sleep 22 (5): 540–555. Manconi M, Govoni V, DeVito A et al. (2004). Pregnancy as a risk factor for restless legs syndrome. Sleep Med 5: 305–308. Mellon SH (1994). Neurosteriods: biochemistry, modes of action and clinical relevance. J Clin Endocrinol Metab 78: 1003–1008. Moe KE, Larsen LH, Vitiello MV et al. (2001). Estrogen replacement therapy moderates the sleep disruption associated with nocturnal blood sampling. Sleep 24 (8): 886–894. Moldofsky H, Lue F, Shahal B et al. (1995). Diurnal sleep/ wake-related immune functions during the menstrual cycle of healthy young women. J Sleep Res 4: 150–159. Montplaisir J, Lorrain J, Denesle R et al. (2001). Sleep in menopause: differential effects of two forms of hormone replacement therapy. Menopause 8 (1): 10–16. Morofushi M, Shinohara K, Kimura F (2001). Menstrual and circadian variations in time perception in healthy women and women with premenstrual syndrome. Neurosci Res 41: 339–344. National Sleep Foundation F (1998). Poll on Women and Sleep. National Sleep Foundation, Washington DC. National Sleep Foundation F (2005). Poll on Adult Sleep Habits and Styles. National Sleep Foundation, Washington DC. Nordin M, Knutsson A, Sundbom E et al. (2005). Psychosocial factors, gender and sleep. J Occup Health Psychol 10 (1): 54–63. O’Connor C, Thornley KS, Hanly PJ (2000). Gender differences in the polysomnographic features of obstructive sleep apnea. Am J Respir Crit Care Med 161: 1465–1472. O’Malley EB, Norman RG, Farkas D et al. (2003). The addition of frontal EEG leads improves detection of cortical arousal following obstructive respiratory events. Sleep 26 (4): 435–439. Parry BL (1989). Reproductive factors affecting the course of affective illness in women. Psychiatr Clin North Am 12: 207–220.
Parry BL, Berga SL, Mostofi N et al. (1997). Plasma melatonin circadian rhythms during the menstrual cycle and after light therapy in dysphoric disorder and normal control subjects. J Biol Rhythms 12: 47–64. Parry BL, Martinez LF, Maurer EL et al. (2006a). Sleep, rhythms and women’s mood. Part I. Menstrual cycle, pregnancy and postpartum. Sleep Med Rev 10: 129–144. Parry BL, Martinez LF, Maurer EL et al. (2006b). Sleep, rhythms and women’s mood. Part II. Menopause. Sleep Med Rev 10: 197–208. Peppard PE, Young T, Palta M et al. (2000). Prospective study of the association between sleep-disordered breathing and hypertension. Nejm 342 (19): 1378–1384. Pickett CK, Regensteiner JG, Woodard WD et al. (1989). Progestin and estrogen reduce sleep disordered breathing in post menopausal women. J Applied Physiol 66 (4): 1656–1661. Pien GW, Schawb RJ (2004). Sleep disorders during pregnancy. Sleep 27 (7): 1405–1417. Pillar G, Lavie P (1998). Psychiatric symptoms in sleep apnea syndrome: effects of gender and respiratory disturbance index. Chest 114 (3): 697–703. Polo-Kantola P, Rauhala E, Helenius H et al. (2003). Breathing during sleep in menopause: a randomized, controlled, crossover trial with estrogen therapy. Obstet Gynecol 102: 68–75. Popovic RM, White DP (1998). Upper airway muscle activity in normal women: influence of hormonal status. J Appl Physiol 84 (3): 1055–1062. Rechtschaffen A, Kales A (Eds.), (1968). A Manual of Standardized Terminology, Techniques and scoring System for Sleep Stages of Human Subjects. UCLA Brain Information Service/Brain Research Institute, Los Angeles. Reyner LA, Horne JA (1995). Gender and age-related differences in sleep determined by home-recorded sleep logs and actimetry from 400 adults. Sleep 18 (5): 391 and Sleep 18 (2): 127–134. Scharf MB, McDannold MD, Stover R et al. (1997). Effects of estrogen replacement therapy on rates of cyclic alternating patterns and hot-flush events during sleep in postmenopausal women: a pilot study. Clin Ther 19: 304–311. Schmidt PJ, Roca CA, Block M et al. (1997). The peri-menopause and affective disorders. Semin Reprod Endocrinol 15: 91–100. Shahar E, Redline S, Young T et al. (2003). Hormone replacement therapy and sleep disordered breathing. Am J Respir Crit Care Med 167 (9): 1186–1192. Shaver JL, Paulsen VM (1993). Sleep, psychological distress and somatic symptoms in perimenopausal women. Fam Pract Res J 13: 373–384. Shellenbarger S (2005). The Breaking Point: How Female Midlife Crisis Is Transforming Today’s Women. Henry Holt, New York. Strawbridge WJ, Shema SJ, Roberts RE (2004). Impact of spouses’ sleep problems on partners. Sleep 27 (3): 527–531. Thurnheer R, Wraith PK, Douglas NJ (2001). Influence of age and gender in upper airway resistance in NREM and REM sleep. J Appl Physiol 90: 981–988.
WOMEN AND SLEEP Ultberg J, Carter N, Talback M et al. (2000). Adverse health effects among women living with heavy snorers. Health Care Women Int 21: 81–90. Vgontzas A, Legro R, Bixler E et al. (2001). Polycystic ovary syndrome is associated with obstructive sleep apnea and daytime sleepiness: role of insulin resistance. J Clin Endocrinol Metab 86 (2): 517–520. Virginia M (1996). Setting a biological stopwatch. Science 271: 905–906. Vitiello MV, Larsen LH, Moe KE (2004). Age-related sleep change. Gender an estrogen effects on the subjective– objective sleep quality relationships of healthy, noncomplaining older men and women. J Psychosom Res 56: 503–510. Walsleben JA, Kapur VK, Newman AB et al. (2004). Sleep and reported daytime sleepiness in normal subjects: the Sleep Heart Health Study. Sleep 27 (2): 293–298. Wesstrom J, Ulfberg J, Nilsson S (2005). Sleep apnea and hormone replacement therapy: a pilot study and literature review. Acta Obstet Gynecol Scand 84: 54–57. Wiedemann KM, Lauer CJ, Hirschmann M et al. (1998). Sleep-endocrine effects of mifepristone and megestrol acetate in healthy men. Am J Physiol 274: E139–E145.
651
Williams RL, Karacan J, Hursch CJ (1974). Electroencephalography of Human Sleep: Clinical Applications. Wiley, New York. Woodward S, Freedman RR (1994). The thermoregulatory effects of menopausal HF on sleep. Sleep (6): 497–501. Writing Group for the Women’s Health Initiative Investigators RR (2002). Risks and benefits of estrogen plus progestin in healthy post menopausal women: principal results from the Women’s Health Initiative randomized controlled trial. JAMA 288: 321–333. Young TB, Palta M, Dempsey J et al. (1993). The occurrence of sleep-disordered breathing among middle-aged adults. N Engl J Med 328: 1230–1235. Young T, Hutton R, Finn L et al. (1996). The gender bias in sleep apnea diagnosis. Are women missed because they have different symptoms. Arch Intern Med 156: 2445–2451. Young T, Rabago D, Zgierska A et al. (2003a). Objective and subjective sleep quality in pre-menopausal, peri-menopausal and postmenopausal women in the Wisconsin Sleep Cohort Study. Sleep 26: 667–672. Young T, Finn L, Austin D et al. (2003b). Menopausal status and sleep disordered breathing in the Wisconsin Sleep Cohort Study. Am J Respir Crit Care Med 167: 1181–1185.
Handbook of Clinical Neurology, Vol. 98 (3rd series) Sleep Disorders, Part 1 P. Montagna and S. Chokroverty, Editors # 2011 Elsevier B.V. All rights reserved
Chapter 41
Normal and abnormal sleep in the elderly 1
JANA R. COOKE 1 AND SONIA ANCOLI-ISRAEL 2 * Division of Pulmonary and Critical Care Medicine, University of California, San Diego, CA, USA 2
Department of Psychiatry, University of California, San Diego, CA, USA
INTRODUCTION Our knowledge about how sleep changes with age has grown significantly over the past few decades. Researchers have shown that there are typical agerelated normal changes that occur in sleep architecture and sleep patterns. However, aging is also accompanied by a variety of sleep complaints and sleep disorders. This chapter will review both normal and abnormal sleep in the elderly.
SLEEPAND AGING Polysomnography (PSG) has provided objective evidence of the changes in sleep architecture that occur with aging. In general, sleep becomes more fragmented and lighter with an increase in the number of arousals and awakenings. There is a reduction in the amount of slow-wave sleep (stages 3 and 4), beginning in middle age, with some reports that these deeper stages of sleep are completely absent after the age of 90 (Bliwise, 1993; Ohayon et al., 2004). There is a compensatory increase in the lighter stages of sleep (stages 1 and 2), and there is a decrease in rapid eye movement (REM) sleep, which is proportional to the decrease in total sleep time. Sleep efficiency and total sleep time are reduced with age and there are an increased number of sleep stage shifts. One study that included more than 1000 older French adults reported that the mean amount of nightly sleep was approximately 7 hours, with men sleeping slightly more than women (Ohayon and Vecchierini, 2005). Van Cauter et al. (2000) found that, in men aged 16–83 years, total sleep time decreased on average by 27 minutes per decade from midlife until the eighth decade. Compared with younger adults, the elderly
spend more time in bed but have deterioration in both the quality and quantity of sleep. All of these changes can lead to excessive daytime sleepiness (EDS), which in turn can lead to intentional and unintentional napping. Objective tests of daytime sleepiness performed in the elderly have shown that they are sleepier than younger adults (Carskadon et al., 1980), suggesting that the elderly are not able to obtain an adequate amount of sleep at night (Dement et al., 1982). Research has suggested that the elderly have a decreased ability to sleep (Bliwise, 1993; Ancoli-Israel, 1997b), which is often reported as insomnia. This decreased ability or insomnia may be due to a variety of factors, each discussed below.
INSOMNIA Studies have found insomnia, defined as the inability to initiate or maintain sleep resulting in daytime consequences, to be the most common sleep disturbance in older adults (Reid et al., 2006), with up to 40–50% of those over the age of 60 reporting disturbed sleep (Foley et al., 1995). However, the annual incidence rate is estimated to be 5% in those over the age of 65 (Foley et al., 1999). Complaints range from difficulty falling asleep, to difficulty with sleep maintenance, to frequent nighttime awakenings and early-morning awakenings. Gender differences exist as well, with women being more likely to complain about insomnia than men (Rediehs et al., 1990). There are a variety of factors associated with the development of insomnia in the elderly, including depression and psychological distress, medical conditions, medications, and circadian rhythm disturbances
*Correspondence to: Sonia Ancoli-Israel, Ph.D., Department of Psychiatry, UCSD, 9500 Gilman Drive, La Jolla, CA 92093-0733, USA. Tel: 858-822-7710, Fax: 858-822-7711, E-mail:
[email protected]
654
J.R. COOKE AND S. ANCOLI-ISRAEL
(Ancoli-Israel, 2000). Foley et al. (1999) reported that, while 28% of older adults suffered from complaints of chronic insomnia, only 7% of the incident cases of insomnia in the elderly occur in the absence of one of these risk factors.
Foundation survey of adults aged 65 years and over, those with more medical conditions, including cardiac and pulmonary disease and depression, reported significantly more sleep complaints (Foley et al., 2004).
Sleep and medications Depression and psychological distress Psychological distress, manifested as daytime anxiety and stress, is a common cause of transient insomnia. However, depression, often the result of more serious life events such as divorce or the death of a loved one, can trigger long-lasting, chronic insomnia. It has long been known that depression and insomnia are associated with each other (Ford and Kamerow, 1989), as the presence of depressed mood may predict insomnia and, conversely, untreated insomnia may result in depression (Dryman and Eaton, 1991; Livingston et al., 1993; Buysse et al., 1994; Cole and Dendukuri, 2003), and having insomnia at baseline is a significant predictor of developing depression 1–3 years later (Riemann and Voderholzer, 2003; Fava, 2004). A large study of more than 2000 community-dwelling older men (the MrOs study) confirmed these associations, finding that those with depression subjectively and objectively had greater sleep disturbances (Paudel et al., 2008). Older women with insomnia seem to be especially susceptible to depression (Buysse et al., 1994; Breslau et al., 1996; Cole and Dendukuri, 2003; Perlis et al., 2006). Studies in younger adults have suggested that treating the insomnia might also improve depression (Asnis et al., 1999; Nowell and Buysse, 2001), but these types of studies have not been conducted in the elderly.
Sleep and medical illness Older individuals often suffer from multiple medical problems. Pain caused by osteoarthritis, shortness of breath due to chronic obstructive pulmonary disease or congestive heart failure, nocturia due to enlarged prostate, and neurologic deficits related to cerebrovascular accidents or Parkinson’s disease can all lead to difficulty with sleep initiation and maintenance. Additionally, reports of trouble with sleep are strongly correlated with complaints about health and depression (Foley et al., 1995). Studies examining the prevalence of sleep disturbances in patients with chronic medical diseases have reported that 31% of patients with arthritis and 66% of chronic pain patients report difficulty falling asleep, while 81% of patients with arthritis, 85% of patients with chronic pain, and 33% of diabetes patients report difficulty staying asleep (Sridhar and Madhu, 1994; Wilcox et al., 2000). In a National Sleep
The medications used to treat these various underlying medical problems can also cause disruptions in sleep. Beta-blockers, bronchodilators, corticosteroids, decongestants, and diuretics as well as other cardiovascular, neurologic, psychiatric, and gastrointestinal medications can all cause sleep disturbances. Furthermore, polypharmacy is increasingly common among older adults, often without consideration of its effect on the patient’s sleep. Whenever feasible, sedating medications should be administered before bedtime, whereas stimulating medications and diuretics should be taken during the day.
Consequences of insomnia Insomnia symptoms are associated with overall poor health and mental well-being status in older adults (Ohayon and Vecchierini, 2005; Reid et al., 2006). In addition to the development of depression, untreated insomnia may result in a number of other adverse consequences. Objectively measured sleep disturbances in older adults have been found to be associated with poorer cognition (Ohayon and Vecchierini, 2005; Blackwell et al., 2006). In older men, disturbed sleep is associated with poor physical performance (Dam et al., 2008). In a large study of older women, poor sleep (defined as sleep time 7 hours/night and a sleep efficiency 65%) was associated with 30–40% increased risk of subsequent falls (Stone et al., 2006).
Treatment of insomnia BEHAVIORAL
TREATMENT
Behavioral treatments have been shown to be effective in the treatment of insomnia (Morin et al., 1999b). The concept of sleep hygiene (Morin et al., 1999b), which consists of a set of guidelines for the maintenance of healthy sleep and wake habits, should be introduced (Table 41.1). Poor sleep hygiene practices can be associated with behavioral patterns that interfere with sleep. Patients should be educated on how to identify specific factors that may be disturbing their own sleep. The use of alcohol, which is widely used as a sleep aid due to its ability to shorten sleep latency, should be discouraged, as it has been shown to induce sleep fragmentation and early-morning awakenings (Roehrs and Roth, 2001).
NORMAL AND ABNORMAL SLEEP IN THE ELDERLY Table 41.1 Sleep hygiene rules Do not spend too much time in bed Maintain a consistent sleep/wake time Get out of bed if unable to fall asleep Restrict naps to 30 minutes in the late morning or early afternoon Exercise regularly Spend more time outside, especially late in the day Increase overall light exposure Eat a light snack (i.e., milk, bread) before bed Avoid caffeine, tobacco, and alcohol after lunch
Cognitive-behavioral therapy (CBT) has been shown to be as effective as medications in the short run and to have better long-term outcomes in the treatment of insomnia, in both younger and older adults (Morin et al., 1999a). A 2005 National Institutes of Health State of the Science Conference on Insomnia (NIH, 2005) concluded that CBT is as effective as prescription medications for the treatment of chronic insomnia. Additionally, there are indications that the beneficial effects of CBT, in contrast to those produced by medications, may last well beyond the termination of treatment (Morin et al., 1999a). Two specific behavioral therapies, which are often included as part of CBT, are stimulus control therapy and sleep restriction therapy. Stimulus control is based on the belief that insomnia may be the result of maladaptive classical conditioning (Bootzin and Nicassio, 1978). Patients are instructed to eliminate all in-bed activities other than sleep, such as reading and television watching. If they are not able to fall asleep within 20 minutes, they are instructed to get out of bed until they feel sufficiently sleepy, when they can return to bed and again attempt to fall asleep. If they are not able to fall asleep within 20 minutes, the pattern of getting out of bed until they are sleepy repeats itself. This therapy tries to break the association between the bed and wakefulness. Sleep restriction therapy limits the time spent in bed to about 15 minutes beyond the duration of time spent asleep at night (Spielman et al., 1987). As sleep efficiency improves, the amount of time spent in bed gradually increases.
PHARMACOLOGICAL
TREATMENT
A number of different classes of medications have been used to treat insomnia in the elderly, including sedative hypnotics, antihistamines, antidepressants, antipsychotics, and anticonvulsants. The National Institutes of
655
Health State of the Science Conference on Insomnia concluded that there is no systematic evidence for the effectiveness of antihistamines, antidepressants, antipsychotics, or anticonvulsants in the treatment of insomnia (NIH, 2005). The panel also expressed significant concerns about the risks associated with the use of these medications, particularly in the elderly. Sedative hypnotic medications are at times appropriate for the management of insomnia; however, studies have shown that pharmacologic treatment should be accompanied by behavioral therapy for the most effective treatment (Lichstein and Reidel, 1994; Morin et al., 1999a; NIH, 2005). Choosing the sedative hypnotic that best fits the specific complaint related to insomnia is the key to using this class of medication successfully. For example, agents with a long onset of action would not benefit patients with difficulty falling asleep. When prescribing sedative hypnotics, particularly benzodiazepines, the potentially harmful effects must be taken into account. The administration of longacting hypnotics can cause adverse daytime effects such as EDS and poor motor coordination, which may lead to injuries (Roth et al., 1988). In the elderly, the risk of falls, cognitive impairment, and respiratory depression is of particular concern, although data suggest that insomnia per se, and not hypnotics might increase the risk of falls (Avidan et al., 2005). Chronic use of long-acting benzodiazepines can lead to tolerance and withdrawal symptoms if abruptly discontinued, and the benefits of these agents for long-term use have not been studied with randomized clinical trials. Additionally, the potential for exacerbating coexisting medical conditions such as hepatic or renal disorders exists when these medications are used. The newer selective short-acting type-1 gammaaminobutyric acid benzodiazepine receptor agonists (i.e., zolpidem, zaleplon, eszopiclone) have been shown to be effective with a low propensity for causing clinical residual effects, withdrawal, dependence, or tolerance. All three benzodiazepine receptor agonists, zolpidem, zaleplon, and eszopiclone, have been found to be effective in the short-term management of insomnia in the elderly (Scharf et al., 1991, 2005; Roger et al., 1993; Ancoli-Israel et al., 1999, 2005). In addition, eszopiclone has been found to be safe and effective for the treatment of chronic insomnia (Krystal et al., 2003); however, these studies have only been conducted in younger adults. Particularly in the elderly, these newer sleep aids should be considered first-line agents in the pharmacological treatment of insomnia. Ramelteon, a melatonin agonist, has also been approved for the treatment of insomnia (Roth et al., 2005).
656
J.R. COOKE AND S. ANCOLI-ISRAEL
CIRCADIAN RHYTHM DISTURBANCES In humans, many physiological variables such as hormone secretion, blood pressure, immune function, core body temperature, and sleep–wake are regulated by a biological clock that operates over a 24-hour period, termed the circadian rhythm. This rhythm entrains to the 24-hour day by external time cues or zeitgebers, with the light–dark cycle being the most important. Circadian rhythm sleep disturbances typically develop when dysynchrony between the endogenous circadian pacemaker, located in the suprachiasmatic nucleus of the anterior hypothalamus, and exogenous environment demands occurs. In the elderly, several factors likely contribute to circadian rhythm desynchronization. First, the suprachiasmatic nucleus deteriorates with age, which may result in weaker and/or more disrupted rhythms (Swaab et al., 1985). Second, other circadian rhythm disturbances known to be involved in the entrainment of the circadian rhythm of sleep may develop. For example, the nocturnal secretion of endogenous melatonin gradually decreases with age (Touitou, 2001). As melatonin secretion plays an important role in the sleep–wake cycle, the decline may result in reduced sleep efficiency and an increased incidence of circadian rhythm sleep disturbances. Third, elderly patients may have exogenous cues that are too weak to entrain the circadian rhythm of sleep–wake. For example, light is one of the most powerful zeitgebers, yet studies have shown that elderly patients, especially those who are institutionalized, spend too little time in daylight. Daily bright-light exposure averaged about 60 minutes for healthy elderly, 30 minutes for Alzheimer’s disease patients living at home, and 0 minutes for nursinghome patients (Campbell et al., 1988; Espiritu et al., 1994; Ancoli-Israel et al., 1997a; Shochat et al., 2000).
This reduced level of bright light has been shown to be associated with nighttime sleep fragmentation and circadian rhythm sleep disorders (Shochat et al., 2000). Changes in the phase of the circadian rhythm can develop in the elderly, influencing the timing of the sleep period. Many older patients experience a phase advance in their sleep–wake cycle, causing them to feel sleepy early in the evening. Individuals with advanced sleep phase syndrome will typically fall asleep between 7 and 9 p.m. and wake up some 8 hours later, at 3–5 a.m. (Figure 41.1). As a result of societal norms, many older individuals will opt to stay up late, in spite of their sleepiness, yet still awaken early in the morning due to their advanced sleep–wake cycle. Sleep deprivation can ensue, which can result in daytime sleepiness and subsequent daytime napping. Finally, the amplitude of the circadian rhythm may also decrease with age. Reductions in rhythm amplitude can increase the frequency of nighttime awakenings and the severity of daytime sleepiness (Vitiello, 1996). Like insomnia, circadian rhythm changes are considered to be common with age, and presenting symptoms may mimic those of insomnia. Making a distinction between the two disturbances is important, however, as each warrants different treatment approaches. In addition to a careful and detailed sleep history, sleep diaries and activity monitoring with wrist actigraphy can be useful in distinguishing between the two conditions. Treatments known to strengthen and entrain the sleep–wake cycle are the most appropriate therapies for shifts in the circadian rhythm. The most common treatment for circadian rhythm shifts is bright-light therapy, as light is the strongest cue for circadian entrainment. Evening light exposure has been found to delay circadian rhythms and strengthen the sleep– wake cycle in both healthy community-living older
Sleepy, go to bed
Wake up
Standard phase 18:00 19:00 20:00 21:00 22:00 23:00 24:00
1:00
2:00
3:00
4:00
5:00
6:00
7:00
8:00
9:00
10:00 11:00
Advanced phase Sleep
Go to bed
Wake up
Fig. 41.1. Standard phase of sleep versus advanced phase of sleep. (Reproduced from Ancoli-Israel (1996), with permission from Elsevier.)
