Bipolar Disorder: Clinical and Neurobiological Foundations

Bipolar Disorder

Bipolar Disorder: Clinical and Neurobiological Foundations Edited by Lakshmi N. Yatham and Mario Maj © 2010 John Wiley & Sons, Ltd. ISBN: 978-0-470-72198-8

Bipolar Disorder: Clinical and Neurobiological Foundations Editors Lakshmi N. Yatham Department of Psychiatry, The University of British Columbia, Vancouver, Canada

Mario Maj Department of Psychiatry, University of Naples SUN, Naples, Italy

This edition first published 2010, Ó 2010 by John Wiley & Sons, Ltd Wiley-Blackwell is an imprint of John Wiley & Sons, formed by the merger of Wiley’s global Scientific, Technical and Medical business with Blackwell Publishing. Registered office: John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, UK Other Editorial Offices: 9600 Garsington Road, Oxford, OX4 2DQ, UK 111 River Street, Hoboken, NJ 07030-5774, USA For details of our global editorial offices, for customer services and for information about how to apply for permission to reuse the copyright material in this book please see our website at www.wiley.com/wiley-blackwell The right of the author to be identified as the author of this work has been asserted in accordance with the Copyright, Designs and Patents Act 1988. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by the UK Copyright, Designs and Patents Act 1988, without the prior permission of the publisher. Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not be available in electronic books. Designations used by companies to distinguish their products are often claimed as trademarks. All brand names and product names used in this book are trade names, service marks, trademarks or registered trademarks of their respective owners. The publisher is not associated with any product or vendor mentioned in this book. This publication is designed to provide accurate and authoritative information in regard to the subject matter covered. It is sold on the understanding that the publisher is not engaged in rendering professional services. If professional advice or other expert assistance is required, the services of a competent professional should be sought. The contents of this work are intended to further general scientific research, understanding, and discussion only and are not intended and should not be relied upon as recommending or promoting a specific method, diagnosis, or treatment by physicians for any particular patient. The publisher and the author make no representations or warranties with respect to the accuracy or completeness of the contents of this work and specifically disclaim all warranties, including without limitation any implied warranties of fitness for a particular purpose. In view of ongoing research, equipment modifications, changes in governmental regulations, and the constant flow of information relating to the use of medicines, equipment, and devices, the reader is urged to review and evaluate the information provided in the package insert or instructions for each medicine, equipment, or device for, among other things, any changes in the instructions or indication of usage and for added warnings and precautions. Readers should consult with a specialist where appropriate. The fact that an organization or Web site is referred to in this work as a citation and/or a potential source of further information does not mean that the author or the publisher endorses the information the organization or Web site may provide or recommendations it may make. Furthermore, readers should be aware that Internet Web sites listed in this work may have changed or disappeared between when this work was written and when it is read. No warranty may be created or extended by any promotional statements for this work. Neither the publisher nor the author shall be liable for any damages arising herefrom. Library of Congress Cataloging-in-Publication Data Bipolar disorder : clinical and neurobiological foundations / editors, Lakshmi N. Yatham and Mario Maj. p. cm. Includes bibliographical references and index. ISBN 978-0-470-72198-8 (cloth) 1. Manic-depressive illness. I. Yatham, Lakshmi N. II. Maj, Mario, 1953– [DNLM: 1. Bipolar Disorder. WM 207 B6161 2010] RC516.B5223 2010 616.89’5—dc22 2010005586 ISBN: 9780470721988 A catalogue record for this book is available from the British Library. Set in 9.25/12pt, Palatino by Thomson Digital, Noida, India Printed in Singapore by Markono Print Media Pte Ltd 1

2010

Contents

Preface

vii

List of Contributors

ix

12 Genetics of Bipolar Disorder

Falk W. Lohoff and Wade H. Berrettini 13 Structural Brain Imaging in Bipolar Disorder

1 From Mania to Bipolar Disorder

1

2 Clinical Features and Subtypes of Bipolar

8

Fred K. Goodwin and D.Z. Lieberman 17

Lewis L. Judd and Pamela J. Schettler 31

Mark A. Frye and Giulio Perugi 44

Jan Fawcett 6 Update on the Epidemiology of Bipolar Disorder

52

62

69

Ivan J. Torres and Gin S. Malhi 83

90

R. Sabes-Figuera, D. Razzouk and Paul E. McCrone

Robert M. Post and Marcia Kauer-Sant’Anna

17 Molecular Biology of Bipolar Disorder

210

228

18 Mitochondrial Dysfunction and Oxidative

244

Tadafumi Kato, Flavio Kapczinski and Michael Berk 19 Neuroendocrinology of Bipolar Illness

255

Timothy Dinan and Michael Bauer Disorder

21 Treatment Adherence in Bipolar Disorder

263

96

275

Jan Scott and Mary Jane Tacchi 22 Acute Mania

11 An Introduction to the Neurobiology of Bipolar

Illness Onset, Recurrence and Progression

16 Neurotransmitter Systems in Bipolar Disorder

Greg Murray and Allison Harvey

Hagop S. Akiskal and Kareen K. Akiskal 10 Economics of Bipolar Disorder

200

20 Circadian Rhythms and Sleep in Bipolar

9 The Genius-Insanity Debate: Focus on Bipolarity,

Temperament, Creativity and Leadership

Disorder: Focus on Cerebral Metabolism and Blood Flow

Stress

Zolt an Rihmer and Jan Fawcett 8 Neurocognition in Bipolar Disorder

In Kyoon Lyoo and Perry F. Renshaw

Ana Andreazza, Jun Feng Wang and Trevor Young

Kathleen R. Merikangas and Tracy L. Peters 7 Suicide and Bipolar Disorder

133

Marina Nakic, John H. Krystal and Zubin Bhagwagar

5 DSM-V Perspectives on Classification

of Bipolar Disorder

Diffusion Tensor Imaging, and Magnetic Resonance Spectroscopy in Bipolar Disorder

John O. Brooks III, Po W. Wang and Terence A. Ketter

4 Comorbidity in Bipolar Disorder: A Focus on

Addiction and Anxiety Disorders

Paolo Brambilla and Jair C. Soares

15 Functional Brain Imaging Studies in Bipolar

3 The Long-Term Course and Clinical Management

of Bipolar I and Bipolar II Disorders

124

14 Functional Magnetic Resonance Imaging,

David Healy Disorder

110

285

Paul E. Keck, Jr, Susan L. McElroy and John M. Hawkins

v

vi

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Contents

23 Pharmacological Treatment of Bipolar

Depression

31 Psychoeducation as a Core Element of

294

Allan H. Young and Charles B. Nemeroff

32 Cognitive-Behavioural Therapy for Bipolar

304

Alan C. Swann

342

353

367

36 Bipolar Disorder in Women

463

Benicio N. Frey, Karine A. Macritchie, Claudio N. Soares and Meir Steiner

Chris J. Bushe and Mauricio Tohen 29 Somatic Treatments for Bipolar Disorder:

384

37 Phenomenology and Treatment of Bipolar

I Disorder in Children: A Critical Review

Mark S. George

477

Gabrielle A. Carlson and Elizabeth B. Weller

30 Novel Therapeutic Strategies for Bipolar

Rodrigo Machado-Vieira, Husseini K. Manji and Carlos A. Zarate Jr

453

Amy M. Kilbourne, David E. Goodrich and Mark S. Bauer

28 Bipolar Disorder and Safety Monitoring

Disorder

443

David J. Miklowitz 35 Collaborative Care for Bipolar Disorder

Ihsan M. Salloum, Luca Pani and Tiffany Cooke

ECT, VNS and TMS

430

Holly A. Swartz, Ellen Frank, Laura E. Zajac and David J. Kupfer Disorder

27 Management of Comorbidity in Bipolar

for Clinicians: A Review of the Evidence and the Implications

Bipolar Disorder

34 Family Therapy Approaches to Bipolar

Gordon Parker and Terence A. Ketter Disorder

422

33 Interpersonal and Social Rhythm Therapy for

333

Joseph F. Goldberg and Michael Berk 26 Management of Bipolar II Disorder

Disorder Sagar V. Parikh and Jan Scott

25 Rapid Cycling Bipolar Disorder:

Phenomenology and Treatment

412

Francesc Colom and Lesley Berk

24 Practical Pharmacological Maintenance

Treatment of Bipolar Disorder

Psychological Approaches for Bipolar Disorders

395

38 Bipolar Disorder in the Elderly

488

Martha Sajatovic and Lars Vedel Kessing Index

499

Preface

Bipolar disorder is a relatively recent concept, which emerged in the middle of the 20th century. However, bipolar disorder is not a new disease. Indeed, Aretaeus of Cappadocia, in his descriptions, captured the essence of the nature and course of mood changes of mania and depression almost 2000 years ago. The objective of this book is to describe the clinical and neurobiological foundations of the modern concept of bipolar disorder as defined by the American Psychiatric Association’s Diagnostic Manual of Mental Disorders and the International Classification of Diseases. In order to capture both the American and the international perspectives, the editors deliberately chose authors from different continents for most chapters. The book is divided into four sections. The first section covers the descriptive aspects of the disorder. This section begins with an historical overview of the evolution of the concept of bipolar disorder. While Dr. Healy admits that bipolar disorder is a distinct clinical entity, he argues that the boundaries of the modern concept of bipolar disorder have been shaped primarily by the interests of the industry over the past 15 years. The next two chapters review clinical features, course and outcome in the context of new data and suggest that depressive symptoms dominate the course of bipolar disorder and that the disorder is chronic for a significant proportion of patients. Comorbidity is the rule rather than an exception for bipolar patients and this chapter illustrates some of the common comorbidities patients with bipolar disorder experience. Dr. Fawcett then outlines the DSM-V process and some of the issues that the DSM-V will address with regard to classification of bipolar disorder in the next chapter. The remaining chapters in this section emphasize that bipolar disorder is common, associated with cognitive impairment in a significant proportion of patients, that suicide risk is high, and that the disorder is

associated with significant economic burden. This section also contains a fascinating review of the genius–insanity debate. The biological aspects section begins with an overview of the neurobiology of bipolar disorder by Robert Post. Subsequent chapters address in greater detail some of the following questions: what is the current status with regard to the search for bipolar susceptibility genes? What brain regions and brain chemicals are altered in bipolar patients? Are changes in neurotransmitters and neurohormones still relevant or are changes in post-receptor signalling pathways more critical to the neurobiology of bipolar disorder? Is bipolar disorder associated with oxidative stress, mitochondrial dysfunction or alterations in biological rhythms? Treatment adherence is a major challenge in the management of bipolar disorder. Thus, the section on management begins with an overview of reasons for non-adherence and strategies to improve adherence. This is followed by a series of chapters that describe the current status of the pharmacological management of various phases and subtypes of bipolar disorder. This section also contains chapters that review the role of novel treatments, somatic treatments, and safety monitoring, as well as the role of psychological treatments as adjuncts to pharmacotherapy. The final section on special populations provides clinicians with the latest information and guidance on the management of bipolar disorders in women, children and the elderly. We hope that this book will become a useful resource for psychiatrists and other health care professionals to improve their understanding and management of bipolar disorder. Lakshmi N. Yatham Mario Maj

vii

List of Contributors

Hagop S. Akiskal University of California at San Diego, 3350 La Jolla Village Drive, San Diego, CA 92161-9116, USA Kareen K. Akiskal International Mood Center, La Jolla, CA 92093-0603, USA

John O. Brooks III Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine at UCLA, 760 Westwood Plaza, B8-233b NPI, Los Angeles, CA 90024-1759, USA

Ana Andreazza Department of Psychiatry, University of British Columbia, 2255 Westbrook Mall, Vancouver, BC V6T 2A1, Canada

Chris J. Bushe Lilly UK, Lilly House, Priestley Road, Basingstoke, RG24 9NL, UK

Mark S. Bauer Center for Organization, Leadership, and Management Research (152M), Boston VA Healthcare System, 150 South Huntington Avenue, Boston, MA 02130, USA

Gabrielle A. Carlson Department of Child and Adolescent Psychiatry, Stony Brook University School of Medicine, Putnam Hall-South Campus, Stony Brook, NY 11794-8790, USA

Michael Bauer Department of Psychiatry and Psychotherapy, University Hospital Carl Gustav Carus, Technische Universita¨t Dresden, Fetscherstraße 74, D-01307 Dresden, Germany Lesley Berk ORYGEN Research Centre and Department Clinical & Biomedical Sciences, University of Melbourne, Victoria, Australia Michael Berk Barwon Health and the Geelong Clinic, University of Melbourne, Kitchener House, Ryrie Street, Geelong, Victoria 3220, Australia Wade H. Berrettini University of Pennsylvania School of Medicine, Room 2206, 125 South 31st Street, Philadelphia, PA 19104, USA Zubin Bhagwagar Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA; Bristol Myers Squibb, USA Paolo Brambilla Inter-University Center for Behavioural Neurosciences, Department of Pathology and Experimental & Clinical Medicine, Section of Psychiatry, University of Udine, Udine, Italy

Francesc Colom Bipolar Disorders Program, Clinical Institute of Neuroscience, IDIBAPS-CIBERSAM, Hospital Clinic Barcelona, University of Barcelona, Barcelona, Catalonia, Spain Tiffany Cooke Emory University, Rollins School of Public Health, 1518 Clifton Road Northeast Atlanta, GA 30329, USA Timothy Dinan Department of Psychiatry, Cork University Hospital, Wilton, Cork, Ireland Jan Fawcett Department of Psychiatry, University of New Mexico School of Medicine, National Institute of Albuquerque, Albuquerque, NM 87131, USA Ellen Frank Department of Psychiatry and Department of Psychology, University of Pittsburgh School of Medicine, Western Psychiatric Institute and Clinic, 3811 O’Hara Street, Pittsburgh, PA 15213, USA ix

x

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List of Contributors

Benicio N. Frey Department of Psychiatry and Behavioural Neurosciences, McMaster University and Women’s Health Concerns Clinic, St. Joseph’s Healthcare, Hamilton, ON, Canada

Marcia Kauer-Sant’Anna Molecular Psychiatry Laboratory, Department of Psychiatry, Hospital de Clinicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Brazil

Mark A. Frye Department of Psychiatry and Psychology, Mayo Clinic, 200 First Street, Rochester, MN 55905, USA

Paul E. Keck, Jr. Lindner Center of HOPE and Department of Psychiatry, University of Cincinnati College of Medicine, 4075 Old Western Row Road, Mason, OH 45040, USA

Mark George Brain Stimulation Laboratory, MUSC IOP, Radiology and Neurosciences Medical University of South Carolina, 67 President Street, Room 502 North, PO Box 250861, Charleston, SC 29425, USA

Lars Vedel Kessing Department of Psychiatry, Rigshospitalet, University Hospital of Copenhagen, 2100 Copenhagen, Denmark

Joseph F. Goldberg Mount Sinai School of Medicine, New York, NY, USA David E. Goodrich VA Ann Arbor National Serious Mental Illness Treatment Research and Evaluation Center, 2215 Fuller Road, Ann Arbor, MI 48105, USA Fred K. Goodwin Department of Psychiatry and Behavioral Sciences, Center on Neuroscience, Medical Progress, and Society, George Washington University Medical Center, Washington, DC 20037, USA

Terence A. Ketter Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 401 Quarry Road, Room 2124, Stanford CA 94305, USA Amy M. Kilbourne VA Ann Arbor Serious Mental Illness Treatment Research and Evaluation Center, 2215 Fuller Road, Ann Arbor, MI 48105, USA John H. Krystal Department of Psychiatry, Yale University School of Medicine, Yale-New Haven Hospital, 300 George Street, Suite 901, New Haven, CT, 06511, USA

Allison Harvey Psychology Department, Sleep and Psychological Disorders Lab, University of California, 3210 Tolman Hall, Berkeley, CA 94720-1650, USA

David J. Kupfer Department of Psychiatry, University of Pittsburgh School of Medicine, Western Psychiatric Institute and Clinic, 3811 O’Hara Street, Pittsburgh, PA 15213, USA

John M. Hawkins Lindner Center of HOPE; Associate Professor, Department of Psychiatry, University of Cincinnati College of Medicine, 4075 Old Western Row Road, Mason, OH 45040, USA

D.Z. Lieberman George Washington University Medical Center, 2150 Pennsylvania Avn., NW, Department of Psychiatry and Behavioral Sciences, 8th Floor, Washington, DC 20037, USA

David Healy Hargest Unit, North Wales Department of Psychological Medicine, Cardiff University, Ysbyty Gwynedd, Bangor, LL57 2PW, UK

Falk W. Lohoff University of Pennsylvania School of Medicine, Department of Psychiatry Center for Neurobiology and Behavior Translation Research Laboratories., 125 South 31st Street, Room 2213, Philadelphia, PA 19104, USA

Lewis L. Judd Department of Psychiatry, University of California at San Diego (UCSD), 9500 Gilman Drive, MC: 0603, La Jolla, CA 92093-0603, USA

In Kyoon Lyoo Seoul National University, Seoul, South Korea

 vio Kapczinski Fla ISBD Hospital de Clinicas, UFRGS Brizil Porto Alegre, RS, Brazil

Rodrigo Machado-Vieira Experimental Therapeutics, Mood and Anxiety Disorders Research Program, NIMH-NIH, Bldg 15K, 15 North Drive, MSC 2670, Bethesda, MD 20892, USA

Tadafumi Kato Laboratory for Molecular Dynamics of Mental Disorders, RIKEN Brain Science Institute, Hirosawa 2-1, Wako, Saitama, 350-0198, Japan

Karine A. Macritchie Institute of Mental Health, Department of Psychiatry, University of British Columbia, Suite 403 - 5950 University Blvd., Vancouver, BC V6T 1Z3, Canada

List of Contributors

Gin S. Malhi Department of Psychiatry, University of Sydney, CADE (Clinical Assessment Diagnostic Evaluation) Clinic, Royal North Shore Hospital, Sydney, Australia Husseini K. Manji Johnson & Johnson Pharmaceuticals Group, 1125 Trenton-Harbourton Road, E32000, Titusville, NJ 08560, USA Paul E. McCrone Centre for the Economics of Mental Health, Section of Community Mental Health Service and Population Research, Department PO24, Institute of Psychiatry, King’s College, De Crespigny Park, London SE5 8AF, UK Susan L. McElroy Lindner Center of HOPE and Department of Psychiatry, University of Cincinnati College of Medicine, 4075 Old Western Row Road Mason, OH 45040, USA Kathleen R. Merikangas Genetic Epidemiology Research Branch, Porter Neuroscience Research Centre, National Institute of Mental Health, Building 35, Room 1A-201, 35 Convent Drive, MSC 3720, Bethesda, MD 20892-3720, USA David J. Miklowitz UCLA Semel Institute for Neuroscience and Human Behavor Division of Child and Adolescent Psychiatry, 760 Westwood Plaza, Rm 58-217 David Geffen School of Medicine at UCLA, Los Angeles, CA 90024-1759, USA Greg Murray Faculty of Life and Social Sciences, Swinburne University of Technology, PO Box 218 John Street, Hawthorn 3122, Australia Marina Nakic Department of Psychiatry, Yale University School of Medicine, Yale-New Haven Hospital, 300 George Street, Suite 901, New Haven, CT, 06511, USA Charles B. Nemeroff Department of Psychiatry and Behavioral Sciences, University of Miami Miller School of Medicine, Miami FL, USA Luca Pani Istituto Tecnologie Biomediche, Consiglio Nazionale delle Ricerche, Sede di Cagliari-Pula and PharmaNess Scarl, Edificio 5 - Parco Scientifico e Tecnologico della Sardegna - 09010 Pula (Cagliari), Italy Sagar V. Parikh Department of Psychiatry, University Health Network, University of Toronto, Room 9M-329, Toronto Western Hospital, 399 Bathurst Street, Toronto, ON M5T 2S8, Canada

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xi

Gordon Parker School of Psychiatry, University of New South Wales (UNSW), New South Wales, Australia 2031; Black Dog Institute, Hospital Road, Prince of Wales Hospital, Ranwick, NSW 2031, Australia Giulio Perugi Department of Psychiatry, University of Pisa; Institute of Behavioural Sciences “G. De lisio”, Viale Monzone 3, 54031 Carrara, Italy Tracy L. Peters Genetic Epidemiology Research Branch, Mood and Anxiety Program, Intramural Research Program, National Institute of Mental Health, National Institute of Health, Porter Neuroscience Research Center, Building 35, Room 1A-201, 35 Convent Drive, Bethesda, MD 20892-3720, USA Robert M. Post George Washington University Medical School, Bipolar Collaborative Network, 5415 W. Cedar Kabem Suite 201B, Bethesda, MD 20814, USA D. Razzouk Department of Psychiatry, Universidade Federal de Sao Paulo (UNIFESP), Sao Paulo, Brazil Perry F. Renshaw University of Utah, Salt Lake City, UT USA  n Rihmer Zolta Department of Clinical and Theoretical Mental Health, and Department of Psychiatry and Psychotherapy, Semmelweis Medical University, Ku´tvo¨lgyi Clinical Centre, Budapest, Hungary R. Sabes-Figuera Centre for the Economics of Mental Health, Health Service and Population Research Department PO24, Institute of Psychiatry, King’s College, De Crespigny Park, London SE5 8AF, UK Martha Sajatovic University Hospitals Case Medical Center, 10524 Euclid Avenue, Cleveland, OH 44106, USA Ihsan M. Salloum Department of Psychiatry, University of Miami Miller School of Medicine, 1120 NW 14th Street, Rm 1450, Miami, FL 33136, USA Pamela J. Schettler Mood Disorders Research Group, Department of Psychiatry, University of California at San Diego (UCSD), 9500 Gilman Drive, La Jolla, CA 92093-0603, USA

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List of Contributors

Jan Scott University Department of Psychiatry, Newcastle University, Institute of Psychiatry, Institute of Neuroscience, Newcastle-upon-Tyne NE1 4RU, UK Claudio N. Soares Department of Psychiatry and Behavioural Neurosciences, McMaster University and Women’s Health Concerns Clinic, St. Joseph’s Healthcare, Hamilton, ON, Canada Jair C. Soares Department of Psychiatry and Behavioral Sciences, UT Houston Medical School, Houston, TX, USA Meir Steiner Department of Psychiatry and Behavioural Neurosciences, McMaster University and Women’s Health Concerns Clinic, St. Joseph’s Healthcare, Hamilton, ON, Canada Alan C. Swann Department of Psychiatry and Behavioral Sciences, The University of Texas Health Science Center at Houston, 1300 Moursund Street, Houston, TX 77037, USA Holly A. Swartz Department of Psychiatry, University of Pittsburgh School of Medicine, Western Psychiatric Institute and Clinic, 3811 O’Hara Street, Pittsburgh, PA 15213, USA Mary Jane Tacchi Institute of Psychiatry, Institute of Neuroscience, Newcastle University, Newcastle-upon-Tyne, NE1 7RU, UK Mauricio Tohen University of Texas Health Science Center at San Antonio, 7730 Floyd Curl Drive, San Antonio, TX 78229, USA



Sadly, Elizabeth B. Weller died during preparation of the manuscript

Ivan J. Torres Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada; Riverview Hospital, British Columbia Mental Health and Addictions Services, 2601 Lougheed Highway, Coquitlam, BC V3C 4J2, Canada Jun Feng Wang Department of Psychiatry, University of British Columbia, 2255 Westbrook Mall, Vancouver, BC V6T 2A1, Canada Po W. Wang Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA Elizabeth B. Weller Deceased Allan H. Young Institute of Mental Health, Department of Psychiatry, University of British Columbia, Suite 430, 5950 University Blvd., Vancouver, BC V6T 1Z3, Canada Trevor Young, MD Department of Psychiatry, University of British Columbia, 2255 Westbrook Mall, Vancouver, BC V6T 2A1, Canada Laura E. Zajac Department of Psychology, University of Pittsburgh School of Medicine, Western Psychiatric Institute and Clinic, 3811 O’Hara Street, Pittsburgh, PA 15213, USA Carlos A. Zarate, Jr. Experimental Therapeutics, Mood and Anxiety Disorders Research Program, National Institute of Mental Health (NIMH-NIH), Bldg 15K, 15 North Drive, Bethesda, MD 20892-2670, USA

Plate 1 Sample magnetic resonance spectroscopy spectra from P31 MRS at 2T (A) and from H1 MRS at 3T (B). Abbreviations: ATP, adenosine tri-phosphate; MRS, Magnetic Resonance Spectroscopy; PCr, Phosphocreatine; PDE, Phosphodiesters; Pi, Inorganic Phosphate; PME, Phosphomonoesters; T, Tesla. (a) A sample P31 spectra is shown. Reprinted from [3]. Association between cortical metabolite levels and clinical manifestations of migrainous aura: An MR-spectroscopy study. Brain;130:3102–3110, by permission of Oxford University Press. (b) A sample H1 spectra is shown. Reprinted from [4]. Abnormal glutamatergic neurotransmission and neuronal-glial interactions in acute mania. Biol. Psych.; 64:718–726, by permission of Elsevier.