NORMAL AND ABNORMAL SLEEP IN THE ELDERLY 657 subjects and nursing-home patients (Campbell et al., Each event must last a minimum of 10 seconds and 1995). Patients with advanced rhythms should spend recur throughout the night, resulting in repeated aroumore time outdoors during the late afternoon or early sals from sleep as well as nocturnal hypoxemia. The evening and avoid bright light in the morning hours. total number of apneas plus hypopneas per hour of If patients are unable to spend enough time outdoors, sleep is called the apnea–hypopnea index (AHI) or studies have shown that exposure to artificial light via respiratory disturbance index (RDI). Depending on a bright-light box in the early evening can improve the laboratory, an AHI or RDI 5–10 is required for sleep continuity in both healthy and institutionalized the diagnosis of SDB. elderly patients (Campbell et al., 1995). In addition, a SDB has been shown to be quite common in the regular sleep schedule helps to promote a stronger elderly. In the largest series of randomly selected comsleep–wake cycle. munity-dwelling elderly, 65–95 years of age, AncoliAs discussed above, endogenous secretion of melaIsrael et al. (1991c) reported that 81% of the study tonin, secreted primarily at night, is known to promote subjects had an AHI 5, with prevalence rates of sleep and is reduced in older adults. Some studies sug62% for an AHI 10, 44% for an AHI 20, and gest that melatonin replacement therapy may improve 24% for an AHI 40. The Sleep Heart Health Study sleep efficiency in this population (Garfinkel et al., (Young et al., 2002), a large cohort of some 6400 1995; Haimov and Lavie, 1995). However, there is little patients with a mean age of 63.5 years, with a range consensus on the recommended dose or timing of from 40 to 98 years, reported prevalence rates of administration. In addition, melatonin is not regulated SDB by 10-year age groups. For those subjects aged by the US Food and Drug Administration, and there60–69, 32% had an AHI 5–14 and 19% had an AHI fore there is no control over the purity and exact drug 15. For those aged 70–79, 33% had an AHI 5–14 composition of the various brands currently available. and 21% had an AHI 15. For those aged 80–98, Little is known about the possible drug interactions 36% had an AHI 5–14 and 20% had an AHI 15. In or side-effects related to the administration of melacontrast, Young et al. (1993) reported the estimated tonin in the long term. Therefore, clinicians should prevalence of SDB among middle-aged adults 30–60 exercise caution when considering a trial of melatonin years of age, defined by an AHI 5 and the presence replacement therapy in elderly patients. The National of EDS, to be 4% of men and 2% of women. Institutes of Health State of the Science Insomnia ConLongitudinal and cross-sectional studies have both ference concluded that, although melatonin appears shown that the prevalence of SDB increases or stabito be effective for the treatment of circadian rhythm lizes with increasing age (Bliwise et al., 1984; Hoch disorders, there is little evidence for efficacy in the et al., 1990; Ancoli-Israel et al., 1991c; Bixler et al., treatment of insomnia. They also concluded that there 1998). In cross-sectional studies, Hoch et al. (1990) is no definition of an effective dose. Although melatofound that the median AHI and prevalence of SDB nin is thought to be safe in the short term, there is no both increased significantly from age 60 to 90 years, information about the safety of long-term use (NIH, and the Sleep Heart Health Study (Young et al., 2005). However, as mentioned above, the Federal Drug 2002) found a small increase in SDB prevalence with Administration has approved the first melatonin agoincreasing 10-year age groups for those subjects with nist, ramelteon, for the treatment of sleep-onset insoman AHI 15. In a longitudinal study where older nia (Roth et al., 2005). adults were followed for 18 years, Ancoli-Israel et al. (2001) found that AHI remained stable and only PRIMARY SLEEP DISORDERS changed with associated changes in body mass index. Elderly nursing-home patients, in particular those There are three primary sleep disorders that are comwith dementia, have been shown to have higher prevamonly found in the elderly: sleep-disordered breathing lence rates of SDB than those who live independently, (SDB), restless-legs syndrome (RLS)/periodic limb with prevalence rates ranging from 33% to 70% movements in sleep (RLS/PLMS), and REM sleep (Ancoli-Israel et al., 1991a; Gehrman et al., 2003). Sevbehavior disorder (RBD). eral studies have also found that the severity of the dementia was positively correlated with the severity Sleep-disordered breathing of the SDB (Ancoli-Israel et al., 1991a; Hoch and SDB is an umbrella term that includes a spectrum of Reynolds, 1991). Despite these findings, several other breathing disorders ranging from benign snoring to studies have failed to show a significant difference in obstructive apneas. In general, SDB is characterized the amount of SDB in demented elderly when comby the complete cessation of respiration (apneas) and pared to age-matched controls (Smallwood et al., partial or reduced respiration (hypopneas) during sleep. 1983; Bliwise et al., 1989).
658 J.R. COOKE AND S. ANCOLI-ISRAEL Established risk factors for SDB in the elderly risk of developing cardiovascular disease, including include increasing age, gender, and obesity (Phillips coronary artery disease and stroke (Shahar et al., and Ancoli-Israel, 2001). Other conditions that increase 2001). This study has also found that the severity of the risk of developing SDB include the use of sedating SDB was positively associated with the development medications, alcohol consumption, family history, race, of congestive heart failure, and, like ischemic disease, smoking, and upper-airway configuration (Phillips and even mild to moderate SDB was associated with its Ancoli-Israel, 2001). development (Shahar et al., 2001). Snoring and EDS are the two principal symptoms of The negative effect of severe SDB (AHI 30) SDB in the elderly. Other less common presentations in on cognitive dysfunction in the healthy elderly is well the elderly include insomnia, nocturnal confusion, and established, with consistent reports of impairment on daytime cognitive impairment, including difficulties attention-based tasks, immediate and delayed recall of with concentration and attention, and short-term memverbal and visual material, executive tasks, planning ory loss. It should be noted, however, that the sympand sequential thinking, and manual dexterity (Aloia toms and clinical presentations of SDB may not et al., 2003). Studies examining the relationship between differ from those of younger adults. milder SDB and cognition are less clear-cut, as some Approximately 50% of patients with habitual snorstudies have found that milder SDB (AHI 10–20) in ing have some degree of SDB, and snoring has been the absence of sleepiness does not cause cognitive dysidentified as an early predictor of SDB (Collop and function (Redline et al., 1997). Cassell, 2002). In subjects 65 years and older, Enright In addition to the cognitive deficits that may occur et al. (1996) reported that loud snoring was indepenas a result of SDB, there is evidence that many of dently associated with body mass index, diabetes, and the progressive dementias, including Alzheimer’s disarthritis in elderly women and alcohol use in elderly ease and Parkinson’s disease, may have neuronal men. It should be noted, however, that not all patients degeneration in areas of the brainstem that are responwho snore have SDB and not all patients with SDB sible for maintaining sleep, which may place the patient snore. As many elderly live alone, this symptom may at increased risk of developing SDB. For example, be difficult to identify. Ancoli-Israel et al. (1991a) found that those institutioEDS, resulting from recurrent nighttime arousals nalized elderly with severe dementia had more severe and sleep fragmentation, is a major feature of SDB SDB compared to those with mild to moderate or no in the elderly. The presence of EDS may be manifested dementia. Furthermore, those with more severe SDB as unintentional napping as individuals may fall asleep performed worse on the dementia rating scales, sugat inappropriate times during the day, such as while gesting that more severe SDB was associated with watching television or movies, while reading, during more severe dementia. conversations, while working, and while driving. EDS In regard to mortality, in general, rates from all can cause reduced vigilance and is associated with cogcauses increase 30% during the night, and for those nitive deficits which may be particularly serious in aged 65 and over, the excess deaths typically occur older adults who may already have some cognitive between the hours of 2 and 8 a.m. (Mitler et al., impairment at baseline (Martin et al., 2002). 1987). The presence of unrecognized or untreated The body of literature reporting negative conseSDB may partially account for these findings as sevquences and associated conditions related to SDB, eral studies have found an association between SDB including hypertension, cardiac arrhythmias, congesin the elderly and increased mortality rates (Bliwise tive heart failure, myocardial infarction, and stroke, et al., 1988; He et al., 1988), although some studies of continues to grow. However, most of the research to community-dwelling, nondemented elderly subjects date has focused on younger or middle-aged adults, have not found AHI to be an independent predictor and therefore, the exact relationship between SDB of mortality (Mant et al., 1995; Ancoli-Israel et al., and these various morbidities in the elderly remains 1996). Rather than directly causing an increased morunknown. tality, these studies have found that SDB may be one Earlier studies have reported a positive association of several predisposing factors for cardiopulmonary between SDB and hypertension in the elderly (Stoohs disease, which, in combination, leads to increased moret al., 1996). The Sleep Heart Health Study (Haas tality. This hypothesis is strengthened by a study by et al., 2005) has provided some additional insight, Ancoli-Israel et al. (2003b) which reported that elderly although no association was found between SDB and men with congestive heart failure had more severe systolic/diastolic hypertension in those aged 60 years. SDB than those with no heart disease. Further, men The authors did report a positive association between with both heart failure and SDB had shortened lifethe severity of SDB (based on overnight PSG) and the spans compared to those with just congestive heart
NORMAL AND ABNORMAL SLEEP IN THE ELDERLY failure, just SDB, or neither. More studies are needed to elicit further the exact nature of the relationship of SDB and mortality in the elderly, specifically in older women, as most of the studies completed in this age category have predominantly involved men. To assess accurately the presence of SDB in the elderly, a stepwise process should be employed. A complete sleep history should be obtained, focusing on symptoms of SDB such as EDS, unintentional napping, and snoring, as well as symptoms of other sleep disorders (i.e., RLS), and sleep-related habits and routines, in the presence of a bedpartner, roommate, or caregiver if possible. The patient’s medical and psychiatric history should be thoroughly reviewed, paying particular attention to associated medical conditions and medications, the use of alcohol, and evidence of cognitive impairment. Lastly, when the evaluation is suggestive of SDB, an overnight sleep recording should be obtained. Treatment of SDB in the elderly should be guided by the significance of the patient’s symptoms and the severity of the SDB (Ancoli-Israel and Coy, 1994). Patients with more severe SDB (AHI > 20) deserve a trial of treatment. For those with milder SDB (AHI < 20), treatment should be considered if comorbid conditions are present, such as hypertension, cognitive dysfunction, or EDS. Age alone should never be a reason to withhold treatment, nor should assumed noncompliance. There are a number of effective treatments for SDB. Continuous positive airway pressure (CPAP) is the gold-standard treatment of SDB. This device provides continuous positive pressure via the nasal passages or oral airway, creating a pneumatic splint to keep the airway open during inspiration. If used appropriately, CPAP has been shown to manage SDB safely and effectively at night with minimal side-effects and is generally well tolerated. Three months of compliant CPAP use in older adults has been reported to improve cognition, particularly in the areas of attention, psychomotor speed, executive functioning, and nonverbal delayed recall (Aloia et al., 2003). CPAP compliance can be an issue for any adult with SDB, and clinicians should not assume that elderly patients would be noncompliant simply because of more advanced age. Our laboratory has found that patients with mild to moderate Alzheimer’s disease and SDB tolerate CPAP treatment (Ayalon et al., 2006), and the only factor associated with poor compliance was the presence of depression – not age, severity of dementia, or severity of SDB (Ayalon et al., 2006). Alternatives to CPAP include oral appliances and surgery; however, neither has been shown to be as effective as CPAP. All patients should be counseled
659
on weight loss and smoking cessation if indicated. Longer-acting benzodiazepines should generally be avoided in the elderly with SDB as most of these medications are respiratory depressants and may actually increase the number and duration of apneas. Elderly patients with SDB should be encouraged to abstain completely from alcohol consumption, as even small amounts can exacerbate SDB. While there is a growing body of literature exploring SDB in the elderly, there is also an ongoing debate in the field as to what the presence of SDB in the elderly means and whether it represents an entity which is different from that found in younger or middle-aged adults. Some propose that a distinction should be made between age-dependent conditions, in which aging causes the pathology, and age-related conditions, in which the disease only occurs during a particular age period (Young, 1996). Whether SDB is an age-dependent or an age-related condition remains unknown and as more research is focused in this area, answering this question may help target new therapies. However, from a clinical standpoint, as Ancoli-Israel (2007) and others (Launois et al., 2006) have proposed, the answer may not be as relevant, as elderly patients with symptoms and/or related consequences of SDB (i.e., EDS, cognitive dysfunction, stroke) should be treated, regardless of age. This recommendation has recently been substantiated further by a review of the literature which concluded that data suggest that, in the elderly, CPAP improves daytime sleepiness, vascular resistance, platelet coagulability, and other factors affecting cardiac function, some aspects of memory and cognitive functioning, nocturia, self-reported snoring, and sleep architecture (Weaver and Chasens, 2006).
Periodic limb movement disorder in sleep/restless-legs syndrome PLMS is a disorder characterized by clusters of repetitive leg movements during sleep, typically accompanied by nighttime arousals and sleep fragmentation. These leg jerks or kicks occur typically every 20–40 seconds, and may recur several hundred times over the course of the night, with each jerk potentially causing a brief awakening. Patients with PLMS may complain of EDS and/or insomnia due the frequent arousals from sleep. As PLMS can also interfere with sleep onset, patients may have shorter total sleep times at night. The number of limb movements per hour of sleep is called the periodic limb movement index (PLMI). Clinically, the diagnosis of PLMS requires a PLMI 5. A diagnosis of PLMS therefore can only be made with an overnight sleep recording. The etiology of PLMS is unknown. PLMS can be seen in
660
J.R. COOKE AND S. ANCOLI-ISRAEL
patients with fibromyalgia and in conjunction with other primary sleep disorders, including SDB and narcolepsy. In adults, the prevalence of PLMS is estimated at 5–6% (Bixler et al., 1982). This rate increases dramatically with age, however, with reported prevalence rates of up to 45% in community-dwelling elderly over the age of 65 (Ancoli-Israel et al., 1991b; Ohayon and Roth, 2002). Although the prevalence of PLMS increases with age, its severity remains stable and does not appear to worsen with advancing age (Gehrman et al., 2002). RLS is a condition strongly linked to PLMS. This disorder is characterized by leg dysesthesia, often described as a “creepy-crawling” or “restless” sensation, which occurs while in a relaxed awake state and can only be relieved by movement (Walters et al., 1995). The diagnosis of RLS can be made on the basis of history alone, often with one question: “When you try to relax in the evening or sleep at night, do you ever have unpleasant, restless feelings in your legs that can be relieved by walking or movement?” Patients may have no knowledge that they kick and therefore, interviewing the patient’s bedpartner may be helpful in elucidating the history. If symptoms of RLS are present, clinicians should also assess the patient for irondeficiency states, including pregnancy, uremia, and peripheral neuropathy, as each of these conditions can cause or exacerbate RLS. Like PLMS, the prevalence of RLS increases significantly with age, with rates in older adults reported to range from 9% to 20% (Ohayon and Roth, 2002; Allen et al., 2003; Hornyak and Trenkwalder, 2004). Women have been reported to be affected twice as often as men (Allen et al., 2003). Pharmacologic intervention is typically required to manage RLS/PLMS. Dopamine agonists are effective in both reducing the number of kicks and associated arousals and are therefore considered the preferred therapy for RLS/PLMS in the elderly (Hening et al., 2004; Littner et al., 2004). Both ropinirole and pramipexole are currently approved by the Food and Drug Administration for the treatment of RLS, although the off-label use of other dopamine agonists (e.g., carbidopa-levodopa) may be effective alternatives (Table 41.2). Clinicians should be aware that carbidopa-levodopa (Sinemet) may shift the leg movements from the nighttime to the early morning.
Rapid eye movement sleep behavior disorder RBD is characterized by the intermittent absence of normal skeletal muscle atonia during REM sleep, associated with excessive motor activity while dreaming.
Table 41.2 Dopamine agonists for restless-legs syndrome/periodic limb movements in sleep Recommended doses Ergot dopamine agonists Bromocriptine* Cabergoline* Nonergot dopamine agonists Pramipexole Ropinirole
7.5 mg qhs 2 mg qhs 0.25–0.75 mg qhs 2 mg qhs
*Off-label use.
This disorder typically occurs during the second half of the night when REM is more common. Patients may walk, talk, eat, or appear to be acting out their dreams, which can result in violent movements that are potentially harmful to themselves and their bedpartner. Vivid dreams, consistent with the patient’s aggressive and/or violent behavior, may be recalled upon waking. The estimated prevalence of RBD in the elderly is reported to be 0.5% (Ohayon et al., 1997) with the highest incidence occurring after the age of 50 years in elderly men (Olson et al., 2000a, b; Schenck et al., 1993). Although the etiology of RBD remains unknown, there appears to be a strong association between idiopathic RBD and degenerative neurologic diseases, including Parkinson’s disease, multiple system atrophy, and Lewy body dementia (Boeve et al., 1998; Olson et al., 2000b; Montplaisir, 2004). Additionally, in many cases of neurodegenerative disease, RBD may precede other symptoms of the neurodegenerative disorder by years (Schenck et al., 1996; Boeve et al., 1998; Olson et al., 2000b). Olson et al. (2000b) reported that 50% of patients diagnosed with idiopathic RBD developed Parkinson’s disease or multiple system atrophy within 3–4 years. Schenck et al. (1996) found that parkinsonism developed in 38% of men a mean of 3.7 years after an initial diagnosis of idiopathic RBD. Withdrawal of REM-suppressing agents such as alcohol, tricyclic antidepressants, amphetamines, and cocaine has been strongly linked to the onset of acute RBD (Sforza et al., 1997; Olson et al., 2000b). Other medications and conditions reported to induce acute RBD include monoamine oxidase inhibitors, fluoxetine, and stress disorders (Sforza et al., 1997; Olson et al., 2000b). As with the other primary sleep disorder, the diagnosis of RBD requires a thorough sleep history in the presence of the bedpartner if possible. A screening questionnaire has been developed and validated and
NORMAL AND ABNORMAL SLEEP IN THE ELDERLY may become useful in the clinical evaluation of RBD (Stiasny-Kolster et al., 2007). In order to confirm a relationship between REM sleep and the patient’s complex motor behaviors, an overnight PSG with video recording of the nighttime behavior should be performed. Clinicians should pay close attention to intermittent elevations in muscle tone or limb movements on the electromyogram channel during REM sleep. Clonazepam, a long-acting benzodiazepine, is the treatment of choice for RBD. It has been shown to result in partial or complete cessation of abnormal nocturnal motor movements in 90% of patients (Schenck and Mahowald, 1990). However, patients may complain of residual sleepiness due to its long half-life. Clonazepam is contraindicated in patients with coexisting SBD. Several alternative medications have shown positive effects in RBD, including carbamazepine (Schenck et al., 1987), melatonin (Boeve et al., 2003), and dopaminergic agents (Bamford, 1993), although none has been shown to be as effective as clonazepam. In addition to pharmacologic treatment, sleep hygiene changes and education of the patient and the bedpartner are important aspects of RBD treatment. Efforts to make the bedroom safer, such as removing heavy or breakable or potentially injurious objects from the bed’s vicinity, should be employed. Heavy curtains should be placed on bedroom windows and doors and windows should be locked at night. Finally, to avoid falling out of bed, patients may consider sleeping on a mattress on the floor.
SLEEP IN DEMENTIA There is considerable evidence that dementia affects sleep differently from the normal aging process (Bliwise, 1993). This is not surprising considering that dementing illnesses such as Alzheimer’s disease, Parkinson’s disease, multiinfarct dementia, and Lewy body dementia may result in irreversible damage to the brain in areas responsible for regulating sleep. In general, patients with dementia have disturbed sleep at night, and laboratory sleep studies of demented patients have found increased sleep fragmentation and sleep-onset latency, and decreased sleep efficiency, total sleep time, and slow-wave sleep (Vitiello, 1996). Furthermore, the severity of dementia appears to be associated with the severity of the sleep disruption (Pat-Horenczyk et al., 1998). Due to these sleep architecture changes, patients with dementia may have EDS, nighttime wandering, confusion, and agitation (sundowning). Such nighttime behavior and disruptions may eventually lead to institutionalization (Pollak and Perlick, 1991). Therefore, addressing issues related to sleep disturbances
661
in the community-dwelling demented elderly is especially important, as it may potentially postpone institutionalization. It may be difficult to determine the exact nature of the sleep disturbance in patients with dementia, although caregivers can be a valuable source of information. The same causes of sleep disruption in the nondemented older adult will also be found in the patient with dementia. Pain from medical illnesses, medications, circadian rhythm changes, and depression are all potential causes of sleep disturbances in this population. It is also important to inquire about treatable primary sleep disorders such as SDB, RLS, or PLMS. Depending on the severity of the dementia, overnight sleep studies may not be feasible and therefore actigraphy may serve as a useful method to assess sleep and circadian rhythms in these patients (AncoliIsrael et al., 2003a). Treatment of specific sleep disturbances in the elderly with dementia should be guided by the specific sleep disorder. SBD should be treated with CPAP if appropriate, RLS/PLMS should be treated with a dopamine agonist, and circadian rhythm disturbances should be treated with bright-light therapy. Maintenance of regular physical activity and social interaction can also promote a more robust sleep/wake cycle. Sedating medications, including benzodiazepines, tricyclic antidepressants, antihistamines, anticonvulsants, and antipsychotics, are frequently prescribed for the nighttime restlessness associated with dementia. However, attempting to enhance sleep continuity with these medications may paradoxically result in increased sleep disturbance and daytime sleepiness (“hangover effect”) which may result in impaired motor and cognitive functioning. Therefore, in general, nonpharmacologic interventions are preferred.