Plate 2 Schematic presentation of the findings from cross-sectional H1 MRS and P31 MRS studies that show differences in brain metabolite levels between adult patients with bipolar disorder and comparison subjects. Abbreviations: Cho, Choline; Cr, Creatine; Glx, Glutamate, Glutamine and g-amino butyric acid; MRS, Magnetic Resonance Spectroscopy; NAA, N-acetylaspartate; PCr, Phosphocreatine; PME, Phosphomonoesters. Regular triangles represent higher brain metabolite levels or metabolite/Cr þ PCr ratios in patients with bipolar disorder relative to comparison subjects. Inverted triangles represent lower metabolite levels or metabolite/Cr þ PCr ratios in patients with bipolar disorder relative to comparison subjects. Rectangles represent no differences in metabolite levels or metabolite/Cr þ PCr ratios between patients with bipolar disorder and comparison subjects. Bipolar Disorder: Clinical and Neurobiological Foundations Edited by Lakshmi N. Yatham and Mario Maj © 2010 John Wiley & Sons, Ltd. ISBN: 978-0-470-72198-8

Plate 3 Schematic presentation of the findings from longitudinal H1 MRS studies that examine medication effects on brain metabolite levels in adult patients with bipolar disorder. Abbreviations: Cho, Choline; Cr, Creatine; Glx, Glutamate, Glutamine and g-amino butyric acid; HDRS, 17-item Hamilton Depression Rating Scale; MRS, Magnetic Resonance Spectroscopy; NAA, N-acetylaspartate. (a) Lithium effects on brain metabolite levels in patients with bipolar disorder. Regular triangles represent increase in brain metabolite levels or metabolite/Cr þ PCr ratios in patients with bipolar disorder after lithium treatment compared to those in their baseline. Inverted triangles represent decrease in brain metabolite levels or metabolite/Cr þ PCr ratios in patients with bipolar disorder after lithium treatment compared to those in their baseline. Rectangles represent no changes in metabolite levels or metabolite/Cr þ PCr ratios in patients with bipolar disorder after lithium treatment. (b) Cytidine effect on brain metabolite levels and depressive symptoms in depressed patients with bipolar disorder. Bars represent estimated glutamate/glutamine changes from baseline in cytidine and placebo add-on patients with bipolar depression. P values above the bars indicate significant difference between treatment groups in rates of decreasing glutamate/glutamine levels throughout the treatment period with mixed-effect regression model. Squares and trend lines represent the estimated HDRS score in cytidine and placebo add-on patients with bipolar depression. Asterisks represent p < 0.01 significant difference between treatment groups in rates of improvement in HDRS scores from Week 1 through Week 4 with mixed-effect regression model. (Copied from Yoon et al. [Yoon, S.J., Lyoo, I.K., Haws, C., Kim, T.S., Cohen, B.M., Renshaw, P.F., in press. Decreased glutamate/glutamine levels may mediate cytidine’s efficacy in treating bipolar depression: A longitudinal proton magnetic resonance spectroscopy study. Neuropsychopharmacology.]. Courtesy should be sought).

Plate 4 Regions of increased and decreased FA in patients with bipolar disorder relative to comparison subjects. Abbreviations: Ant, Anterior; Post, Posterior; Sup, Superior. Red circles represent higher FA in patients with bipolar disorder relative to comparison subjects, blue circles represent lower FA in patients with bipolar disorder relative to comparison subjects. Parcellated white matter mask is adapted from stereotaxic white matter atlas [122].

Plate 5 Regions of increased and decreased activation under emotional processing tasks in patients with bipolar disorder. Abbreviations: Sup, Superior; Mid, Middle; Inf, Inferior. Regions of increased (red circle) and decreased (blue circle) activation under emotional processing tasks in patients with bipolar disorder from the Table .8. Regions were marked based on the Talairach coordinates, Brodmann areas or anatomical description in the literature. In patients with bipolar disorder, there were abnormal cortical and subcortical activations in the brain regions including prefrontal and temporal cortex, striatum, thalamus and amygdala when taking emotional processing tasks such as the facial affect recognition and emotional Go-NoGo tasks relative to comparison subjects.

Plate 6 A model of corticolimbic dysregulation in bipolar disorder. Areas generally associated with increased activation in bipolar disorder are in red and those with decreased activation are in blue. Note that colour-coding of regions is intended to represent the consensus findings for the region, because all findings have not been uniform. Numbers for BAs are provided where appropriate. ACC ¼ anterior cingulate cortex; AMYG ¼ amygdala; ATC ¼ anterior temporal cortex; CV ¼ cerebellar vermis; DLPFC ¼ dorsolateral prefrontal cortex; HYPTH ¼ hypothalamus; MOFC ¼ medial orbital prefrontal cortex; PHG ¼ parahippocampal gyrus; SGPFC ¼ subgenual prefrontal cortex; THAL ¼ thalamus; VLPFC ¼ ventrolateral prefrontal cortex. From Brooks et al. [6].

Plate 7 Metabolic changes associated with bipolar depression relative to healthy controls. Decreased absolute metabolism is in blue. From Brooks et al. [6].

Plate 8 Metabolic changes associated with bipolar mania relative to healthy controls. Regions with decreased metabolism are in blue, and increased metabolism in red. From Brooks et al. (2010).

Plate 9 Resting state cerebral metabolic differences in older, euthymic patients with bipolar disorder compared to healthy controls. Regions with increased metabolism in bipolar disorder patients are in red and those with decreased metabolism are in blue. From Brooks et al. [6].

CHAPTER

1

From Mania to Bipolar Disorder David Healy Hargest Unit, North Wales Department of Psychological Medicine, Cardiff University, Ysbyty Gwynedd, Bangor, UK

From Pinel to Kraepelin When the first asylums opened, around 1800, mania was a generic term for insanity. Philippe Pinel’s Treatise on Insanity that appeared in 1800 was accordingly named Trait
e sur la Manie. For 2000 years before Pinel, the chief determinant of diagnosis in medicine lay in the visible presentation of the patient. These visible presentations could lead to reliable diagnoses of tumours, diabetes, catatonia, epilepsy and insanity. The visible presentations of insanity involved flushing, overactivity and maniacal behaviour. Mania was diagnosed in patients who were overactive and who might now be seen as having schizophrenia, depression, delirium, senility, imbecility and other conditions. Pinel took a stand on the importance of science in medicine, and was the first to call for an Evidence Based Medicine. Faced with patients hospitalized for years, he was the first to incorporate the course of a patients’ disorders into his diagnostic considerations. He recorded outcomes where patients were treated or left untreated, and noting responses followed by relapses, argued that some disorders were periodic or recurrent and that the vast majority of available treatments made the underlying condition worse. When a final and more complete version of his treatise was published in 1809, it distinguished in its title, Trait
e M
edico-Philosophique sur l’Ali
enation Mentale ou la Manie, between insanity in general and a new, more specific diagnosis of mania [1]. Once this distinction was made, and mania was separated out from idiocy dementia and melancholia, the rates of admission for mania settled at approximately 50% of all admissions in asylums in Europe and America until around 1900. While asylum nomenclature remained relatively constant for a century, there was an evolution in the thinking about insanity. The idea that there might be a distinct mood faculty that could be disordered in its own right was put forward in

Bipolar Disorder: Clinical and Neurobiological Foundations Edited by Lakshmi N. Yatham and Mario Maj © 2010 John Wiley & Sons, Ltd. ISBN: 978-0-470-72198-8

the 1830s by one of Pinel’s pupils, Jean-Dominique Etienne Esquirol, who described profound sadness – lypemanie – as a distinct disorder. The notion of a disease entity took shape in the 1850s when two of Esquirol’s pupils, Jean-Pierre Falret and Jules Baillarger, both described disorders that laid the basis for what became circular insanity. Falret outlined folie circulaire; Baillarger termed his disorder folie a double forme [2]. The idea that mania or insanity might give rise to protean manifestations had posed little difficulty, but as clinicians moved towards the concept of a disease entity, they had difficulties with the idea that two clinical states that looked so different might be presentations of the same underlying disease state. In their efforts to overcome these conceptual problems, both Falret and Baillarger posited a disorder with alternating cycles of mania and melancholia of fixed length and with fixed intervals between episodes. But crucially if neither the superficial features of mania nor the superficial features of melancholia accounted for the disorder, then some common ground between them must be responsible for the disorder. Some substrate must be diseased. The new disorder was not one that commanded clinical attention. Both men conceded that what they were describing was a rare condition. The condition described was moreover at this point not clearly a mood disorder. Others described alternating or circular insanity. None of these states were bipolar affective disorder, as that term would be understood today. The first to approach modern bipolar disorder was Karl Kahlbaum who in 1883 described cyclothymia. Where circular insanity was a psychotic disorder, with regular and stable features that led to degeneration, cyclothymia was for Kahlbaum a specific mood disorder from which patients could recover. Kahlbaum also introduced disease course as a classificatory principle, but this was resisted. Most academics at the time expected a localization of clinical features in different brain areas to provide the key to unlocking the mysteries of mental illness rather than disease course. However disease course was used by Charcot to distinguish between hysteria and Tourette’s syndrome, and later to distinguish between Alzheimer’s and Creutfeld-Jacob disease. 1

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Manic-depressive illness In 1899, building on a series of syndromes first outlined by Kahlbaum, and on his principle of disease course, but eschewing brain localization, Emil Kraepelin distinguished between two disease entities – dementia praecox and manicdepressive insanity [3]. Dementia praecox was a disorder of cognitive function where the sufferer never returns to normal. Within this group, Kraepelin included three disorders outlined by Kahlbaum – hebephrenia, catatonia and paranoia. Given that clinical course was to be the main determinant of disease status, if in the one case recovery was to be the exception, there had to be a contrasting state in which recovery was the norm. Manic-depressive illness therefore emerged as the foil to dementia praecox. Kraepelin’s manicdepressive illness was a disorder where sufferers recovered from acute episodes but were at risk of a relapse. For Kraepelin, a bipolar alternation between excitement and stupor could not be a classificatory principle in that a similar alternation happens in many states of dementia praecox or general paralysis of the insane. But periodic, circular and simple manias, in addition to melancholic disorders, could all be regarded as manifestations of the one illness if they showed a remitting course. Involutional melancholia brings out the rigidity with which Kraepelin held to a disease course criterion. These classic depressive psychoses had their onset over the age of 50, when patients typically presented with disturbed sleep and appetite, diurnal variation of mood and either paranoid, nihilistic or guilt-laden delusions. In 1899 Kraepelin thought that these patients were much less likely to recover than other patients with mood disorders. Clinicians now would have no doubt that this condition was a mood disorder. However, because involutional melancholia apparently failed to remit, it posed difficulties for Kraepelin. As a result, he kept involutional melancholia separate from manic-depressive illness until the eighth edition of his textbook. Kraepelin’s distinctions between two almost identical clinical presentations (involutional and non-involutional melancholias) and amalgamation of what appeared to be quite different clinical presentations (unipolar and bipolar affective disorders) produced an illness concept that almost certainly baffled many of his contemporaries. The puerperal psychoses further clouded the diagnostic picture. Kraepelin’s compelling descriptions of a characteristic confusion and fleeting hallucinatory features in these psychoses, as well as their unstable cycling states, made a good case for a separate diagnosis to either dementia praecox or manic-depressive illness. But his disease course criterion left him no option but to argue that they were in all cases either manic-depressive insanity or dementia praecox.

Between these puerperal psychoses and good prognosis psychoses with cycloid features, there was a group of patients accounting for close to 10% of admissions for serious mental illness, double the number of admissions for bipolar affective disorder, but these all disappeared from view, because polarity did not count for Kraepelin as a classificatory principle.

The reception of manic-depressive illness – the academic response When Kraepelin’s work was discussed both within and outside of Germany, it was largely in terms of dementia praecox. For a quarter of a century, there was little mention of manic-depressive illness. In America, Kraepelin’s clinical approach was welcomed by Adolf Meyer as the breakthrough psychiatry was waiting for, although he later criticized it as being too neurological, and failing to place the patient’s disorder within the context of their life story. In Britain, there were regular references to Kraepelin’s work at psychiatric meetings and in the academic literature, in a way that did not happen with other German formulations [4]. These references were to dementia praecox; some disliked the term dementia and some disliked praecox, but the concept was widely discussed, whereas manicdepressive illness was rarely raised. The French did not accept that all psychotic disorders had the same degenerative clinical course, distinguishing instead between acute and chronic psychoses and amongst a variety of chronic non-deteriorating psychoses. The discovery of chlorpromazine in France validated traditional distinctions between the chronic psychoses and schizophrenia, on the basis that schizophrenia was poorly responsive to antipsychotics [5]. Nevertheless, from 1900, dementia praecox swept rapidly into use for a number of reasons. First, many psychiatrists had been struggling with the same issues and had come up with variants of the same idea from primary dementia to adolescent insanity. Kraepelin’s formulation balanced simplicity and complexity. It was more complex than simply adolescent insanity but much simpler than making distinctions amongst the chronic psychoses, as the French and Kahlbaum had done. Second, before 1900, diagnoses across medicine were made on the basis of the visible presentations of patients at admission, giving rise to diagnoses of consumption, ague, debility or mania. These diagnoses were essentially descriptions of the presenting problem. Following the triumph of bacteriology, after 1900 there was a move to defer diagnoses to later in the course of the admission, after the appropriate laboratory tests had been done and there had been more time to consider which, amongst a number of differential diagnoses, best accounted for the features of the illness. This

From Mania to Bipolar Disorder

The reception of manic-depressive illness: a typical asylum The North Wales Asylum, which opened in 1848, offers an opportunity to look at the uptake of concepts like Kraepelin’s. In North West Wales, the overall population and ethnic mix was almost precisely the same in 2000 as it had been in 1900. Elsewhere, because of geography and rising wealth, a growing number of people had a choice of hospitals. Because of this choice, it is difficult to know how representative patients, ending up in the public or private asylums across the Western world between 1800 and 1950, were of the mental illness happening in their communities of origin. In North West Wales, because of enduring poverty and geography, those with mental illnesses had nowhere to go except to one asylum. The resulting asylum records and case registers for modern admissions shed light on a number of issues. The first is the impact of Kraepelin’s diagnoses of dementia praecox and manic-depressive illness on clinical practice within Britain. The second set of issues has to do with quantitative aspects of the syndromes underpinning Kraepelin’s diagnoses. The first thing that strikes any reader of the asylum records is that up until 1900 over 50% of patients admitted apparently had mania (Figure 1). As late as 1900, patients who were suicidal, patients with senility, and patients with what now would be called schizophrenia, were all labelled as manic. However, manic-depressive illness was not dramatically more common 100 years ago than it is now. The

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The Diagnosis of Mania as a Percentage of all Admissions to the North Wales Asylum: 1875-1924 60 50 40 30 20 10 0 20

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95

00

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85

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applied also to psychiatry, so that from 1900 diagnoses were less likely to be made on admission, bringing the likely chronicity of a patient’s illness to the fore as a diagnostic feature. The time was convenient for Kraepelin’s new ideas. In contrast, while there were many formulations of early onset dementia, Kraepelin’s manic-depressive illness concept was quite idiosyncratic. The new illness also introduced a new nomenclature. Why manic-depressive illness? Why not manic-melancholic disease, given that almost all the ‘depressions’ Kraepelin was faced with were melancholic in terms of their severity and clinical features? The answer may lie in a quirk in the man – he had a partiality for novelty. Melancholia was an old-fashioned word. Depression was creeping into use. The first major paper on depressive illness had come a few years earlier, in 1886, from the Danish neurologist Carl Lange [6]. When it came to manic-depressive insanity, Kraepelin’s concept may have ultimately survived, because he had picked a name that worked. Names as well as concepts have survival value. But it took a quarter of a century for the new illness to achieve recognition, as data from North Wales indicates.

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Fig. 1 The diagnosis of mania as a percentage of all admissions to the North Wales Asylum: 1875–1924.

explanation for this finding is, as outlined above, that a diagnosis of mania referred to any state of overactive insanity. Around 1900, primarily in response to Kraepelin’s impact, the use of mania as a diagnosis in North Wales began to fall, and it fell progressively to the current rate of less than 5% of patients. Two questions arise. First, when do modern diagnoses emerge in the records and, second, how many manics had what would now be diagnosed as having in fact bipolar affective disorder? The contrasting reception of dementia praecox and manic-depressive illness helps bring these points out and can be seen in the cases of Bessie Hughes and William Thomas. Bessie Hughes was a 17-year-old girl admitted on 16 October 1905 with hebephrenic and catatonic features. She was noted to be a good case of dementia praecox. The records indicate that up until then a case like Bessie’s would have been diagnosed as melancholia with stupor. The term dementia praecox thereafter rapidly came into use in North Wales, and was not replaced by schizophrenia in these records before 1949. In contrast, William Thomas had been admitted in 1891 at the age of 45, having been looked after at home by his family for a number of years. A businessman, who had travelled back and forth between Wales and Argentina, his family wondered if his first breakdown 17 years previously, from which he had recovered at home, had stemmed from an engagement to a Catholic woman, or whether it had been triggered by the general alarum that had accompanied an outbreak of Yellow Fever. He had recovered and continued working until his early 40s, when his family committed him to the asylum where he remained until his death. On admission, in contrast to most patients, he seemed far from manic in the sense of agitated or overactive. After some days, grandiosity and probable delusional beliefs became apparent. Periods of elation alternated with mute and almost catatonic states, and he settled down to a cycle of episodes of depression, followed by overactivity and periods of lucidity. In 1904, 13 years after admission, the notes

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indicate that his alternating states were being viewed as circular insanity. The reference to circular insanity is the first of its kind in these records, but the overall diagnosis remained mania and never became manic-depressive illness. In 1906, a national conference on the classification of insanity in Britain introduced a new set of diagnoses. This system proposed a new disorder, primary dementia, which was the equivalent of Kraepelin’s dementia praecox. The new national classification system subdivided mania and melancholia into recent, chronic and recurrent mania or melancholia, and introduced the term alternating insanity. None of these terms were used in North Wales but dementia praecox was and it was this that led to the fall in the frequency of diagnoses of mania. Within the affective disorders domain, RO, who was admitted in 1908 and discharged in 1909, was diagnosed with maniacal depressive insanity – a disorder not on the list. In fact, this odd use of words was a better description of his case than a diagnosis of manic-depressive insanity would suggest, in that he only presented on one occasion, showing features of agitated (or maniacal) depression without any alternation of mood. Despite the example of RO, except for clearcut cases of dementia praecox, other cases continued to be diagnosed as having mania or melancholia rather than alternating insanity or manic-depressive illness. It was not until the 1920s that we begin to find diagnoses of manic-depressive illness appearing. In September 1920, a 30-year-old sailor, RP, was admitted with grandiose beliefs and violent behaviour. He remained in hospital for over a year, during which time he had attacks of agitation at regular intervals. On discharge he was diagnosed as manic-depressive. This man was readmitted two years later and spent most of the following 15 years as an inmate of the asylum, during which time he was noted to have a clinical state that alternated from manic to depressive poles on a one month cycle. The diagnosis only came into regular use in 1924. In that year, three cases were diagnosed as manic-depressive. One was AA, whose records from 1924 outline a 60-year-old woman who had two admissions for what would now be diagnosed as psychotic depression – no hint of mania. ER, also admitted and diagnosed in 1924 as manic-depressive, had a postpartum psychosis. In 1924, WH had her tenth admission, and during this admission she was diagnosed as manic-depressive. There had been nine previous admissions starting from May 1900, mostly for mania, none of which led to this diagnosis. Later in the 1920s, the pattern of taking previous episodes into account takes hold, and also a willingness to make the diagnosis if the person during the course of one admission has distinct spells of elevated and depressed moods. In addition to mirroring the wider resistance to Kraepelin’s concept of manic-depressive illness, the asylum

records reveal a quantitative factor to this resistance. During the historical period 1875–1924, there were 3872 admissions from North West Wales. These came from 3172 patients. Amongst patients admitted for the first time during the 1875–1924 period, only 127 (4%) had what retrospectively appears to be a bipolar disorder. Against the background population of North West Wales, this rate of admission gives rise to 10 cases per million per year, a rate that remained constant across the 50-year period, and continues to hold true today [2,7]. In contrast, there were 1041 patients with non-affective psychoses, who between them had 1304 admissions, and 658 admissions from 568 individuals for severe depression or melancholia. These melancholias account for 17% of all admissions and over 80% of the manic-depressive cohort. Without inclusion in a larger manic-depressive group, bipolar patients would have been close to invisible, and this may have been a factor that led Kraepelin to collapse these disorders into one entity. From this perspective, it is clear why concepts such as folie circulaire, folie a double forme or alternating insanity were simply not used in a working asylum like Denbigh before 1900. Too few patients were involved. The viability of the modern concept of a bipolar affective disorder depends critically on the diagnosis of hypomanic or cyclothymic states in the community. Of the patients with retrospective bipolar diagnoses admitted to the North Wales Asylum, 60% were female, compared to the 66% Kraepelin reported. The average age of first admission was 32 years old, with the youngest admission being for a 17 year old. The average length of stay in hospital for any one episode was 6 months. Almost all patients went home well, with only a very small proportion having continuous fluctuations in clinical state that precluded discharge. This group of 127 patients had 345 admissions and on average each person had 4 admissions every 10 years. Today the district general hospital unit serving the same area has a slightly higher proportion of female admissions. The average age of first admission is 31 years old. The average length of stay is a month. But bipolar patients have 6.5 admissions every 10 years. There is therefore a substantial increase in admission prevalence [7]. In the 1875–1924 cohort, 80% of the admissions for bipolar disorder were for manic presentations. Today, over 50% of the admissions from bipolar patients are for depression. Thus either the presentation of the illness is changing, or treatment is having an impact on presentations, or we have a greater sensitivity to episodes of depression that would formerly not have led to admission. The records also shed light on involutional melancholia. When patients with melancholia admitted to North Wales Asylum between 1875 and 1924 were tracked for length of stay and rates of recovery, broken down by age, one

From Mania to Bipolar Disorder

might have expected, if Kraepelin was right, that those who had an episode of melancholia in their 50s and 60s would have much longer lengths of stay and a much lower rate of recovery. Also patients with melancholia in their 50s and 60s had a somewhat lower rate of recovery, but this was in fact governed by the greater likelihood that they would die in hospital from physical illness. The length of stay of those patients who did not die in hospital was the same as those who had an onset of the disorder earlier in life. Overall patients admitted in their 30s or 40s were 1.2 times more likely to recover than patients admitted in their 50s or 60s, hardly the behaviour of a distinct disorder [8]. Between 1875 and 1924, puerperal psychoses accounted for close to 10% of admissions of women of childbearing years and 3% of admissions overall (Table 1). This disorder was as common as bipolar affective disorder. Two different sets of women were admitted with postpartum psychoses. The larger of the two sets were women who had no mental illness prior to the postpartum period. A smaller group (20%) were women with a prior mental illness [9]. In the modern period, psychoses with a first onset in the postpartum period in North West Wales have all but vanished, while the incidence of postpartum psychoses in women with a pre-existing mental illness remains the same. Data from across Europe support these findings. If so, this would support claims that these disorders are distinct from other disorders. Alternately, if regarded as affective disorders, establishing the basis for the apparent decline in frequency of these disorders may have implications for other affective disorders.

Table 1 The incidence of postpartum psychoses in North West Wales: 1875–1924 vs. 1994–2005.

All Female Admissions All Women All Women of Child-Bearing Age All Postpartum Psychotic Admissions All Women with Postpartum Psychoses Women with no prior Mental Illness Women with Prior Mental Illness Postpartum Cases/All Admissions from Women of Child-Bearing Age All Postpartum Cases/1000 Births Postpartum Onset Cases/1000 Births All Postpartum Cases/100 000 Childbearing Yrs Postpartum Onset Cases/100 000 Childbearing Yrs

1875–1924

1994–2005

1946 1577 1100 103 101 80 21 9.2%

3956 1827 1032 7 7 1 6 0.68%

0.34 0.26 3.43

0.19 0.03 0.94

2.70

0.13

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The emergence of bipolar disorder A new chapter in the affective disorder story opened up in the psychotropic era. By this time, Manic-Depressive Illness had become a stable and accepted category, and anomalies such as calling someone who only ever had depressive episodes manic-depressive no longer registered. Two factors brought about a change. First, in 1954, Mogens Schou demonstrated that manic states responded to lithium. Second, in 1957, Karl Leonhard distinguished amongst affective disorders on the basis of polarity, separating manic-depressive illness from pure melancholia and pure depression. Several prominent European and American researchers picked up his lead. The effect of lithium appeared both to endorse the existence of a bipolar subgroup within manic-depressive illness, and put a premium on the diagnosis of a mood disorder rather than a psychotic disorder. Combined, these developments underpinned the emergence of bipolar disorder in the mid-1960s and its incorporation into DSM III in 1980. DSM III was badged as a neo-Kraepelinian revolution in psychiatry. As of 1980, bipolar disorder was still embedded within the affective disorders, of which depression was the most important. The research focus was on distinguishing between subtypes of depression so that biological markers might be discovered. The failure to discover such markers was widely attributed to the heterogeneity of the samples being studied and this had led to proposals to distinguish between neurotic and psychotic, primary and secondary, reactive and endogenous depressions and other distinctions including bipolar and unipolar depression. In the early 1970s, the bipolar/unipolar dichotomy looked amongst the less fruitful avenues of research, in that clinically there was less to distinguish bipolar and unipolar depression, for instance from neurotic and psychotic depressions or endogenous and reactive depressions. As of 1980, the effects of pharmacological and biological dissection of nervous disorders seemed more likely to lead to distinctions between ever smaller groups of disorders rather than the reverse. Lithium, for instance, seemed only helpful for a proportion of either manic-depressive or bipolar patients. In the decade from 1980 to the mid-1990s, manicdepressive illness and bipolar disorder co-existed, with Goodwin and Jamison’s 1990 monograph on the illness still entitled Manic-Depressive Illness [10]. It was only in 1992, with ICD 10, that the term bipolar disorder spread beyond America. But with the launch of Depakote as a moodstabilizer in 1995, the bipolar offspring ate its manicdepressive parent. The term mood-stabilizer essentially had not existed before 1995. Sedatives had been widely used to manage manic patients prior to that, but demonstrating a sedative effect in mania is quite different to showing a drug is

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prophylactic for bipolar disorder. Depakote was licensed for the treatment of mania but its adverts claimed it was a mood-stabilizer. Had Abbott said Depakote was prophylactic, they would have broken the law, as it had not been shown to be prophylactic but the term mood-stabilizer had no precise meaning. It suggested prophylaxis and this suggestion led to the use of Depakote and other anticonvulsants for maintenance purposes, despite a failure in controlled trials to demonstrate these agents are prophylactic. Bipolar disorder, in my view, has become more a brand than a well-grounded scientific term – as successful a brand as the creation of the terms tranquilizer and SSRI. A brand is something whose value lies in the perception of a consumer rather than in a tangible benefit. Where there had been almost no uses of the term mood-stabilizer before 1995, by 2000 there were over 100 articles per year featuring this term in their titles. The dramatic and rapid switch from Manic-Depressive Illness to Bipolar Disorder in the mid-1990s took place in the absence of any clinical or research facts to underpin the switch. The term bipolar disorder is rarely found in the titles of articles listed in Medline before 1992, but its use rapidly escalates from 1995 to reach 500 articles per year by 2005, while the term manic-depressive vanished. Estimates of the frequency of bipolar disorder in the population soared to a 100-fold compared with figures for admissions to the North Wales Asylum in the period from 1875 to 1924. The possibilities offered by ‘mood-stabilization’ and ‘bipolar disorder’ led companies producing second generation antipsychotics into the market, greatly expanding the use of these terms. Bipolar affective disorder is unquestionably a distinct clinical type; this does not mean it is necessarily a distinct disease entity. We still do not know enough about the bases for any remitting disorders to carve nature definitively at its joints in these domains. Many clinicians and scientists associate history with postmodernism, an all but psychiatric disorder in its own right, where academics refuse to concede there is any reality to human behaviours, or to the physical underpinnings of disorders of human behaviour. That which scientists regard as hard data or even facts, post-modernists treat as texts to be interpreted and re-interpreted without external constraint. The analysis of Kraepelin’s concept of manic-depressive illness outlined above demonstrates how complex his concept was, and how open to revision, but it also makes clear that clinical realities were once the primary determinant of clinical concepts. Concepts arose from the clinical material. In contrast, the post-modernism at which the marketing departments of pharmaceutical companies excel think nothing of shaping the clinical material to fit a marketing concept.

In the decade from 2000, all of the companies producing antipsychotics have targeted bipolar disorder as a means to enhance sales. The companies have recognised that to do this the attitudes of primary care physicians would have to change. Market research had shown that these doctors were reluctant to use antipsychotics, but they could be reeducated to the possibilities of mood-stabilizers. These were doctors who thought that bipolar disorder was a severe mental illness comparable to schizophrenia whose treatment appropriately was either in secondary care rather than primary care – they would need to be re-educated to recognise that many of the anxious and depressed patients going through their practices could be re-conceptualized as having bipolar disorder. These points are illustrated using the documents in the public domain from litigation involving Zyprexa, but a similar scenario applies to other drugs in the group. Thus: ‘As the current market leader in primary care, Zyprexa will continue to revolutionize the way complicated mood disorders are treated by primary care physicians. Just as Prozac revolutionized the treatment of depression in the late 1980s and throughout the 1990s, so too will Zyprexa forever change the way primary care physicians view and treat bipolar disorder’ [11]: The facts: up to 30% of patients with a diagnosis of depression or anxiety may actually have bipolar disorder [12].

Scenarios like Donna’s have been put forward as typical: ‘Donna is a single mom, in her mid-30s appearing in your office in drab clothing and seeming somewhat ill at ease. Her chief complaint is “I feel so anxious and irritable lately”. Today she says she has been sleeping more than usual and has trouble concentrating at work and at home. However, several appointments earlier she was talkative, elated, and reported little need for sleep. You have treated her with various medications including antidepressants with little success. . . You will be able to assure Donna that Zyprexa is safe and that it will help relieve the symptoms she is struggling with’ [13]. There is clearly a nexus of nervous problems that patients endure in the community without ever coming to the attention of mental health services. Company marketers have been adept at framing the symptoms these give rise to in a manner most likely to lead to a script for the remedy of the day. Donna could have featured in adverts for tranquilizers from the 1960s to the 1980s, or for antidepressants in the 1990s, and would have probably been more likely to respond to either of these treatment groups than to an antipsychotic, and less likely to be harmed by them than by an antipsychotic. There have traditionally been difficulties in seeing these conditions simply as anxiety or as depression [14]. But

From Mania to Bipolar Disorder

while bipolar affective disorders probably exist in the community without coming to the attention of the secondary services, it flies in the face of a century of psychiatric thinking to see conditions that patients like Donna have as bipolar disorder. The concept of juvenile bipolar disorder flies even more in the face of a century of psychiatric thinking, but as of 2008, upwards of a million children in the United States, in many cases preschoolers, are on ‘mood-stabilizers’ for bipolar disorder, even though the condition remains unrecognized in the rest of the world [2]. While this was happening, the cycloid disorders, which provided sound clinical grounds to unpick or go beyond the Kraepelinian synthesis, remained neglected. Instead, in a return to a pre-Kraepelinian psychiatry, company marketing departments have used a template of a supposedly neo-Kraepelinian medical science to promote a form of bipolar disorder based more on the visible presentations of patients rather than on any valid classificatory basis. This new disorder would have been unrecognizable to Kraepelin, whose tombstone bears an inscription – ‘your name may vanish but your work remains’ – that has become ironic.

References 1. Pinel, P. (1809/2008) Medico-Philosophical Treatise on Mental Alienation (Trans G. Hickish, D., Healyand L.C.C. Charland), Wiley-Blackwell, Chichester. 2. Healy, D. (2008) Mania, in A Short History of Bipolar Disorder, Johns Hopkins University Press, Baltimore.

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3. Kraepelin, E. (1899) Psychiatrie, in Ein Lehrbuch f€ ur Studirende und Aertze. Barth, Leipzig (Translation S. Ayed), (1960), Science History Publications, Canton MA, p. 272. 4. Ion, R.M.and Beer, M.D. (2002) The British reaction to dementia praecox 1893–1913, part 1. Hist. Psychiatr., 13, 285–304, Part 2, 13, 419–432. 5. Pichot, P. (1982) The diagnosis and classification of mental disorders in French-speaking countries. Psychol. Med., 12, 475–492. 6. Lange, C.G. (1886) Om Periodiske Depressionstilstande, Jakob Lunds, Copenhagen. 7. Harris, M., Chandran, S., Chakroborty, N.and Healy, D. (2005) Service utilization in bipolar disorder, 1890 and 1990 compared. Hist. Psychiatry, 16, 423–434. 8. Farquhar, F., Le Noury, J., Tschinkel, S. et al. (2007) The incidence and prevalence of manic-melancholic syndromes in North West Wales: 1875–2005. Acta Psych. Scand, 115 (Suppl 433), 37–43. 9. Tschinkel, S., Harris, M., Le Noury, J.and Healy, D. (2007) postpartum psychosis: two cohorts compared, 1875–1924 & 1994–2005. Psychol. Med., 37, 529–536. doi: 10/1017/ S0033291706009202 10. Goodwin, F.K. and Jamison, K.R. (1990) Manic Depressive Illness, Oxford University Press, New York. 11. Zyprexa. Primary Care Sales Force Resource Guide (2002) Zyprexa MDL 1596, Plaintiffs’ Exhibit 01926, page 3. 12. Zyprexa. Primary Care Sales Force Resource Guide (2002) Zyprexa MDL 1596, Plaintiffs’ Exhibit 01926, page 6. 13. Zyprexa. Primary Care Sales Force Resource Guide (2002) Zyprexa MDL 1596, Plaintiffs’ Exhibit 01926, page 7. 14. Shorter, E. and Tyrer, P. (2003) Separation of anxiety and depressive disorders: blind alley in psychopharmacology and classification of disease. Br. Med. J., 327, 158–160.

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Clinical Features and Subtypes of Bipolar Disorder Fred K. Goodwin1 and D.Z. Lieberman2 1

Department of Psychiatry and Behavioral Sciences, Center on Neuroscience, Medical Progress, and Society, George Washington University Medical Center, Washington, DC, USA 2 Department of Psychiatry and Behavioral Sciences, George Washington University Medical Center, Washington, DC, USA

Introduction: the phenomenology of cyclicity and polarity The origins of the bipolar illness concept have been reviewed in the previous chapter by David Healy. Nevertheless, before discussing the clinical features and subtypes of bipolar disorder, it is worth reiterating a few salient points concerning the evolution of the bipolar illness construct. Kraepelin’s unitary concept of manic-depressive illness included all recurrent mood disorders, which were differentiated from dementia praecox by a family history of mood disorders, the episodic nature of the patient’s illness, and the relatively benign course and outcome. In 1957 Leonhard observed that manic-depressive patients with a history of mania (whom he termed bipolar) had a higher incidence of mania in their families as compared with those with recurrent depressions only (whom he termed monopolar) [1], a distinction that was validated by the extensive family history studies in the 1960s by Perris, and independently by Angst [2]. The bipolar–unipolar distinction was formally incorporated into the American diagnostic system, DSM. In 1980, the third edition (DSM-III) was subsequently carried forward into DSM-IV, and became explicit in the international classification system in ICD-10. Unfortunately, the structure of DSM-IV (see Figure 1), which breaks out bipolar disorder as a separate illness distinct from all other mood disorders (i.e. from the depressive disorders) obscures the fact that originally the bipolar–unipolar distinction was conceived of as a way to distinguish two forms of a recurrent illness. In other words, the DSM structure gives precedence to polarity over cyclicity, obscuring the reality that one rather common variant of unipolar illness is as recurrent or cyclic as bipolar illness. Furthermore, DSM-IV really has no language for the unipolar patient with frequent recurrences, since its ‘recurrent’ category is so broad as to include patients with only two depressions in a lifetime, comprising at least 80% of all patients with major depression (Figure 2).

Because cyclicity in DSM-IV-TR is largely restricted to the bipolar category, there is a tendency to include highly cyclic forms of unipolar depression within a ‘bipolar spectrum’. While common features can be observed amongst patients with diverse cyclic mood disorders, broadening the definition of ‘bipolar disorder’ to such a large degree may weaken the core concept of bipolar disorder. It may also de-emphasize some of the important clinical differences between unipolar and bipolar patients. For example, one proposed definition of bipolar spectrum disorder includes recurrent unipolar patients with an early onset of illness who have a family history of bipolar disorder in a first-degree relative [3]. This definition moves beyond the clinical phenomenology of bipolar disorder to a definition based on presumptive genetic vulnerability to elevated mood states.

Clinical features of affective episodes Under the current system, the diagnosis of bipolar disorder is based on symptom presentation and the natural course of the illness. Although progress has been made in advancing our understanding of the neurobiology and genetics of bipolar disorder, we are far from being able to validate the diagnosis and sharpen its boundaries by reference to an identified aetiologic agent or a characteristic pathophysiological abnormality. There are significant challenges associated with using symptoms as a basis for diagnosis. Some patients’ symptoms may correspond well with published diagnostic criteria, while others are more ambiguous. Over time, debate about what constitutes the core clinical features of mood episodes has been reflected in changing diagnostic criteria in the DSM and ICD. This debate is more than an academic exercise. Because diagnosis guides treatment decisions as well as the composition of research samples, the content of the diagnostic criteria has a profound impact on patient care, as well as on our ability to advance neurobiological and genetic research on mood disorders.

Mania Bipolar Disorder: Clinical and Neurobiological Foundations Edited by Lakshmi N. Yatham and Mario Maj © 2010 John Wiley & Sons, Ltd. ISBN: 978-0-470-72198-8

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Mania represents the primary defining feature of bipolar disorder. Although primary emphasis has been placed on

Clinical Features and Subtypes

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The Diagnosis of Mania as a Percentage of all Admissions to the North Wales Asylum: 1875-1924 60 50 40 30 20 10 0 20

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Fig. 1 DSM-IV classification of mood disorders. Note: NOS ¼ not otherwise specified. Reprinted with permission from Goodwin FK, Jamison KR: Manic Depressive Illness: Bipolar Disorders and Recurrent Depression. New York, NY, Oxford University Press, 2007.

the elevation of mood, Kraepelin described activation of motoric and cognitive processes that can be the more predominant features in some patients. For example, there has been an increasing appreciation for the role of irritability in the absence of euphoria [4]. Accordingly, DSM-IV-TR allows elevated, expansive or irritable mood in the core criterion A of the diagnostic definition (Box 1). While elevated mood is a fairly specific symptom of mania and hypomania, irritability can be more ambiguous because it

is also commonly seen in bipolar depressive episodes [5] and major depressive disorder [6]. Irritability can be defined as extreme reactions to relatively minute stimuli [7], or as a low threshold for experiencing anger in response to negative emotional events [8]. Irritability is particularly prominent in paediatric bipolar disorder, although lacking in specificity [8]. Thus in children irritability is present in a number of common diagnoses including attention deficit hyperactivity disorder, anxiety disorders, and oppositional

Affective Disorders

Depressive Disorders < 3 Episodes; Onset < age 30

Recurrent (Episodic) Affective Disorders > 3 Episodes; Onset < age 30 (Kraepelin’s manic-depressive illness)

Bipolar

BP-I

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BPNOS

Unipolar

Cyclothymia

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Nonpsychotic

Major Depression

Psychotic

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The Bipolar Spectruma

Fig. 2 Recurrence as the primary organizing feature of the affective disorders. Note: BP ¼ bipolar; NOS ¼ not otherwise specified. Reprinted with permission from Goodwin FK, Jamison KR: Manic Depressive Illness: Bipolar Disorders and Recurrent Depression. New York, NY, Oxford University Press, 2007.

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Chapter 2

Box 1 DSM-IV-TR Definition of a Manic Episode DSM-IV (p. 328) defines a manic episode as follows: Criterion A: A Manic Episode is a distinct period during which there is an abnormally and persistently elevated, expansive or irritable mood. This period of abnormal mood must last at least one week (or less if hospitalization is required). Criterion B: The mood disturbance must be accompanied by at least three additional symptoms from a list that includes inflated self-esteem or grandiosity, decreased need for sleep, pressure of speech, flight of ideas, distractibility, increased involvement in goal-directed activity or psychomotor agitation, and excessive involvement in pleasurable activities with a high potential for painful consequences. If the mood is irritable (rather than elevated or expansive), at least four of the above symptoms must be present. Criterion C: The symptoms do not meet criteria for a mixed episode. Criterion D: The disturbance must be sufficiently severe to cause marked impairment in social or occupational functioning or to require hospitalization, or it is characterized by the presence of psychotic features. Source: Reprinted with permission from the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (Copyright 2000). American Psychiatric Association.

defiant disorder. And, of course, some level of irritability is observed in the course of normal development. Overactivity, defined in the DSM as either increased goal directed activity or psychomotor agitation, is an optional criteria for the diagnosis rather than a core criterion A symptom. A study by Benazzi suggests that overactivity may play a more central role in the diagnosis than the DSMIV-TR organization implies [9]. In a sample of 213 patients, focusing the probing for history of hypomania on overactivity in addition to mood change reduced false-negatives for a bipolar II diagnosis. Using Angst’s diagnostic criteria for hypomania [10], which emphasizes overactivity rather than simply elevated mood, and comparing the results to the Structured Clinical Interview for DSM-IV, no significant differences were found between the two samples on age, gender, symptom structure of hypomania, number of episodes, episodes duration and level of functioning. Compared to elevated mood, overactive behaviour may be less vulnerable to the cognitive distortions associated with loss of insight that occurs during manic and hypomanic episodes, and therefore easier for patients to identify. The kind of psychomotor activation which is stereotyped, repetitive and purposeless, such as pacing and fidgeting (i.e. agitation) is, unfortunately, conflated with increased goal directed activity in DSM-IV-TR. Psychomotor agitation is also part of the criteria for major depressive disorder, and this overlap may serve to blur the distinction between the activation of mania and that of depression.

In order to meet the criteria for a manic episode, four or five out of nine criteria must be met. It is not necessary to have all of the symptoms listed, and for each individual patient certain symptoms may be more likely than others to accompany a manic episode. Patients may experience a degree of symptom consistency over the course of consecutive episodes. Capitalizing on this tendency, identifying personally relevant early signs of mania or hypomania is a common ingredient in a number of bipolar-specific psychotherapies, including psychoeducation [11], cognitive behavioural therapy [12], family-focused therapy [13] and interpersonal and social rhythm therapy [14]. These early symptoms, of which decreased need for sleep is a common example, may not be especially pathological in and of themselves. However, because they can be consistent and reliable predictors of serious affective decompensation, systematically documenting the nature of the symptoms, and developing a level of vigilance for their emergence, can create an opportunity for early intervention that may prevent an impending manic episode or decrease its severity. Formally evaluating the consistency of symptoms across episodes can be complex. Effects of medications, such as an antidepressant that can induce or heighten agitation, or a benzodiazepine that modulates the decreased need for sleep, may introduce variance. In addition, the timing of the assessment can lead to the presentation of differing symptoms. Carlson and Goodwin found substantial differences in symptomatology based on the stage of mania during which a subject was evaluated [15]. One study that attempted to control for these potentially confounding factors, evaluated 77 subjects during two discrete manic episodes, which occurred an average of two years apart. The authors reported that four symptom factors as well as manic severity were significantly correlated across episodes. The symptom factors were dysphoria, hedonic activation, psychosis and irritable aggression [16]. Psychotic symptoms that occur in the context of a manic episode may have special status as defining a specific subtype of bipolar disorder. Psychosis is generally associated with more severe symptoms of mania and possibly a less favourable long-term course [17]. The McLean-Harvard First-Episode Mania Study found that psychosis was a predictor of mania recurrence [18], and a recent two-year prospective study conducted in 14 European countries found that psychotic symptoms during the initial presentation predicted poor response to treatment, and chronicity of mania [19].