Sleep in the institutionalized elderly The institutionalized elderly experience extremely fragmented sleep (Ancoli-Israel and Kripke, 1989). Middelkoop et al. (1994) reported that patients living in nursing homes had poorer sleep quality, more disturbed sleep onset, more phase-advanced sleep periods, and higher use of sedative hypnotics when compared with those elderly living in the community or in assisted-living environments. Studies have found that for older adults living in nursing homes, not a single hour in a 24-hour day was spent fully awake or fully asleep (Ancoli-Israel and Kripke, 1989; Jacobs et al., 1989; Pat-Horenczyk et al., 1998). There are a variety of environmental factors that contribute to the reduction in sleep quality. Noise and light exposure occur intermittently throughout the
662
J.R. COOKE AND S. ANCOLI-ISRAEL
Table 41.3
REFERENCES
Tips for improving sleep in the nursing home
Allen RP, Picchietti DL, Hening WA et al. (2003). Restless legs syndrome: diagnostic criteria, special considerations, and epidemiology. A report from the restless legs syndrome diagnosis and epidemiology workshop at the National Institutes of Health. Sleep Med 4: 101–119. Aloia MS, Ilniczky N, Di Dio P et al. (2003). Neuropsychological changes and treatment compliance in older adults with sleep apnea. J Psychosom Res 54: 71–76. Ancoli-Israel S (1996). All I Want is a Good Night’s Sleep. Mosby Year Book, Chicago. Ancoli-Israel S (2000). Insomnia in the elderly: a review for the primary care practitioner. Sleep 23 (Suppl 1): S23–S30. Ancoli-Israel S (2007). Guest Editorial. Sleep apnea in older adults – is it real and should age be the determining factor in the treatment decision matrix? Sleep Med Rev 11: 83–85. Ancoli-Israel S, Coy TV (1994). Are breathing disturbances in elderly equivalent to sleep apnea syndrome? Sleep 17: 77–83. Ancoli-Israel S, Kripke DF (1989). Now I lay me down to sleep: the problem of sleep fragmentation in elderly and demented residents of nursing homes. Bull Clin Neurosci 54: 127–132. Ancoli-Israel S, Klauber MR, Butters N et al. (1991a). Dementia in institutionalized elderly: relation to sleep apnea. J Am Geriatr Soc 39 (3): 258–263. Ancoli-Israel S, Kripke DF, Klauber MR et al. (1991b). Periodic limb movements in sleep in community-dwelling elderly. Sleep 14 (6): 496–500. Ancoli-Israel S, Kripke DF, Klauber MR et al. (1991c). Sleep disordered breathing in community-dwelling elderly. Sleep 14 (6): 486–495. Ancoli-Israel S, Kripke DF, Klauber MR et al. (1996). Morbidity, mortality and sleep disordered breathing in community dwelling elderly. Sleep 19: 277–282. Ancoli-Israel S, Klauber MR, Jones DW et al. (1997a). Variations in circadian rhythms of activity, sleep and light exposure related to dementia in nursing home patients. Sleep 20: 18–23. Ancoli-Israel S, Jones DW, McGuinn P et al. (1997b). Sleep disorders. In: J Morris, J Libshitz, K Murphy et al. (Eds.), Quality Care in the Nursing Home. Mosby Lifeline, St. Louis, pp. 64–73. Ancoli-Israel S, Walsh JK, Mangano RM et al. (1999). Zaleplon, a novel nonbenzodiazepine hypnotic, effectively treats insomnia in elderly patients without causing rebound effects. Prim Care Companion J Clin Psychiatry 1: 114–120. Ancoli-Israel S, Gehrman P, Kripke DF et al. (2001). Longterm follow-up of sleep disordered breathing in older adults. Sleep Med 2: 511–516. Ancoli-Israel S, Cole R, Alessi CA et al. (2003a). The role of actigraphy in the study of sleep and circadian rhythms. Sleep 26: 342–392. Ancoli-Israel S, DuHamel ER, Stepnowsky C et al. (2003b). The relationship between congestive heart failure, sleep disordered breathing and mortality in older men. Chest 124: 1400–1405.
1. 2. 3. 4. 5.
Determine cause of sleep problem and initiate specific treatment Limit naps to 1 hour in the early afternoon Adjust medications Avoid all caffeine Improve environment a. Keep the environment dark at night b. Keep the environment bright during the day c. Keep the environment quiet at night d. Match roommates
(Modified from Ancoli-Israel et al. (1997b)
24-hour day. Schnelle et al. (1998) demonstrated that both ambient light and nighttime noise contributed significantly to sleep disruption in nursing-home patients. This study also found that those patients living in nursing homes where nighttime noise and light were kept to a minimum had better sleep. Ancoli-Israel and Kripke (1989) reported that the nursing-home patients were exposed to less than 10 minutes of bright light per day and those with more light exposure had fewer sleep disruptions (Shochat et al., 2000). Chronic bed rest is known to disrupt circadian rhythms, yet institutionalized patients typically spend large amounts of the 24-hour day in bed (Ancoli-Israel and Kripke, 1989). Changes in sleep hygiene and the sleep environment may greatly improve the sleep quality of nursing-home inhabitants. Strategies to reduce nighttime disturbances and to promote stronger sleep/wake cycles are listed in Table 41.3.
SUMMARY Significant changes in sleep accompany aging for most adults. There are a variety of potential causes, including SDB, circadian rhythm disturbances, RLS/PLMS, RBD, depression and other psychiatric disorders, medical illness, and medications. The diagnosis requires a good sleep history and at times, a sleep study. Treatment should address the primary problem rather than the complaint and may result in significant improvement in quality of life and daytime functioning in the elderly.
ACKNOWLEDGEMENTS This study was supported by NIA AG08415 and National Institutes of Health M01 RR00827 and the VA Center of Excellence for Stress and Mental Health (CESAMH), which is supported by the Department of Veterans Affairs.
NORMAL AND ABNORMAL SLEEP IN THE ELDERLY Ancoli-Israel S, Richardson GS, Mangano R et al. (2005). Long-term use of sedative hypnotics in older patients with insomnia. Sleep Med 6: 107–113. Asnis GM, Chakraburrty A, Duboff EA et al. (1999). Zolpidem for persistent insomnia in SSRI-treated depressed patients. J Clin Psychiatr 60: 668–676. Avidan AY, Fries BE, James MC et al. (2005). Insomnia and hypnotic use, recorded in the minimum data set, as predictors of falls and hip fractures in Michigan nursing homes. J Am Geriatr Soc 53: 955–962. Ayalon L, Ancoli-Israel S, Stepnowsky C et al. (2006). Adherence to continuous positive airway pressure treatment in patients with Alzheimer’s disease and obstructive sleep apnea. Am J Geriatr Psychiatry 14: 176–180. Bamford CR (1993). Carbamazepine in REM sleep behavior disorder. Sleep 16: 33–34. Bixler EO, Kales A, Vela-Bueno A et al. (1982). Nocturnal myoclonus and nocturnal myoclonic activity in a normal population. Res Commun Psychol Psychiatr 36: 129–140. Bixler EO, Vgontzas AN, Ten Have T et al. (1998). Effects of age on sleep apnea in men. Am J Res Crit Care Med 157: 144–148. Blackwell T, Yaffe K, Ancoli-Israel S et al. (2006). Poor sleep is associated with impaired cognitive function in older women: the Study of Osteoporotic Fractures. J Gerontol Med Sci 61: 405–410. Bliwise DL (1993). Review. Sleep in normal aging and dementia. Sleep 16: 40–81. Bliwise DL, Carskadon MA, Carey E et al. (1984). Longitudinal development of sleep-related respiratory disturbance in adult humans. J Gerontol 39: 290–293. Bliwise DL, Bliwise NG, Partinen M et al. (1988). Sleep apnea and mortality in an aged cohort. Am J Public Health 78: 544–547. Bliwise DL, Yesavage JA, Tinklenberg JR et al. (1989). Sleep apnea in Alzheimer’s disease. Neurobiol Aging 10: 343–346. Boeve BF, Silber MH, Ferman TJ et al. (1998). REM sleep behavior disorder and degenerative dementia: an association likely reflecting Lewy body disease. Neurology 51: 363–370. Boeve BF, Silber MH, Ferman TJ (2003). Melatonin for treatment of REM sleep behavior disorder in neurologic disorders: results in 14 patients. Sleep Med 4: 281–284. Bootzin RR, Nicassio PM (1978). Behavioral treatments for insomnia. In: M Hersen, RM Eisler, PM Miller (Eds.), Progress in Behavior Modification, vol. 6. Academic Press, New York, pp. 1–45. Breslau N, Roth T, Rosenthal L et al. (1996). Sleep disturbance and psychiatric disorders: a longitudinal epidemiological study of young adults. Biological Psychiatry 39: 411–418. Buysse DJ, Reynolds CF, Kupfer DJ et al. (1994). Clinical diagnoses in 216 insomnia patients using the international classification of sleep disorders (ICSD), DSM-IV and ICD-10 categories: a report from the APA/NIMH DSMIV field trial. Sleep 17: 630–637.
663
Campbell SS, Kripke DF, Gillin JC et al. (1988). Exposure to light in healthy elderly subjects and Alzheimer’s patients. Physiol Behav 42: 141–144. Campbell SS, Terman M, Lewy AJ et al. (1995). Light treatment for sleep disorders: consensus report. V. Agerelated disturbances. J Biol Rhythms 10: 151–154. Carskadon MA, van den Hoed J, Dement WC (1980). Sleep and daytime sleepiness in the elderly. J Geriatr Psychiatry 13: 135–151. Cole MG, Dendukuri N (2003). Risk factors for depression among elderly community subjects: a systematic review and meta-analysis. Am J Psychiatry 160: 1147–1156. Collop NA, Cassell DK (2002). Snoring and sleep-disordered breathing. In: TL Lee-Chiong, MJ Sateia, MA Carskadon (Eds.), Sleep Medicine. Hanley & Belfus, Philadelphia, pp. 349–355. Dam TL, Ewing SK, Ancoli-Israel S et al. (2008). Is there an association between objective measures of sleep and physical function in older men? The MrOS Sleep Study. J Am Geriatr Soc 56: 1665–1673. Dement WC, Seidel W, Carskadon MA (1982). Daytime alertness, insomnia and benzodiazepines. Sleep 5: S28–S45. Dryman A, Eaton WW (1991). Affetive symptoms associated with the onset of major depression in the community: findings from the US National Institute of Mental Health epidemiologic catchment area program. Acta Psychiatr Scand 84: 1–5. Enright PL, Newman AB, Wahl PW et al. (1996). Prevalence and correlates of snoring and observed apneas in 5,201 older adults. Sleep 19: 531–538. Espiritu RC, Kripke DF, Ancoli-Israel S et al. (1994). Low illumination by San Diego adults: association with atypical depressive symptoms. Biol Psychiatry 35: 403–407. Fava M (2004). Daytime sleepiness and insomnia as correlates of depression. J Clin Psychiatry 65 (Suppl 16): 27–32. Foley DJ, Monjan AA, Brown SL et al. (1995). Sleep complaints among elderly persons: an epidemiologic study of three communities. Sleep 18: 425–432. Foley DJ, Monjan A, Simonsick EM et al. (1999). Incidence and remission of insomnia among elderly adults: an epidemiologic study of 6800 persons over three years. Sleep 22 (Suppl 2): S366–S372. Foley DJ, Ancoli-Israel S, Britz P et al. (2004). Sleep disturbances and chronic disease in older adults: results of the 2003 National Sleep Foundation Sleep in America survey. J Psychosom Res 56: 497–502. Ford DE, Kamerow DB (1989). Epidemiologic study of sleep disturbances and psychiatric disorders: an opportunity for prevention? J Am Med Assoc 262 (11): 1479–1484. Garfinkel D, Laudon M, Nof D et al. (1995). Improvement of sleep quality in elderly people by controlled-release melatonin. Lancet 346: 541–544. Gehrman PR, Stepnowsky C, Cohen-Zion M et al. (2002). Long-term follow-up of periodic limb movements in sleep in older adults. Sleep 25: 340–346. Gehrman PR, Martin JL, Shochat T et al. (2003). Sleep disordered breathing and agitation in institutionalized
664
J.R. COOKE AND S. ANCOLI-ISRAEL
adults with Alzheimer’s disease. Am J Geriatr Psychiatry 11: 426–433. Haas DC, Foster GL, Nieto FJ et al. (2005). Age-dependent associations between sleep-disordered breathing and hypertension: importance of discriminating between systolic/diastolic hypertension and isolated systolic hypertension in the Sleep Heart Health Study. Circulation 111: 614–621. Haimov I, Lavie P (1995). Potential of melatonin replacement therapy in older patients with sleep disorders. Drugs Aging 7: 75–78. He J, Kryger MH, Zorick FJ et al. (1988). Mortality and apnea index in obstructive sleep apnea: experience in 385 male patients. Chest 94: 9–14. Hening W, Allen RP, Picchietti DL et al. (2004). An update on the dopaminergic treatment of restless legs syndrome and periodic limb movement disorder. Sleep 27: 560–583. Hoch CC, Reynolds CFI (1991). Cognitive function and sleep disordered breathing in dementia: the Pittsburg experience. In: ST Kuna, PM Suratt, JE Remmers (Eds.), Sleep and Respiration in Aging Adults. Elsevier, New York, pp. 245–250. Hoch CC, Reynolds CFI, Monk TH et al. (1990). Comparison of sleep-disordered breathing among healthy elderly in the seventh, eighth, and ninth decades of life. Sleep 13 (6): 502–511. Hornyak M, Trenkwalder C (2004). Restless legs syndrome and periodic limb movement disorder in the elderly. J Psychosom Res 56: 543–548. Jacobs D, Ancoli-Israel S, Parker L et al. (1989). Twentyfour hour sleep–wake patterns in a nursing home population. Psychol Aging 4 (3): 352–356. Krystal AD, Walsh JK, Laska E et al. (2003). Sustained efficacy of eszopiclone over 6 months of nightly treatment: results of a randomized, double-blind, placebo-controlled study in adults with chronic insomnia. Sleep 26: 793–799. Launois SH, Pepin JL, Levy P (2006). Sleep apnea in the elderly: a specific entity? Sleep Med Rev 11: 87–97. Lichstein KL, Reidel BW (1994). Behavioral assessment and treatment of insomnia: a review with an emphasis on clinical application. Behav Ther 25: 659–688. Littner M, Kushida C, Anderson WM et al. (2004). Practice parameters for the dopaminergic treatment of restless legs syndrome and periodic limb movement disorder. Sleep 27: 557–559. Livingston G, Blizard B, Mann A (1993). Does sleep disturbance predict depression in elderly people? A study in inner London. Br J Gen Pract 43: 445–448. Mant A, King M, Saunders NA et al. (1995). Four-year follow-up of mortality and sleep-related respiratory disturbance in non-demented seniors. Sleep 18: 433–438. Martin J, Stepnowsky C, Ancoli-Israel S (2002). Sleep apnea in the elderly. In: WT McNicholas, EA Phillipson (Eds.), Breathing Disorders During Sleep. W.B. Saunders, London, pp. 278–287. Middelkoop HA, Kerkhof GA, Smilde-van den Doel DA et al. (1994). Sleep and ageing: the effect of institutionalization
on subjective and objective characteristics of sleep. Age Ageing 23: 411–417. Mitler MM, Hajdukovic RM, Shafor R et al. (1987). When people die. Cause of death versus time of death. Am J Med 82: 266–274. Montplaisir J (2004). Abnormal motor behavior during sleep. Sleep Med 5 (Suppl 1): S31–S34. Morin CM, Colecchi C, Stone J et al. (1999a). Behavioral and pharmacological therapies for late life insomnia. J Am Med Assoc 281: 991–999. Morin CM, Hauri PJ, Espie CA et al. (1999b). Nonpharmacologic treatment of chronic insomnia. An American Academy of Sleep Medicine review. Sleep 22: 1134–1156. NIH (2005). National Institutes of Health State of the Science Conference Statement on Manifestations and Management of Chronic Insomnia in Adults, June 13–15, 2005. Sleep 28: 1049–1057. Nowell PD, Buysse DJ (2001). Treatment of insomnia in patients with mood disorders. Depress Anxiety 14: 7–18. Ohayon MM, Roth T (2002). Prevalence of restless legs syndrome and periodic limb movement disorder in the general population. J Psychosom Res 53: 547–554. Ohayon MM, Vecchierini MF (2005). Normative sleep data, cognitive function and daily living activities in older adults in the community. Sleep 28: 981–989. Ohayon MM, Caulet M, Priest RG (1997). Violent behavior during sleep. J Clin Psychiatry 58: 369–376. Ohayon MM, Carskadon MA, Guilleminault C et al. (2004). Meta-analysis of quantitative sleep parameters from childhood to old age in healthy individuals: developing normative sleep values across the human lifespan. Sleep 27: 1255–1273. Olson EJ, Boeve BF, Silber MH (2000a). Rapid eye movement sleep behaviour disorder: demographic, clinical and laboratory findings in 93 cases. Brain 123: 331–339. Olson EJ, Boeve BF, Silber MH (2000b). Rapid eye movement sleep behaviour disorder: demographic, clinical and laboratory findings in 93 cases. Brain 123: 331–339. Pat-Horenczyk R, Klauber MR, Shochat T et al. (1998). Hourly profiles of sleep and wakefulness in severely versus mild-moderately demented nursing home patients. Aging Clin Exp Res 10: 308–315. Paudel M, Taylor B, Diem S et al. (2008). Association between depressive symptoms and sleep disturbances among community-dwelling older men. J Am Geriatr Soc 56: 1228–1235. Perlis ML, Smith LJ, Lyness JM et al. (2006). Insomnia as a risk factor for onset of depression in the elderly. Behav Sleep Med 4: 104–113. Phillips B, Ancoli-Israel S (2001). Sleep disorders in the elderly. Sleep Med 2: 99–114. Pollak CP, Perlick D (1991). Sleep problems and institutionalization of the elderly. J Geriatr Psychiatry Neurol 4: 204–210. Rediehs MH, Reis JS, Creason NS (1990). Sleep in old age: focus on gender differences. Sleep 13 (5): 410–424.
NORMAL AND ABNORMAL SLEEP IN THE ELDERLY Redline S, Strauss ME, Adams N et al. (1997). Neuropsychological function in mild sleep-disordered breathing. Sleep 20: 160–167. Reid KJ, Martinovich Z, Finkel S et al. (2006). Sleep: a marker of physical and mental health in the elderly. Am J Geriatr Psychiatry 14: 860–866. Riemann D, Voderholzer U (2003). Primary insomnia: a risk factor to develop depression? J Affect Disord 76: 255–259. Roehrs T, Roth T (2001). Sleep, sleepiness, sleep disorders and alcohol use and abuse. Sleep Med Rev 5: 287–297. Roger M, Attali P, Coquelin JP (1993). Multicenter, doubleblind, controlled comparison of zolpidem and triazolam in elderly patients with insomnia. Clin Ther 15 (1): 127–136. Roth T, Roehrs T, Zorick F (1988). Pharmacological treatment of sleep disorders. In: RL Williams, I Karacan, CA Moore (Eds.), Sleep Disorders: Diagnosis and Treatment. John Wiley, New York, pp. 373–395. Roth T, Stubbs C, Walsh JK (2005). Ramelteon (TAK-375), a selective MT1/MT2-receptor agonist, reduces latency to persistent sleep in a model of transient insomnia related to a novel sleep environment. Sleep 28: 303–307. Scharf MB, Mayleben DW, Kaffeman M et al. (1991). Dose response effects of zolpidem in normal geriatric subjects. J Clin Psychiatry 52 (2): 77–83. Scharf MB, Erman M, Rosenberg R et al. (2005). A 2-week efficacy and safety study of eszopiclone in elderly patients with primary insomnia. Sleep 28: 720–727. Schenck CH, Mahowald MW (1990). Polysomnographic, neurologic, psychiatric, and clinical outcome report on 70 consecutive cases with the REM sleep behavior disorder (RBD): sustained clonazepam efficacy in 89.5% of 57 treated patients. Cleve Clin J Med 57: S10–S24. Schenck CH, Bundlie SR, Patterson AL et al. (1987). Rapid eye movement sleep bahavior disorder. A treatable parasomnia affecting older adults. J Am Med Assoc 257: 1786–1789. Schenck CH, Hurwitz TD, Mahowald MW (1993). Symposium. Normal and abnormal REM sleep regulation: REM sleep behaviour disorder: an update on a series of 96 patients and a review of the world literature. J Sleep Res 2: 224–231. Schenck CH, Bundlie SR, Mahowald MW (1996). Delayed emergence of a parkinsonian disorder in 38% of 29 older men initially diagnosed with idiopathic rapid eye movement sleep behavior disorder. Neurology 46: 388–393. Schnelle JF, Cruise PA, Alessi CA et al. (1998). Sleep hygiene in physically dependent nursing home residents. Sleep 21: 515–523. Sforza E, Krieger J, Petiau C (1997). REM sleep behavior: clinical and physiopathological findings. Sleep Med Rev 1: 57–69. Shahar E, Whitney CW, Redline S et al. (2001). Sleepdisordered breathing and cardiovascular disease: cross sectional results of the Sleep Heart Health Study. Am J Respir Crit Care Med 163: 19–25.
665
Shochat T, Martin J, Marler M et al. (2000). Illumination levels in nursing home patients: effects on sleep and activity rhythms. J Sleep Res 9: 373–380. Smallwood RG, Vitiello MV, Giblin EC et al. (1983). Sleep apnea: relationship to age, sex, and Alzheimer’s dementia. Sleep 6: 16–22. Spielman AJ, Saskin P, Thorpy MJ (1987). Treatment of chronic insomnia by restriction of time in bed. Sleep 10: 45–56. Sridhar GR, Madhu K (1994). Prevalence of sleep disturbance in diabetes mellitus. Diabetes Res Clin Pract 23: 183–186. Stiasny-Kolster K, Mayer G, Schafer S et al. (2007). The REM sleep behavior disorder screening questionnaire – a new diagnostic instrument. Mov Disord 22: 2386–2393. Stone KL, Ewing SK, Lui LY et al. (2006). Self-reported sleep and nap habits and risk of falls and fractures in older women: the study of osteoporotic fractures. J Am Geriatr Soc 54: 1177–1183. Stoohs RA, Gingold J, Cohrs S et al. (1996). Sleepdisordered breathing and systemic hypertension in the older male. J Am Geriatr Soc 44: 1295–1300. Swaab DF, Fliers E, Partiman TS (1985). The suprachiasmatic nucleus of the human brain in relation to sex, age and senile dementia. Brain Res 342: 37–44. Touitou Y (2001). Human aging and melatonin. Clinical relevance. Exp Gerontol 36: 1083–1100. Van Cauter EV, Leproult R, Plat L (2000). Age-related changes in slow wave sleep and REM sleep and relationship with growth hormone and cortisol levels in healthy men. J Am Med Assoc 284: 861–868. Vitiello MV (1996). Sleep disorders and aging. Curr Opin Psychiatry 9: 284–289. Walters AS, Aldrich MS, Allen R et al. (1995). Toward a better definition of the restless legs syndrome. Mov Disord 10: 634–642. Weaver TE, Chasens ER (2006). Continuous positive airway pressure treatment for sleep apnea in older adults. Sleep Med Rev 11: 99–111. Wilcox S, Brenes GA, Levine D et al. (2000). Factors related to sleep disturbance in older adults experiencing knee pain or knee pain with radiographic evidence of knee osteoarthritis. J Am Geriatr Soc 48: 1241–1251. Young T (1996). Sleep-disordered breathing in older adults: is it a condition distinct from that of middle-aged adults? Sleep 19: 529–530. Young T, Palta M, Dempsey J et al. (1993). The occurrence of sleep disordered breathing among middle-aged adults. N Engl J Med 328: 1230–1235. Young T, Shahar E, Nieto FJ et al. (2002). Predictors of sleep-disordered breathing in community-dwelling adults: the Sleep Heart Health Study. Arch Intern Med 162: 893–900.