Depression Despite the predominance of depressive symptoms in bipolar disorder, there has been less quantitative study of the clinical features of bipolar depression than is the case for either mania or nonbipolar depression. Although the

Clinical Features and Subtypes

DSM-IV-TR does not distinguish between unipolar and bipolar depression (Box 2), studies that have compared the two generally find differences in the clinical presentations. The most widely replicated findings point to a picture of bipolar I depressed patients as having more mood lability, psychotic features, psychomotor retardation and comorbid substance abuse. In contrast, the typical unipolar patient in these studies had more anxiety, agitation, insomnia, physical complaints, anorexia and weight loss [20]. However, none of the contemporary studies of unipolar-bipolar differences match the samples for number of previous episodes (i.e. for cyclicity) and only a few even match for age of onset. Indeed, Benazzi has found that when unipolar and

Box 2 DSM-IV-TR Definition of a Major Depressive Episode DSM-IV (p. 320) defines a major depressive episode as follows: Criterion A1: The essential feature of a Major Depressive Episode is a period of at least 2 weeks during which there is either depressed mood or the loss of interest or pleasure in nearly all activities. In children and adolescents, the mood may be irritable rather than sad. The individual must also experience at least four additional symptoms drawn from a list that includes changes in appetite or weight, sleep and psychomotor activity; decreased energy; feelings of worthlessness or guilt; difficulty thinking, concentrating or making decisions; or recurrent thoughts of death or suicidal ideation, plans or attempts. To count towards a Major Depressive Episode, a symptom must either be newly present or must have clearly worsened compared with the person’s pre-episode status. The symptoms must persist for most of the day, nearly every day, for at least 2 consecutive weeks. The episode must be accompanied by clinically significant distress or impairment in social, occupational or other important areas of functioning. For some individuals with milder episodes, functioning may appear to be normal, but requires markedly increased effort. The mood in a Major Depressive Episode is often described by the person as depressed, sad, hopeless, discouraged or “down in the dumps”. Criterion A2: Loss of interest or pleasure is nearly always present, at least to some degree. Criterion A3: When appetite changes are severe (in either direction), there may be a significant loss or gain in weight or, in children, a failure to make expected weight gains may be noted. Criterion A4: The most common sleep disturbance associated with a Major Depressive Episode is insomnia. Criterion A5: Psychomotor changes include agitation (e.g. the inability to sit still, pacing, hand-wringing; or pulling or rubbing of the skin, clothing or other objects) or retardation (e.g. slowed speech, thinking and body movements; increased pauses before answering; speech that is decreased in volume, inflection, amount or variety of content, or muteness). Source: Reprinted with permission from the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (Copyright 2000). American Psychiatric Association.

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bipolar samples are matched for age of onset, many of the UP-BP differences disappear [21]. In bipolar II depression, some studies have found more atypical features such as hypersomnia, increased appetite, leaden paralysis and interpersonal rejection sensitivity compared to those with unipolar depression [3,22,23], but typically these studies also fail to control for cyclicity and age of onset. Compared to mania, the cumulative impact of syndromal and subsyndromal depression on role functioning is greater [24]. Thus a long-term study that evaluated bipolar patients over the course of 4 years found functional outcome was correlated with depressive but not manic symptoms [25]. Similarly, resource utilization and direct health care costs have been shown to be highest amongst bipolar depressed patients compared to those who were manic or mixed [26]. The impact of depressive symptoms on functioning is seen even in sub-syndromal presentations. In a study of bipolar patients that excluded patients who currently met the full DSM criteria for any acute mood episode, those with higher Hamilton Depression Rating Scale scores had poorer outcomes as measured by the psychosocial components of the Global Assessment of Functioning Scale [27].

Mixed states of bipolar disorder The DSM-IV-TR criteria for a mixed episode require a patient to meet the full criteria for both a manic episode and a major depressive episode (Box 3). Our knowledge of mixed states is more limited than it is for other manifestations of bipolar disorder because patients experiencing mixed episodes are often excluded from studies. This relative lack of knowledge is unfortunate because mixed states occur frequently. Although estimates vary, in one study, 40% of bipolar I inpatient admissions were for mixed episodes [28]. Mixed episodes may evolve from a depressive episode, a manic episode, or the mixed symptoms may emerge at the same time. Patients may also experience mixed symptoms when a bipolar depression is treated with an antidepressant [29]. However, this would fail to meet the strict criteria because symptoms that occur as a direct consequence of the effect of a substance are excluded by the DSM. A mixed episode may evolve into a major depressive episode, but it is uncommon for a mixed episode to become a pure mania. In an early study, patients who presented with a mixed episode accounted for 31% of 84 outpatients with manicdepressive disorder [30]. The mixed states were not associated with illness severity or cycling, but did correlate with sedative abuse and poor response to treatment. Himmelhoch and associates commented that ‘. . .drug abuse (particularly alcohol and sedatives) alters the clinical presentation of manic-depressive swings, and the impact of

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Chapter 2

Box 3 DSM-IV-TR and ICD-10 Definitions of a Mixed Episode DSM-IV (p. 333) defines a mixed episode as follows: Criterion A: A Mixed Episode is characterized by a period of time (lasting at least 1 week) in which the criteria are met both for a manic episode and for a major depressive episode nearly every day. The individual experiences rapidly alternating moods (sadness, irritability, euphoria) accompanied by symptoms of a manic episode and a major depressive episode. The symptom presentation frequently includes agitation, insomnia, appetite dysregulation, psychotic features and suicidal thinking. Source: Reprinted with permission from the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (Copyright 2000). American Psychiatric Association.

oversedation or withdrawal or both on a “pure” affective state is to make it dysphoric and mixed’. More recently, Goldberg and colleagues, evaluating the long-term effects of substance abuse on the course of bipolar I disorder, also found that substance abuse was more common amongst those who had mixed states [31]. The direction of causality could not be determined from this study. Compared to patients with pure mania, those with mixed mania have been found to have more prior mixed episodes, longer hospitalizations, higher rates of comorbid obsessivecompulsive disorder, and they are more likely to be female [32]. Dilsaver and colleagues found a highly significant difference in suicidality as measured by the Schedule for Affective Disorders and Schizophrenia suicide subscale between patients with pure and mixed mania. Only 1 of 49 manic patients was suicidal, compared to 24 of 44 with mixed mania [33]. One would expect that suicidality in bipolar disorder would be associated with depressed mood. Potential additional risk factors present in a mixed episode include higher levels of energy, impulsivity and irritability. A study of 191 psychiatric inpatients and outpatients confirmed this expectation. Suicidality, as measured by the Scale for Suicidal Ideation, was highest for patients with mixed phase presentations [34]. The Scale for Suicidal Ideation measures various dimensions of suicidality, including self-destructive thoughts or wishes, the extent of the wish to die, the desire to make an actual suicide attempt, and details of any plans. Actual suicide attempts during the index episodes were also measured, and like ideation, attempts were more common in the mixed patients. Suicidality was particularly correlated with hopelessness, which was highest during the mixed phase. It is important to note, however, that suicidality is often a poorly defined construct, and whether it

correlates with or predicts actual suicide is not at all clear. See Chapter 7, Suicide and Bipolar Disorder, for an in-depth discussion of this issue. Some authors have suggested that the DSM-IV-TR definition for a mixed episode is too narrow. Failure to meet the full criteria for a major depressive episode, even by a single symptom, results in a diagnosis of a manic state. However, patients who have prominent sub-syndromal depressive symptoms may differ in clinically important ways from those with pure mania. Consequently, other definitions have been developed. The broadest definition permits the presence of one or more depressive symptoms within a manic episode to be sufficient for diagnosis of a mixed episode [35]. Swann and colleagues, using a broad definition of this nature, found that the depressive symptoms responded poorly to lithium compared to the classic manic symptoms [36]. The depressive manic patients had better outcomes on divalproex. A moderate definition midway between the strict and broad criteria has been proposed, in which a mixed episode would be defined as a full manic presentation with three or more symptoms of depression [37]. Just as limited symptoms of depression can accompany a manic episode, limited symptoms of hypomania may be present during a depressive episode. Although there is no formal DSM-IV-TR category for a patient who is experiencing simultaneous or closely juxtaposed symptoms of depression and hypomania, it appears that it is common. The Stanley Foundation Bipolar Treatment Network prospectively studied more than 900 patients for up to seven years, and evaluated the co-occurrence of depressive and hypomanic symptoms. Amongst all visits in which patients had hypomanic symptoms, 57% met criteria for mixed hypomania defined as Young Mania Rating Scale score of 12 or higher and an Inventory of Depressive Symptomatology–Clinician-Rated Version score of 15 or higher [38]. The specific diagnostic entity, ‘depressive mixed state’, has been defined as a major depressive episode plus three or more intra-episodic hypomanic symptoms (DMX3). In a sample of 151 outpatients with major depressive disorder who were presenting with psychoactive drug-free major depressive episode, 23.1% met the criteria for DMX3 [39]. The presence of DMX3 was significantly associated with variables distinguishing bipolar from strictly defined unipolar disorders: younger age at onset; greater recurrence; more atypical features; more bipolar II family history. A number of reports suggest that the number and severity of depressive symptoms during mania or hypomania is a continuous rather than a modal phenomenon. In a study of 37 outpatients, depending on the threshold used, the prevalence of mixed features during a manic or hypomanic episode rose incrementally from 5–73% [40]. Patients who met one of the threshold criteria during a given episode were no more likely than chance to have a similar symptom

Clinical Features and Subtypes

constellation during a subsequent episode. The authors concluded that dichotomizing mania and mixed episodes based on the presence of a predefined number of depressive symptoms was not supported by the data.

Diagnostic subgroups of bipolar disorder Bipolar I In one version of a mood disorder spectrum, bipolar I disorder is at one end while recurrent unipolar major depressive disorder is at the other end. Characterized by manic or mixed episodes, patients with bipolar I disorder experience the highest levels of severity with respect to elevated mood. The National Comorbidity Survey Replication, a nationally representative survey of mental disorders amongst adults in the United States, estimated a lifetime prevalence of bipolar I disorder of 1.0% [41]. Unlike major depressive disorder, which is twice as prevalent in females, the prevalence of bipolar I disorder was approximately equal for males and females (0.8 and 1.1%, respectively). One gender difference that was noted was that men were more likely than women to be initially manic, but overall, both were more likely to have a first episode characterized by depression. The typical age of onset varied from the teens to early 40s, with a mean value of 18.2 years. Patients with bipolar I disorder experience substantial morbidity and mortality, and tend to function below the level of the general population, even in between episodes when mood is euthymic (see Chapter 8: Neurocognition and Bipolar Disorder). During a two-year follow-up of patients hospitalized for a psychotic affective episode (72.6% bipolar I), almost all of the subjects achieved syndromic recovery by the end of the study. However, functional recovery was 2.6 times less likely than syndromal recovery [42]. Most of those recovering syndromally did not recover functionally by two years. Patients who had an older age of onset of their mood disorder were more likely to experience functional recovery than those who were younger when they experienced their first episode, probably reflecting more cumulative time ill. Episodes of psychosis are common, affecting at some time 75% of patients with bipolar I disorder [43]. Psychotic features are most common in mixed presentations and least common during pure depressive episodes [44]. Patients who experience psychotic episodes may represent a distinct phenotype, and there appears to be genetic overlap between these patients and patients with schizophrenia (see Chapter 12: Genetics of Bipolar Disorder).

Bipolar II Bipolar II disorder, first described by Dunner, Gershon and Goodwin [45], is characterized by at least one major depres-

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sive episode with one or more hypomanic episodes, as opposed to the manic or mixed episodes seen in bipolar I disorder. As discussed in the section on hypomania, the criteria are essentially the same as for mania; however, the manifestations are less severe. Patients diagnosed with hypomania do not require hospitalization, are not psychotic, and do not experience marked impairment in social or occupational functioning. Bipolar II disorder is described in DSM-IV-TR, but not in ICD-10. DSM-IV-TR requires hypomanic episodes to last a minimum of 4 days. This durational criterion is largely arbitrary and may not represent the best choice. Reducing the duration to two days increases the sensitivity of diagnosis, and a recent study found no differences in characteristics of patients with bipolar II disorder, whether the two or four day duration was used [46]. Using the two-day minimum duration adequately distinguishes bipolar II patients from those with major depressive disorder based on external validators such as family history and course of illness [47]. Using the more restrictive DSM-IV criteria, the National Comorbidity Survey Replication study estimated that the lifetime prevalence of bipolar II disorder was 1.1%; approximately equal to bipolar I disorder, which was 1% [41] (See Chapter 6: Epidemiology of Bipolar Disorder). The Zurich Study found an additional 2.8% of patients who experienced brief hypomania [48]. In one sample, patients with bipolar II disorder (diagnosed using the two-day duration criterion) comprised approximately half of patients who presented for treatment with a major depressive episode [49]. Bipolar II disorder is sometimes viewed as a milder form of bipolar disorder. However, the cumulative effect of the illness is no less severe than bipolar I disorder. Although mania is characterized by greater symptom intensity than hypomania, bipolar II disorder has a more chronic course, and is associated with greater episode frequency, comorbidity, suicidal behaviour [50], and more time spent depressed [51]. Bipolar II disorder can be difficult to recognize because by definition hypomanic episodes do not cause marked functional impairment. Patients may not identify episodes of hypomania as pathological, or view them as related to episodes of depression. Alternatively, episodes may manifest as brief periods of irritability and agitation, which may not be easily recognized as hypomania. As a result, misdiagnosis is common, especially when a clinician fails to include a member of the family in the intake diagnostic evaluation process. A chart review of 85 patients found that bipolar disorder was misdiagnosed as unipolar depression in 37% of patients who first saw a mental health professional after their first episode of elevated mood [52]. A inpatient study found a similar result. Bipolar disorder was misdiagnosed as unipolar depression in 40% of patients [53]. Family and genetic data suggest that there is a true separation of bipolar I and II into separate categories, as

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Chapter 2

opposed to a more continuous spectrum. Bipolar II disorder clusters within families, and appears to ‘breed true’, as evidenced by the finding that bipolar II patients have more bipolar II and unipolar relatives, and fewer bipolar I relatives compared to patients with bipolar I [54,55]. Bipolar II disorder also appears to be phenomenologically stable. In a 10-year follow-up study, only 7.5% of a sample of patients with bipolar II disorder experienced a full manic episode, compared to 66.4% of patients with bipolar I disorder [56]. By far the predominant polarity of bipolar II disorder is depression. A prospective study of the natural history of the weekly symptomatic status of bipolar II patients conducted over more than 10 years found that during times when patients experienced mood symptoms, depression was 39 times more common than hypomania (50.3% vs. 1.3%). Overall, patients were symptomatically ill 53.9% of the weeks studied [46]. A similar result was seen in patients with bipolar I disorder; however the imbalance between symptoms of depression and symptoms of mania or hypomania was not as great. That is, bipolar I patients were symptomatic 47.3% of the weeks, and depressive symptoms were 3.6 times more common than manic/hypomanic symptoms [57]. The greater predominance of depression in bipolar II disorder may contribute to the higher rates of suicidal behaviour seen in this illness. A study of psychiatric inpatients found that a prior history of a suicide attempt and suicide after discharge were more frequent amongst bipolar II patients compared to those with bipolar I disorder [45]. Similar results have been found with outpatients [58] although not all studies agree.

Cyclothymia Cyclothymia, like bipolar II disorder, is characterized by attenuated severity of symptoms in the context of a high degree of chronicity. Patients with cyclothymia experience numerous periods with hypomanic symptoms and periods with depressed symptoms that do not meet the full criteria for a major depressive disorder. Emphasizing chronicity, the diagnostic criteria require that patients are not symptom-free for more than two months at a time. Cyclothymia may be a precursor to other forms of bipolar disorder, rather than a stable diagnostic entity in itself. In a study of the natural course of cyclothymia, 35% developed full syndromal depression, hypomania or mania during drug-free follow-up [59]. Compared to patients with a definite history of mania, cyclothymic patients had milder symptoms of abnormal mood and cognition. Most showed sleep disturbances and fluctuating levels in the quality of work or school productivity. Cyclothymic patients reported periods of irritability or aggressiveness, patterns of frequent shifts in interests or plans, and drug or alcohol abuse.

Episodic promiscuity or extra-marital affairs were reported by 40% of the sample, and 25% reported joining new movements with zeal, followed by subsequent disappointment. Because of the high level of chronicity, it can be difficult to distinguish cyclothymia from personality disorders.

Conclusion The current definitions and classification schemes of bipolar disorder remain a work in progress. While the diagnoses have relatively high inter-rater reliability, there is considerable heterogeneity within each diagnostic category. Recognizing the various manifestations, which may reflect differing positions on a spectrum or alternatively genuine subgroups, can be important to treatment selection as our pharmacologic armamentarium continues to expand. Some mood stabilizing medications may work best in a specific subpopulation of patients with a bipolar diagnosis. Alternatively, some mood stabilizing treatments may be effective in a population that does not meet the current bipolar criteria, but is nevertheless characterized by recurrent affective illness that falls within the broader Kraeplinian manic-depressive conceptualization. As our understanding of this group of disorders continues to evolve, continued development of evidence-based approaches to treatment will require accurate and detailed descriptions of clinical trial samples that go beyond simple diagnosis.

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patients with bipolar I disorder. Bipolar Disord., 4 (6), 398–405. Altshuler, L.L., Gitlin, M.J., Mintz, J. et al. (2002) Subsyndromal depression is associated with functional impairment in patients with bipolar disorder. J. Clin. Psychiatry, 63 (9), 807–811. Kr€ uger, S., Young, L.T. and Br€ aunig, P. (2005) Pharmacotherapy of bipolar mixed states. Bipolar Disord., 7 (3), 205–215. Dilsaver, S.C. and Swann, A.C. (1995) Mixed mania: apparent induction by a tricyclic antidepressant in five consecutively treated patients with bipolar depression. Biol. Psychiatry, 37 (1), 60–62. Himmelhoch, J.M., Mulla, D., Neil, J.F. et al. (1976) Incidence and signficiance of mixed affective states in a bipolar population. Arch. Gen. Psychiatry, 33 (9), 1062–1066. Goldberg, J.F., Garno, J.L., Leon, A.C. et al. (1999) A history of substance abuse complicates remission from acute mania in bipolar disorder. J. Clin. Psychiatry, 60 (11), 733–740. McElroy, S.L., Strakowski, S.M., Keck, P.E. Jr et al. (1995) Differences and similarities in mixed and pure mania. Compr. Psychiat., 36 (3), 187–194. Dilsaver, S.C., Chen, Y.-W., Swann, A.C. et al. (1994) Suicidality in patients with pure and depressive mania. Am. J. Psychiatry, 151 (9), 1312–1315. Valtonen, H.M., Suominen, K., Mantere, O. et al. (2007) Suicidal behaviour during different phases of bipolar disorder. J. Affect Disord., 97 (1–3), 101–107. Marneros, A. (2001) Origin and development of concepts of bipolar mixed states. J. Affect. Disord., 67 (1–3), 229–240. Swann, A.C., Bowden, C.L., Morris, D. et al. (1997) Depression during mania. Treatment response to lithium or divalproex. Arch. Gen. Psychiatry, 54 (1), 37–42. McElroy, S., Keck, P. Jr, Pope, H. Jr et al. (1992) Clinical and research implications of the diagnosis of dysphoric or mixed mania or hypomania. Am. J. Psychiatry, 149 (12), 1633–1644. Suppes, T., Mintz, J., McElroy, S.L. et al. (2005) Mixed hypomania in 908 patients with bipolar disorder evaluated prospectively in the Stanley Foundation Bipolar Treatment Network: a sex-specific phenomenon. Arch. Gen. Psychiatry, 62 (10), 1089–1096. Akiskal, H.S. and Benazzi, F. (2003) Family history validation of the bipolar nature of depressive mixed states. J. Affect. Disord., 73 (1), 113–122. Bauer, M.S., Whybrow, P.C., Gyulai, L. et al. (1994) Testing definitions of dysphoric mania and hypomania: prevalence, clinical characteristics and inter-episode stability. J. Affect Disord., 32 (3), 201–211. Merikangas, K.R., Akiskal, H.S., Angst, J. et al. (2007) Lifetime and 12-month prevalence of bipolar spectrum disorder in the national comorbidity survey replication. Arch. Gen. Psychiatry, 64 (5), 543–552. Tohen, M., Hennen, J., Zarate, C.M. Jr et al. (2000) Two-year syndromal and functional recovery in 219 cases of firstepisode major affective disorder with psychotic features. Am. J. Psychiatry, 157 (2), 220–228. Tohen, M., Waternaux, C.M. and Tsuang, M.T. (1990) Outcome in Mania. A 4-year prospective follow-up of 75 patients

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utilizing survival analysis. Arch. Gen. Psychiatry, 47 (12), 1106–1111. Dilsaver, S.C., Chen, Y.W., Swann, A.C. et al. (1997) Suicidality, panic disorder and psychosis in bipolar depression, depressive-mania and pure-mania. Psychiatry Res., 73 (1–2), 47–56. Dunner, D.L., Gershon, E.S. and Goodwin, F.K. (1976) Heritable factors in the severity of affective illness. Biol. Psychiatry, 11 (1), 31–42. Judd, L.L., Akiskal, H.S., Schettler, P.J. et al. (2003) A prospective investigation of the natural history of the long-term weekly symptomatic status of bipolar II disorder. Arch. Gen. Psychiatry, 60 (3), 261–269. Benazzi, F. (2007) Testing predictors of bipolar-II disorder with a 2-day minimum duration of hypomania. Psychiatry Res., 153 (2), 153–162. Angst, J. (1998) The emerging epidemiology of hypomania and bipolar II disorder. J. Affect Disord., 50 (2–3), 143–151. Benazzi, F. (1999) Prevalence of bipolar II disorder in atypical depression. Eur. Arch. Psychiatry Clin. Neurosci., 249 (2), 62–65. Vieta, E. and Suppes, T. (2008) Bipolar II disorder: arguments for and against a distinct diagnostic entity. Bipolar Disord., 10 (1 Pt 2), 163–178. Suppes, T. and Dennehy, E.B. (2002) Evidence-based longterm treatment of bipolar II disorder. J. Clin. Psychiatry, 63 (Suppl 10), 29–33.

52. Ghaemi, S.N., Boiman, E.E. and Goodwin, F.K. (2000) Diagnosing bipolar disorder and the effect of antidepressants: a naturalistic study. J. Clin. Psychiatry, 61 (10), 804–808; quiz 809. 53. Ghaemi, S.N., Sachs, G.S., Chiou, A.M. et al. (1999) Is bipolar disorder still under-diagnosed? Are antidepressants overutilized? J. Affect Disord., 52 (1–3), 135–144. 54. Fieve, R.R., Go, R., Dunner, D.L. and Elston, R. (1984) Search for biological/genetic markers in a long-term epidemiological and morbid risk study of affective disorders. J. Psychiatr. Res., 18 (4), 425–445. 55. Coryell, W., Endicott, J., Reich, T. et al. (1984) A family study of bipolar II disorder. Br. J. Psychiatry, 145, 49–54. 56. Coryell, W., Endicott, J., Maser, J.D. et al. (1995) Long-term stability of polarity distinctions in the affective disorders. Am. J. Psychiatry, 152 (3), 385–390. 57. Judd, L.L., Akiskal, H.S., Schettler, P.J. et al. (2002) The longterm natural history of the weekly symptomatic status of bipolar I disorder. Arch. Gen. Psychiatry, 59 (6), 530–537. 58. Goldring, N. and Fieve, R.R. (1984) Attempted suicide in manic-depressive disorder. Am. J. Psychother, 38 (3), 373–383. 59. Akiskal, H.S., Djenderedjian, A.M., Rosenthal, R.H. and Khani, M.K. (1977) Cyclothymic disorder: validating criteria for inclusion in the bipolar affective group. Am. J. Psychiatry, 134 (11), 1227–1233.