Subject Index NB: Page numbers in italics refer to boxes, figures and tables
A Absolute risk reduction, 281 Acetazolamide, 342, 444, 478, 1081, 1125 Acetylcholine (ACh), 79, 134, 179, 268–269 agonists, 155 Acetylcholinesterase (AChE), 134, 135 inhibitors, 876 Acoustic perturbation, 704–705, 705 Actigraphic monitoring, 55–60 acceleration signal, 56 applications, 55 circadian/diurnal rhythms, 59–60, 60 perspectives, 60–61 placement, 56, 56 sleep-wake state/sleep parameters, 56–58, 57, 58 versus polysomnography, 58–59, 59, 61 Active wakefulness (AW), 837 Acupuncture, 5, 366 Acute insomnia, 670 Acute-phase response (APR), 229, 233–234 Adenosine, 776, 1082–1083 Adie, William John, 19 Adjustment insomnia, 670 Adrenergic uptake inhibition, 804 Adrenocorticotropic hormone (ACTH), 241, 627–628, 1129 Adult obstructive sleep apnea syndrome (OSAS), 671–672 Adults, thermoregulation, 220–222 Advanced sleep phase syndrome (ASPS), 690, 958 Aerophagia, 465 African trypanosomiasis (sleeping sickness), 19 Age aging effects, 653, 1011–1015 circadian rhythm changes, 1012, 1013–1014 EEG patterns, 704, 705 headache and, 1077 melatonin and, 1012–1013, 1017 pharmacological treatment and, 758 restless-legs syndrome (RLS) and, 925–926, 927 sleep structure and, 218 sleep-related erections (SREs) and, 358 ‘Agrypnia excitata’, concept of, 990–991
AIDS (acquired immunodeficiency syndrome), 231 Air pollution, 503 Airways see Upper-airway Akinetic mutism, 1051 Akira Amemiya, 16 Alarm devices, enuresis, 365–366 Alcmaeon, 6–7, 11–12 Alcohol abuse, 442–443, 587–588 alcoholism, 757 dreaming and, 552 in pregnancy, 503–504 relapse, 589 sleep-disordered breathing (SDB) and, 589 withdrawal, 588, 990 Alertness, 919 Alice in Wonderland syndrome, 894 Alligator mississippiensis (American alligator), 102, 102 Allopregnanolone, 250 Almitrine bismesylate, 478 Alpha2 agonists, 600–601 Alternating leg muscle activation (ALMA), 889, 890 Alveolar hypoventilation, 472–473, 475, 1089, 1090, 1094 Alzheimer’s disease (AD), 656, 830, 1011, 1144 circadian dysrhythmias, 972, 1016–1021 hallucinations and, 1024–1025 insomnia and, 59, 60 medication-induced insomnia and, 1025–1026 obstructive sleep apnea syndrome (OSAS) and, 1026–1027, 1026 prevalence, 1015, 1016 see also Dementia Amantadine, 1060 Ambulatory monitoring, 385–386 American Academy of Sleep Medicine (AASM), 17, 21, 34, 712 actigraphy and, 55, 58 bright light and, 966 Manual for the Scoring of Sleep and Associated Events, 34 Multiple Sleep Latency Test (MSLT) and, 49 polysomnographic systems recommendations, 41, 42 psychological/behavioral therapy and, 731
American Academy of Sleep Medicine (AASM), (Continued) video polysomnography (VPSG) and, 65, 66 American alligator, 102, 102 American Association of Sleep Technologists, 21 American Board of Otolaryngology, 21 American Board of Pediatrics, 21 American Board of Psychiatry and Neurology, 21 American Cancer Society, 285 American College of Graduate Medical Education, 21 American Electroencephalographic Society, 66 American Sleep Disorders Association, 21, 33 American Sleep Medicine Foundation, 21 Amphetamines, 592, 1059, 1104, 1129 Aminergic systems, 373, 374–375 Amitriptyline bruxism and, 909 efficacy, 755 insomnia and, 734, 739, 755 isolated sleep paralysis (ISP) and, 895 sleep-related painful erections and, 359 Amnesia, 752 Amphibians, 101–102 Amplifiers, analog, 38–40, 40 Amyotrophic lateral sclerosis (ALS), 1035, 1091–1092, 1093, 1094, 1095, 1102 Anabolic androgenic steroids, 603 Analog amplifiers, 38–40, 40 Analytical studies, 275–276 Anemia theory, 12 ‘Animal spirits’, 10, 11, 16 Ankle dorsiflexion myoclonus, 888 Antiadrenergics, 600 Antiallergy drugs, 47 Antibiotics, 47 Anticholinergics, 366 Anticonvulsants elderly and, 754 excessive daytime sleepiness (EDS) and, 47 insomnia and, 735, 740–741, 749, 749 periodic limb movement disorder (PLMD) and, 827
(Volume 1: pages 1–666; Volume 2: pages 667–1160)
I-2
SUBJECT INDEX
Anticonvulsants (Continued) posttraumatic stress disorder (PTSD) and, 568 restless-legs syndrome (RLS) and, 937, 939–940 Antidepressants bruxism and, 902 elderly and, 754 enuresis and, 366 excessive daytime sleepiness (EDS) and, 47 hypersomnia and, 1059 insomnia and, 705–706, 734, 749, 1025 narcolepsy and, 803, 804 psychiatric diseases and, 564, 568 restless-legs syndrome (RLS) and, 1028 sleep dysfunction and, 593–596 see also Sedating antidepressants Antiepileptic drugs (AEDs), 1125, 1132–1133 continuous spikes waves during NREM sleep (CSWS) and, 1129 sleep dysfunction and, 596–597 Antihistamines, 601–602, 741, 749, 756, 1025 Antihypertensives, 47 Antiparkinsonian agents, 47, 597–598, 1001 Antipsychotics, 598–599 atypical, 740 excessive daytime sleepiness (EDS) and, 47 insomnia and, 735, 749, 756 mechanisms of action, 598 specific agents, 598–599 Antireflux medication, 47 Anxiety, 566, 583 Anxiolytics, 599–600, 749, 749 Apathy, 1057–1058 Apis mellifera (honey bee), 99–100, 100 Aplysia californica (sea slug), 99 Apnea-hypopnea index (AHI), 441, 657, 658, 689, 1060, 1061, 1097 Apparent life-threatening event (ALTE), 501–502 Aqtuqsinniq, 894 Aristotle, 7, 10, 13, 231 Armodafinil, 829, 1104 Arousability, 363, 364 Arousal, 33–34 cyclic alternating pattern (CAP) and, 708, 708, 709 cyclic nature of, 701, 702, 703, 703 diffuse projection systems, 135–136, 138–141 effects, 316, 392–393, 393 hypothesis, 510 reactivity and, 700–701, 701, 702 responses, modulation, 617 slow-wave sleep, 858–859 thresholds, 378–379 Arousal disorders, 1150–1151 classification, 674 confusional, 674, 853, 1150–1151
Arousal disorders, (Continued) paroxysmal, 1112, 1112, 1113, 1114–1115 pathophysiology, 1151 violence and, 1151 see also Parasomnias Arrhythmias, 334 Artemidorus of Daldis, 5 Arterial hypertension, 294–295, 1064 pulmonary, 332–333 systemic, 331–332 Arteries, cerebral blood flow (CBF), 319 Artifacts actigraphy and, 56 video polysomnography (VPSG) and, 70 Ascending reticular activating system (ARAS), 18, 154, 766, 1057 Aschoff, Jules, 19 Asclepiades of Bithynia, 7, 20 Asclepios, 6, 6 Aserinsky, Eugene, 17 Association of Polysomnographic Technologists, 21 Association of Professional Sleep Societies, 21 Association for the Psychophysiological Study of Sleep, 20–21 Association of Sleep Disorder Centers (ASDC), 19, 21 Asthma, 482 Astrology, 9 ‘Athalamic’ cats, 989 Atherogenesis, 1064 Atomism, 7, 10 Atomoxetine, 803, 804 Attention, 494 Attention deficit hyperactivity disorder (ADHD), 489, 490, 493–494, 826 Atypical benign partial epilepsy, 1129 Augmentation, 939 Autonomic control hypothesis, 509–510 Autonomic dysfunction, 874–875 Autonomic nervous system (ANS), 689 Autonomisms, law and, 1153–1154 Autosomal dominant nocturnal frontal lobe epilepsy (ADNFLE), 1110, 1117–1118, 1123, 1125 Avicenna, 9 Awakening concept of, 700 scoring, 33–34
B ‘Baby blues’, 645 Bacon, Francis, 9–10 Barbiturates, 19, 748, 754, 827 Barthel Index, 1067 Basal forebrain, 137, 141 Basalocortical projection system, 132, 135, 136, 137 Bayes theorem, 279–280 Beck depression inventory scores, 561 ‘Bedridden by the witch’, 894 Bed-sharing, 505
Bee, 99–100, 100 Behavioral factors, 1014–1015, 1020 arousal/quiescence, 132, 133 problems, 493–494 theories, 3, 16, 20 treatment, insomnia, 654–655 see also Rapid eye movement (REM) sleep behavior disorder (RBD) Behavioral insomnia of childhood, 671 Behavioral Sleep Medicine (Journal), 21 Behaviorally induced insufficient sleep syndrome, 673 Bekhterev, Vladimir Michailovich, 16 Belgian Association for the Study of Sleep, 21 ben Maimon, Moses (aka Maimonides), 9 Benign epilepsy of childhood with centrotemporal spikes (BECTS), 1125, 1129, 1131 Benign epilepsy with occipital paroxysms (BEOP), 1125–1126 Benign sleep myoclonus of infancy, 887–888 classification, 676 Benzodiazepine receptor agonists (BzRAs) daytime function, 751–752 dependence liability, 753 discontinuation effects, 752–753 efficacy, 737–738, 748, 749–751, 750 elderly and, 753–754 indications/limitations, 738 insomnia and, 734, 736–738, 741, 747, 749–754, 750 safety, 752–754, 756, 757 side-effects, 738 substance abuse and, 758 Benzodiazepines arousal disorders and, 1151 continuous spikes waves during NREM sleep (CSWS) and, 1129 effect on sleep, 1132 elderly and, 655, 661, 753, 754 excessive daytime sleepiness (EDS) and, 47 insomnia and, 705, 734, 736, 741, 748 NREM parasomnias and, 863 periodic limb movement disorder (PLMD) and, 827 REM behavior disorder (RBD) and, 875–876 restless-legs syndrome (RLS) and, 940, 1028 sleep-related eating disorder (SRED) and, 583 withdrawal, 990, 1080 Benztropine, 598 Berger, Johannes (Hans), 17 Bermuda reef fish, 101 Beta-agonists, 601 Beta-blockers, 552, 600, 601, 909, 1024 Bible, 8 Bilevel positive airway pressure (BiPAP), 463, 1101
(Volume 1: pages 1–666; Volume 2: pages 667–1160)
SUBJECT INDEX Billiard, Michel, 20 Binge eating, 583 Biological clocks, 18–19 Birds, 97, 103–105 Bite splint, 908, 909 ‘Black box warning’, 740, 1024 ‘Blip’ syndrome, 885 Blood pressure, 1065, 1066 Bloodletting, 4, 8, 9, 10 Blumenbach, Johann Fredreich, 12 Bmal1 genes, 954, 956 Board of Internal Medicine, 21 Board of Sleep Medicine, 21 ‘Body sleep’, 991 Body temperature, 216–218, 1018 Bodyrocking, 889 Bodyrolling, 889 Boerhaave, Hermann, 11, 12 Bootzin, Richard, 20 Botulinum toxin, 909 Bouchard, Abel, 13 Bovine spongiform encephalopathy, 981 Boyle, Robert, 10 Brain anatomy, 152–157 ‘brain sleep’, 991 damage, dreaming, 553 neuropathological examination, 818–819 obstructive sleep apnea syndrome (OSAS), changes, 81–83 organization theory, 234–236 pain processing, 617 serial reaction time (SRT), 263, 264 -signaling, 234 stimulation, 75 stress adaptation, 121–122 Brainstem aminergic systems, 373 caudal, 838–840, 839 electrical stimulation, 131 enuresis and, 365 lesions, 528 neoplasm, 1144 pontine reticular formation (PRF), 153–154, 153, 154 REM sleep-generating system, 767–768 sleep-wake cycle regulation, 773, 773 Breaking Point: How Female Midlife Crisis is Transforming Today’s Women (Shellenbarger), 647 Breath of Life (Catlin), 15, 15 Breathing, control of, 1087–1089, 1088 behavioral control, 373 central control, 371–375, 1087–1088 changes during sleep, 1089, 1090 chemical regulation, 375–377 chest bellow component, 1088–1089, 1089 control hypothesis, 509 wakefulness/sleep influences, 374–375, 374 see also Sleep-disordered breathing (SDB); Sleep-related breathing disorders (SRBDs)
Breathing pattern types, 1096–1097, 1096 Bremer, Fre´de´ric, 18 Bright light exposure circadian rhythm sleep disorders, 966, 967, 969, 971, 972 dementia and, 1020–1021, 1021 elderly and, 1014, 1019, 1025 British Sleep Society, 21 Broadbent, William Henry, 15 Bromocriptine, 1059 Bronchial irritation, 379 Bronchodilators, 478, 601, 1025 Brotizolam, 705, 708 Broughton, Roger, 20 Brown-Se´quard, Charles Edouard, 13 ‘Brux index’, 904, 907 Bruxism, 901–909 classification, 675 diagnosis, 903–905, 904 epidemiology, 901–902 genetics, 901–902 headache and, 1077 management, 907–909, 908 pathophysiology, 904, 905–907, 906 risk factors, 902–903 ‘Bruxomanie’, 905 Bufo boreas (western toad), 102 Bullfrog, 102, 102 Bunning, Erwin, 18 Bupropion, 78, 595 Burwell, Charles Sidney, 20 Buspirone, 599–600, 909
C
Cabergoline, 937, 938 Caffe, P., 14 Caffeine headache and, 1082–1083 restless-legs syndrome (RLS) and, 940 slow release, 972 wakefulness and, 590, 776 withdrawal, 1080 Caiman sclerops (caiman), 102 Cajal, Santiago Ramo´n y, 12–13 Calcium, 1014 Calcium channel blockers, 601, 1025 Canadian Continuous Positive Airway Pressure for patients with central sleep apnea and heart failure (CANPAP) study, 415, 434 Cancer patients, 231 Canine narcolepsy models, 787–788, 789, 790, 791 Cannabidiol, 590 Cappie, James, 12 Carassius auratus (goldfish), 101 Carbamazepine effect on sleep, 1132 hallucinations and, 1023 Kleine–Levin syndrome and, 830 nocturnal frontal lobe epilepsy (NFLE) and, 1125 REM behavior disorder (RBD) and, 1023
I-3 Carbamazepine (Continued) restless-legs syndrome (RLS) and, 937, 939 sleep dysfunction and, 596 Carbidopa, 597 Carbon dioxide, cerebral blood flow (CBF) and, 318–319, 319 Cardiac failure see Heart (cardiac) failure Cardiac pacing, 341–342 Cardiac resynchronization therapy (CRT), 341 Cardiac transplantation, 341 Cardiocerebrovascular disorders, 330, 331 Cardiorespiratory failure, 425–426 Cardiovascular diseases, 327–342 central sleep apnea (CSA) and, 322, 322, 338–339 congestive heart failure, 336–342 continuous positive airway pressure (CPAP) and, 330, 334–335, 341, 433 definitions, 327, 328, 329 obstructive sleep apnea syndrome (OSAS) and, 320–321, 321, 329–336, 329, 330, 331, 335 polysomnography, 329 Cardiovascular effects of arousal, 316 Cardiovascular events, 316–317, 317 Cardiovascular medications, 600–601 Cardiovascular physiology neural circulatory regulation, 315, 316 NREM sleep, 315, 316, 317 REM sleep, 315–316, 316, 317 Caretta caretta L. (loggerhead sea turtle), 103 Carskadon, Mary, 17 Cartoon face scale, 48 Case-control studies, 276 Casein Kinase 1 epsilon gene, 956 Castration, 250, 359 Cataplexy, 14, 16, 289, 672, 785, 828 atonia, 845 narcolepsy with, 672, 785, 786, 793–794, 796 Cataracts, 1013 Catathrenia (groaning), 674, 891–892, 891 Catlin, George, 15, 15 Caton, Richard, 17 Caudal brainstem, 838–840, 839 Cellular aspects, 191, 261–262 stress, 193–194, 194 Cellular prion protein (PrPC), 981–982, 991 Central nervous system (CNS) hypersomnia and, 830 pain and, 614 stimulants, 592–593, 783, 802, 1025 Central pattern generator (CPG) neuronal network, 906 Central sensitization, 627 Central sleep apnea (CSA), 411–417 at altitude, 413, 413
(Volume 1: pages 1–666; Volume 2: pages 667–1160)
I-4
SUBJECT INDEX
Central sleep apnea (CSA), (Continued) cardiovascular diseases and, 322, 322, 338–339 Cheyne-Stokes breathing (CSB), 413–415, 414, 415–417, 416 classification, 671 complex sleep apnea, 417 continuous positive airway pressure (CPAP) and, 415–416, 416, 422, 422, 433–434 defined, 411 dementia and, 1028 hemodynamic changes, 321–322, 322 hypercapnic, 411–412 hypocapnic, 412–417, 412 idiopathic, 413 periodic breathing, 338 sleep hypoventilation syndrome, 411–412, 412 stroke and, 322, 322, 1060, 1063 treatment, 340, 340 Cerebral blood flow (CBF) intrinsic vasogenic autoregulation, 317–318, 318 major arteries, 319 metabolic regulation, 318 oxygen/carbon dioxide concentration, 318–319, 319 regional (rCBF), 72–73, 72, 78, 319 regulation, 317–319 Cerebral glucose metabolism (CMRGlu), 74, 76, 76, 81, 81 Cerebral reactions, experiencedependant, 263–264, 264 Cerebrospinal fluid (CSF), 16, 320, 771–773, 775, 930–932, 1143 narcolepsy and, 789–790, 792, 794–796, 795, 799, 829 studies, 934 Cerebrovascular events, 316–317, 317 Cerebrovascular physiology, 317–319, 318 Cetirizine, 601–602 Charcot–Marie–Tooth (CMT) disease, 924, 1093 Charcot–Wilbrand syndrome, 1053 Chemical regulation, breathing, 375–377 Chemical theories, 13, 15–16 Chemoreceptors, 375 Chest bellow component, 1088–1089, 1089 Chester Beatty papyrus, 4 Cheyne–Stokes breathing (CSB), 295, 327 central sleep apnea (CSA) and, 413–415, 414, 415–417, 416, 671 stroke and, 1060–1061, 1061, 1063 ‘Chicago criteria’ (AASM), 411 Children, 489–496 behavioral insomnia of childhood, 671 behavioral problems, 490–493, 492, 493 child care setting, 505 epilepsy and, 1125–1126 headache and, 1075, 1077 psychobehavioral problems, 493–496
Children, (Continued) restless-legs syndrome (RLS) and, 916, 917, 940 snoring/sleep apnea, 294 see also Enuresis Children’s Sleep Habits Questionnaire, 49 China, ancient, 5 Chloral hydrate, 754 Chlordiazepoxide (LibriumÒ), 748 Choking syndrome, sleep-related, 892 Choline acetyltransferase (ChAT), 134, 135 Cholinergic agonists, 155–156 Cholinergic modulators, 805 Cholinergic neurons, 156, 838 Cholinergic pontomesencephalic neurons, 132, 134 Cholinergic projections, 152, 155, 155 Christianity, 8 Chronic fatigue syndrome (CFS) see Fibromyalgia (FM)/chronic fatigue syndrome (CFS) Chronic insomnia, 231 Chronic morning headache (CMH), 1073 Chronic obstructive pulmonary disease (COPD), 471–481 mechanisms, 473–476, 474 medications, 478–479 noninvasive intermittent positive pressure ventilation (NIPPV) and, 463 studies, 476–477 therapeutic intervention, 477 treatment, 477–480 Chronobiology, 14 Chronotherapy, 20, 966, 967 Chuang Tzu, 5 Cichlosoma nigrofasciatum (perch), 101 Cimetidine, 602 Circadian rhythm, 19, 963–964 actigraphic monitoring, 59–60, 60 age-related changes, 1012, 1013–1014 cardiovascular/cerebrovascular events, 316–317, 317 control, 167 cryptochromes, 954–955 elderly, 656–657, 656 genetics, 952–954, 955, 956 master neural clock, 951–952 molecular model, 956–957, 957 sleep regulation, 768 snoring and, 298 stroke and, 298, 1054, 1059–1060 women, 641–642 Circadian rhythm sleep disorders, 20, 673–674, 686, 826 advanced sleep phase type, 673, 865, 966–967, 967, 1017 delayed sleep phase type (DSPT), 673, 964–966, 964, 965, 1017 free-running type (nonentrained), 673, 968–969, 968 genetics, 690 irregular sleep-wake type, 673, 969–970, 969
Circadian rhythm sleep disorders, (Continued) jet lag type, 673, 971–972, 971 mental condition and, 972, 972 shiftwork type, 673–674, 970–971, 970 Cirignotta, F., 20 Citalopram, 1024 Clapare`de, Edouard, 16 Classification, 669–676 development of new, 669 history, 669–670 Climate, 503 Clinical Antipsychotic Trials of Intervention Effectiveness Alzheimer’s disease (CATIE-AD), 1024 Clinical Journal of Sleep Medicine (Journal), 21 Clinical Sleep Society, 21 Clobazam, 1129 Clock genes, 953–954, 953 Clomipramine, 803, 803, 1129 Clonazepam bruxism and, 908 continuous spikes waves during NREM sleep (CSWS) and, 1129 elderly and, 661 REM behavior disorder (RBD) and, 875–876, 1023 restless-legs syndrome (RLS) and, 937, 940 Clonidine, 600, 909, 940 Clozapine, 598–599, 1023 Cluster headache (CH), 1076, 1078, 1079 Cocaine, 592–593 Cognition, 1022 Cognitive impairment, 916 Cognitive-behavioral therapy (CBT) bruxism and, 908 elderly and, 655 insomnia and, 731, 733, 736, 758 Cohort studies, 276 Color vision dysfunction, 874 Comorbid insomnia, 698, 725, 757 treatment, 732–733 Complex motor seizure, 1115–1116, 1117 Computerization, 40–41 Confusional arousals, 674, 853, 1150–1151 Congenital central hypoventilation syndrome, 672 Congestion theory, 12 Congestive heart failure, 336–342 central sleep apnea (CSA) and, 414, 415–417, 416 Cheyne-Stokes breathing (CSB) and, 415–417 Continuous positive airway pressure (CPAP), 20, 82, 83 autotitrating, 426–428 cardiac failure, 433–434 cardiovascular diseases, 330, 334–335, 341, 433 central sleep apnea (CSA), 415–416, 416, 422, 422, 433–434
(Volume 1: pages 1–666; Volume 2: pages 667–1160)
SUBJECT INDEX Continuous positive airway pressure (CPAP), (Continued) chronic obstructive pulmonary disease (COPD), 476, 479 compliance, 430–432 elderly and, 659 health outcomes, 432–433 home setting, 426 interface, 429 long-term, 431 management, failure, 432 mode of action, 422, 422 neuromuscular disorders, 1101 obstructive sleep apnea syndrome (OSAS), 421–434, 1027, 1066, 1076 practical aspects, 422–426, 424, 425 pressure level/airflow, 427, 429–430 side-effects, 428–430, 428 sleep-related breathing disorder (SRBDs), 1030–1031 technologists, 432 treatment comparisons, 430 upper-airway resistance syndrome (UARS), 407 usage, 431–432 vascular effects, 1065, 1066 Continuous spikes waves during NREM sleep (CSWS), 1127–1129 age of onset/complications, 1127–1128 differential diagnosis, 1128–1129 pathology/physiology, 1128 polysomnographic findings, 1128 subtypes, 1127 treatment, 1129 Continuous ventilation, 464 Coronary artery disease, 334 Coronary disease, 1064 Corpus Hippocraticum (Hippocrates), 7 Cortical activation, 131, 132, 133 episodic, 33 Cortical pathology, 934–935, 935 Cortical silent period (CSP), 934–935 Corticobasal degeneration (CBD), 1033 Corticosteroids, 1025, 1129, 1141 Corticotropin-releasing factor (CRF), 839 Corticotropin-releasing hormone (CRH), 245–246, 685–686 Cortisol, 241, 245 ‘Cosinor’ method, 59 Cramp, 675, 888 Crayfish, 99 Creutzfeldt–Jacob disease (CJD), 981, 983, 985, 987–988 CRY protein, 955, 956, 957, 957 Cryptochromes, 954–955 cryptochrome genes, 685 Cuirass ventilator, 1101 Culture, 503 Cuttlefish, 99 Cyclic alternating pattern (CAP), 701–705, 702, 705, 709, 855 arousal and, 708, 708, 709
Cyclic alternating pattern (CAP), (Continued) effects of zolpidem, 705 scoring, 32, 33–34, 33, 718–719, 720, 721 Cyclobenzaprine, 756 Cyproheptadine, 601 Cystic fibrosis, 482 Cytokines, sleep regulation and, 229–232, 231 Czeisler, C.A., 19
D
Danio rerio (zebrafish), 101 Davey, James George, 14 Daytime light exposure, elderly, 1014, 1019, 1025 see also Bright light exposure de Candolle, Augustin Pyramus, 14 de Lecea, Luis, 16 de Mairan, Jacques, 10, 14, 18 de Manace´¨ıne, Marie, 13 De Humani Corporis Fabrica (Vesalius), 9 ‘Deafferentation’ theory, 17–18 ‘De-arousal’, 990 Death, sudden, 299, 740, 1062 see also Sudden infant death syndrome (SIDS) Decongestants, 1025 Dehydroepiandrosterone (DHEA), 250 Dejerine, Joseph Jules, 17 Delayed sleep phase syndrome (DSPS), 20, 958 Delirium tremens, 710–711, 990 Delta brush patterns, 113 Delta wave patterns, 114, 115, 115, 116 Delta-9-tetrahydrocannabinol (THC), 590–591 Dement, William, 17, 19, 20, 21 Dementia, 661–662, 830, 1015–1027, 1015, 1016 causes, 1016 circadian dysrhythmias, 1016–1021 hallucinations and, 1024–1025 insomnia and, 284, 710 with Lewy bodies (DLB), 1011, 1021–1024, 1145 medication-induced insomnia and, 1025–1026 medications for, 47 multiple system atrophy (MSA) and, 1028–1032 neurodegenerative diseases and, 1022, 1027–1028, 1033–1035 obstructive sleep apnea syndrome (OSAS) and, 1026–1027, 1026 prevalence, 1015, 1016 progressive supranuclear palsy (PSP) and, 710, 1032–1033, 1144 snoring/sleep apnea and, 299 see also Alzheimer’s disease (AD) Democritus of Abdera, 7 Dental appliances, 445–448, 908, 909
I-5 Dental appliances, (Continued) cost, 448 efficacy, 447 mechanism of action, 446 side effects, 448 treatment adherence, 447–448 types, 445–446, 446 vs continuous positive airway pressure (CPAP), 448 Depression, 557–565 elderly and, 654 multiple sclerosis (MS) and, 1140 neuroimaging, 76–78 psychophysiological relationships, 558–560 sleep complaints, 557 sleep variables, 557–558, 560–564, 560, 561, 563 treatment, 564, 593, 594, 756 Descartes, Rene´, 10 Descriptive studies, 275–276 Desert iguana, 104 Desipramine, 803, 804 Desmopressin, 366 Detrusor overactivity, 364 Detrusor relaxants, 366 Dextroamphetamine, 804, 829 Diabetes mellitus, type II, 1064–1065 Diabetic autonomic neuropathy, 1093 Diagnostic Classification of Sleep and Arousal Disorders (DCSAD), 19, 20, 670 Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) circadian rhythm sleep disorders, 963 depression, 76 insomnia, 706, 724, 725, 748 nightmare disorder, 547 NREM parasomnias, 860, 861 sleep-related eating disorder (SRED), 577 sleep-wake cycle, 1025 Dialysis, 922–923 Diaphragmatic pacing, 1103–1104 Diastolic heart failure, 336–337 Diazepam, 908 Dichotomy of sleep, 16 Dickens, Charles, 14–15, 20, 383 ‘Diencephalic’ cats, 989 Dim-light melatonin onset (DLMO), 964 Diogenes, 7 Diphenhydramine, 601–602, 735, 741, 754, 756 Dipsosaurus dorsalis (desert iguana), 104 Diurnal rhythms, actigraphic monitoring, 59–60, 60 Doll, Eric, 20 Donders, Frans Cornelius, 12 Donepezil hallucinations and, 1024 insomnia and, 1025 REM behavior disorder (RBD) and, 876, 1023 Dopamine (DA), 138, 552
(Volume 1: pages 1–666; Volume 2: pages 667–1160)
I-6
SUBJECT INDEX
Dopamine (DA) agents, 876 restless-legs syndrome (RLS) and, 937, 938–939, 1028 Dopamine (DA) agonists, 828 elderly and, 660, 660 excessive daytime sleepiness (EDS) and, 997, 998–999, 1000 restless-legs syndrome (RLS) and, 938 sleep dysfunction and, 583, 597–598 Dopamine (DA) system, 79, 932–934 transmission, 804–805 Dopaminergic antipsychotics, 902 Dopaminergic mesencephalic neurons, 138–139 Dorsal raphe (DR), 767 Dorsal raphe nucleus (DRN), 162, 163, 165, 166, 776, 840 Dorsal raphe serotonergic neurons, 139, 158–159, 159 Dorsal respiratory group (DRG) neurons, 1088 Dorsomedial nucleus of hypothalamus (DMH), 768, 769 Doxepin, 734, 739, 741 Doxylamine, 741 Dreaming, 519–540 Biblical dreams, 8 Charcot–Wilbrand syndrome, 519–520 conditions for, 539–540 excessive, 530, 534–536 functional neuroanatomy, 540 global loss/suppression, 520, 522, 523–527 headache and, 1076 historical perspective, 4, 8, 16, 17 neurobiology, 546 neurochemical/psychopharmacological findings, 533, 539, 5533 neuroimaging, 531–533, 539 pontine brainstem lesions, 528 prefrontal leukotomy, 522, 528, 528, 529–530, 531, 532, 533 psychology, 546–547 REM behavior disorder (RBD), 869–870 sleep cycle and, 545 theoretical considerations, 539–540 visual imagery, loss of, 520, 521 Dreaming, abnormal, 545–554 clinical disorders, 547–552 lucid dreaming, 553–554 nightmares, recurring, 530–531, 537–539 non-clinical disorders, 552–553 see also Nightmare disorder Drosophila, 100, 105, 106, 768, 952, 953, 954, 955 Drosophila doubletime gene, 956 Drosophila melanogaster (fruit fly), 99, 100 Drug abuse, 587–593, 588 addiction, 503 bruxism and, 902 central sleep apnea (CSA) and, 671
Drug abuse, (Continued) circadian rhythm sleep disorders and, 674 dreaming and, 552 hypersomnia and, 673 insomnia and, 671, 757 movement disorder and, 675 parasomnias and, 675 prescribed medications, 593–603 Drug-induced REM behavior disorder (RBD), 873 Dubois, Raymond Emil, 13 Duchenne muscular dystrophy, 1094 Duloxetine, 596 Dupuy General Wellbeing, Vitality subscale, 645 Du¨rer, Albrecht, 9 Durham, Arthur Edward, 12 Duval, Marie Mathias, 12 Dynes, John Burton, 19 Dystonia, 1034–1035
E
Eating disorders, 581, 583 see also Sleep-related eating disorder (SRED) Eaton–Lambert myasthenic syndrome, 1093 Echidna, short-beaked, 104, 105 Ecstasy (3,4-methylenedioxy methamphetamine), 591 Edison, Thomas A., 20 EEG of Human Sleep: Clinical Applications (Williams), 38 Effect size, 281 Effector neurons, 153–154, 153, 154 Egypt, ancient, 4–5 Eichler, Victor B., 18–19 Elderly, 653–662 aging effects, 653, 1011–1015 benzodiazepine receptor agonists (BzRAs) and, 753–754 circadian rhythm, 656–657, 656 daytime light exposure and, 1025 dementia and, 661–662 insomnia and, 653–655 institutionalized, 661–662, 662 obstructive sleep apnea syndrome (OSAS) and, 1026 primary sleep disorders and, 657–661 restless-legs syndrome (RLS) and, 940 snoring/sleep apnea and, 294 thermoregulation, 220–222 Electrical status epilepticus of sleep (ESES), 1127 Electrical stimulation, 131 Electroencephalography (EEG), 19, 30–38 aging, patterns and, 38, 39 behavior episodes, 856, 857 data reduction, 34–37, 35 depression and, 558 discontinuity, 113, 114 electrode placement, 65, 66
Electroencephalography (EEG), (Continued) familial fatal insomnia (FFI) and, 983–985, 984, 985 night patterns, 37–38, 37, 38 pattern maturity, 112–116 power spectral analysis, 403–404 recurrent hypersomnias and, 817 REM sleep analysis, 151–152, 152 sleep homeostasis and, 208–210, 209, 210, 211 sleep terrors and, 859 traditional recording technique, 29–31, 30 waveforms, 31–34, 31 women and, 640 Electromyography (EMG), 30, 34, 35 Electro-oculography (EOG), 34, 35 Electrophysiology, 11, 17 Elementa Physiologiae (von Haller), 11 ‘Elpenor’s syndrome’, 1151 Empedocles, 7 Emys orbicularis (pond turtle), 103 ‘Encephalitis lethargica’, 830 Endocrine/metabolic changes, 241–251 galanin, 248–249 gonadal hormones, 249 hypothalamo-pituitary-adrenocortical (HPA) system, 241, 242, 244–246 hypothalamo-pituitary-somatotrophic (HPS) system, 241–244 hypothalamo-pituitary-thyroid (HPT) system, 246–247 insulin, 247–248 leptin/ghrelin, 247 melatonin, 249 neuroactive steroids, 250 neuropeptide Y, 249 prolactin, 248 End-stage renal disease, 922–923 Energy metabolism, 193–194, 194 Enuresis, 355–356, 363–368 classification, 674 defined, 363 epidemiology, 363 etiology/pathogenesis, 363–365 management, 366–368 treatment, 365–366 Environmental factors light exposure, 1014, 1019 narcolepsy, 784 sudden infant death syndrome (SIDS) and, 504–505, 508, 511–512, 511 Ephedra (Ma Huang), 5 Epic dreaming, 551–552 Epicurus, 7 Epidemiological methods, 275–282 confounding, 278–279 data collection, 276 information bias, 278 P-value, 277 population size, 277 population surveys, 276 population-based rates, 279–282
(Volume 1: pages 1–666; Volume 2: pages 667–1160)
SUBJECT INDEX Epidemiological methods, (Continued) power calculations, 277 randomized controlled trials, 279 selection bias, 278 standardization/matching, 279 studies, 275–276 validity, 277–278 Epidemiology, sleep disorders, 282–303 bruxism, 901–902 enuresis, 363 epilepsy, 1110 excessive daytime sleepiness (EDS), 286–289, 287–288, 997–998 insomnia, 282–285, 723 narcolepsy, 289, 290, 784 parasomnias, 300 REM behavior disorder (RBD), 1001 restless-legs syndrome (RLS), 300, 301–302, 303, 1142 sleep-related breathing disorder (SRBD), 286, 291 smoking, 589 snoring/sleep apnea, 289–300 upper-airway resistance syndrome (UARS), 402 Epilepsy, 1109–1133 antiepileptic drugs (AEDs) and sleep, 1125, 1132–1133 dreaming and, 552 effect on sleep, 1129–1130 epidemiology, 1110 focal, 68–69 generalized syndromes, 68, 1110, 1126 historical perspectives, 1109–1110 insomnia and, 710 interictal epileptiform discharge (IED), 1126, 1130–1131 overview, 1133 pathogenesis, 1110–1111 sleep deprivation and, 1131 sleep disorders and, 1131–1132 subtypes, clinical/polysomnographic features, 1111–1129 see also Nocturnal frontal lobe epilepsy (NFLE) Epileptic nocturnal wanderings (ENW), 1112 Episodic nocturnal wanderings, 1152 Epworth Sleepiness Scale (ESS), 48, 48, 598, 999, 1051, 1098 antiepileptic drugs (AEDs) and, 1132 Erectile dysfunction (ED), 357, 358–359, 359 Erections (SREs), sleep-related, 357–359 Errera, Leo, 13 Estazolam, 734, 736, 749, 750 Estrogen levels, 642–643 Estrogen replacement therapy (ERT), 603, 646, 647 Eszopiclone circadian sleep disorders and, 826 elderly and, 655 insomnia and, 734, 738, 749, 750, 751 restless-legs syndrome (RLS) and, 940
Ethnic differences, 294 Ethosuximide, 1129 European data format (EDF), 43 European Neurological Society, 383 European Sleep Research Society, 21 Event-related desynchronization (ERD), 935–936 Event-related synchronization (ERS), 935 Evoked potentials, 51 Excessive daytime sleepiness (EDS), 45–52, 825–830 clinical characteristics, 1051–1052 elderly and, 653, 658, 659 epidemiology, 286–289, 287–288, 997–998 etiology, 46, 998–999 evaluation, 999, 1000 hallucinations and, 1002–1003 historical perspective, 45–47 Maintenance of Wakefulness Test (MWT), 50–51 medications, 47 Multiple Sleep Latency Test (MSLT), 48–49, 49–50 narcolepsy and, 783, 784–785, 786, 788, 792, 800 neurological basis, 825 nocturnal polysomnography, 49 obstructive sleep apnea syndrome (OSAS) and, 231 orexin (hypocretin) and, 769, 770, 800 Parkinson’s disease (PD) and, 997–1000 pathophysiology, 998–999, 1057–1058 physical examination, 47–48 practical applications, 51–52 sleepiness syndromes, 825–830 special tests, 51 subjective testing, 48–49, 48 treatment, 802, 802, 999–1000 Excessive fragmentary myoclonus, 676 hypnic (EFHM), 884–885, 885 Exorcism, 9 Exploding head syndrome, 885, 1075, 1077, 1079 classification, 674 Eye motility, 30
F ‘Factor S’, 16 Familial advanced sleep phase syndrome (FASPS), 198 Familial sleep disorders, genetics, 686–690 Famotidine, 602 Fatal familial insomnia (FFI), 20, 198, 710–711, 981, 982–988, 1035 ‘agrypnia excitata’, concept of, 990–991 clinical features, 982–983, 983 genetics, 198 laboratory findings, 983–985, 984, 985 molecular neurobiology, 987–988 neuroimaging, 985–988, 986
I-7 Fatal familial insomnia (FFI), (Continued) neuropathological aspects, 986–987 prion protein and, 991–992 thalamus and, 988–990 Fatigue, 231, 919 clinical characteristics, 1051–1052 pathophysiology, 1057–1058 see also Fibromyalgia (FM)/chronic fatigue syndrome (CFS) Fatigue Severity Scale (FSS), 1051 Fear and Avoidance Scale, 431 Feet movement foot tremors, hypnagogic, 676, 889 rhythmic, 889 Felbamate, 596, 1132 Ferritin, 930–932 Fetal growth retardation, 503 Fibromyalgia (FM)/chronic fatigue syndrome (CFS), 231, 621–631, 1080 associated conditions, 624–625 background, 621–622 definitions, 622–623 diagnosis, 622, 628–629 pathogenesis/pathophysiology, 627–628 prevalence/risk factors, 623–624 recommendations, 630–631 sleep disturbance and, 614, 625–626 treatment, 629–630 Filter settings, 39, 40 Finley, Knox H., 19 Finnish Twin Cohort, 275 ‘First-night effect’, 58 Fischer, Franz, 14 Fish, 100–102 Flamingos, 104 Fleming, Alexander, 12 ‘Flip-flop’ switch, 712, 776 Flourens, Marie Jean Pierre, 11, 13 Flower clock, 10 Fluoxetine, 595, 706, 803, 804 Flurazepam bruxism and, 909 insomnia and, 708, 734, 736, 749, 750 Fluvoxamine, 803 Focal epilepsy, 68–69 Focal temporal lobe epilepsy, 1130 Follicle-stimulating hormone (FSH), 644 Food allergy insomnia, 20 Food deprivation, 777 Food and Drug Administration (FDA), 657, 736, 741, 748, 754, 938, 971, 1020, 1028, 1104 Foot tremors, hypnagogic, 676, 889 Forebrain basal, 137, 141 modulation, 840–842, 841 reticular activating system, 134–135, 766 reticular neuron projection, 132, 133 Forel, Auguste Henri, 18 Forensic experts, 1154 Framington Cohort, 275
(Volume 1: pages 1–666; Volume 2: pages 667–1160)
I-8
SUBJECT INDEX
Freud, Sigmund, 15, 16, 19 Frogs, 102 Frontal Lobe Epilepsy and Parasomnias (FLEP) Scale, 1123 Frontal lobe lesions, 529–530 Frontotemporal dementia (FTD), 1017 Fruit fly, 99, 100 Fu Hsi, 5 Fujita, Shiro, 20 Functional magnetic resonance imaging (fMRI), 71 memory and, 263, 266 narcolepsy, 79–80 obstructive sleep apnea syndrome (OSAS), 83 periodic limb movement, 85 Functional Outcomes of Sleep Questionnaire, 49 Functional residual capacity (FRC), 475
G GABAergic influences dorsal raphe nucleus (DRN)/locus caeruleus (LC), 163, 166 pontine reticular formation (PRF), 165 REM sleep, 161–164, 164–167, 165 Gabapentin, 596–597 bruxism and, 909 effect on sleep, 1132 insomnia and, 735, 740 restless-legs syndrome (RLS) and, 828, 937, 939, 1028 Gaboxadol, 1132 Galanin, 248–249 Galantamine, 1025 Galbraith, J.J., 19 Galen, 8 Galvani, Luigi, 11 Gamma-aminobutyric acid (GABA), 133, 591, 726, 1111 agonists, 1132 complex, 749 GABAergic neurons, 141–143, 166–167, 178, 179–181, 767 hypnotic drugs and, 143 REM sleep disinhibition, 163–164, 164 system, 740–741 see also GABAergic influences Gamma-hydroxybutyrate (GHB), 591, 802–803 modes of action, 805 ‘Gas’, 10 Gastaut, Henri, 20 Gastroesophageal reflux (GER), 348–350, 348, 349, 350 clinical aspects, 350–351 disease (GERD), 348, 350–351 Gastrointestinal functioning, 348–353 intestinal motility, 351–353 Gating, sensory transmission, 618–619 Gayet, Maurice Edouard Marie, 13 Ge´lineau, Jean Baptiste Edouard, 14, 19 Gender differences bruxism, 901–902
Gender differences (Continued) restless-legs syndrome (RLS), 924–925 see also Women Generalized anxiety disorder (GAD), 566, 728 Generalized epilepsy syndromes, 68 Generalized tonic-clonic seizures (GTCSs), 1110, 1126 Genetics, 681–690 bruxism, 901–902 circadian rhythm, 690, 952–954, 955, 956 familial sleep disorders, 686–690 fatal familial insomnia (FFI), 198 gene expression, 191–196, 196 Kleine–Levin syndrome (KLS), 690 memory, 268–269 narcolepsy, 198, 688–689, 784 normal sleep regulation, 681–686, 682, 684, 685 obstructive sleep apnea syndrome (OSAS), 689 periodic leg movements (PLMs), 687 restless-legs syndrome (RLS), 686–688, 929–930 of sleep, 106 sleep disorders, 197–198, 197 sleep terrors, 858 somnambulism (sleepwalking), 854 studies, 196–199, 197 sudden infant death syndrome (SIDS), 507–508 Genitourinary systems, 355 Georg Ebers papyrus, 4 German Migraine and Headache Society Study Group, 1077 Gerstmann–Straussler–Sheinker syndrome (GSS), 981 ‘Ghost oppression phenomenon’, 894 Ghrelin, 242, 247 Ginseng, 5 Glutamatergic neurons, 178–179 Glycine, 838 Goldfish, 101 Golgi, Camillo, 12 Gonadal hormones, 249 Gopherus flavomarginatus (tortoise), 103 Greece, ancient, 6–7 Griesinger, Wilhelm, 16 Groaning, nocturnal (catathrenia), 674, 891–892, 891 Growth hormone (GH), 241–242, 243 Growth hormone-releasing hormone (GHRH), 241–243 Guilleminault, Christian, 20
H
Habitual snoring see under Snoring Hallucinations, 674 complex nocturnal visual, 893–894 dementia and, 1024–1025 hypnagogic, 787, 828, 893–894, 1052, 1152 hypnopompic, 787, 893–894 Lhermitte’s peduncular, 1053