CHAPTER

3

The Long-Term Course and Clinical Management of Bipolar I and Bipolar II Disorders Lewis L. Judd1 and Pamela J. Schettler2 1 2

Department of Psychiatry, University of California at San Diego (UCSD), La Jolla, CA, USA Mood Disorders Research Group, Department of Psychiatry, University of California at San Diego (UCSD), La Jolla, CA, USA

Introduction It is surprising that mood disorders, with their fundamental tendency for episodes to recur during the life cycle, have had so few prospective longitudinal studies of their longterm course of illness. Apart from studies by Jules Angst et al. covering 20 years or more of the life span [1,2], most long-term studies of the course of bipolar illness have been derived from the National Institute of Mental Health (NIMH) Collaborative Depression Study (CDS) [3–17]. The vast majority of treatment studies for bipolar disorders are short-term, and until recently have focused primarily on resolution of acute manic episodes. If any follow-up course is examined, it rarely extends beyond two years. Over a decade ago, our research group at the University of California, San Diego, in conjunction with our collaborators from the NIMH CDS, designed a series of studies to describe and delineate the long-term course of mood disorders. Initially, we investigated the long-term course of unipolar major depressive disorder (MDD) [18–20]. We found that unipolar MDD tends to be a chronic lifelong illness, not an illness of single isolated acute major depressive episodes surrounded by long periods of symptom free euthymia. Furthermore, we found that the long-term course of the disorder is expressed symptomatically along a continuum of depressive symptom severity, primarily involving minor, dysthymic and subsyndromal depression. Each increase or decrease in depressive symptom severity, including subsyndromal depressive symptoms, is associated with a progressive and significant increase or decrease in psychosocial impairment [20]. Recovery from a major depressive episode (MDE) with ongoing residual depressive symptoms is associated with significantly faster episode relapse, as well as with a more chronic future course of illness [21,22]. Following our work on unipolar MDD, we designed another series of investigations of patients with bipolar disor-

ders [11–17,23]. The purpose of these studies was to fill the enormous gap in empirical data concerning the long-term course and the life impacts of bipolar I (BP-I) and bipolar II (BP-II) disorders. While findings from these eight peer-reviewed studies have been reported individually in scientific publications, the present chapter afforded an opportunity to compile all of our findings about the long-term symptomatic and episodic course of bipolar I and bipolar II disorders and their associated psychosocial impairment. When first published, our analyses of the weekly symptom status of bipolar CDS patients during up to 20 years of follow-up provided the field with a uniquely detailed and comprehensive picture of the long-termcourseofbipolardisorders.Whilethepresentchapter is primarily based upon our data, we also reference reports by other groups, whose work in this rapidly advancing field of research supports, complements or extends our observations. The findings presented here have strong implications for how bipolar illnesses should be managed over time. Recommendations for this are presented at the conclusion of this chapter.

Methods of the NIMH CDS The data for these publications is derived from the clinical mood disorder cohort of the NIMH CDS [24,25]. This study is unique in that it obtains prospective, naturalistic, systematic, long-term follow-up data on the weekly symptom status of a very large cohort of patients with mood disorders diagnosed using research-based criteria. Patients entered the study in a major affective episode, during a three-year period from 1978 to 1981. Some of these subjects have now been followed for 27 years. Findings reported in this chapter were derived from data extending up to 20 years of followup, with an average of 15 years per subject, for 291 patients with bipolar I or bipolar II disorder.

Subjects Bipolar Disorder: Clinical and Neurobiological Foundations Edited by Lakshmi N. Yatham and Mario Maj © 2010 John Wiley & Sons, Ltd. ISBN: 978-0-470-72198-8

Subjects entered the CDS as inpatients or outpatients at one of five tertiary care centres, while experiencing an active 17

18

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Chapter 3

affective episode. All of the patients in the CDS were required to be Caucasian (genetic hypotheses were being tested), speak English, have an IQ score of at least 70, and have no evidence of any organic brain syndrome or terminal medical illness. Written informed consent was obtained for participation in the research. Patients in the CDS received a diagnosis using the Research Diagnostic Criteria (RDC) [26], based on Schedule for Affective Disorders and Schizophrenia interviews [27] and on a review of medical records. They were included in the present analysis if they met criteria for bipolar I (definite) or bipolar II (definite or probable) at entry. Since we found no difference in clinical, demographic or follow-up characteristics of patients with bipolar II disorder who had hypomanic episodes lasting 1 week or more (definite BP-II) versus three to six days (probable BP-II) [12], we combined both groups into the BPII cohort. Consistent with DSM-IV criteria [28], we excluded N ¼ 25 patients (6.8%) who had no MDD by the end of follow-up (unipolar manic/hypomanic patients and those with lifetime mania/hypomania plus minor depression/ dysthymia but no MDD). For those patients who switched from unipolar MDD to BP-I or BP-II during follow-up, their data on psychosocial impairment were included, starting from the time of their first lifetime manic or hypomanic episode [15]. Patients who ever met RDC criteria for schizophrenia or schizoaffective disorder were excluded. Interview forms rated with poor or very poor reliability of weekly symptom status or monthly psychosocial impairment were excluded from the analysis (3% of follow-up forms). The resulting analysis sample included 158 patients with BP-I (lifetime MDD and mania) and 133 patients with BP-II (lifetime MDD and hypomania, but no mania). Demographic and clinical characteristics are shown in Table 1.

Weekly psychiatric symptom ratings As described in greater detail elsewhere [11–13], trained professional raters interviewed patients every six months for the first five years and then yearly thereafter, using variations ofthe Longitudinal Interval Follow-up Evaluation (LIFE) [29]. During these semi-structured interviews, chronological memory prompts are used to obtain information on changes in weekly symptom severity for all mood and other mental disorders. This information, supplemented by available medical records, is integrated into weekly Psychiatric Status Ratings that have scale values anchored to diagnostic thresholds for RDC mental disorders. The CDS raters undergo rigorous training, resulting in intraclass correlation coefficients of 0.90 for reliability of psychiatric symptom ratings, 0.95 for recovery from major affective episodes, and 0.88 for subsequent appearance of affective symptoms [29]. For the analyses reported here, each week’s psychiatric symptom ratings for all affective conditions were combined and classified into one of eight mutually exclusive symptom

Table 1 Demographic and clinical characteristics of patients with BP-I and BP-II disorders in the NIMH CDS.

Demographics Age Female Married/Living Together Some College Intake Episode Inpatient Severity – Worst Week Global Assessment Scale (GAS) score Last Available Follow-up (years)

BP-I (N ¼ 158)

BP-II (N ¼ 133)

P Value

Mean (sd) Range % %

38.2 (12.6) 17–79 60.1 44.9

35.2 (12.7) 17–74 67.6 42.1

0.18 0.63

%

60.1

57.1

0.61

% Mean (sd)

88.6 33.6 (10.7)

66.9 37.1 (9.2)

<0.001 0.004

Mean (sd) Range

15.2 (4.7) 2.5–20.0

15.2 (4.9) 2.5–20.0

0.89

0.04

severity categories. These are three levels of severity of symptoms in the pure depressive spectrum, namely major depression (MDD), minor depression/dysthymia (MinD) and subsyndromal depression (SSD); three levels of symptom severity in the pure manic spectrum, namely mania, hypomania (Hyp.) and subsyndromal hypomania (SSH); cycling or mixed polarity (indicating change in polarity or coexistence of both manic and depressive symptoms within a given month); or the asymptomatic status (no affective symptoms, return to usual self). To analyze monthly psychosocial impairment ratings in relation to affective symptom severity and polarity, the weekly symptom status categories were then combined and coded with the most severe level of symptom severity (separately for the depressive and the manic spectrum) that occurred during any week of each one-month period of psychosocial ratings. Based on the worst level of affective symptoms recorded in that month, the entire month was then categorized into one of three levels of pure depressive symptom severity, three levels of pure manic/hypomanic symptom severity, a combination of depressive and manic/hypomanic symptoms, or asymptomatic status (no affective symptoms, return to usual self for the entire month).

Characteristics of the long-term course of bipolar illness In the remainder of this chapter, we summarize our findings about the fundamental characteristics of the long-term

The Long-Term Course and Outcome

course of bipolar I and bipolar II disorders based on the weekly affective symptom status data described above. The chapter ends with recommendations for treatment implications derived from these findings. The remainder of the chapter is organized in the following sections: 1 Chronicity of the Course of Bipolar Illness 2 Dynamic and Changeable Affective Symptom Course of Bipolar Illness 3 Affective Symptom Expression Along a Dimensional Continuum of Symptom Severity 4 Dominance of Affective Symptoms Below Syndromal Threshold of Major Depression and Mania 5 Dominance of Depressive Episodes and Symptoms 6 Psychosocial Impairment Associated with Bipolar Disorders 7 Clinical Importance of Bipolar II Disorder 8 Incomplete Recovery from Major Affective Episodes As a Predictor of Early Episode Relapse/Recurrence 9 Conclusions About the Long-Term Course of Bipolar Illness 10 Implications for the Long-Term Clinical Management of BP-I and BP-II Disorders.

Chronicity of the course of bipolar illness It is generally understood that bipolar disorders, with their repeat episodes, are chronic in nature. However, a unique picture of just how chronic these disorders really are emerged from these studies. As seen from Table 2, the Table 2 Lifetime chronicity of BP-I and BP-II disorders in the NIMH CDS.

Prior to Intake Age of Onset of First Lifetime Affective Episode First Episode before Age 21 Number of Previous Episodes (Including the Intake Episode) During Follow-up % Wks Symptomatic during
20 Yrs of Follow-up Number of Episodes during 10 Yrs after End of Intake Episode

BP-I

BP-II

P Value

Mean (sd) Range

23.6 (10.4) 1–62

22.1 (10.5) 1–64

0.22

%

49.4

53.4

0.50

Median

5.5

5.0

0.52

Mean (sd)

46.6 (34.1)

55.8 (33.1)

0.06

Median

2.5

4.0

0.05

|

19

illness begins early in life, with mean age of onset of first affective episode in the low 20s for both bipolar I and bipolar II disorders, and approximately half the samples experiencing their first affective episode before age 21. Patients entering the CDS with either bipolar disorder had already experienced a median of five separate affective episodes (including the index/intake episode). During the first 10 years of follow-up after the end of the intake episode, patients with bipolar I disorder experienced a median of 2.5 episodes and those with bipolar II disorder experienced a median of four episodes; this difference was marginally significant (P ¼ 0.05). This is consistent with Angst et al.’s findings from a 27-year follow-up of a large cohort of patients hospitalized between 1959 and 1963 and evaluated at five-year intervals thereafter [2]. Those authors found that the risk of recurrence of bipolar disorders (0.4 episodes per year) was about twice that of unipolar depressive patients (0.2 episodes per year); that the risk of recurrence was slightly higher for BP-II than for BP-I; and that the risk of recurrence for all groups was constant over the life span, up to the age of 70. A new measure of chronicity, which we have been advocating for the study of both unipolar MDD and bipolar disorder, is the total percentage of weeks when subjects experience any level of affective symptoms from their illness – in other words, the percentage of time the illness is active. Measurement of total time symptomatic, regardless of the symptom severity or whether an individual is in an episode, is a more sensitive measure of illness chronicity than time in episodes, since we have demonstrated that bipolar (and unipolar) patients, even when meeting consensus criteria for ‘recovery’, frequently experience subsyndromal affective symptoms [17,21]. As shown in Table 2, patients with bipolar I disorder were symptomatic from their illness during 47% of follow-up weeks and bipolar II patients were symptomatic 56% of the time. It is very clear that bipolar disorders, both BP-I and BP-II, are intensely chronic with the patients being afflicted from the illness approximately half of the time, during up to 20 years of prospectively observed follow-up.

Dynamic and changeable affective symptom course of bipolar illness Angst and his colleagues reported that BP-II patients experience a slightly higher number of episodes per year than BP-I patients [1,2]. In a 2003 paper [14], we confirmed and extended these findings by comparing BP-I and BP-II patients on the number, duration and percentage of weeks spent in each type of affective episode, during a 10-year period after the end of their intake episode. In this study, both bipolar groups spent about 30% of the time in major or minor mood disorder episodes. BP-II patients tended to have more episodes (mean (sd) ¼ 4.2 (2.6) vs. 3.3 (2.5);

20

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Chapter 3

Table 3 Dynamic follow-up course of BP-I and BP-II disorders in the NIMH CDS.

Total Changes in Symptom Status (Changes in Severity and/or Polarity) Changes per Yr Mean (sd) More than % 5 Times per Yr Changes in Symptom Polarity Changes per Yr More than 5 Times per Yr

Mean (sd) %

BP-I

BP-II

5.9 (7.7) 35.6

3.8 (4.9) 22.5

3.5 (7.5) 19.3

1.5 (4.2) 5.6

P ¼ 0.052), including significantly more episodes of MDD and significantly more episodes of minor depression or dysthymia. BP-I patients, on the other hand, had significantly more episodes with cycling/mixed polarity (some depression and some mania/hypomania). During this 10-year period, the duration of each type of episode was slightly (non-significantly) longer for patients with BP-II than for those with BP-I. When data on episode status is supplemented with weekly data on change in the entire spectrum of affective symptom categories, the results show a strikingly high number of changes in symptom status per year for bipolar patients. As seen in Table 3, the mean total number of changes per year in symptom status (symptom severity and/or polarity) is nearly 6 for BP-I patients and approximately 4 for BP-II patients. By contrast, we found that unipolar MDD patients in the CDS changed depressive symptom severity level only

Hyp. 5% SSH 3%

Mania 2% Mixed 6%

Affective symptom expression along a dimensional continuum of symptom severity Over the long-term course, affective symptoms in bipolar disorder are expressed along a dimensional continuum of progressively increasing symptom severity, ranging from subsyndromal, through minor depressive and hypomanic affective symptoms, to symptoms at the full syndromal severity of mania and major depression. Figure 1 shows the percentage of weeks of follow-up that BP-I and BP-II subjects in the CDS spent in each of eight mutually exclusive symptom categories – three levels of depressive symptom severity, three levels of manic/hypomanic symptom severity, symptoms of mixed polarity and the asymptomatic status [13]. BP-I patients were without symptoms of the illness 53% of the time, and BP-II patients were asymptomatic only 44% of the time. This is a striking confirmation of

Hyp. 1% SSH .4%

Mixed 2.5%

MDD 13%

MDD 9% MinD 13%

two times per year [18], corroborating Angst’s findings of greater change in bipolar patients compared to unipolar patients [1,2]. Shifts per year in symptom polarity are defined by a patient shifting from symptoms in the depressive spectrum to the manic spectrum or vice versa. On average, BP-I patients change polarity between three and four times per year and BP-II patients change between one and two times per year. Examination of shifts across the entire spectrum of affective symptoms complements the picture of long-term course based on episode status alone, and shows that BP-I is the more dynamic and changeable of the two disorders, while BP-II is characterized by greater chronicity and more frequent episodes. It is noteworthy that a subset of each group suffers from a highly changeable course that could be labelled as rapid cycling. What is presented here is a rather dramatic picture of the changeable and quixotic nature of the naturalistic course of bipolar disorders.

Asymptomatic 53%

Asymptomatic 44% MinD 25%

SSD 9% SSD 14%

Bipolar I

Bipolar II

Fig. 1 Mean percent weeks in each category of affective symptoms during long-term follow-up.

The Long-Term Course and Outcome

the highly chronic nature of BP-II. We found that the great majority of bipolar patients experience the full range of categories of symptom severity of both depressive and manic symptoms during their course of illness. This, combined with the information on changeability of course (above), shows that bipolar patients not only change episode status frequently, but move and flow from one category of symptom severity and polarity to another during the course of their illness. Observing bipolar patients serially or cross-sectionally is like taking a snapshot of an ongoing movie. When seen at one point in time, patients may be in an episode of mania or depression, while at another time they are likely to be experiencing minor or subsyndromal affective symptoms, and at yet another time they may be free of symptoms and euthymic. It is only when the entire, continuous symptomatic course is recorded and analyzed, that a true picture of the long-term symptomatic course of bipolar disorders can be seen.

Dominance of affective symptoms below syndromal threshold of major depression and mania Contained in Table 4 are the mean percent of follow-up weeks at the threshold of major depression or mania versus the mean percent weeks beneath that threshold – that is with symptoms at or below the threshold for minor depression or hypomania. As can be seen, most of the symptomatic course of both BP-I and BP-II disorder is below the syndromal threshold. Even though bipolar disorder is traditionally defined by episodes at the syndromal threshold of major depression or mania, most of the illness occurs over time at a mild or moderate level of affective symptom severity. These data on the dominance of subthreshold symptoms during the course of bipolar illness complement our previous findings, derived from the NIMH Epidemiological Catchment Area (ECA) study [30]. The original authors of the ECA reported that the lifetime prevalence of bipolar I disorder was 0.8%, and bipolar II disorder was 0.5% for

Table 4 Dominance of subthreshold symptoms during long-term follow-up of patients with BP-I and BP-II disorders in the NIMH CDS.

Percent of Wks with Symptoms beneath the Threshold of MDE/Mania Percent of Wks with Symptoms at the Threshold of MDE/Mania Subthreshold/Threshold

BP-I

BP-II

Mean

34.2

43.2

Mean

12.3

12.6

Ratio

<3 : 1

>3 : 1

|

21

a combined lifetime prevalence of bipolar illness of 1.3% [31]. With our reanalysis of the ECA data adding subthreshold hypomanic symptoms [23], the lifetime prevalence figures increased substantially, from 1.3 to 6.4% for the bipolar spectrum. In that study, having had symptoms at the subsyndromal hypomanic level at some time in one’s life was found to be associated with significantly greater health service utilization for mental/emotional or substance abuse problems, as well as greater use of welfare and disability benefits. Subsyndromal symptoms are particularly important when they are present during an episode of the opposite polarity. Angst et al. [32] and others [33,34] have pointed out that, in persons with a history of major or even mild depression, subsyndromal hypomanic symptoms are an important indicator of bipolarity that needs to be considered during diagnosis and treatment. Investigators analyzing the NIMH STEP-BD data found that two-thirds of the 1380 subjects presenting with bipolar I or II depressive syndromes also had subsyndromal manic/hypomanic symptoms at intake, and that these were markers for a more severe form of bipolar illness [33]. Further analysis of the STEP-BD data has shown that use of adjunctive antidepressants in these subjects does not speed recovery from the index depression compared to mood stabilizers alone, and it may even increase the severity of the manic symptoms [34].

Dominance of depressive episodes and symptoms As the new picture of the long-term symptomatic course of bipolar illness began to emerge, the high prevalence of depressive episodes and symptoms was very striking. While bipolar illness has traditionally been defined and treated with a focus on the often chaotic episodes of mania, these comprise a relatively small portion of the total symptomatic course of illness. Table 5 shows the percent of weeks during long-term follow-up that bipolar patients in the CDS spent with depressive episodes and symptoms, compared

Table 5 Dominance of depressive episodes and symptoms during long-term follow-up of patients with BP-I and BP-II disorders in the NIMH CDS.

Percent of Wks with Depressive Episodes and Symptoms Percent of Wks with Manic/Hypomanic Episodes and Symptoms Depression/Mania

BP-I

BP-II

Mean

30.6

51.9

Mean

9.8

1.4

Ratio

3:1

37 : 1

22

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Chapter 3

to all weeks with manic/hypomanic episodes and symptoms. The ratio of depression to mania (D:M) in BP-I is approximately 3 : 1. The ratio in BP-II is dramatically different, with approximately 52% of the weeks involving depressive episodes and symptoms and only 1.4% of weeks when BP-II patients experience hypomanic episodes and subsyndromal hypomanic symptoms – resulting in a ratio of depressive to hypomanic symptom spectrum of 37 : 1. This provides compelling data supporting the conclusion that BP-I is primarily a depressive illness and that BP-II is almost exclusively a chronic depressive illness. This is interesting, since most of the scientific effort in the study of bipolar disorder has focused on the management of manic or mixed polarity symptoms, with far less attention to depressive episodes and symptoms. It is an important fact that depression is far more prevalent during the course of bipolar illness. Other investigators have documented the importance of depression in the long-term course of BP-I disorder. Turvey et al. [10] found that individual CDS patients with BP-I tended to have consistency across prospectively observed episodes in terms of their starting polarity, that episodes beginning with major depression were significantly longer than those beginning with mania, and that patients whose first prospectively observed episode began with depression had a significantly worse follow-up course. More recently, the 10-year McLean-Harvard First Episode Project & International Consortium for Bipolar Disorder Research found that most early morbidity after first lifetime onset of bipolar I disorder is associated with depression, and that initial depression or mixed states predict more depressive symptoms and greater overall morbidity during subsequent follow-up [35]. Coryell et al. recently reported [36] that early onset age predicts greater depressive morbidity in BP-I patients during CDS follow-up, and that depressive symptoms increasingly predominate as individuals move through their third, fourth and fifth decades of BP-I illness.

Psychosocial impairment associated with bipolar disorders Data summarized in this section are from the first investigation that we are aware of, studying psychosocial impairment associated with every level of affective symptom severity, as well as periods of euthymia in a large cohort of BP-I and BP-II patients followed prospectively for many years [15]. In Figure 2, mean ratings of global psychosocial impairment associated with various symptom status categories are presented. Results were generated by mixed regression analysis, used to model the relationship between monthly psychosocial ratings and the severity and polarity of affective symptoms within those months, as individual patients experience different symptom status categories

during long-term follow-up. The height of the bars represents mean level of impairment, and the error bars represent the 95% confidence intervals of those means, from the mixed regression analysis. As clearly conveyed in Figure 2, affective symptom severity and psychosocial disability fluctuate together during the course of bipolar illness. As we found for unipolar MDD [20], every stepwise increase or decrease in depressive symptom severity is associated with a corresponding significant, stepwise increase or decrease in psychosocial impairment in both BP-I and BP-II disorders. When subjects with either disorder have no mood disorder symptoms, no impairment is present and psychosocial functioning is rated as good. When the same patients are experiencing subsyndromal depressive symptoms, they have mild impairment; during months with symptoms at the level of minor depression or dysthymia, their psychosocial impairment is rated between mild and moderate; and when bipolar patients are experiencing symptoms at the syndromal threshold of major depression, their psychosocial functioning is rated as moderately impaired. Even subsyndromal depressive symptoms are associated with significantly more impairment than the asymptomatic (euthymic) status, for both BP-I and BP-II disorder. There is a similar picture of stepwise increases in psychosocial impairment associated with stepwise increases in manic symptom severity, for patients with BP-I disorder. By contrast, for those with BP-II disorder, hypomanic and subsyndromal hypomanic symptoms are not associated with significant increases in psychosocial impairment, and may even enhance psychosocial function. This is consistent with Akiskal’s and others’ findings that minimal disability, and possibly even enhanced psychosocial functioning, frequently occurs during subsyndromal and syndromal hypomanic periods of bipolar II disorder, which may make it difficult to diagnose hypomania [37–40]. Figure 2 also conveys that depressive symptoms, which have been seen to dominate the course of both bipolar disorders, are at least as disabling as symptoms of comparable severity in the manic/hypomanic spectrum. Data from these studies shows that much of the psychosocial disability associated with BP-I and BP-II is derived from symptoms in the depressive spectrum. This is in striking contradiction to the traditional view that mania and manic symptoms are more disabling than depression. The figure further shows that within each level of depressive symptom severity, BP-II is associated with a level of psychosocial impairment comparable to BP-I disorder. These findings again underscore the importance of depressive symptoms in BP-II. What should be very encouraging to all is the fact that when affective symptoms are abated and the patient with either BP-I or BP-II is asymptomatic, no psychosocial impairment is noted and the patient’s function is rated as normalized.

The Long-Term Course and Outcome

Mean Global Impairment Rating

Asymptomatic

Marked

5

Depressive Spectrum

|

23

Manic Spectrum

Patients with Bipolar I Disorder (N=158)

Impairment

4

Moderate Impairment

3

Mild Impairment

2

No Impairment

1 Asympt.

Mean Global Impairment Rating

5

SSD SSH

MinD Hypom.

MDD Mania

Patients with Bipolar II Disorder (N=133)

Marked Impairment

4

Moderate Impairment

3

Mild Impairment

2

No Impairment

1 Asympt.

SSD SSH

MinD Hypom.

Clinical importance of bipolar II disorder Bipolar II disorder is generally considered to be the lesser of the two bipolar subtypes and some think it is of little clinical significance; as a result, it not treated as often as it should be. Findings presented here provide strong evidence that these impressions of BP-II disorder are incorrect. CDS subjects with BP-II were symptomatic during 56% of weeks during an average of 15 years of follow-up; this is evidence of even greater symptomatic chronicity than for patients with BP-I disorder, who were symptomatic during 47% of weeks in their long-term course. Furthermore, BP-II patients spent approximately the same mean percentage of follow-up weeks at the full syndromal threshold of MDE as BP-I patients spent with MDE/mania [mean (sd) ¼ 12.6 (15.9) vs. 12.3 (14.6); P ¼ 0.834]. They also spent significantly more weeks with symptoms of minor depression/dysthymia or hypomania [mean (sd) ¼ 27.0 (23.3) vs. 20.1 (21.2); P ¼ 0.036]. In our study comparing the episodic course of BP-I and BP-II patients in the CDS [14], we found that those with BP-II had significantly longer intake episodes (P < 0.001), and 18% even had psychotic symptoms. They also had marginally more episodes during follow-up (P ¼ 0.052),

MDD

Fig. 2 Mean global impairment rating at each level of affective symptom severity (single polarity months).

including significantly more episodes of MDD and minor depression/dysthymia (P < 0.001 for both). Patients with BP-II disorder experienced depressive symptoms during more than half of follow-up weeks, and depressive symptoms outweighed the percent of hypomanic symptoms in a ratio of 37 : 1 (compared to a ratio of 3 : 1 for patients with BP-I disorder). This is notable because all levels of depressive symptoms, as indicated in the last section, are associated with significant psychosocial impairment. When we examined psychosocial disability averaged across all ill and well periods during the long-term course of illness for patients with BP-I and BP-II disorders [16], the mean levels of global disability for the two bipolar groups were identical and reflected a mild level of impairment. Both groups experienced some degree of impairment during nearly 60% of months during follow-up (58.3% for BP-I; 59.1% for BP-II), which included moderate to severe impairment during 30% of long-term follow-up (31.3% for BPI; 30.3% for BP-II). Impairment for both bipolar groups was slightly higher than for unipolar MDD patients (53.8% of months with some impairment, including 25.8% with moderate to severe impairment during long-term follow-up).

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We did not find any difference in BP-II disorder defined on the basis of hypomanic episodes that are longer (7 days or more) compared to shorter (from two to six days) [12]. We and others [32,39] have suggested that hypomanic episodes of either duration are part of the same disease process. Despite the evidence that bipolar II disorder is a ‘real’ disorder, with its intensely chronic and depressive nature and its association with significant psychosocial impairment, treatment of BP-II tends to be overlooked [13]. Table 6 provides cogent data on somatic treatment by symptom severity and polarity categories. Within 5 of 7 symptom categories, including the asymptomatic status when patients often require maintenance treatment for prophylaxis of future episodes, CDS patients with BP-II disorder were prescribed somatic treatment significantly less often than those with BP-I disorder. This was the case even during periods when patients were experiencing symptoms at the level of major depression; BP-II patients were treated only half the time, compared to three-quarters of the time for patients with BP-I during MDE periods. Data presented here clearly shows that bipolar II disorder is not the lesser of the two bipolar subtypes, but is a serious and intensely depressive disorder in its own right, and warrants the same level of clinical management that is given to bipolar I disorder.

Incomplete recovery from major affective episodes as a predictor of early episode relapse/recurrence We previously reported that the presence of ongoing residual subsyndromal depressive symptoms following recovery from a MDE in unipolar MDD patients, although meeting the consensus definition of ‘recovery’, is associated with significantly faster episode relapse/recurrence when

Table 6 Mean percent of weeks with any prescribed somatic treatment for BP-I vs. BP-II disorder, by affective symptom category during long-term follow-up. Affective Symptom Category

BP-I

BP-II

P Value

Levels of Depressive Severity Subsyndromal Depressive Symptoms Minor Depression/Dysthymia Major Depressive Disorder

75.9% 77.2% 76.0%

51.9% 56.9% 60.4%

<0.001 <0.001 0.003

Levels of Hypomanic Severity Subsyndromal Hypomania Hypomania

91.1% 80.7%

53.3% 55.3%

0.003 0.068

Cycling/Mixed Polarity Symptoms (All Levels of Severity)

79.9%

58.8%

0.137

Asymptomatic Status (Prophylaxis)

73.7%

43.5%

<0.001

compared to full asymptomatic recovery [21,22]. We hypothesized that the same would be true in bipolar illness – namely, that residual affective symptoms seen following resolution of major affective episodes in bipolar patients would also be associated with significantly faster relapse/ recurrence of the next major affective episode. Similar to our unipolar MDD papers [21,22], ‘recovery’ for our investigation in the bipolar cohort [17] also followed the current consensus definition of eight or more consecutive weeks asymptomatic or with minimal residual affective symptoms. However, dividing recovery into these two levels, we found (Figure 3) that those bipolar patients recovering from their intake MDE/manic episodes with residual affective symptoms experienced a subsequent major affective episode over five times faster than asymptomatic recoverers (median 24 weeks vs. 123 weeks, respectively; p < 0.001). We also found that those whose recovery was marked by residual affective symptoms had a significantly more chronic and severe future course. Recovery status (asymptomatic vs. residual symptoms) proved to be the strongest correlate of time to major affective episode relapse/recurrence for the bipolar cohort (p < 0.001), followed by a history of three or more affective episodes before intake (p ¼ 0.007). No other variable of the 13 examined was significantly associated with time to relapse/recurrence, once the Bonferroni correction was applied. We concluded that in bipolar disorder, the presence of residual symptoms after the resolution of a major affective episode indicates that the individual is at significant risk for rapid relapse and/or recurrence, strongly suggesting that the illness is still active. Recently, a panel of experts in bipolar disorder proposed a standardized set of definitions for patient status for use in clinical trials [41]. These include ‘remission’, defined as having no or only minimal symptoms of the affective episode for one week, and ‘sustained remission’, defined as maintaining this status for eight consecutive weeks. Our finding that ‘recovery’ with residual affective symptoms predicts much faster episode relapse in unipolar [21,22] and bipolar [17] patients, however, argues for a stricter definition of episode remission based on achieving abatement of all symptoms of the episode. Berk et al. [42] re-analysed data from four pharmacologic treatment studies using a definition of remission based on achieving a Clinical Global Impression-Bipolar Version (CGI-BP) severity score of 1 (representing ’normal, not at all ill’). Compared to the current consensus definition of recovery, which allows minimal affective symptoms to be present, these authors conclude that the stricter definition of remission, while more difficult to attain, is more clinically meaningful. We fully agree and have been advocating this since 1998 [21]. The minimum time (number of consecutive weeks) at this status needed to define a stable state of recovery needs to be determined through empirical study, and may be as short as four weeks. A stable recovery state in bipolar disorder,

Cumulative % of Subjects Remaining Free of Major Affective Episode Relapse/Recurrence

The Long-Term Course and Outcome 100

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25

Asymptomatic Recovery (N = 163) Recovery with Residual Affective Symptoms (N = 60)

75

50

Median Weeks Well

(95% Confidence Interval)

123

(89 - 179)

24

(19 - 31)

25

0

0

200

400

600

800

1000

Weeks from End of Intake MDE/Mania to Next Major Affective Episode Wilcoxon Chi Square = 35.81; P < 0.0001; Hazard Ratio = 3.36 (95% CI = 2.25 - 4.98) Judd et al., Arch Gen Psychiatry, 2008

we believe, is achieved only when the asymptomatic status is reached for a sufficient period of time for the patient to be free of risk for relapse into the previous syndromal episode.

Conclusions about the long-term course of bipolar illness From these data, we conclude that bipolar illness disorders are chronic, primarily lifelong illnesses, with strong tendencies for relapse and recurrence of major and minor affective episodes. Syndromal level episodes are interspersed with euthymic periods, during which subsyndromal symptoms are often present. The long-term symptomatic expression of bipolar disorders is dimensional in character, along a continuum of depressive and manic/hypomanic symptom severity. Affective symptoms beneath the threshold of mania and major depression dominate the course of bipolar disorders on a 3 : 1 basis. Psychosocial impairment changes in a step-wise fashion with each increase or decrease in depressive symptom severity in either bipolar I or bipolar II disorder, and with each increase or decrease in manic symptom severity in bipolar I disorder. When patients are completely without symptoms (asymptomatic), psychosocial impairment is no longer seen and the patient’s psychosocial function normalizes and is rated as good. The longterm course of bipolar disorders is very dynamic and changeable, with patients frequently moving from one level of symptom severity to another and from one polarity to another. Depressive episodes and symptoms dominate the course of BP-I (3 : 1 ratio) and BP-II (37 : 1 ratio). Although both bipolar disorders are primarily depressive in nature, bipolar II disorder is fundamentally a chronic depressive illness. As such, BP-II is not merely the lesser of the two bipolar disorders, but is a more serious illness than previ-

Fig. 3 Comparison of asymptomatic versus residual symptom recovery on time to next major affective episode (N ¼ 223 patients with bipolar I or bipolar II disorder). Reprinted from Judd et al., Arch Gen Psychiatry 2008; 65(4):386–394. Copyright
(2008) American Medical Association. All rights reserved.

ously thought. Asymptomatic recovery from major affective episodes is associated with a significantly longer delay in episode relapse or recurrence, as well as a more benign future course of illness. The methodology of our studies, which takes into account the full range of affective symptom severity and polarity on a weekly basis, should be considered by other researchers interested in studying the long-term course of bipolar and unipolar disorders. Collection of such prospective data by trained clinical raters, using empirically established semistructured interviews such as the LIFE [29], not only provides the basis for accurate identification of the start and end of all types of affective episodes (including those below the syndromal level of MDE and mania), but also provides a complete picture of the true illness burden associated with all levels of affective symptoms, during and between episodes. The empirical findings on the long-term course of bipolar illness summarized here suggest certain principles for effective long-term clinical management strategies. These are the focus of the final section of this chapter.

Implications for the long-term clinical management of BP-I and BP-II disorders There are scores of studies presenting useful empirical data on a wide variety of pharmacological agents, and combinations of agents, used to treat acute bipolar episodes; these have been summarized in recent review papers [43,44]. Early studies focused primarily on the treatment of mania [45], but as the predominance of depression that we have reported [11–13] has gained acceptance, controlled medication trials increasingly address the treatment and prevention of bipolar episodes of depression as well [46–48],

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including mixed polarity episodes consisting of depression with concurrent subsyndromal manic/hypomanic symptoms [33]. Most of these studies are concerned with pharmacological agents to treat BP-I. It has generally been assumed that depression in BP-II responds to the same agents used to treat depression in BP-I, and that hypomania is likely to respond to the same agents that are used for mania. Recently, controlled studies have begun to be conducted examining medication effectiveness for BP-II [49]. The NIMH CDS, on which this chapter is largely based, is a naturalistic study, not a controlled treatment investigation. Some studies have examined the impact of particular classes of medication on course and outcome for unipolar [50–52] and bipolar [53–55] patients in the CDS. However, conclusions about medication selection, dosage schedules and medication combinations should be drawn with caution and confirmed only through reports of controlled clinical trials. By ’naturalistic’ is meant that patients were followed systematically while on and off medications, which were given according to the standards and protocols at each of the five academic centres where they entered the CDS in 1978 through 1981, or practices at other facilities where they received treatment during 20 years of follow-up. Somatic treatments throughout this time were systematically recorded, along with the frequency of various types of ‘talk therapy’ and any periods of hospitalization. Treatments given are likely to be consistent with the best available clinical practices at the particular time and would have changed as new medications, and combinations of medications, came into use. There is little doubt that modern psychopharmacology, with its increasing numbers of mood stabilizing medications to treat bipolar illness, has revolutionized the management of these serious disorders. It has made these devastating illnesses into treatable diseases and it is no longer necessary for bipolar patients to spend significant parts of their lifetime hospitalized. Findings about the long-term course of bipolar disorders, developed using the unique CDS database, highlight the need for certain approaches to the clinical management of bipolar disorders. In the remainder of this chapter we outline a series of therapeutic strategies and health system requirements for effectively treating bipolar patients and supporting those closest to them. As many clinicians have already discovered, these therapeutic principles are proving very useful for controlling and managing these difficult, potentially devastating, chronic disorders, and for normalizing patients’ functioning and well-being.

Paradigm shift from acute to chronic disorders The first and perhaps most important treatment implication based on the CDS data presented here is the shift from understanding bipolar disorders as a series of acute, isolated affective episodes, to the recognition that they are

fundamentally chronic, lifelong illnesses. This necessitates a paradigm shift in the overall approach to managing bipolar disorders. We have established that, while patients with BP-I or BP-II disorder spend only 12 or 13% of longterm follow-up at the syndromal level of MDE or mania, they are symptomatic from their illnesses and psychosocially impaired during over half of their course of illness. This underscores the inherently chronic nature of bipolar illness. Recognizing the chronicity of these disorders is the first step to realizing that patients need to be treated with long-term treatment strategies such as those used for type II diabetes, chronic coronary artery disease and so on. Similarly, chronic illnesses such as BP-I and BP-II also require long-term chronic treatment strategies.

Principles for the long-term clinical management of bipolar disorders Following is a series of suggestions based on the data we have reported here, outlining strategies for how bipolar illness can best be managed throughout the patient’s life cycle. It is beyond the scope of this chapter to provide a comprehensive review of the large number of important medication and psychosocial treatment studies for bipolar disorder. Rather, we have referenced selected studies that are relevant to specific treatment recommendations: 1 Provide accurate, evidence-based information on the clinical characteristics and treatment of bipolar illness. It is essential, at the very beginning of treatment, to initiate an educational programme for patients, spouses, families and significant others concerning the clinical characteristics of bipolar illness, including its chronicity and very strong tendencies for episode relapse and recurrence. Special emphasis should be placed on identifying early warning signs or symptoms that may usher in an impending affective episode, together with the need to contact the clinician at the first appearance of these signs. We have noted that bipolar patients often move from an asymptomatic status to an active illness state, with progressive increases in affective symptom severity. Often, a given patient will experience the same unique symptom or set of symptoms as a precursor to each impending episode. Care should be taken by the clinician to identify the signal symptoms for each individual patient, and the patient needs to be instructed to contact the attending clinician as soon as possible when the signal symptoms appear. In addition, the process of education provides an ideal opportunity to create a treatment team made up of the clinician (as leader), the bipolar patient and willing significant others – all of whose goal is to restore and maintain full recovery for the patient. It is essential for those on the team to maintain open communication about the patient’s status, help monitor treatment adherence and provide support during times of crisis and other difficulties (see No. 5 below, on clinical monitoring, for details).

The Long-Term Course and Outcome

2 The necessity for strict adherence to the therapeutic regimen prescribed should be emphasized to patients, spouses, family members and significant others. It is paramount to highlight to the patient and all concerned the need for scrupulous adherence to the prescribed treatment regimens, both medication and psychosocial, thatare needed for effective treatment during both short-term and long-term management phases of the bipolar disorder. The necessity of complying with all recommended treatments should be clearly explained and discussed with the patient and significant others, so they can understand the importance of these approaches for reducing acute symptoms, stabilizing patients and maximizing their psychosocial functioning and well-being, together with preventing future episodes. 3 Explain the need for extended long-term medication regimens. We and others have found it useful to conceptualize the treatment of mood disorders, including bipolar disorders, in terms of different phases of treatment: First, acute treatment is aimed at amelioration of acute symptoms of the index episode. Second, continuation treatment extends beyond symptom resolution of the index episode, and is aimed at preventing return of the index episode (relapse), as well as achieving a stable state of recovery of at least four weeks asymptomatic, if possible. Third, the maintenance phase of treatment is focused on prevention of future new episodes (recurrence), as well as elimination of psychosocial dysfunction and impaired sense of wellbeing that is associated with even the most minor subsyndromal symptoms. The medications used (singly or in combination) during these treatment phases, along with their dosage schedule, need to be individually tailored to each patient. In deciding what medications to prescribe, clinicians need to consider the latest published research findings as well as the patient’s current symptom status, previous clinical history (including their patterns of cyclicity and risk for depressive vs. manic relapse), their past and current medication response, and their experience of adverse side effects. In some cases it is advisable to continue or maintain the patient indefinitely on the same medication(s) and at the same dosage that proved effective for achieving resolution of their acute episode [56]. 4 Combined treatment with medication and adjunctive psychosocial intervention is optimum. It is becoming increasingly recognized that bipolar disorders typically pose enormous short-term and long-term challenges for patients and their families, despite the best available medication regimens [35,57]. Recently, a considerable body of evidence has been building, demonstrating the effectiveness of psychosocial intervention programmes for improving both acute and long-term outcomes in bipolar illness [58–70]. At a recent roundtable [65], experts in the field concluded that, as with other chronic mental disorders, an integrated approach is best, which includes individualized programmes of psychosocial intervention (such as cogni-

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tive-behavioural therapy, interpersonal and social rhythm therapy, and family therapy), along with extended longterm medication regimens. These combined approaches are effective during acute, continuation and maintenance phases of treatment. The main psychosocial intervention modalities for which there is currently some empirical evidence include the following: cognitive-behavioural therapy, which is focused on assisting patients in modifying dysfunctional cognitions and behaviours; interpersonal and social rhythm therapy, which is aimed at improving interpersonal role and occupational functioning, and regularizing daily biological and social rhythms; and family therapy, which aims at reducing high levels of stress and conflict within the patient’s family and teaching effective strategies for coping with bipolar disorder. Another modality, group psychoeducation, provides a forum for sharing accurate, evidence-based information on the clinical characteristics and course of bipolar disorders, available treatment strategies and the necessity for strict adherence to the prescribed treatment. It is also an ideal opportunity to organize and empower the treatment team (clinician, patient, family and significant others), which has proven invaluable in helping to monitor the bipolar patient and keep them episode and symptomfree. From recent reviews of controlled clinical trials on psychosocial interventions for treatment of bipolar disorders [62,64–67], it now appears that specific psychosocial intervention modalities are most effective, depending on the time when they are introduced (acute, continuation or maintenance treatment phase), the clinical status of the patient, the past history of episode polarity and the presence of comorbid conditions. These efforts are promising and await results of further randomized controlled clinical trials confirming or extending these early observations. In the meantime, it is recommended that integrated pharmacological and psychosocial therapies be used for BP-I and BP-II during all three phases of treatment, with the specific modalities selected and applied based upon the most recent publications in this rapidly expanding area of research. 5 Clinical monitoring should be available on a regular ongoing basis. It is important for physicians who are caring for bipolar patients to maintain contact with those patients, even though they may appear to be euthymic and doing well during certain periods. Regular contact is necessary to evaluate current clinical status, adherence to treatment and patients’ psychosocial well-being. There should be clear two-way communication between the clinician and patient to address questions about medication compliance, dosage adjustments and any adverse side effects, along with checking to see whether the patient needs ‘booster’ sessions of their psychosocial treatment. An effective treatment team is indispensable for maintaining this communication. Many academic centres have organized mood disorder clinics, where knowledgeable clinicians or case managers maintain

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Chapter 3

frequent contact with the patient and other members of the treatment team to monitor patients’ clinical status and early signs of impending affective episodes. It is not sufficient to treat the bipolar patient for an acute affective episode, then discharge them with instructions to return if bipolar symptoms recur. A necessary component of the long-term maintenance strategy consists of ongoing contact, careful clinical monitoring and management, and a partnership within the entire treatment team to keep the patient well and functioning optimally. 6 Treat affective episodes and symptoms to their full symptom abatement. The presence of ongoing residual affective symptoms following ‘recovery’ from a major affective episode, even though it meets consensus criteria for remission, has now been shown to be associated with early episode relapse and a less benign future course of illness [17,21,22]. This indicates that the illness is still active and that until all symptoms of the index episode are fully resolved, the episode is not yet over. These findings support the idea that the optimal goal for treatment of bipolar episodes, as for unipolar MDD, should be to eliminate all residual affective symptoms, restore good psychosocial function, and achieve a sustained state of full recovery. 7 Treat depressive episodes and symptoms with equal priority and rigour as manic episodes and symptoms. Until recently, most of the clinical and research emphasis in bipolar disorders has been on the treatment of acute manic episodes. We have provided evidence here that the course of BP-I and BP-II is largely depressive. Since we published these findings [11–13], recent reports have addressed medication issues specifically for controlling the depressive phases of bipolar disorder [46–48]. As data about the highly depressive course of bipolar illness becomes more widely disseminated, we anticipate that there will be increased numbers of treatment studies focusing on bipolar depression. 8 Treat bipolar II with the same priority and rigour as bipolar I disorder. These studies underscore both the clinical importance and the disabling nature of bipolar II disorder, together with the fact that it is treated significantly less often than bipolar I disorder, even at the same levels of affective symptom severity. Bipolar II disorder is equally impairing as bipolar I disorder, because of its intensely chronic and depressive nature [16]. Patients with bipolar II disorder deserve and need equal therapeutic priority and the same methodical treatment rigour as those with bipolar I disorder, throughout their lifetime.