Hallucinations, (Continued) Lilliputian, 894 Parkinson’s disease (PD) and, 1002–1003 stroke and, 1053, 1055 treatment, 1024–1025 Haloperidol, 599, 902 Hamilton Depression Rating Scale (HDRS), 77 Hammond, William Alexander, 12, 14 Harvey, E. Newton, 17 Harvey, William, 9, 10 Hauri, Peter, 20 Headache, 1073–1083 causes, 1080–1081 clinical evaluation, 1074–1076, 1074 comorbidity, 1079–1081 functional aspects, 1082–1083 insomnia and, 711 prevalence, 1073–1074 sleep disturbances, associated, 1076–1081, 1078, 1081–1082 sleep duration, 1075 sleep pattern, 1075 sleep stage, 1075 sleep-relieved, 1075–1076 sleep-triggered, 1074 Headbanging, 889 Headrolling, 889 Heart (cardiac) failure, 333, 336–342, 433–434, 1064 pathophysiologic sequelae, 337–338 Heart disease, 295 Heart rate variability (HRV), 121 Hemispheric stroke, 1055, 1057, 1059 Henneberg, Richard, 14 Heraclitus, 7 Herbal medicines, 5 Heredity, enuresis and, 363 Hering–Breuer reflex, 372 Herodotus, 4–5 Hess, Walter Rudolph, 17 Heubel, E., 13 High-altitude headache, 1081 High-altitude periodic breathing, 671 Hill, Sir Leonard Erskine, 12 Hill, William, 15 Hippocrates, 7, 9, 11 Histamine (HA), 139 -orexin (hypocretin) interactions, 774–775 Histaminergic tuberomammillary neurons, 139–140 Historical perspective, 3–21 prehistoric and ancient times, 3–8 middle ages and Renaissance, 8–9 17th and 18th centuries, 9–11 19th century, 11–15 20th century, 15–21 classification, 669–670 dreaming, 4, 8, 16, 17 epilepsy, 1109–1110 excessive daytime sleepiness (EDS), 45–47, 46
(Volume 1: pages 1–666; Volume 2: pages 667–1160)
SUBJECT INDEX Historical perspective, (Continued) neurobiology, waking/sleeping, 131, 132, 133 nocturnal eating/drinking syndrome (NEDS), 577–578 recurrent hypersomnias, 815–816 sleep-related eating disorder (SRED), 577–578, 578 Hobart, Garret, 17 Hobson, J. Allan, 18 ‘Hoffman’s anodyne of opium’, 11 Homeostasis see Sleep homeostasis Homer, 3, 6 Homovanillic acid (HVA), 934 Honey bee, 99–100, 100 Hormone replacement therapy (HRT), 445, 603, 643, 647 Hormones, 602 levels, 817, 818 studies, 933 thyroid, 1025 women and, 642–643 Huang Ti, Yellow Emperor, 5 Human leukocyte antigen (HLA), 688 narcolepsy and, 783, 796–800, 797, 798, 829 recurrent hypersomnias and, 817 Humoral factors, sleep regulation, 229, 230, 769 Humoralism, 7 Huntington’s disease, 1034 5-Hydroxytryptamine (5-HT) levels, 158–159, 159, 161, 755, 776, 895, 1082 Hydroxyzine, 601–602, 756 Hygiene see Sleep hygiene Hyla squirella (tree frog), 102 Hyoscyamine, 4 Hyperalgesia, sickness-induced, 617 Hypercapnia, 375–376, 376, 379 Hypercapnic central sleep apnea, 411–412 Hyperhydrosis, sleep, 892–893 Hypersomnias central origin, 828–830 classification, 672–673 clinical characteristics, 1051–1052, 1053–1054, 1056–1057 diagnosis, 1059–1060 headache and, 1077 menstrual-related, 830 nervous system disorder-related, 830 pathophysiology, 1057–1058 primary, 1032 sleep disorder-related, 826–828 treatment, 1059–1060 unspecified, 673 see also Recurrent hypersomnias Hypersomnolence, 1028 Hypersynchronous delta (HSD) waves, 855, 859 Hypertension see Arterial hypertension Hyperthermia, 505 Hypnagogic foot tremors, 676, 889
Hypnagogic hallucinations, 787, 828, 893–894, 1052, 1152 Hypnic headache, 1075, 1076, 1078, 1079 Hypnic jerks, 300, 675, 885–886 Hypnopompic hallucinations, 787, 893–894 Hypnosis, 864 Hypnotic drugs, 709–710 gamma-aminobutyric acid (GABA) and, 143 insomnia and, 705, 708, 748–749, 756–757, 1036 restless-legs syndrome (RLS) and, 937, 940 warnings, 739 Hypnotoxins, 16 Hypocapnic central sleep apnea, 412–417, 412 Hypocretin see Orexin (hypocretin) Hypothalamic orexinergic neurons, 374 Hypothalamic sleep-wake regulation system, 773, 773 sleep-promoting system, 775–776 vigilance control links, 776–777 wake-promoting system, 769–770, 770, 775–776 Hypothalamo-pituitary-adrenocortical (HPA) system, 241, 242, 244–246, 627–628 Hypothalamo-pituitary-somatotrophic (HPS) system, 241–244 Hypothalamo-pituitary-thyroid (HPT) system, 246–247 Hypothalamus, 765–766 posterior, 181 Hypoventilation alveolar, 472–473, 475, 1089, 1090, 1094 signs and symptoms, 460 sleep-related, 411–412, 412, 672 Hypoxemia, 672, 1089 nocturnal, 476–477 Hypoxia, 375, 378
I Ictal events (IEs), 1109, 1111, 1130, 1132 Idiopathic central sleep apnea, 413 Idiopathic hypersomnia, 786, 792, 829 with long sleep, 673 without long sleep, 673 Idiopathic insomnia, 75–76, 76, 670, 725 Idiopathic REM behavior disorder (RBD), 874–875, 1022–1023 Idiopathic sleep-related nonobstructive alveolar hypoventilation syndrome, 672 Iguanas, 102–103, 104 Iliad (Homer), 3, 6 Illness see Medical illness Imagery rehearsal therapy (IRT), 550 Imhotep, 4 Imipramine, 803, 803 Immediate early genes (IEGs), 192, 192 Immune system, 798–799
I-9 Immunomodulating therapy, 1141 Incidence, 280 India, ancient, 5 Indiplon, 750 Infants see Neonates and infants; Sudden infant death syndrome (SIDS) Infections, 505–506 Inflammatory pain models, 620–621 Infratentorial stroke, 1057 Inhalants, 591 Inhibitory postsynaptic potentials (IPSPs), 837–838 Inhibitory theory, 13 Insects, 99–100 Insomnia, 826 autonomic costs, 708–709 behavioral approaches, 654–655, 655, 729–733, 730, 736 biological basis, 726 chronic, 231 classification, 670–671, 699 consequences of, 654 course/prognosis, 725–726 cyclic alternating pattern (CAP) and, 712–713 daytime findings, 724–725 defined, 697–698, 747–748 diagnosis, 698–699, 699, 1060 differential diagnosis, 727–728 elderly and, 653–655 epidemiology, 57, 282–285, 723 etiology, 726 evaluation, 727, 727, 728, 729 food allergy, 20 headache and, 1076, 1077 idiopathic, 75–76, 76, 670, 725 medication-induced, 1025–1026 multiple sclerosis (MS) and, 1139–1142 neurological causes, 709–711, 709 neurological/somatic diseases and, 284–285 neurophysiological bases, 699–705 occupations and, 283 pathophysiology, 726, 1058 pharmacotherapy, 705–706, 733, 734–735, 736–741, 747–759, 1036–1037, 1060 polysomnographic (PSG) findings, 724 presenting complaints, 723–724 psychiatric disorders and, 283–284, 670–671 psychological approaches, 726, 729–733, 730 rebound, 752–753 seasonal differences, 283 secondary, 699, 757 stroke and, 1052, 1055, 1056 subtypes, 725 symptoms, 747–748 underlying factors, 711–712 unspecified, 671 women and, 647
(Volume 1: pages 1–666; Volume 2: pages 667–1160)
I-10
SUBJECT INDEX
Insomnia, (Continued) see also Fatal familial insomnia (FFI); Primary insomnia; Sporadic fatal insomnia (SFI) Insomnia disorder, 698 Insomnia Severity Index, 727, 729 Insomnia symptom, 698 Inspiratory muscle training, 479 Inspiratory vital capacity (IVC), 1097 Institutionalized elderly, 661–662, 662 Insufficient sleep, 825 Insulin, 247–248 Intelligence, children, 495 Interferons, sleep regulation and, 232–233 Interictal discharges (IDs), 1109, 1110–1111, 1130, 1132 Interictal epileptiform activity (IEA), 1126, 1127 Interictal epileptiform discharge (IED), 1126, 1130–1131 International Classification of Diseases (ICD), 501, 669–670 ICD-9-CM, 669–670 ICD-10, 669 International Classification of Headache Disorders (ICHD), 1073, 1076, 1079 International Classification of Sleep Disorders (ICSD-1), 21, 670, 892 International Classification of Sleep Disorders (ICSD-2), 21, 669, 670–676 bruxism, 901, 903 categories, 883 circadian rhythm sleep disorders, 963, 967 excessive fragmentary hypnic myoclonus (EFHM), 884 headache, 1073 insomnia, 697, 698, 699, 706, 725, 725, 748 narcolepsy, 289, 547, 783, 788, 792, 795 parasomnias, 860, 861, 893 recurrent hypersomnias, 816 REM behavior disorder (RBD), 871–872, 871 sleep-related abnormal sexual behaviors (SRASBs), 860 sleep-related eating disorder (SRED), 578, 578, 580, 859 International Restless-Legs Syndrome Study Group (IRLSSG), 913, 924, 927 Interpretation of Dreams (Freud), 19 Interstitial lung disease, 481–482 Intervention studies, 275–276 Intracellular mechanisms, 269 Intracortical facilitation (ICF), 935 Intracortical microstimulation (ICMS), 906 Intracranial pressure (ICP), 1076–1077 Invertebrates, 99 IPPV see Noninvasive intermittent positive pressure ventilation (NIPPV) Iron deficiency, 921, 940
‘Iron lung’, 1101 Iron metabolism, 930 Iron regulatory proteins (IRPs), 931 ‘Irreminiscence’, 520, 522 Irritable bowel syndrome (IBS), 351–353 Isolated sleep paralysis (ISP), 674, 785, 787, 894–895
J Jackson, John Hughlings, 12, 18 Jactatio capitis, 889 Jactatio corporis nocturna, 889 Janota, Otakar, 19 Japanese Society for Sleep Research, 21 Jaw movements (RJMs), rhythmic, 906–907, 906 Jet lag disorder, 673, 971–972, 971 Jouvet, Michel, 18 Jung, R., 20 ‘Junk science’, 1154 Juvenile dystonia, 1035 Juvenile myoclonic epilepsy, 1126
K Kahn, Andre, 20 Kales, Anthony, 17, 20 ‘Kanashibari’, 894 Karolinska scale, 48 Ketamine, 591 Kilduff, Thomas, 16 Kleine–Levin syndrome (KLS), 815, 830 behavioral/cognitive abnormalities, 819 clinical features, 816 demographics, 816 diagnostic criteria, 816–817 genetics, 690 hormonal levels, 817, 818 laboratory tests, 817 neuroimaging, 818 orexin (hypocretin) levels, 817 pathophysiology, 820 treatment, 820 Kleitman, Nathaniel, 17, 18, 19 Konopka, R., 19 Kuhlo, Wolfgang, 20 ‘Kuru’, 981 Kyphoscoliosis, 481
L Lamotrigine, 597, 939 Landau–Kleffner syndrome, 1111, 1128–1129 Laryngospasm, sleep-related, 892 Laser-assisted uvulopalatoplasty (LAUP), 450 Lateral preoptic area (LPOA), 173–174 Lateral vestibular nucleus, 836 Laterodorsal tegmental nucleus (LDT), 174 cholinergic projections, 152, 155, 155 discharge activity, 156 lesion/stimulation effects, 156 serotonergic inhibition, 159–160, 160, 161 Laterodorsal tegmentum (LDT), 766, 767
Latin American Sleep Society, 21 Laudanum, 9 Lavoisier, Antoine-Laurent, 11 Law, medicolegal evaluation, 1153–1155 ` Le probleme physiologique du sommeil (Pieron), 19 Learning, children, 495–496 Lee Fatigue Scale, 645 Leg cramps, 675, 888 Leg muscle activation, alternating, 676 Legendre, Rene´, 16 Lennox–Gastaut syndrome, 1127, 1129, 1130 Lepine, Raphael Jacques, 12 Leptin, 247 Lesion studies, 160–161 Leucippus of Miletus, 7 ‘Leucomaines’, 13 Levetiracetam, 597, 1132 Levodopa excessive daytime sleepiness (EDS) and, 999 hypersomnia and, 1059 restless-legs syndrome (RLS) and, 828, 937, 938, 939 sleep dysfunction and, 597, 598 Lewy bodies (DLB), dementia with, 1011, 1021–1024, 1145 Lhermitte, Jacques Jean, 17 Lhermitte’s peduncular hallucinosis, 1053 LibriumÒ, 748 Lifestyle modification, 442–444 Light dim-light melatonin onset (DLMO), 964 sensitivity, 1013–1014 transmission dysfunction, 1013, 1018–1020 see also Bright light exposure Lilliputian hallucinations, 894 Limb movements see Periodic leg movements (PLMs); Periodic limb movement disorder (PLMD); Periodic limb movement disorder of sleep (PLMS) Linnaeus, C., 10 Lions, 104 Lithium (Li), 596, 830, 1028 Lizards, 102, 102 Locus caeruleus (LC), 156–157, 157–158, 767, 776 GABAergic influences and, 165, 166 neurons, 138, 839–840 REM sleep phenomena and, 160–161, 162–163 Loggerhead sea turtle, 103 Loomis, Alfred L., 17 Loratadine, 601 Lorazepam, 705, 908 Lucid dreaming, 553–554 Lucretius Carus, Titus, 7 Lugaresi, E., 20 Lugaro, Ernesto, 13 Lumbar punctures (LPs), 794
(Volume 1: pages 1–666; Volume 2: pages 667–1160)
SUBJECT INDEX Lung capacities/volumes, 1099–1100, 1100 Lung inflation reflex, 372 Lymnaea stagnalis (pond snail), 99
M McCarley, Robert William, 18 McGregor, Peter Anderson, 21 Machado–Joseph disease, 1033–1034 MacNish, Robert, 12 Maculopathy, 1013 ‘Mad cow disease’, 981 Magnetic resonance imaging (MRI), 86 see also Functional magnetic resonance imaging (fMRI) Magnetic resonance spectroscopy, proton, 80–81, 82–83 Magoun, Horace W., 18 Maimonides, 9 Maintenance of Wakefulness Test (MWT), 50–51, 792, 999, 1133 Malingering, 1152–1153 Malpighi, Marcello, 9 Mammals, 97, 98, 103–105 Mandibular surgery, 450–451 Mania, 565–566 Marijuana, 590–591 Mauthner, Ludwig, 13, 17 Maxillary surgery, 450–451 Medians, 280 Medical illness, 654 central sleep apnea (CSA) and, 671 circadian rhythm sleep disorders and, 674 hypersomnia and, 673 hypoventilation/hypoxemia and, 672 insomnia and, 671 movement disorder and, 675 narcolepsy and, 672 parasomnias and, 675, 860 Medical schools, establishment of, 9 Medication, 19, 20, 654 respiratory-depressant, 442–443 specialists, 1154 see also specific drugs Medroxyprogesterone, 444, 478 Melanin-concentrating hormone (MCH), 777 peptidergic neurons, 182–183 Melanopsin, 1013 Melatonin age-related changes, 1012–1013, 1017 circadian rhythm and, 966, 967, 969, 971, 972 dementia and, 1020 insomnia and, 735, 738, 741 REM behavior disorder (RBD) and, 876 secretion, 769 studies, 249 Melatonin receptor agonists, 734, 738–739, 754–755 Melatonin replacement therapy, 657 Memantine, 1024
Membrane trafficking, 195 Memory, 259–270 biological/genetic factors, 268–269 children, 495 experiments, 259–260 impairment, 752 implications, 269–270 NREM sleep and, 264–268 REM sleep and, 261–264, 263, 264, 266–268 ‘topographical’, 520 types of, 260 Menopause, 249, 360, 645–646 Menstrual cycle, 249, 360, 643–644 hypersomnia and, 830 Mental disorder see Psychiatric diseases Meprobamate, 908, 990 Mesencephalic locomotor region (MLR), 843 Metabolic regulation cerebral blood flow (CBF), 318 see also Endocrine/metabolic changes Metabolic syndrome, 1064–1065 Metal neurotoxicity, 603–604 Methadone, 937, 939 Methamphetamine, 804 Methyldopa, 600–601 3,4-Methylenedioxymethamphetamine (ecstasy), 591 Methylphenidate hypersomnia and, 1059 insomnia and, 1037 narcolepsy and, 804, 829 neuromuscular disorders and, 1104 recurrent hypersomnias and, 820 Methylprednisolone, 1142 Metu (system of channels), 4 Mianserin, 1060 Michelangelo, Buonarroti, 9 Microarrays, 686 Micturition, 355–357 Midlife crisis, 646–647 Midline alpha/theta activity, 115, 117 Mignot, Emmanuel, 16 Migraine, 711, 1075, 1077, 1078, 1078, 1081–1082 Milnacipran, 803 Mink encephalopathy, 981 transmissible (TME), 992 Minnesota Multiphasic Personality Inventory (MMPI), 561 Mirtazapine efficacy, 755–756 insomnia and, 734, 740, 755 safety, 756 sleep dysfunction and, 595 Mitchell, Robert A., 20 Mobile phone radiation, 1081 Modafinil cataplexy and, 803 excessive daytime sleepiness (EDS) and, 1000 hypersomnia and, 1059 narcolepsy and, 804
I-11 Modafinil (Continued) neuromuscular disorders and, 1104 obstructive sleep apnea syndrome (OSAS) and, 445 Parkinson’s disease and, 1028 recurrent hypersomnias and, 820 sleep dysfunction and, 592 Molecular neurobiology, 191–200 cellular function, 191 gene expression, 191–196, 196 genetic studies, 196–199, 197 Moniz, Egas, 17 Monoamine oxidase inhibitors (MAOIs), 593–594, 595, 598, 827 Monoaminergic modulators, 805 Monoaminergic neurons, 176–178, 179–181 Montgomery–Asberg Depression Rating Scale, 1067 Mood disorders, 581, 583, 919–920 Mood stabilizers, 820 Moore, Robert Y., 18 Morning headache, 1081, 1081 Mortality rates, 280 Moruzzi, Giuseppe, 18 Morvan’s chorea, 710–711 Mosso, Angelo, 12 Motility patterns, 117 Motor behaviors, neuroimaging, 84–87 Motor control, 835–845 caudal brainstem, 838–840, 839 disturbances, nocturnal, 1031–1032 early studies, 836–837 forebrain modulation, 840–842, 841 motor neuronal activity, 837–838, 837 motor suppression, 835–836 REM sleep characteristics, 843–845, 845 REM sleep without atonia, 842–843, 844 Motor neuron disease, 1091–1092, 1093, 1094, 1095 Mouth dryness, 465 Movement disorders classification, 675 unspecified, 675 Moxibustion, 5 Multiple sclerosis (MS), 1139–1144 insomnia and, 1139–1142, 1142 medication and, 1141–1142 narcolepsy and, 1142–1143 REM behavior disorder (RBD) and, 1144 sleep-disordered breathing (SDB) and, 1142, 1143 Multiple Sleep Latency Test (MSLT), 17, 19 antiepileptic drugs (AEDs) and, 1132, 1133 children and, 489, 494 excessive daytime sleepiness (EDS), 48–49, 49–50, 999 idiopathic hypersomnia, 829 narcolepsy, 783, 786, 788–790, 792, 794–795, 800, 828–829
(Volume 1: pages 1–666; Volume 2: pages 667–1160)
I-12
SUBJECT INDEX
Multiple Sleep Latency Test (MSLT), (Continued) neuromuscular disorders, 1099 obstructive sleep apnea syndrome (OSAS), 432 periodic limb movement index (PLMI) and, 1027 recurrent hypersomnias, 817, 830 stroke, 1059 Multiple system atrophy (MSA), 1028–1032 Munchausen syndrome by proxy, 1153 Munich-Composite International Diagnostic Interview (M-CIDI), 920 Muscle atonia, 156–157, 278, 842–843, 844, 845, 870, 1023 Muscle disorders cramps, 675, 888 primary, 1093–1094 Muscle relaxants, 47, 366, 756, 908 Muscle training, 479 Muslim world, 8–9 Mutation screening, 794 Myoclonus, 884–885, 885, 887–888 ankle dorsiflexion, 888 benign sleep, of infancy, 676, 887–888 epilepsy syndromes, 888 fragmentary, 676, 883–884, 884–885, 884, 885 nocturnal, 827 propriospinal (PSM), 676, 886–887, 887 Myofascial pain, 1080 Myotonic dystrophy, 1094–1096 Mysticism, 9
N Narcolepsy, 14, 16, 19, 783–807, 828–829 animal models, 787–788, 791 cataplexy, with, 672, 785, 786, 793–794, 796 cataplexy, without, 672, 786, 798, 799–800 classification, 672 defined, 783 diagnostic criteria, 788–792, 791 differential diagnosis, 792 dreaming and, 551 environmental factors, 784 epidemiology, 289, 290, 784 evaluation, 788–792 gene mutation, 765 genetics, 198, 688–689, 784 headache and, 1077, 1077 human leukocyte antigen (HLA) and, 796–798, 797, 798–799, 798, 800 immune system and, 798–799 multiple sclerosis (MS) and, 1142–1143 neuroimaging, 78–81, 81 neurological diseases and, 769, 770 orexin (hypocretin) and, 769, 770 pathophysiology, 793–802 REM behavior disorder (RBD) and, 873
Narcolepsy, (Continued) secondary, 786 symptomatic, 792, 800 symptoms, 784–787, 786 treatment, 802–805, 802, 803, 805–806, 806 unspecified, 672 ‘Narcoleptic tetrad’, 894 Narcotics, 754 Nasal congestion, 428–429, 464 Nasal dryness, 464 Nasal obstruction, 444 Nasal surgery, 450 National Academy of Sciences, 1020 National Institute of Mental Health, 757 National Institutes of Health State of the Science Conference on Insomnia, 655, 657 State of the Science Conference on Manifestation and Management of Chronic Insomnia, 698, 747 National Sleep Foundation, 21, 648 Nauta, Walle Jetz Harinx, 18 Nefazodone, 568, 595, 706 Negative-pressure ventilation, 479 ventilators, 1101 Nei Ching (Canon of Medicine) (Yu Hsiung), 5 Neonates and infants, 111–125 brain adaptation to stress, 121–122 electrographic pattern maturity, 112–116 neurophysiologic interpretation, 111–112 physiologic behaviors, 116–118, 116 recording techniques, 112 sleep ontogenesis, 119–121 sleep organization analysis, 122–125, 122, 123 state organization, 118–119 thermoregulation, 222–224, 223 see also Sudden infant death syndrome (SIDS) Neural circulatory regulation, 315, 316 Neural control, breathing, 371–375 Neural plasticity, 124–125 Neural theories, 12–13 Neuroactive steroids, 250 Neurobiology, REM sleep, 151–167 electroencephalography (EEG) analysis, 151–152, 152 GABAergic influences, 161–164 neurons, REM-off/REM-on, 157–161, 157, 165–167, 165, 176–179, 767–768 orexin (hypocretin) effects and circadian control, 167 physiology and brain anatomy, 152–157 promoting systems, 152–154, 153, 154–157 REM sleep generation model, 164–167, 165 suppressive systems, 157–161, 157