Summary of the expanded goals for the long-term management of bipolar disorders The first step in the treatment of patients with bipolar disorders is to ameliorate the severe symptoms of an acute affective episode. To this we now add the need to treat even

residual symptoms of the episode to their full abatement, where possible. Our findings about the chronicity of bipolar disorders underscore the importance of ongoing clinical monitoring and long-term maintenance treatment to prevent affective episode relapse and recurrence, as well as the need to treat even minor and subsyndromal affective symptoms in order to reduce the overall chronicity of the illness. Our findings of psychosocial impairment associated with all levels of affective symptom severity highlight the treatment goal of restoring bipolar patients to their optimal level of psychosocial functioning. In summary, the focus of treatment has shifted from the reduction of severe symptoms of acute episodes, to maintaining patients as symptom-free and optimally functioning as possible throughout their lifetime.

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The Long-Term Course and Outcome 13. Judd, L.L., Schettler, P.J., Akiskal, H.S. et al. (2003) Long-term symptomatic status of bipolar I vs. bipolar II disorders. Int. J. of Neuropsychopharm., 6, 127–137. 14. Judd, L.L., Akiskal, H.S., Schettler, P.J. et al. (2003) The comparative clinical phenotype and long-term longitudinal episode course of bipolar I and II: a clinical spectrum or distinct disorders? J. Affect. Disord., 73, 19–32. 15. Judd, L.L., Akiskal, H.S., Schettler, P.J. et al. (2005) Psychosocial disability in the course of bipolar I and II disorders: a prospective, comparative, longitudinal study. Arch. Gen. Psychiatry, 62, 1322–1330. 16. Judd, L.L., Schettler, P.J., Solomon, D.A. et al. (2008) Psychosocial disability and work role function compared across the long-term course of bipolar I, bipolar II and unipolar major depressive disorders. J. Affect. Disord., 108, 49–58. 17. Judd, L.L., Schettler, P.J., Akiskal, H.S. et al. (2008) Residual symptom recovery from major affective episodes in bipolar disorders and rapid episode relapse/recurrence. Arch. Gen. Psychiatry, 65, 386–394. 18. Judd, L.L., Akiskal, H.S., Maser, J.D. et al. (1998) A prospective 12-year study of subsyndromal and syndromal depressive symptoms in unipolar major depressive disorders. Arch. Gen. Psychiatry, 55, 694–700. 19. Judd, L.L.,and Akiskal, H.S., (2000) Delineating the longitudinal structure of depressive Illness: beyond clinical subtypes and duration thresholds (Anna-Monika-Prize paper). Pharmacopsychiatry, 33, 3–7. 20. Judd, L.L., Akiskal, H.S., Zeller, P.J. et al. (2000) Psychosocial disability during the long-term course of unipolar major depressive disorder. Arch. Gen. Psychiatry, 57, 375–380. 21. Judd, L.L., Akiskal, H.S., Maser, J.D. et al. (1998) Major depressive disorder: a prospective study of residual subthreshold depressive symptoms as predictor of rapid relapse. J. Affect. Disord., 50, 97–108. 22. Judd, L.L., Paulus, M.J., Schettler, P.J. et al. (2000) Does incomplete recovery from first lifetime major depressive episode herald a chronic course of illness? Am. J. Psychiatry, 157, 1501–1504. 23. Judd, L.L. and Akiskal, H.S. (2003) The prevalence and disability of bipolar spectrum disorders in the U.S. population: reanalysis of the ECA database taking into account subthreshold cases. J. Affect. Disord., 73, 123–131. 24. Katz, M.M. and Klerman, G.L. (1979) Introduction: overview of the Clinical Studies Program. Am. J. Psychiatry, 136, 49–51. 25. Katz, M.M., Secunda, S.K., Hirschfeld, R.M. and Koslow, S. H. (1979) NIMH Clinical Research Branch Collaborative Program on the Psychobiology of Depression. Arch. Gen. Psychiatry, 36, 765–771. 26. Spitzer, R.L., Endicott, J. and Robins, E. (1977) Research Diagnostic Criteria for a Selected Group of Functional Disorders, 3rd edn, Biometrics Research Division, New York State Psychiatric Institute, New York. 27. Spitzer, R.L. and Endicott, J. (1979) Schedule for Affective Disorders and Schizophrenia (SADS), 3rd edn, Biometrics Research Division, New York State Psychiatric Institute, New York.

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28. American Psychiatric Association (1994) Diagnostic and Statistical Manual of Mental Disorders: DSM-IV, 4th edn, American Psychiatric Association, Washington, DC. 29. Keller, M.B., Lavori, P.W., Friedman, B. et al. (1987) The Longitudinal Interval Follow-up Evaluation: a comprehensive method for assessing outcome in prospective longitudinal studies. Arch. Gen. Psychiatry, 44, 540–548. 30. Regier, D.A., Myers, J.K., Kramer, M. et al. (1984) The NIMH Epidemiologic Catchment Area (ECA) Program: historical context, major objectives and study population characteristics. Arch. Gen. Psychiatry, 41, 934–941. 31. Regier, D.A., Farmer, M.E., Rae, D.S. et al. (1990) Comorbidity of mental disorders with alcohol and other drug abuse. Results from the Epidemiologic Catchment Area (ECA) Study. JAMA, 264, 2511–2518. 32. Angst, J., Gamma, A., Benazzi, F. et al. (2003) Toward a redefinition of subthreshold bipolarity: epidemiology and proposed criteria for bipolar-II, minor bipolar disorders and hypomania. J. Affect. Disord., 73, 133–146. 33. Goldberg, J.F., Perlis, R.H., Bowden, C.L. et al. (2009) Manic symptoms during depressive episodes in 1.380 patients with bipolar disorder: findings from the STEP-BD. Am. J. Psychiatry, 166, 173–181. 34. Goldberg, J.F., Perlis, R.H., Ghaemi, S.N. et al. (2007) Adjunctive antidepressant use and symptomatic recovery among bipolar depressed patients with concomitant manic symptoms: findings from the STEP-BD. Am. J. Psychiatry, 164, 1348–1355. 35. Salvatore, P., Tohen, M., Khalsa, H.M. et al. (2007) Longitudinal research on bipolar disorders. Epidemiol. Psichiatr. Soc., 16, 109–117. 36. Coryell, W., Fiedorowicz, J., Solomon, D. and Endicott, J. (2009) Age transitions in the course of bipolar I disorder. Psychol. Med., 39, 1247–1252. 37. Akiskal, H.S. and Akiskal, K. (1988) Re-assessing the prevalence of bipolar disorders: clinical significance and artistic creativity. Psychiatrie et Psychobiologie, 3, S29–S36. 38. Akiskal, H.S., Bourgeois, M.L., Angst, J. et al. (2000) Reevaluating the prevalence of and diagnostic composition within the broad clinical spectrum of bipolar disorders. J. Affect. Disord., 59 (suppl 1), S5–S30. 39. Akiskal, H.S. (2002) Classification, diagnosis and boundaries of bipolar disorders, in Bipolar Disorder (eds M. Maj, H.S. Akiskal, J.J. Lopez-Ibor and N. Sartorius), John Wiley & Sons, London, pp. 1–52. 40. Jamison, K.R., Gerner, R.H., Hammen, C. and Padesky, C. (1980) Clouds and silver linings: positive experiences associated with primary affective disorders. Am. J. Psychiatry, 137, 198–202. 41. Hirschfeld, R.M., Calabrese, J.R., Frye, M.A. et al. (2007) Defining the clinical course of bipolar disorder: response, remission, relapse, recurrence, and roughening. Psychopharmacol. Bull., 40, 7–14. 42. Berk, M., Ng, F., Wang, W.V. et al. (2008) The empirical redefinition of the psychometric criteria for remission in bipolar disorder. J. Affect. Disord., 106, 153–158. 43. CME Institute of Physicians Postgraduate Press, Inc. (2008) Easing the burden of bipolar disorder: from urgent situations

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to remission. Prim. Care Companion J. Clin. Psychiatry, 10, 391–402, [also available on-line at psychiatrist.com]. Fountoulakis, K.N. and Vieta, E. (2008) Treatment of bipolar disorder: a systematic review of available data and clinical perspectives. Int. J. Neuropsychopharmacol., 11, 999–1029. Grunze, H., Vieta, E., Goodwin, G.M. et al. (2009) The World Federation of Societies of Biological Psychiatry (WFSBP) guidelines for the biological treatment of bipolar disorders: update 2009 on the treatment of acute mania. World J. Biol. Psychiatry, 10, 85–116. Bowden, C.L. (2005) A different depression: clinical distinctions between bipolar and unipolar depression. J. Affect. Disord., 84, 117–125. Bowden, C.L. (2005) Treatment options for bipolar depression. J. Clin. Psychiatry, 66 (Suppl 1), 3–6. Kemp, D.E., Muzina, D.J., McIntyre, R.S. and Calabrese, J.R. (2008) Bipolar depression: trial-based insights to guide patient care. Dialogues Clin. Neurosci., 10, 181–192. Benazzi, F. (2007) Bipolar II disorder: epidemiology, diagnosis and management. CNS Drugs, 21, 727–740. Dawson, R., Lavori, P.W., Coryell, W.H. et al. (1998) Maintenance strategies for unipolar depression: an observational study of levels of treatment and recurrence. J. Affect. Disord., 49, 31–44. Leon, A.C., Keller, M.B., Warshaw, M.G. et al. (1999) Prospective study of fluoxetine treatment and suicidal behavior in affectively ill subjects. Am. J. Psychiatry, 156, 195–201. Leon, A.C., Solomon, D.A., Mueller, T.I. et al. (2003) A 20-year longitudinal observational study of somatic antidepressant treatment effectiveness. Am. J. Psychiatry, 160, 727–733. Coryell, W., Winokur, G., Solomon, D. et al. (1997) Lithium and recurrence in a long-term follow-up of bipolar affective disorder. Psychol. Med., 27, 281–289. Coryell, W., Solomon, D., Leon, A.C. et al. (1998) Lithium discontinuation and subsequent effectiveness. Am. J. Psychiatry, 155, 895–898. Coryell, W., Arndt, S., Turvey, C. et al. (2001) Lithium and suicidal behavior in major affective disorder: a case-control study. Acta Psychiatr. Scand., 104, 193–197. Kupfer, D.J., Frank, E., Perel, J.M. et al. (1992) Five-year outcome for maintenance therapies in recurrent depression. Arch. Gen. Psychiatry, 49, 769–773. Solomon, D.A., Keitner, G.I., Miller, I.W. et al. (1995) Course of illness and maintenance treatments for patients with bipolar disorder. J. Clin. Psychiatry, 56, 5–13.

58. Keller, M.B. (2004) Improving the course of illness and promoting continuation of treatment of bipolar disorder. J. Clin. Psychiatry, 65 (Suppl 15), 10–14. 59. Frank, E., Kupfer, D.J., Thase, M.D. et al. (2005) Two-year outcomes for interpersonal and social rhythm therapy in individuals with bipolar I disorder. Arch. Gen. Psychiatry, 62, 996–1004. 60. Swann, A.C. (2005) Long-term treatment in bipolar disorder. J. Clin. Psychiatry, 66 (Suppl 1), 7–12. 61. Miklowitz, D.J. and Johnson, S.L. (2006) The psychopathology and treatment of bipolar disorder. Annual Rev. Clin. Psychol., 2, 199–235. 62. Miklowitz, D.J. (2006) A review of evidence-based psychosocial interventions for bipolar disorder. J. Clin. Psychiatry, 67 (Suppl 11), 28–33. 63. Miklowitz, D.J., Otto, M.W., Frank, E. et al. (2007) Intensive psychosocial intervention enhances functioning in patients with bipolar depression: results from a 9-month randomized controlled trial. Am. J. Psychiatry, 164, 1340–1347. 64. Soares-Weiser, K., Bravo Vergel, Y., Beynon, S. et al. (2007) A systematic review and economic model of the clinical effectiveness and cost-effectiveness of interventions for preventing relapse in people with bipolar disorder. Health Technol. Assess., 11, iii–iv, ix–206. 65. Keck, P.E. Jr, McIntyre, R.S. and Shelton, R.C. (2007) Bipolar depression: best practices for the outpatient. CNS Spectr., 12 (Suppl 20), 1–14. 66. Sachs, G.S. (2008) Psychosocial interventions as adjunctive therapy for bipolar disorder. J. Psychiatr. Pract., 14 (Suppl 2), 39–44. 67. Miklowitz, D.J. (2008) Adjunctive psychotherapy for bipolar disorder: state of the evidence. Am. J. Psychiatry, 165, 1408–1419. 68. Frank, E., Soreca, I., Swartz, H.A. et al. (2008) The role of interpersonal and social rhythm therapy in improving occupational functioning in patients with bipolar I disorder. Am. J. Psychiatry, 165, 1559–1565. 69. Solomon, D.A., Keitner, G.I., Ryan, C.E. et al. (2008) Preventing recurrence of bipolar I mood episodes and hospitalizations: family psychotherapy plus pharmacotherapy versus pharmacotherapy alone. Bipolar. Disord., 10, 798–805. 70. Colom, F., Vieta, E., Sanchez-Moreno, J. et al. (2009) Group psychoeducation for stabilised bipolar disorders: 5-year outcome of a randomised clinical trial. Br. J. Psychiatry, 194, 260–265.

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Comorbidity in Bipolar Disorder: A Focus on Addiction and Anxiety Disorders Mark A. Frye1 and Giulio Perugi2 1 2

Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA Department of Psychiatry, University of Pisa; Institute of Behavioural Sciences ‘G. De lisio’, Carrara, Italy

Introduction Bipolar affective disorder is an illness with substantial morbidity and mortality, characterized by episodic recurrence of mania/hypomania and major depression. Our current DMS- IV TR and ICD-10 based diagnoses have operationalized criteria for the specific diagnosis of bipolar I, II, and not otherwise specified with delineating course specifiers and subtype patterns. As recently reviewed by Soreca et al. [1], these criteria fail to capture the dimensional aspects and multisystem involvement of bipolar disorder. Mulitsystem or comorbid symptoms and disease, not defined as core or primary symptoms related to mood disorder, are highly prevalent and clinically relevant in the management of bipolar disorder. Two comorbid conditions that are the focus of this chapter, substance use, particularly alcohol and nicotine dependence, and anxiety disorders, clearly impact the course of bipolar illness.

Alcohol abuse and dependence Since the Kraepelian observation nearly 90 years ago [2], contemporary epidemiologic studies, including the Epidemiologic Catchment Area (ECA) study, the National Comorbidity Study (NCS), the National Comorbidity SurveyReplication (NCS-R) and the National Epidemiological Survey on Alcohol and Related Conditions (NESARC), have reported rates of alcohol abuse or dependence in bipolar disorder that are consistently higher than the general population and/or most other axis I disorders [3–8]. A subscale analysis of the ECA study [3] remarkably showed that BPI and BPII populations had the highest lifetime prevalence rate of alcohol abuse or dependence (46.2 and 39.2%, respectively) followed by schizophrenia (33.7%), panic disorder (28.7%), unipolar depression (16.5%) and the general

Bipolar Disorder: Clinical and Neurobiological Foundations Edited by Lakshmi N. Yatham and Mario Maj © 2010 John Wiley & Sons, Ltd. ISBN: 978-0-470-72198-8

population (13.8%). A lifetime diagnosis of alcohol dependence was associated with significantly increased risk of having mania in both men (Odds ratio ¼ 12.03) and women (Odds ratio ¼ 5.3) [4]. These epidemiological studies suggest that some aspect of bipolar disorder, in comparison to other serious mental illness, is associated with high rates of developing alcoholism. Clinical studies done over the past 50 years [9–13] have confirmed similar lifetime prevalence rates (8–42%). It is important to emphasize that careful assessment for dual diagnosis, ideally with a structured diagnostic interview, is critical to confirm the comorbidity. The diagnosis of bipolar illness in the presence of active substance use, in this case alcohol abuse or dependence, can be made in any or all of the following criteria: (1) the presence of a historical manic, hypomanic or depressed episode while not drinking (DSM-IV early partial or complete remission); (2) a manic, hypomanic or depressed episode that predated the onset of alcohol abuse or dependence; and (3) a manic, hypomanic or depressed episode with high moderate to severe mood symptoms with minimal drinking [14]. This is relevant as a recent study by Stewart and colleagues [15] recently examined clinical diagnoses of bipolar disorder in 21 patients participating in a community-based substance treatment programme and found only 9 out of 21 were found to have concordance with a structured diagnostic interview. A second retrospective analysis by Goldberg and associates [16], of records of 85 adults admitted to a private dual disorders chemical dependency programme, found that only 33% of individuals with suspected bipolar diagnoses actually met DSM-IV criteria, utilizing a structured diagnostic interview. Careful assessment needs to be done to confirm the dual diagnosis. Despite high prevalence rates of alcoholism in bipolar disorder, gender and specific mood state analyses have received less contemporary systematic study. As originally described by Kraepelin in 1921, alcoholism could be found in about a quarter of men with bipolar disorder ‘but it is to be

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regarded as the consequence of debaucheries committed in excitement, not as a cause’. These initial reports underscore the observation that drinking tends to be associated with acute mania. Dipsomania was also a clinical description of increased alcohol consumption during mania [17]. As most of these early studies focused predominantly on male inpatients at VA hospitals, very little is known about bipolar outpatients and bipolar women and mood state dependent drinking behaviour. In more contemporary samples, gender differences in prevalence rate, relative risk and clinical correlates of alcohol dependence in bipolar disorder have been reported. In clinical samples, gender differences in prevalence rate, relative risk and clinical correlates of alcohol dependence in bipolar disorder have been reported. Compared to bipolar men, bipolar women have an increased odds ratio of developing alcohol abuse or dependence compared to gender matched controls [18]. Compared to bipolar alcoholic men, bipolar alcoholic women have increased illness burden characterized by mixed mania, depressive episodes, polarity shifts, less time spent euthymic [18,19], history of physical and/or sexual abuse [20], increased anxiety burden including social phobia, post-traumatic stress disorder [21,22], higher rates of incarceration [23] and a greater number of maximum drinks in a 24-hour period (HallFlavin 2008 [24]). Any and all of these clinical correlates may be the reason that bipolar women do not seek medical attention for the substance use disorder. From the NESARC study, the lifetime prevalence of substance use disorders in bipolar disorder was significantly greater amongst those women with lifetime anxiety disorders; this increased risk was not identified in bipolar men [25]. Whereas it is generally known that women are more likely to seek help than men, the health care utilization pattern of bipolar I men and women with alcohol dependence appears to be different. In a second NESARC post-hoc analysis, bipolar I disorder is more likely to go untreated in men, and addiction treatment is more likely to go untreated in bipolar women. This differential pattern of gender and health care utilization in dual diagnosis patients will be relevant in how we clinically monitor patients in initial diagnostic assessment and longitudinal follow-up. Future studies should be developed to better understand and correct the under-utilization of addiction programmes for patients with bipolar disorder and to identify clinical correlates that predispose bipolar women to binge drinking.

Comorbid alcoholism and bipolar course of illness It is increasingly clear that co-occurring alcohol use disorders in bipolar disorder phenomenologically changes the illness presentation. As reviewed by [26], bipolar patients

with co-occurring alcohol use disorders in comparison to bipolar patients without co-occurring alcohol use disorders have higher rates of mixed or dysphoric mania, rapid cycling, increased manic and depressed symptom severity, and higher levels of novelty seeking, suicidality, aggressivity and impulsivity. Whatever the aetiology of the association, it is apparent that substance use may precede formal symptoms of bipolar illness and subsequently complicate the bipolar course of illness. A case controlled study by Black et al. [27] reported that patients with ‘complicated mania’ (mania accompanied with an antecedent or current nonaffective psychiatric disorder, including alcohol abuse) were significantly less likely to both obtain a therapeutic trial of lithium during hospitalization for mania and achieve recovery at hospital discharge. Poor lithium outcome measures have been consistently reported when bipolar disorder is comorbid with current substance use of even a history of alcoholism ([13,28–30]; Keller et al., 1986 [31]). Interestingly, the Aagaard and Vestergaard study is the only one that identified substance use disorders as predictive of noncompliance, but not non-response. Thus, to date, it is unclear whether the lithium non-responsivity in co-occurring bipolar disorder and alcohol abuse/dependence is related to: (4) lack of aggressive mood stabilization such that subsyndromal symptoms are being self treated with alcohol; (5) side-effect intolerability promoting medication non-compliance and relapse; (6) solely non-compliance promoting relapse; or (7) the high prevalence rate of rapid cycling and dysphoric mania, which by itself, can present with higher rates of lithium failure. Further studies are needed to better identify risk factors of relapse (mood and/or alcohol) and whether, in addition to mood stabilization prophylaxis, aggressive treatment for bipolar illness can be a prophylaxis against alcohol abuse relapse.

Treatment implications for dual diagnosis bipolar disorder and alcoholism Despite landmark epidemiological studies highlighting extensive comorbidity between alcohol use disorders and bipolar disorder, recent retrospective data would suggest that patients with bipolar disorder represent the minority of patients (
3%) in residential alcohol addiction treatment (Hall Flavin et al., unpublished data). These findings are similar to secondary analyses of the NESARC survey that reported that subjects with bipolar I (12.5%) and bipolar II (3%) disorder were a minority representation of subjects who sought treatment for their alcohol use disorder within the past year [32]. Individuals with undiagnosed, unstable or untreated bipolar disorder may be less motivated or viewed as less favourably to successfully engage and benefit

Comorbidity in Bipolar Disorder

from the specialized addiction treatment. Also, access to primary chemical dependency treatment services may be less available because of programme availability or reimbursement issues. It may also be that most chemical dependency treatment programmes, even those targeting the need of those with substantial psychiatric comorbidity, require a degree of behavioural stabilization that may decrease the likelihood of intervention in a chemical dependency setting during a period of acute decompensation, when substance use might be at its peak. Despite a high prevalence rate, patients with bipolar disorder and active alcohol abuse/dependence are routinely excluded from controlled clinical trials, leaving clinicians with little evidence-based medicine or randomized controlled studies to guide treatment. This routine exclusion may be related in part to the difficulties of confirming a diagnosis of bipolar disorder in the context of active drinking, but as well may be due to a lack of hypothesis-driven study designs or a lack of validated assessment tools to reliably quantify patterns of alcohol use.

Nicotine dependence The morbidity and mortality of smoking-related illnesses are substantial. Cigarette smoking is the leading preventable cause of illness and premature death in the United States. This public health problem is only magnified in patients with major mental illness and in particular in patients with bipolar disorder. The National Comorbidity Survey (NCS) reported a 1990–1992 prevalence rate of nicotine dependence amongst individuals with bipolar disorder more than twice (69 vs. 29%) that of the general population [33]. In the more recent 2001–2002 NESARC study, the 12-month prevalence rate of nicotine dependence in patients with bipolar I (35%) and II (33%) disorder was more than three-fold higher than the 12.8% prevalence rate in patients with no psychiatric comorbidity (OR 3.9 BPI, OR 3.5 BPII [7]. It is estimated that dually diagnosed nicotine dependent patients comprise more than 40% of the US tobacco market. The NCS and NESARC landmark epidemiological studies would suggest that while the prevalence of tobacco use has decreased over the course of a decade, the decrease has been less substantial in the bipolar patient population. The NCS quit rate for nicotine dependent patients without additional mental illness was 43%; the quit rate for bipolar disorder was significantly reduced at (17%) and was the lowest of all Axis I diagnoses (panic disorder ¼ 41%, major depression ¼ 38%, dysthymia ¼ 37%, alcohol abuse or dependence ¼ 34%, social phobia ¼ 33%, generalized anxiety disorder ¼ 33%, drug abuse or dependence ¼ 32%, post-traumatic stress disorder ¼ 28%). These reason that patients with bipolar disorder are not benefitting from smoking cessation therapies in the same

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way as the general population or other anxiety disorders is not known.