Neurobiology, waking and sleeping, 131–144 arousal systems, diffuse projection, 135–136, 138–141 dreaming, 546 forebrain relays, activating system, 134–135 historical perspective, 131, 132, 133 reticular activating system, 133–134, 134–135 sleep-promoting systems, 141–143 see also Molecular neurobiology Neurochemistry of sleep, 16, 173–184 dreams, 533, 539 models, 176, 176, 183, 184 REM sleep onset/maintenance, 176–183 sleep onset/maintenance, 173–176 Neurocognition, 494 Neurodegenerative diseases, 1022, 1027–1028, 1033–1035 comorbidity, 1027–1028 REM parasomnias and, 873–874 see also Dementia Neurogenic tachypnea, 892 Neuroimaging dreams, 531–533, 539 fatal familial insomnia (FFI), 985–988, 986 Kleine–Levin syndrome (KLS), 818 normal human, 71–75 recurrent hypersomnias, 818 sleep disorders, 75–87 Neuroleptics, 1028 Neurological diseases, 284–285, 769, 770, 1150–1152 Neuromelanin cells, 931 Neuromuscular disorders, 481, 711, 1087–1104 breathing, control of, 1087–1089, 1088 breathing pattern types, 1096–1097, 1096 junctional, 1093 respiratory failure, 1097–1100 sleep disorders and, 1089–1096 treatment in, 1101–1104, 1101 Neuropathy, 923, 1093 pain models, 621 Neuropeptide Y, 249 Neurophysiology, 17–18 insomnia, 699–705 neonates and infants, 111–112 Neurospora, 956 Neurospora crassa, 952 Neurotransmitters, 156, 592 ventrolateral preoptic area (VLPO) neurons, 174–176 Newborn Individualized Developmental Care and Assessment Program (NIDCAP), 223 Nicotine, 589–590 acute exposure to, 589–590 transdermal, 1125 withdrawal, 590 see also Smoking
(Volume 1: pages 1–666; Volume 2: pages 667–1160)
SUBJECT INDEX Niemann–Pick type C disease, 792 Night sweats, 892–893 Nightmare disorder, 547–550, 894 classification, 674 diagnosis, 547–549 differential diagnosis, 549 medication-induced, 1025–1026 recurring, 530–531, 537–539 sleep terrors, 550–551 treatment, 549–550 see also Dreaming, abnormal Nighttime mental activity (NTMA), 267–268 N-methyl-D-aspartate (NMDA), 843 Nociception, 619–620 Nocturia, 356–357, 1140 Nocturnal eating/drinking syndrome (NEDS) differential diagnosis, 579–580, 579 historical perspective, 577–578 neuroendocrine studies, 582 prevalence, 580 treatment, 582–583 Nocturnal frontal lobe epilepsy (NFLE), 1110 age of onset/complications, 1114, 1117 clinical/pathophysiological subtypes, 1112–1114, 1112, 1113, 1114–1115, 1115–1116, 1117 differential diagnosis, 1123–1125, 1124 pathology/pathophysiology, 1117–1118 polysomnographic findings, 1118–1123, 1120–1121, 1121–1122 treatment, 1125 Nocturnal hypoxemia, 476–477 Nocturnal myoclonus, 827 Nocturnal oxygen therapy (NOT), 477–480 supplemental nasal, 342 Nocturnal polysomnography, 49 Nocturnal polyuria, 363–364 Nocturnal ventilation, 463–464 Nonbenzodiazepines excessive daytime sleepiness (EDS) and, 47 insomnia and, 734–735, 737, 741, 749 restless-legs syndrome (RLS) and, 940 Noninvasive intermittent positive pressure ventilation (NIPPV), 459–465 chronic obstructive pulmonary disease (COPD) and, 476, 479–480 complications, 464–465, 1103 continuous ventilation, 464 criteria for use, 460–461 diseases, potential treatment, 461, 461 effects, 465 indications for, 462–463, 462, 1102–1103, 1103 interfaces, 457 management, 463–464 methods/uses, 459–460 neuromuscular disorders and, 1101–1102, 1102–1103, 1103
Noninvasive intermittent positive pressure ventilation (NIPPV), (Continued) nocturnal ventilation, 463–464 survival and, 461–462 ventilator and mode, 459–460 Non-rapid eye movement (NREM) sleep memory and, 264–268 neuroimaging, 71–73, 72, 74, 78 scoring, 34, 36, 36 see also Parasomnias, NREM; Slowwave sleep (SWS) Nonrestorative sleep, 626–627 Nonsteroidal anti-inflammatory drugs (NSAIDs), 47, 602 Noradrenaline (NA) (norepinephrine), 136, 138, 776 Noradrenergic control, gene expression, 195–196 Noradrenergic locus caeruleus neurons, 138 NPPV see Noninvasive intermittent positive pressure ventilation (NIPPV) Nucleus magnocellularis (NMC), 838, 839, 843 Nucleus paramedianus (NPM), 838, 839 Nucleus pontis oralis (NPO), 838, 840, 842 Nucleus tractus solitarius (NTS), 1088 Number needed to treat (NNT), 281, 907, 908 Nurses’ Health Study, 297
O Obesity, 298, 577, 580–581, 776 Obsessive compulsive disorder (OCD), 566 Obstructive sleep apnea syndrome (OSAS), 14–15, 20, 826–827 behavioral problems, 493, 494 cardiocerebrovascular disorders and, 330, 331 cardiovascular complications, 331–334 cardiovascular diseases and, 320–321, 321, 329–336, 329, 330, 331, 335 children and, 489, 490, 491–493, 495–496 chronic obstructive pulmonary disease (COPD) and, 475–476, 477, 478 classification, 671–672 continuous positive airway pressure (CPAP) and, 421–434, 443–444, 1066, 1076–1077 dementia and, 1026–1027, 1026 dental appliances, 445–448 devices, treatment, 445 diagnosis, 384–386 epidemiology, 292, 384 epilepsy and, 1131–1132 evolution, 299–300 genetics, 689 headache and, 1076, 1077 hemodynamic changes, 319–320, 320 historical perspective, 383
I-13 Obstructive sleep apnea syndrome (OSAS), (Continued) lifestyle modification, 442–444 manifestations, 329–330, 330 mortality, cause of, 334–335, 335 neuroimaging, 81–84 oxygen and, 445 pathophysiology, 389–393 pharmacotherapy, 444–445 risk factors, 386–389, 386 stroke and, 320–321, 321, 1060, 1060, 1062–1063 treatment, 335–336, 335, 339–340, 441–451 upper-airway resistance syndrome (UARS) and, 404–407 upper-airway surgery, 448–451 women and, 647–648 Obstructive sleep apnea/hypopnea syndrome (OSAHS), 330, 330, 403, 1003 Occipital alpha/theta rhythms, 114, 114 Octopus vulgaris (octopus), 99 Odds ratio, 280 Ogle, William, 14 Olanzapine, 599, 735, 740, 756, 1024 ‘Old Hag’, 894 Olfactory dysfunction, 874 Olivopontocerebellar atrophy, 1144 Ondine (Giraudoux), 20 ‘Ondine’s curse’, 20 ‘Oneiric stupors’, 982, 982, 984 Oneirocritica (Artemidorus of Daldis), 5 Opiates, 1028 Opioids, 593, 937, 939 Opium poppy (Papaver somniferum), 4, 7 ‘Hoffman’s anodyne of opium’, 11 Oral guard, 908, 909 Orexin (hypocretin), 80, 167, 182, 765–766 behavioral state control, 770–775, 841–842 discovery of, 16 -histamine interactions, 774–775 interactions of HPS system, 243–244 narcolepsy and, 789–790, 792, 804, 829 neurons, 771, 771, 772, 773 receptors, 771, 771, 772, 773 recurrent hypersomnias and, 817 sleep regulation, 801–802 transmission deficiency, 794–796, 795 vigilance control, role, 773–774 see also Cerebrospinal fluid (CSF) Orexinergic posterior hypothalamic neurons, 140–141, 142 Orienting response, 858 Ornithorhynchus anatinus (platypus), 105 Orphan receptors, 765 Osamu Hayaishi, 16 Osborne, Jonathon, 13 Osler, Sir William, 20 Ovariectomy, 250
(Volume 1: pages 1–666; Volume 2: pages 667–1160)
I-14
SUBJECT INDEX
Over-the-counter (OTC) drugs, 735, 736, 738, 741, 756–757 Oxcarbazepine, 597 Oxygen cerebral blood flow (CBF) and, 318–319, 319 chronic obstructive pulmonary disease (COPD) and, 476 discovery of, 11 nocturnal therapy (NOT), 342, 477–480 obstructive sleep apnea syndrome (OSAS)and, 445 pulmonary diseases, 477–478 therapy, supplemental, 1103 Oxytocin, 646
P Pain, 613–614 definitions, 614–615 medication, 47 multiple sclerosis (MS) and, 1139–1140 processing/modulation, 615–617 regulation, 1082 sleep disturbance studies, 620–621 sleep loss studies, 619–620 sleep modulation studies, 617–619 terminology, 615 see also Fibromyalgia (FM)/chronic fatigue syndrome (CFS) Palatal procedures, 450 Panayotopoulus syndrome, 1125 Panic disorders, 568–569 panic attacks, 893, 1061 Papaver somniferum see Opium poppy Paper tracings, 38–40 speed, 39–40 Pappenheimer, John, 16 Paracelsus, 9, 10 Paradoxical insomnia, 670, 707–708, 725 Paradoxical sleep (PS) see Rapid eye movement (REM) sleep Paralysis (ISP), isolated sleep, 674, 785, 787, 894–895 Paraneoplastic syndrome, 1093 Parasomnias, 583, 1052–1053, 1055 classification, 674–675 epidemiology, 300 unspecified, 675 see also Violent parasomnias Parasomnias, NREM, 851–864 clinical variants, 859–860 confusional arousals, 853 diagnosis, 860, 861, 862–863, 862 medical illness and, 860 polysomnographic features, 1124 primary sleep disorders and, 860 REM parasomnia comparisons, 852 sleep terrors, 856–859 somnambulism (sleepwalking), 853–856 treatment, 863–864 Parasomnias, REM, 869–878 NREM parasomnia comparisons, 852 Parkes, J. David, 20
Parkinson’s disease (PD), 61, 284, 597, 598, 830 bruxism and, 902 daytime alertness disorders and, 997–1000 insomnia and, 710 nocturnal sleep disorders and, 1000–1004 REM behavior disorder (RBD) and, 874–875 restless-legs syndrome (RLS) and, 923 Parkinson’s Disease Sleep Scale (PDSS), 999, 1000 Paroxysmal arousal, 1112, 1112, 1113, 1114–1115 Paroxysmal nocturnal dystonia, 20 Passouant, Pierre, 20 Pathology of sleep, 19–20 Pavlov, Ivan Petrovitch, 13, 16 Pavor nocturnus see Sleep terrors Pediatric Daytime Sleepiness Scale, 49 Pediatric Sleep Questionnaire, 49 Pediatrics obstructive sleep apnea syndrome (OSAS), 671–672 restless-legs syndrome (RLS) and, 926 Pedunculopontine nuclei (PPN), 766, 767, 839 Pedunculopontine tegmental nucleus (PPT), 174 cholinergic projections, 152, 155, 155 discharge activity, 156 lesion/stimulation effects, 156 serotonergic inhibition, 159–160, 160, 161 Pemoline, 804 Peptidergic sleep regulation model, 250, 251 PER protein, 952–953, 955, 956, 957, 957 period genes, 685, 952–953, 954 Perch, 101 Performance Vigilance Test, 51 Pergolide, 938 Periaqueductal gray, 163 Perimenopause, 645–646 Periodic leg movements (PLMs), 827 diagnosis, 915–916, 915 genetics, 687 studies, 932–933, 940 Periodic limb movement disorder (PLMD), 827, 828, 830 diagnosis, 915–916, 915 Parkinson’s disease and, 1003–1004 studies, 940 treatment, 940–941 Periodic limb movement disorder of sleep (PLMS), 84–86, 915–916 classification, 675 elderly and, 659–660, 660 epilepsy and, 1131–1132 headache and, 1077, 1077 motor control and, 1032 multiple sclerosis (MS) and, 1140–1141, 1142, 1143
Periodic limb movement disorder of sleep (PLMS), (Continued) neurodegenerative diseases and, 1027–1028 REM parasomnias and, 871 Periodic limb movement index (PLMI), 659, 827, 1027 ‘Periodic limb movements in wake’ (PLMW), 915 Periodische Schlafsucht (Kleine), 815 Peripheral afferents, pain processing, 616–617 Pettenkofer, Max, 13 Pfeffer, Wilhelm Friedrich Phillip, 14 Pflu¨ger, Eduard Friedrich Wilhelm, 13 Pharyngeal muscles, 390–391 Phencyclidine, 591 Phenobarbital, 596, 1129, 1132 Phenothyazines, 19 Phenotypes, sleep, 198–199, 199 Phenylpropanolamine, 592 Phenytoin, 596, 1132 Philosophy of Sleep (MacNish), 12 ‘Phrenitis’, 8 Phylogenic studies, 87, 105–106 Physiological fragmentary (partial) hypnic myoclonus (PFHM), 883–884, 884 Physiological (organic) hypersomnia, 673 ‘Pickwickian syndrome’, 20, 383 Pieron, Henri, 16, 19 Pineal gland, 1014 Pittsburg Sleep Quality Index, 1036 Plasma renin activity (PRA), 241 Platypus, 105 ‘Pneumo-wrap ventilator’, 1101 Podalirios, 6 Poliomyelitis, 1091, 1091, 1092 Polyglutamine diseases, 1022 Polyphasic sleep pattern, 4 Polysomnography (PSG), 20, 30 AASM recommendations, 41, 42 continuous spikes waves during NREM sleep (CSWS), 1128 neuromuscular disorders and, 1099 nocturnal, 49 nocturnal frontal lobe epilepsy (NFLE), 1118–1123, 1120–1121, 1121–1122 NREM parasomnias, 860, 862 obstructive sleep apnea syndrome (OSAS), 385 recurrent hypersomnias, 817 REM behavior disorder (RBD), 870–871, 870 upper-airway resistance syndrome (UARS), 403–404, 404, 405, 406 versus actigraphy, 58–59, 59, 61 see also Video polysomnography (VPSG) Polyuria, nocturnal, 363–364 Pond snail, 99 Pond turtle, 103 Pontine brainstem lesions, 528 Pontine inhibitory area (PIA), 838, 842, 843
(Volume 1: pages 1–666; Volume 2: pages 667–1160)
SUBJECT INDEX Pontine reticular formation (PRF), 153–154, 153, 154, 767 acetylcholine agonists and, 155 cholinergic agonists and, 155–156 cholinergic projections and, 152, 155, 155 GABAergic influences, 165 neurons, 155–156 REM sleep disinhibition, 163–164, 164 ventral to locus caeruleus (LC), 156–157 Pontogeniculooccipital (PGO) waves, 73, 74, 153, 154, 158, 767, 844 Population factors, 275, 277, 279–282 Positional therapy, 443–444 Positive airway pressure (PAP) therapy, 827, 829 see also Continuous positive airway pressure (CPAP) Positive end-expiratory pressure (PEEP), 463, 480, 1102 Positron emission tomography (PET), 71, 86–87 cerebral blood flow (CBF) and, 319 dreams, 531–532 18F-fluorodeoxyglucose (FDG), 76, 77, 81 Postdialysis fatigue, 231 Posterior hypothalamus, 181 Posthumous Papers of the Pickwick Club (Dickens), 14, 15, 20, 383 Postpartum period, 644–645 Posttraumatic stress disorder (PTSD), 566–568 nightmare disorder and, 548, 550 pharmacological treatment, 568 violence and, 1152 Potassium channels, 199, 199 Power spectral analysis, 706 Practice of Physick (Willis), 10 Pramipexole REM behavior disorder (RBD) and, 876–877, 1023 restless-legs syndrome (RLS) and, 828, 937, 938 sleep dysfunction and, 598 ‘Predormitum’, 991 Pre-eclampsia patients, 231 Prefrontal leukotomy, 522, 528, 528, 529–530, 531, 532, 533 Pregabalin, 597, 735, 741 Pregnancy, 249, 644–645 pharmacotherapy and, 757 restless-legs syndrome (RLS) and, 921–922, 940 Pregnenolone, 250 Prematurity, 503, 508 Premenstrual dysphoric disorder (PMDD), 641, 644 Premenstrual syndrome (PMS), 644 Preoptic area (POA), 137, 141, 173 ‘Presleep behavior’, 990, 991 Prevalence, 279 Preyer, Thierry Wilhelm, 13 Priestley, Joseph, 11
Primary care settings, 927 Primary central sleep apnea (CSA), 671 Primary hypersomnia, 1032 Primary insomnia, 706–709 arousals, 708, 708, 709 classification, 699 diagnostic criteria, 724 psychological/behavioral therapy, 730 subtypes, 725 Primary muscle disorders, 1093–1094 Primary REM behavior disorder (RBD), 873 Primary sleep apnea of infancy, 671 Primary sleep disorders, 860 Principles and Practice of Sleep Disorders Medicine, 19 Prion diseases, 981–982 ‘Prion protein only’ theory, 988 Prionopathies, 1022 Procambarus clarkii (crayfish), 99 Process-C curve, 703–704, 768, 826, 963 Process-S curve, 38, 703, 768, 826, 963–964 Profile of Mood States, 645 Progesterone, 250, 603, 643 Progressive supranuclear palsy (PSP), 710, 1032–1033, 1144 Prokineticin 2 (PK2), 769 Prolactin, 248, 933 Prolactinoma, 248 Promethazine, 601 Prone sleeping position, 504 Propranolol, 909 Propriospinal myoclonus (PSM), 676, 886–887, 887 Prostaglandin, 16, 776 Protein synthesis, 195 Proton magnetic resonance spectroscopy, 80–81, 82–83 Protriptyline, 444, 478–479, 803, 804 Proximal myotonic myopathy (PROMM), 1095–1096 PRPN gene, 982, 985, 987, 988 Pseudoephedrine, 592 ‘Pseudo-hypersomnia’, 990 Psychiatric diseases, 557–571, 624 anxiety, 566 depression, 557–565 insomnia and, 283–284, 670–671 mania, 565–566 obsessive compulsive disorder (OCD), 566 panic disorders, 568–569 posttraumatic stress disorder (PTSD), 566–568 schizophrenia, 569–571, 571 violent parasomnias and, 1152–1153 Psychiatry, enuresis and, 364 Psychogenic dissociative states, 1152 Psychological distress, elderly and, 654 Psychology, dreaming, 546–547 Psychophysiological insomnia, 670, 725 Psychophysiological relationships, 558–560
I-15 Psychosocial issues, 646–648 Psychotherapy, 864 Public Health Service (US), 669 Pulmonary diseases, 471–483 alveolar hypoventilation, 472–473 etiologies, 473–476 sleep quality, 471–472 sleep studies, 476 treatment, 477–480 ventilatory abnormalities, 472 Pulmonary function tests, 1099–1100, 1100 Pupillometry, 51 ‘Pure’ insomnia, 706 Purgatives, 9, 10 Purkinje, Johannes Evangelista, 12 Python saebe (snake), 102
Q
Quazepam, 734, 736, 749, 750 Quetiapine, 735, 740, 756, 1023, 1024 Quiet wakefulness (QW), 836, 837, 838, 840
R Rabl-Ruckhardt, H., 12 Race, 503 ‘Rain coat’, 1101 Ramelteon dementia and, 1020 elderly and, 655 insomnia, 734, 738–739, 754–755 safety, 757 substance abuse and, 758 Rana catesbiana (bullfrog), 102, 102 Rana temporaria (frog), 102 Randomized controlled trials, 279 Ranitidine, 602 Ranson, Steven Walter, 18 Raphe nuclei, 157 dorsal raphe nucleus (DRN), 162, 163, 165, 166, 776, 840 Rapid eye movement (REM) sleep characteristics, 844–845, 845 depression, 78 elderly and, 660–661 -generating system, 767–768 historical perspective, 3, 17, 18 memory and, 261–264, 263, 264, 266–268 motor control, 838–840, 839 neuroimaging, 73–75, 74, 78 onset/maintenance, neuronal network, 176–183 parasomnias, 869–878 scoring, 36–37, 37 see also Neurobiology, REM sleep Rapid eye movement (REM) sleep behavior disorder (RBD), 20, 869–878 classification, 674 clinical features, 1001–1002, 1031–1032
(Volume 1: pages 1–666; Volume 2: pages 667–1160)
I-16
SUBJECT INDEX
Rapid eye movement (REM) sleep behavior disorder (RBD), (Continued) defined, 869–871 dementia with Lewy bodies (DLB) and, 1021–1024 diagnosis, 871–873, 871, 872 dreaming and, 549, 551 epidemiology, 1001 epilepsy and, 1131–1132 hallucinations and, 1002–1003 idiopathic, 1022–1023 motor control and, 842, 843 multiple sclerosis (MS) and, 1144 neuroimaging, 84, 86–87 Parkinson’s disease (PD) and, 1001–1003 pathogenesis, 1023, 1032 pathophysiology, 1002 physiopathology, 877–878 progressive supranuclear palsy (PSP) and, 1033 secondary, 873 treatment, 875–877, 1002, 1023–1024, 1032 types, 873–874 violence and, 1151–1152 Rapid eye movement (REM) sleep without atonia (RWA), 842–843, 844, 1023 epidemiology, 1001 Parkinson’s disease (PD) and, 1001–1003 Rauwolfia serpentina, 5 Rebound, 939 Rechtschaffen, Allan, 17 Recording neonates and infants, techniques, 112 technology, evolution of, 38–43 see also Electroencephalography (EEG) Recurrent hypersomnias, 672–673, 815–821 clinical features, 816 clinical variants, 819 course, 819 demographics, 816 diagnostic criteria, 816–817 differential diagnosis, 819 historical perspective, 815–816 laboratory tests, 817 medical history, 816 pathophysiology, 820 predisposing factors, 819–820, 819 psychological investigations, 818 treatment, 820 Recurrent isolated sleep paralysis, 674 Red Emperor, Shen Nung, 5 Regulation see Sleep homeostasis; Sleep regulation; Thermoregulation Relative risk reduction, 281 Relaxation, 731, 731, 864, 908 REM behavior disorder see Rapid eye movement (REM) sleep behavior disorder (RBD)
Reptiles, 102–103 Respiratory disturbance index (RDI), 657 Respiratory effort related arousals (RERAs), 1097 Respiratory failure, neuromuscular disorders, 1097–1100 diagnosis, 1098 laboratory investigations, 1098–1100 Respiratory physiology, 371–379 airway resistance/muscle tone, 377–378, 378 arousal thresholds, 378–379 efferents, 372 feedback regulation, 375–377 muscles, 1088, 1089 neural control, 371–375 rhythm/pattern generation, 371–372, 372 tonic activation, 372–374, 373 Restless-legs syndrome (RLS), 913–941 classification, 675 clinical consequences, 918–920 clinical features, 913, 914 diagnosis, 913–915, 914, 916–918, 917, 925 elderly and, 659–660, 660 epidemiology, 300, 301–302, 303, 924–928, 924, 1142 excessive daytime sleepiness (EDS) and, 828 excessive fragmentary hypnic myoclonus (EFHM) and, 884, 885 genetics, 686–688, 929–930 headache and, 1077, 1077 motor control and, 1032 multiple sclerosis (MS) and, 1140, 1142 neurodegenerative diseases and, 1027–1028 neuroimaging, 84–85 Parkinson’s disease (PD) and, 1003–1004, 1004 pathophysiology, 930–937 phenotypes, 928 secondary, 920–924, 940 sleep-related eating disorder (SRED) and, 583 symptoms, 925 therapeutics, 937–941, 937 women and, 648 Reticular activating system, 133–134 forebrain and, 134–135 Reticular formation, 373, 374 neurons, 152, 155, 155 Retrorubral nucleus (RRN), 839 Rey Auditory Verbal Learning Test, 82 Rey-Osterrieth Complex Figure Design, 82 Rhines, Ruth, 18 Rhinitis, 464–465 Rhythmic movement disorders (RMD), 675, 889, 890 jaw movements (RJMs), 906–907, 906 masticatory muscle activity (RMMA), 901, 904, 905, 906, 909
Richardson, Gary, 17, 19 Richter, Curt P., 18 Risk absolute reduction, 281 ratio, 280 relative reduction, 281 Risperidone, 599, 1024 Rivastigmine, 876, 1025 Rodent narcolepsy models, 788, 791 Roentgen, Wilhelm Konrad, 15 Roffwarg, Howard, 19 Rolando, Luigi, 11, 13 Rome, ancient, 7–8 Ropinirole, 598, 828, 937, 938, 1028 Roth, Bedrich, 20 Rotigotine, 938 Rythmie du sommeil, 889
S Saccadic eye movements, 33 Sanctorious, 10 Scales for Outcomes in PD Sleep Scale (SCOPA-S), 999, 1000 Scandinavian Sleep Research Society, 21 Scheele, Karl, 11 Schenck, Carlos, 20 Schizophrenia, 569–571, 571 School performance, 495–496 Scopolamine, 4 ‘Scrapie’, 981 Sea slug, 99 Seasonal affective disorder (SAD), 958 Seasons, 503 Secondary insomnia, 757 classification, 699 Secondary narcolepsy, 786 Secondary REM behavior disorder (RBD), 873 Secondary restless-legs syndrome (RLS), 920–924, 940 Sedating antidepressants efficacy, 755–756 insomnia and, 739–740, 741, 755–756 safety, 756 Sedation, residual, 752 Seizures bruxism and, 902 complex motor, 1115–1116, 1117 diaries, 1125 generalized tonic-clonic (GTCSs), 1110, 1126 nightmare disorder and, 531–532, 537–539 tonic, 1127 violence and, 1152 Selective serotonin reuptake inhibitors (SSRIs) bruxism and, 902, 909 cataplexy and, 803 insomnia and, 706 nightmare disorder and, 552 periodic limb movement disorders and, 827, 1028 psychiatric diseases and, 568
(Volume 1: pages 1–666; Volume 2: pages 667–1160)
SUBJECT INDEX Selective serotonin reuptake inhibitors (SSRIs) (Continued) safety, 756 sleep-related eating disorder (SRED) and, 583, 594 Selegiline, 598 Sensory transmission gating, 618–619 Sepia pharonis (cuttlefish), 99 Serial reaction time (SRT), 263, 264 Serotonergic inhibition, 159–160, 160, 161 Serotonergic raphe neurons, 139, 158–159, 159, 839 Serotonin, 1082 Serotonin norepinephrine reuptake inhibitors, 596 Severinghaus, John W., 20 Shen Nung, Red Emperor, 5 Sherin, J.E., 18 Shiftwork disorder, 673–674, 970–971, 970 Shiro Fujita, 20 Short-beaked echidna, 104, 105 Shy–Drager syndrome, 1144 Siffre, Michel, 19 Simpson, Sutherland, 19 Single-photon emission computed tomography (SPECT), 71 motor behaviors, 85–86 narcolepsy, 78–79 obstructive sleep apnea syndrome (OSAS) and, 83 recurrent hypersomnias, 818, 820 restless-legs syndrome (RLS) and, 934 Skala, A., 19 Sleep: Its Physiology, Pathology, Hygiene, and Psychology (Manace´¨ıne), 13, 14 Sleep architecture, 1012, 1054–1055 defined, 97–99 diary, 727, 728 fragmentation, 1001 insufficient, 825 length, 285–286, 675 parameters, 56–58, 57, 58, 855–856, 858–859 pattern, 1075 process of, 699–700, 700 Sleep apnea, 231 complex, 417 epidemiology, 289–300, 292 headache and, 1076, 1077 of infancy, primary, 671 pregnancy and, 645 risk factors, 293 threshold, 376–377, 377 see also Central sleep apnea (CSA); Obstructive sleep apnea syndrome (OSAS) ‘Sleep attacks’, 828, 997–998, 1000, 1051, 1142 ‘Sleep center’, 17, 769 Sleep deprivation depression, 77–78
Sleep deprivation (Continued) epilepsy and, 1131 gene expression, 196 nociception and, 619–620 REM (REMSD), 619–620 symptoms, 707 total (TSD), 564 Sleep disorders classification see Classification effects, assessing, 105–106 epidemiology see Epidemiology familial, 686–690 genetics see Genetics primary, 860 treatment models, 106 see also specific disorders Sleep disturbance headache and, 1076–1081, 1077–1079, 1078, 1081–1082 restless-legs syndrome (RLS) and, 919 ‘Sleep drunkenness’, 1150 Sleep Heart Cohort, 275 Sleep Heart Health Study, 333, 658 Sleep homeostasis, 205–211 defined, 205 electroencephalography (EEG) and, 208–210, 209, 210, 211 modeling, 207–208, 208 perspectives, 210–211, 211 physiological correlates, 205–207 two process model, 703–704, 704, 768 Sleep hygiene, 444, 671, 908, 1036 education, 730, 731 elderly and, 654, 655, 661 Sleep and its Derangements (Hammond), 14 Sleep (journal), 21, 670 Sleep Medicine (Journal), 21 Sleep Medicine Reviews (Journal), 21 Sleep paralysis (ISP), isolated, 674, 785, 787, 894–895 Sleep regulation, 229–236 acute-phase response (APR), 229, 233–234 brain organization theory, 234–236 cytokines in, 229–232, 231, 234–236 humoral, 229, 230 interferons and, 232–233 mechanisms of, 229 orexin (hypocretin) and, 801–802 Sleep regulatory substances (SRSs), 229, 234–235 Sleep Research Society, 21 Manual, 34 Sleep restriction, 20, 490–491, 707, 730, 730 Sleep Society of Canada, 21 Sleep starts see Hypnic jerks ‘Sleep state probability’ model, 221 ‘Sleep swimming’, 101 Sleep terrors, 550–551, 674, 856–859 clinical features, 856, 858 genetics, 858 orienting response, 858
I-17 Sleep terrors, (Continued) pathophysiology, 858 prevalence, 858 psychopathology, 858 sleep parameters, 858–859 violence and, 1150–1151 Sleep and Wakefulness (Kleitman), 19 Sleep-disordered breathing (SDB) alcohol and, 589 children, 489, 491–493, 492, 493 clinical characteristics, 1060–1062, 1060 diagnosis, 1065–1067 elderly, 657–659 epidemiology, 291 evaluation, 1090, 1099 multiple sclerosis (MS) and, 1142 neuromuscular disorders and, 1090, 1099, 1101, 1101 Parkinson’s disease (PD) and, 1003 pathophysiology, 1062–1065 psychobehavioral consequences, 493–495 pulmonary disease and, 475–476 smoking and, 589 stroke and, 1060–1067 treatment, 1065–1067, 1101 women and, 647–648 Sleeping sickness (African trypanosomiasis), 19 Sleep-onset REM periods (SOREMPs) hypersomnias and, 817, 828–829, 830 narcolepsy and, 783, 789–790, 792, 800 Sleep-promoting systems, 141–143 Sleep-related abnormal sexual behaviors (SRASBs), 860 Sleep-related breathing disorders (SRBDs), 830 classification, 671–672 epidemiology, 286, 291 multiple system atrophy (MSA) and, 1028–1032 pathogenesis, 1029–1030, 1031–1032 treatment, 1030–1031, 1030 Sleep-related dissociative disorder, 674 Sleep-related eating disorder (SRED), 577–583, 859 associated disorders, 581 characteristics, 578 classification, 674–675 consequences, 580–581 differential diagnosis, 579–580, 579 historical perspective, 577–578, 578 physiology, 581–582 prevalence, 580 treatment, 582–583, 583 Sleep-related erections (SREs), 357–359 painful, 359 Sleeptalking (somniloquy), 889–891, 1152 classification, 675 Sleep-Wake Activity Inventory (SWAI), 49
(Volume 1: pages 1–666; Volume 2: pages 667–1160)
I-18
SUBJECT INDEX
Sleep-wake cycle actigraphic monitoring, 56–58, 57, 58 behavioral manipulations, 966 dreaming, 545 elderly, 656–657 free-running, 968, 968 hypothalamic/brainstem regulation, 773, 773, 775–776 patterns, 4, 19 regulation, 681–686, 682, 684, 685 substrates, 132 Sleep-wake disorders (SWDs) circadian rhythm factors, 1059–1060 clinical characteristics, 1051–1057 diagnosis, 1059–1060 pathophysiology, 1057–1059 stroke and, 1051–1060, 1059 treatment, 1059–1060 Sleep-Wake Disorders Unit, 21 Sleepwalking see Somnambulism (sleepwalking) Slow-wave activity (SWA), 855–856 epilepsy and, 1126 Slow-wave sleep (SWS), 3, 862, 862 arousals, 858–859 defined, 98–99 REM parasomnias and, 870–871 scoring, 33, 38 see also Non-rapid eye movement (NREM) sleep Smoking epidemiology, 589 obstructive sleep apnea syndrome (OSAS) and, 443 in pregnancy, 501, 503–504 sleep-disordered breathing (SDB) and, 589 see also Nicotine Snakes, 102 Snoring classification, 675 elderly and, 658 epidemiology, 289–300 habitual, 289, 291, 298, 493 headache and, 1076, 1077 risk factors, 293 Snyder, Frederick, 20 Socioeconomic class, 503 Sodium oxybate (GHB), 802–803, 805 Software, sleep analysis, 61 Somatic diseases, insomnia and, 284–285 Somatostatin, 243 Sommer, Wilhelm, 13 Somnambulism (sleepwalking), 853–856 clinical features, 853–854 genetics, 854 pathophysiology, 854–855 prevalence, 854 psychopathology, 854 sleep parameters, 855–856 violence and, 1150–1151 Somniloquy (sleeptalking), 675, 889–891, 1152 Spielman, Arthur, 20
Spinal cord, pain processing, 616–617 Spine pathology, 936–937 reflexes, 838 reticular neuron projection, 132, 133 Spinocerebellar ataxia, 923–924, 1033–1034 Split-night studies, 426 Sporadic fatal insomnia (SFI), 981, 988–992 thalamus and, 988–990 Stanford Sleepiness Scale, 48 Staphylococcus aureus, 233 Status cataplecticus, 785 Status dissociatus (SD), 895 Stephan, F.K., 19 Steroids, 250, 603 Stimulus control therapy, 20, 730–731, 730 Stress system dysregulation, 627–628 Stridor, 1030–1031, 1030 Stroke, 1051–1067 central sleep apnea (CSA) and, 322, 322 hemispheric, 1055, 1057, 1059 infratentorial, 1057 insomnia and, 285, 711 obstructive sleep apnea syndrome (OSAS) and, 320–321, 321 sleep apnea and, 298 sleep-disordered breathing (SDB) and, 1060–1067 sleep-wake disorders (SWDs) and, 1051–1060, 1059 snoring and, 295, 296, 297 supratentorial, 1055–1057, 1056, 1057 thalamic, 1053, 1055, 1055, 1056, 1057 Study of Women’s Health Across the Nation, 642 Subcortical pathology, 936 Sublaterodorsal nucleus (SLD), 178–179 Subparaventricular zone (SPZ), 768, 769 Substance abuse, 588 treatment, 595 ‘Subwakefulness’, 990 Sudden death, 299, 740, 1062 Sudden infant death syndrome (SIDS), 223, 501–512 critical development period, 507, 508 definitions, 501–502 environment, 504–505, 508, 511–512, 511 incidence, 502 mechanisms implicated, 508–510 model, 506–508, 507 pathologic examinations, 502 perinatal risk factors, 503–504 physiopathology, 510–511 prenatal vulnerability, 507–508 protective factors, 506, 511 recurrence rates, 504 risk factors, 502–506 sociodemographic/climatic factors, 503
Suggested immobilization test (SIT), 916, 932 Sullivan, Colin, 20 Suprachiasmatic nuclei (SCN), 60, 174, 765, 768, 769 circadian rhythms and, 951–952, 954–955, 956 neurodegenerative diseases and, 1013–1014, 1019 non-photic circadian inputs, 1014 Supratentorial stroke, 1055–1057, 1056, 1057 Swallowing, abnormal syndrome, 892 Sweats, night, 892–893 Sydenham, Thomas, 10 Symptomatic narcolepsy, 792, 800 Symptoms, isolated, 675–676 Synaptic depression, 195 Synaptic potentiation, 193–194, 194 Synchrony/asynchrony, 113 Synucleinopathies, 710, 1022, 1022 Systolic heart failure, 336–337
T
Tachyglossus aculeatus (short-beaked echidna), 104, 105 Takeshi Sakurai, 16 Tanenosuke, Ikematsu, 20 Tank respirator, 1101 Tau mutation, 956 Tauopathies, 1022 Technologists, sleep, 68 Temazepam efficacy, 751 elderly and, 753 insomnia and, 733, 734, 736, 749, 750 Temperature, body, 216–218, 219–220, 220, 1018 see also Thermoregulation Temporal lobe epilepsy (TLE), 1126–1127, 1130 Temporal theta rhythm, 114, 115 Tench, 101 Tension-type headache, 1075, 1077, 1078–1079, 1078 Terrors see Sleep terrors Testosterone, 643 Testudo marginata (tortoise), 103 Tetracyclic antidepressants, 593 Thalamic stroke, 1053, 1055, 1055, 1056, 1057 Thalamocortical projection system, 132, 134–135 Thalamocortical sleep oscillations, 766–767 Thalamus, 133, 986–987 sleep regulation and, 988–990 Theogony of Hesiod, 6 Theophylline, 342, 479, 601 Theriac, 9 Thermoregulation, 215–236 adults/elderly, 220–222 body temperature, 216–218, 219–220, 220
(Volume 1: pages 1–666; Volume 2: pages 667–1160)
SUBJECT INDEX Thermoregulation, (Continued) neonates, 222–224, 223 sleep stage responses, 218–219, 219 sleep structure, age and, 218 thermal exchanges, 215–216 thermal load, 220 Thoth, 4 Thyroid hormones, 1025 Thyroid replacement therapy (TRT), 602 Thyroid-stimulating hormone (TSH), 246, 602 Tiagabine effect on sleep, 1132, 1133 insomnia and, 735, 740–741 TIM protein, 955 Timeless gene, 955 Tinca tinca (tench), 101 Titus Lucretius Carus, 7 Toads, 102 Toh, K., 19 Tokoloshis, 894 Tongue base surgery, 451 Tonsillectomy, 449 Tooth grinding see Bruxism Topiramate, 583, 597, 1133 ‘Topographical memory’, 520 ‘Tortoise shell’ ventilator, 1101 Tortoises, 98, 103 Total sleep deprivation (TSD), 564 Toxicity, drug, 752 Tracheostomy (tracheotomy), 20, 451, 1030, 1067, 1103 Tramadol, 937, 939 Transcranial magnetic stimulation (TMS), 934–935, 935 Transection studies, 152–154, 153 Transferrin, 930–931 Transforming growth factor (TGF)-a, 769 Transmissible mink encephalopathy (TME), 992 Trauma, decreased dream recall, 552–553 Trazodone efficacy, 755 hallucinations and, 1024 insomnia and, 734, 739–740, 741, 755 psychiatric diseases and, 568 safety, 756 sleep dysfunction and, 594–595 Tree frog, 102 Triazolam efficacy, 751 insomnia and, 705, 734, 736, 749, 750, 1037 primary insomnia and, 708 Tricyclic antidepressants (TCAs) arousal disorders and, 1151 bruxism and, 909 cataplexy and, 803, 803 enuresis and, 366 insomnia and, 739–740, 748 narcolepsy and, 804
Tricyclic antidepressants (TCAs) (Continued) NREM parasomnias and, 863 periodic limb movement disorder (PLMD), 827 safety, 756 sleep dysfunction and, 593 Trihexyphenidyl, 598 Trimipramine, 756 L-Tryptophan, 895 Tuberomammillary nucleus (TMN), 174, 770, 774–775 neurons, 776 Turtle headache, 1075, 1077, 1079 Turtles, 103 Two process model (Borbely), 38, 826 sleep homeostasis and, 703–704, 704, 768
U Ullanlinna Narcolepsy Scale (UNS), 289 Upper-airway narrow, 293 surgery, 448–451 Upper-airway resistance syndrome (UARS), 377–378, 401–407 clinical symptoms, 402 epidemiology, 402 neuromuscular disorders and, 1097–1098 pathophysiology, 404–407 physical examination, 402–404 treatment, 407 Uqumangirniq, 894 Uremia, 940 Urination see Enuresis Urotherapy, 366 ‘Urotoxins’, 13 Uvulopalatopharyngoplasty (UPPP), 20, 449–450
V Valproate, 596, 830, 1129, 1132 Valproic acid, restless-legs syndrome (RLS) and, 939 van Helmont, Jan Baptista, 10 Vascular theories, 11–12, 15 Vasoactive intestinal polypeptide (VIP), 248 Venlafaxine, 596, 803, 1028 Ventilation continuous, 464 negative-pressure, 479 nocturnal, 463–464 see also Noninvasive intermittent positive pressure ventilation (NIPPV) Ventilation-perfusion matching, 475 Ventilators, 459–460 negative-pressure, 1101 Ventilatory abnormalities, 472 Ventilatory control changes, 473–475 instability (loop gain), 392–393, 393
I-19 Ventilatory control (Continued) obstructive sleep apnea syndrome (OSAS), 83–84, 84 Ventilatory effort, 379 Ventral respiratory group (VRG) neurons, 1088 Ventrolateral preoptic area (VLPO), 142, 163–164 sleep-promoting neurons, 174–176, 775–776 Verispan Physician Drug Audit (2002), 748, 748 Vesalius, Andreas, 9 Video polysomnography (VPSG), 65–70 EEG electrode placement, 65, 66 interpretation, 68–70 montages, 65–68, 66–67 sleep stage effect, 69–70, 69 sleep technologist, 68 video recording, 68 viewing/reformatting, 68 Vigilance state-regulatory systems, 766–769, 766, 776–777 Vigilance testing, 51 Viloxazine, narcolepsy and, 804 Violent parasomnias, 1149–1155 case example, 1149 clinical/laboratory evaluation, 1154–1155 medicolegal evaluation, 1153–1155 neurological conditions and, 1150–1152 psychiatric conditions, associated, 1152–1153 sleep state-dependent, 1149–1150 sleep-related disorders, associated, 1150, 1150 Visual dream imagery, 894 loss of, 520, 521 Vitamin B12, 966 Vogel, Gerald, 19 von Economo, Constantin, 17–18, 769, 830 von Haller, Albrecht, 10, 11, 12 von Linne, Karl, 10 von Voit, Carl, 13 Voxel-based morphometry (VBM), 80, 82, 83, 85
W Wadd, William, 15 Wakefulness, 991 depression, 77 gene expression, 193–194, 194 scoring, 34, 36 ‘stimulus’, 374–375, 374 stroke and, 1062 transition to sleep, 32, 32 Wakefulness after sleep onset (WASO), 58–59, 59 ‘Waking center’, 17, 18, 769, 777 Waldeyer, Heinrich, 12 Wallenberg’s syndrome, 1062 Wanderings epileptic nocturnal (ENW), 1112
(Volume 1: pages 1–666; Volume 2: pages 667–1160)
I-20
SUBJECT INDEX
Wanderings (Continued) episodic nocturnal, 1152 Water fowl, 104 Weight loss, 442 Weitzman, Elliot David, 19, 20, 21 Wells, William Hughes, 15 West syndrome, 1127 Western toad, 102 Westphal, Carl Friedrich Otto, 14 Wever, Kurt, 19 White matter injury, 1064 Willis, Thomas, 10 Wisconsin Sleep Cohort Study, 275, 646 Women, 249, 639–648 circadian rhythmicity, 641–642 common sleep disorders, 640, 647–648 hormonal factors, 642–643 lifespan physiologic changes, 643–646 objective sleep differences, 639–642
Women, (Continued) psychosocial issues, 646–648 subjective sleep differences, 642 Women’s Health Initiative, 603 World Health Organization (WHO), 669
X Xe inhalation, 78–79
Y Yellow Emperor, Huang Ti, 5 Yin-yang symbol, 5 Yu Hsiung, 5 Yutaka Honda, 19
Z Zaleplon circadian sleep disorders and, 826 efficacy, 750
Zaleplon (Continued) elderly and, 655, 753 insomnia and, 734, 737, 738, 749, 750, 758 restless-legs syndrome (RLS) and, 940 Zebrafish, 101 Zolpidem circadian rhythm sleep disorders and, 826, 972 cyclic alternating pattern (CAP) and, 705 efficacy, 750 elderly and, 655 insomnia and, 734, 737, 738, 740, 749, 750 long-term efficacy, 705 primary insomnia and, 708 restless-legs syndrome (RLS) and, 940 Zopiclone, 705, 708 Zucker, Irving, 19
(Volume 1: pages 1–666; Volume 2: pages 667–1160)