Bipolar disorder course of illness and nicotine dependence Nicotine impacts the course of bipolar illness in such a way where the illness is more virulent and less response to mood treatment interventions. Bipolar patients with nicotine dependence, in comparison to bipolar patients without nicotine dependence, have higher rates of mixed episodes, suicide attempts, rapid cycling, additional drug and alcohol comorbidity, greater severity of mood symptoms, and lower rates of response to mood stabilizing pharmacotherapy [34–36]. Despite the severity of mania and smoking rates as high as 70% [37], it is clear that when bipolar patients are symptomatic of their illness, they are far more likely to be depressed than manic [38,39]. In comparison to acute mania, bipolar depressive episodes are longer and more likely to be functionally disabling [40]. Recent data would suggest higher rates of hazardous drinking in bipolar patients when depressed (Abulseoud et al., 2008 [41]). To our knowledge, this phenomenon has not been systematically studied with tobacco dependence. Finally, there is increasing recognition that sub-syndromal bipolar depression (significant symptoms but not meeting DSM-IV criteria for major depressive episode) are not only a prodrome to syndromal relapse [37], but they themselves are highly prevalent and functionally disabling [38]. Moreover, subsyndromal depressive symptoms have consistently predicted poorer outcomes in smoking cessation trials (Niaura et al., 2001 [112]). The NCS and NESARC landmark epidemiological studies would suggest that while the prevalence of tobacco use has decreased over the course of a decade, the decrease has been less substantial in the bipolar patient population. This clearly has significant public health implications. It is likely that the presence of nicotine dependence plus limited access to preventative medical services may put bipolar patients at greater risk for cancer. There has been very little systematic study in this regard, but one linkage analysis based on a psychiatric inpatient diagnosis of bipolar disorder and a cancer national database, did report a significant increased standardized incidence ratio (SIR) for cancer in both bipolar women (SIR ¼ 1.75, 95% CI ¼ 1.31 to 2.18) and bipolar men (SIR ¼ 1.59, 95% CI 1.01 to 2.17, [42]). Furthermore, at least one Swedish registry study has reported increased standardized mortality ratios (SMR ¼ observed deaths/expected deaths) for respiratory death in bipolar men (3.1) and women (3.2), respectively [43]. While many of these excess deaths may be directly related to infection, it is generally assumed that these are preventable smokingrelated deaths (i.e. lung cancer, chronic obstructive pulmonary disease).

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Treatment considerations in bipolar disorder with nicotine dependence There has been remarkable progress in developing therapeutic interventions for patients with tobacco dependence [44]. Currently, there are three pharmacotherapies approved by the US Food and Drug Administration (FDA) for smoking cessation: nicotine replacement systems (gum, patch, nasal spray, inhaler and lozenge), sustained release bupropion or Zyban (aminoketone antidepressant also approved for major depression and seasonal affective disorder) and varenicline or Chantix (a4b2 nicotinic acetylcholine receptor partial agonist). According to the Public Health Service-sponsored Clinical Practice Guideline on treatment of tobacco dependence, counselling and behavioural therapies are considered the standard of care for smoking cessation treatment (SCT) [45]. These behavioural interventions have been shown to be effective in combination with smoking cessation pharmacotherapy in the general population [45–48]. In November 2007, the FDA issued an early communication on post-marketing surveillance reports of suicidal thinking associated with varenicline. In February 2008, the FDA issued an alert highlighting revisions to the Warning and Precaution section of the Chantix package insert. These changes are described as neuropsychiatric symptoms and included: behaviour change, agitation, depressed mood, suicidal ideation, and attempted and completed suicide. Most of these symptoms occurred during treatment but in some cases, symptoms developed following withdrawal of varenicline. These surveillance data cannot establish direct cause and effect. To date, there is one case report each for a vareniclineassociated manic and hypomanic episode [49,50]. A recent National Health Service pre-post comparison of abstinence rates by [51] reported 4-week abstinence rates that were higher with varenicline therapy than nicotine replacement therapy. Varenicline was equally effective in those with and without mental illness. In this study of more than 400 subjects, 27% of them (111) reported they were currently receiving treatment for mental illness. Of those, the primary diagnosis were depression (n ¼ 64), bipolar disorder (n ¼ 14), pyschosis (n ¼ 7), psychotic depression (n ¼ 24) and eating disorder (n ¼ 2). This is important preliminary data, suggesting that abstinence rates are similar if not better and that there are no significant adverse events of higher rate in mentally ill dually diagnosed nicotine dependent patients. SCTs need to be developed and optimized for the dually diagnosed. To date, there are no controlled evaluations of any SCT amongst patients with bipolar disorder. Furthermore, the trials of varenicline and other smoking-cessation clinical trials have excluded individuals with bipolar disorder. However, as compared to the general population, smoking cessation has been reported to be more difficult for

many individuals with psychiatric illness [52,53]. This may in part be related to mood symptoms and that for some patients, nicotine is acting as antidepressant. There is preclinical and clinical data documenting that cigarette smokers have reduced monoamine oxidase (MAO) activity [54]; this could potentially be optimized through MAO inibition (i.e. pharmacological mechanism of action of the several antidepressants, such as tranylcopromine or phenelzine). Several [55–57], but not all [58,59] studies in unipolar depression have reported a significant occurrence of depression following smoking cessation; the occurrence of depression seems to be related to a history of prior depressive episodes, persistent withdrawal symptoms and more difficulty with cessation. This has not been studied in bipolar disorder. Comorbidity of bipolar disorder and alcohol use disorder and nicotine dependence is a common clinical presentation and presents with significant challenges. The bipolar course of illness phenomenologically changes when addiction is present. Further work is encouraged to study these specific patterns (i.e. rapid cycling, dysphoric mania) and aetiology of comorbidity directionality (primary vs. secondary drug use) in controlled clinical trials. The question yet to be answered is whether an earlier and/or accurate diagnosis of bipolar disorder can prevent or at least attenuated the degree of subsequent addiction comorbidity or whether bipolar symptoms at onset that are diagnosed and treated can in fact attenuate or minimize the development of addiction comorbidity as a later manifestation of bipolar illness and the impact of self-medication.

Anxiety disorders Epidemiological, clinical and familial studies provide compelling evidence that anxiety disorders (ADs) may be the most prevalent psychiatric comorbidity amongst patients with Bipolar Disorder (BPD). Moreover, anxious comorbidity in individuals with BPD is associated with an intensification of symptoms, increased risk of alcohol and drug abuse, inadequate treatment response, poor functional outcome and suicidality.

Epidemiological and clinical data The reliability of lay interviewers diagnosing ADs in community-based samples is well established, while the reliability of identifying BPD cases with a predominantly mixed/dysphoric presentation is not ideal with the currently available diagnostic interviews [6,60]. Clinical studies indicate that AD comorbidity may be more prevalent in mixed and ‘softer’ expressions of BPD (or bipolar spectrum) [61–63], suggesting that community-based epidemiological studies may underestimate the prevalence of AD comorbidity in BPD subpopulations.

Comorbidity in Bipolar Disorder

Chen and Dilsaver [64], analysing the ECA database, reported lifetime rates of OCD amongst probands with bipolar and unipolar disorder of 21.0 and 12.2%, respectively. Furthermore, a significant association between comorbid OCD and suicidality was reported. In the NCS [5,65], the estimated lifetime prevalence of any AD in BPD was estimated at 92.9% (odds ratio, OR ¼ 31.2). Specific phobia was the most prevalent AD comorbidity (66.6%). while Panic Disorder (PD) was the least prevalent (33.1%). The reported risk of comorbid PD and Social Phobia (SoP) is higher in BPD (Odds Ratios of 11.0 vs. 4.6, respectively) compared to unipolar disorder (Odds Ratios of 7.0 vs. 3.6, respectively). In a European sample, (Angst, 1998 [113]) reported higher rates of comorbidity with PD, SoP and Obsessive-Compulsive Disorder (OCD) in subjects meeting DSM-IV hypomania, recurrent brief hypomania and sporadic brief hypomania compared to population controls. In summary, results from community-based epidemiological studies indicate that respondents screening positive for BPD are also more likely to screen positive for an AD. The co-occurrence of AD in BPD populations is associated with suicidality and possibly an earlier age of onset of bipolar illness. Concerning clinical studies, several investigations have reported on the prevalence of ADs amongst bipolar patients. Rihmer et al. [66] described the prevalence of AD comorbidity amongst 2953 primary care patients with a diagnosable mood disorder. The estimated prevalence of any comorbid AD was lowest amongst persons with BPD-I and highest in the BPD-II patient group. The prevalence of comorbid ADs for the MDD group was intermediary between the two BPD subgroups. This finding is consistent with the observation that softer expressions of BPD are often camouflaged as anxious depression in the primary care setting [67]. MacQueen et al. [68] reported that the prevalence of any AD comorbidity in BPD was higher in subsyndromal (80.6%) than in syndromal (54%) and euthymic (38.6%) phases. In contrast, Dilsaver and Chen [69] reported that SoP and PD presenting during a bipolar episode were highly associated with suicidality, particularly in depressive phases. These observations suggest that in some patients, anxiety comorbidity is most pronounced at the extremes of affective excursions, while in others, anxiety may present primarily as an ‘interepisodic’ disturbance. McElroy et al. [70] reported anxiety (n ¼ 122, 42%) and substance use disorders (n ¼ 122, 42%) as the most frequent lifetime comorbid disorders in BPD. There was no significant difference in AD comorbidity between patients with BPD-I and BPD-II. The reported lifetime and current prevalences of ‘any AD’ was 42 and 30%, respectively. Lifetime Axis I comorbidity was associated with early age of onset of

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BPD symptoms, progressive severity of illness and a family history of alcoholism and drug abuse. Current anxiety comorbidity was also associated with reduced occupational functioning, a history of rapid cycling and a shortening of well intervals. The prevalence of AD and its correlates was investigated in the first 500 patients (BPDI n ¼ 360, BPDII n ¼ 115) enrolled in the Systematic Treatment Enhancement Program for BPD (STEP-BPD) [22]. The prevalences of any lifetime AD for the entire sample were greater amongst patients with BPD-I (51.2%) versus BPD-II (30.5%). The age of onset of BPD was significantly lower for patients with any lifetime AD than in patients without AD (15.6 vs. 19.4 years, respectively). Patients with a lifetime AD also had less education, shorter time euthymic, lower rates of recovery and elevated rates of lifetime suicide attempts. It was also reported that BPD with comorbid ADs had a higher prevalence of alcohol and substance use disorders. The presence of multiple ADs was independently associated with added impairment in quality of life and functioning. Consistently with other reports, the presence of a lifetime AD was significantly associated with an increased number of suicide attempts [22]. The association between ADs and alcohol and substance use disorders is an additional theme that emanates from the BPD literature. Bauer et al. [71] examined the prevalence and the correlates of comorbid substance use disorders and ADs in a sample of inpatients with BPD (n ¼ 348). ADs were associated with earlier age at onset, rapid cycling, higher probability of reporting depressive symptoms, higher rates of prior suicide attempts, greater number of prior-year episodes, higher severity of illness scores and lower quality of life. The negative effect of ADs in BPD was particularly evident in patients with BPD who also had a comorbid substance abuse disorder. Goodwin et al. [72] also reported the association between AD and substance use disorders in BPD. In particular, PD was associated with an increased prevalence of cocaine, sedative and stimulant use disorders. Relatively fewer studies have reported the prevalence of BPDs amongst AD populations. ADs are often a phenomenological antecedent to overt BPD; this calls for careful screening for BPD amongst children and adolescents reporting to health care providers with prominent anxiety symptoms [73]. A history of manic or hypomanic episodes has been observed in patients with PD-Agoraphobia [74]. The development of mania or hypomania in response to treatment with serotonin reuptake inhibitors has also been widely described in OCD case series and reports [75,76]. In a clinical study of 345 outpatients with OCD [77], lifetime comorbidity with BPD (primarily bipolar II) was 16%. Finally, patients with SoP have been found to have high rates of BPD (Himmeloch, 1998 [114]). In a Pisa-San Diego collaborative study [62,63], major depression was the most common comorbid disorder in a

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large sample of patients with AD. However, bipolar II disorder resulted widely associated with SoP (21.1%), OCD (17.7%) and in a lesser extent with PD (5.0%). The relative neglect in clinical and epidemiological research for the comorbidity between bipolar spectrum disorders and AD is especially due to underdiagnosis of bipolar II disorders (often misdiagnosed as unipolar or personality disorders) in patients with AD. It has been documented that current official diagnostic systems grossly underestimate bipolar II and related disorders and that clinicians specifically trained in bipolar II outperformed routine interviewers in such structured interviews as the SADS or the SCID [78]. Although this point goes against the grain in the literature on structured interviewing, it is consistent in suggesting that the proper identification of BPDII requires a more sophisticated approach in diagnosis.

Comorbid ADs and clinical presentation of bipolar disorder The co-occurrence of BPD and ADs seems to result in something more complex than a simple add-on effect. Multiple comorbidity and consequent symptomatological instability appear as the most relevant consequence of the anxious-bipolar co-existence [62,63]. Because of that, many of these patients receive diagnoses of borderline, narcisistic, histrionic personality disorders that in some cases prevent them from receiving adequate pharmacological treatment [79]. Increased risk of mixed states, suicidal behaviour and alcohol and drug abuse are other important prognostic implications. ADs are associated with multiple indices of poor outcome in BPD. Gaudiano and Miller [80] evaluated comorbid ADs in BPD patients, and their association with bipolar illness severity, chronicity and treatment response. Patients with BPD-AD were more likely to report severe depression, chronic illness course and negative treatment outcomes. Henry et al. [81] also reported that ADs comorbidity was associated with an earlier age of BPD onset and lower response to anticonvulsants. Boylan et al. [82] observed that BPD patients with comorbid AD had an earlier age at onset, higher frequency of rapid cycling and a higher usage of benzodiazepine treatment. Moreover, BPD patients with comorbid ADs had significantly higher rates of substance abuse or dependence, illness severity and chronicity, and a lower mean Global Assessment of Functioning (GAF) score. Different temporal relationship seems to characterize the occurrence of hypomania in individual AD subtypes [83]. Usually SoP chronologically preceded hypomanic episodes and disappeared when the latter episodes supervened. By contrast, PD and OCD symptomatology, even when preceding hypomanic episodes, often persisted during such episodes. Interestingly, a relevant proportions

of all onsets of panic attacks, in patients with comorbid PD and BPD, were during (hypo)mania [83]. These findings are consistent with the hypothesis that, at least in some patients, SoP, and to some extent OCD, seem to lie on a broad affective continuum of inhibitory restraint versus disinhibited hypomania. By contrast, PD, in the context of an (hypo)manic episode, might be interpreted as a dysphoric or mixed evolution of the symptomatology. In order to confirm these observations, further investigations should focus on the prospective assessment of patients with concomitant ADS and BPD. Indeed, retrospective methodology utilized in most clinical studies makes it difficult to ascertain the extent to which antidepressants, the most common treatment for severe AD, could explain the anxiety-bipolar comorbidity. Investigations on differential patterns of comorbidity may provide important information in distinguishing more homogeneous clinical subtypes of affective disorders from the biological, genetic and therapeutic point of view. Preliminary evidence support the hypothesis that differential risk for PD comorbidity is a promising tool in order to discern heterogeneous genetic subtypes of BPD. MacKinnon et al. [84] evaluated 528 members of 57 families ascertained for a genetic linkage study of bipolar disorder. Out of 57 bipolar probands, 10 had comorbid PD; in their relatives PD co-segregated with bipolar disorder (in particular Bipolar II and cyclothymia) at a significantly higher rate than expected by chance, suggesting that comorbid PD might be a specific marker for a familial subtype of BPD. Bipolar OCD patients represent more frequently than the non-bipolar, abuse of alcohol, sedatives, stimulants and caffeine, as well as episodic course of the AD, a greater number of major depressive episodes and suicide attempts). Moreover, they currently reported significantly higher rate of sexual obsessions and a significantly lower rate of order rituals [85]. These observations would seem to indicate that bipolar comorbidity has a strong influence on the longitudinal course and complications of OCD. In particular, long-term episodic course of OCD resulted, related to family history for mood disorders, lifetime comorbidity for panic and bipolar II disorders and late age at onset. Evidence based on a single family pedigree [86] suggests a genetic linkage between OCD and BPD, while other studies indicate increased prevalence of OCD in bipolar probands and high rates of obsessional traits in the offspring of bipolar probands [87]. Coryell [88] reported an equal incidence (2.3%) of mania in families of probands with OCD and in families with a bipolar disordered member. These findings are consistent with the hypothesis that, at least in some cases, episodic course of OCD is related to cyclical affective disorders. In a more theoretical vein, episodic OCD symptoms, in a substantial minority of cases, may be considered the phenotypic expression of an underlying affective genotype.

Comorbidity in Bipolar Disorder

As regards the relationships between SoP and BPD, in a clinical study by Himmelhoch [89], 18 patients with FS had a significant improvement of social anxiety after a treatment with MAOI (phenelzine) and RIMA (moclobemide). Out of 32 of these subjects, 14, along with the complete remission of social phobic symptomatology, developed a hypomanic episode, both according to clinical judgement and structured evaluation. On the basis of this observation, the author hypothesized that SoP might actually belong, at least in some cases, to a bipolar spectrum. It is notable that Himmelhoch concluded that social phobia’s special relationship with bipolar II disorder became evident only when social anxiety was ‘perturbed by the central actions of stimulating antidepressants’. Protracted social anxiety may represent, along with inhibited depression, the opposite of hypomania. Moreover, the increased susceptibility to alcohol use in some patients with SP might be related more to the presence of a bipolar diathesis [90,91], with marked reactivity to the ethanol, than to the social-phobic symptomatology per se. This hypothesis is compatible with the observation of Himle et al. [92], on SoP patients without a comorbid BPD, where alcohol use did not reduce social anxiety in performance situations and was not associated by better performance. The socializing and disinhibiting effect that many SoP patients report with alcohol use might therefore be mediated by increased confidence as part of hypomania facilitated by alcohol. The correct identification of SoP-bipolar comorbidity has relevant clinical implications as far as other concomitant disorders, symptomatological features, course and complications are concerned. Severity and generalization of the SoP symptoms, multiple comorbidity and alcohol abuse appear to be the most relevant consequences of SoPbipolar coexistence. Likewise, clinicians must investigate whether or not BPD is a comorbid condition in patients presenting with SoP. The suspicion of bipolar comorbidity should be even greater if patients presented multiple comorbidity or have been previously refractory to treatment. In summary, comorbidity with ADs in the bipolar spectrum population is associated with several indices of severity, such as a more severe subtypes of BPD, an earlier age at onset, mixed state presentations, an intensification of symptoms, poor symptomatic and functional recovery, higher rates of alcohol and substance use disorders, suicidal behaviour, diminished response to pharmacological treatment, decreased quality of life and unfavourable course and outcome.

Treatment implications of anxious comorbidity The lack of information about anxious-bipolar connections may have a negative impact on treatment choice and man-

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agement. Most of the controlled trials on BPD excluded patients with comorbid ADs and vice versa; as a consequence, the empirical basis for treating patients with anxious-bipolar comorbidity are almost exclusively founded on anecdotal reports and open clinical experiences. Overall, lithium has not been studied in AD. Some useful suggestions can be derived from clinical experiences with mood stabilizers and anti-AD agents. Bipolar patients with high anxiety ratings are less likely to respond to lithium [93]. The association of anxiety with suicidality, and less favourable treatment responses in BPD patients, has been consistently reported [22,94]. Feske et al. [94] examined the correlates of acute treatment response in 124 BPD-I patients. Anxiety symptomatology was associated with a longer time to remission in both depression and mania. Moreover, nonremitting patients were more likely to report a history of panic attacks, current or past anxiety, more severe depression and a greater number of previous affective episodes. Patients reporting a history of panic attacks also required a higher mean number of medications to achieve symptomatic remission. Controlled data suggests valproate may be more effective than lithium in mania associated with depressive features, even when the depressive features are mild [95]. Since anxiety symptoms are often seen in mixed states and may even be related to depression in mania, future studies should evaluate anxious features as possible predictors of response of mania to valproate (and other antimanic agents). Regarding AD, valproate has been used successfully in the treatment of panic disorder [96]. In addition, in an open-label study, Calabrese and Delucchi [97] noted 6that rapid-cycling BPD patients with comorbid panic attacks described reduction in their panic symptoms with valproate treatment. In addition, one open-label study [98] and one case report [99] have suggested that valproate may be helpful in the treatment of some patients with OCD, especially those with associated bipolar or epileptiform features. As regards the use of carbamazepine in AD, Uhde et al. [100] did not find carbamazepine to be an efficacious treatment for panic disorder in a double-blind, placebocontrolled study of 14 patients. In OCD, Koopowitz and Berk [101] reported beneficial results with the use of carbamazepine in two patients, while Swinson and Joffe [102] found carbamazepine was ineffective in an open-label study. Gabapentin has shown preliminary evidence of efficacy in the treatment of anxiety but not BPD. In ADs, Gabapentin has been shown to be superior to placebo in one small controlled study on SoP [103], and in another controlled study on severe PD [104]. The predictors of response to gabapentin as adjunctive treatment has been evaluated in 43 patients with BPD, who were resistant to standard moodstabilizers [90,91]. Gabapentin was administered as an

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adjunctive treatment for an eight-week period, in combination with other mood stabilizers, benzodiazepines, antidepressants and neuroleptics. Of 43 patients, 18 (41.9%), who began treatment, were considered responders; in particular gabapentin showed antidepressant and anxiolytic properties. Comorbid PD and alcohol abuse (and to a lesser extent SoP) were the best predictors of response. This finding might has relevant clinical implications as concern the treatment of anxious bipolar comorbidity, but it should be confirmed in controlled clinical trials. As regard anti-anxiety agents, Benzodiazepines are relatively safe and well tolerated when used in combination with mood stabilizers. However, long-term benzodiazepine use may be problematic in most patients, due to development of tolerance, physical dependence and withdrawal phenomena. Antidepressants are often used in the treatment of AD and bipolar depression. However, these compounds may worsen the course of the mood disorder by precipitating mania, mixed states, or rapid cycling (for review see [105]). Antidepressant-induced (hypo)manic symptoms have been reported to occur specifically in the course of treatment of virtually all AD, including obsessive compulsive disorder, panic disorder, and social phobia [106,107,114]. In BPD, prophylactic treatment with mood stabilizers may prevent antidepressant-induced switching [107,108]. When treating comorbid bipolar and AD, it is imperative to begin treatment with a mood stabilizer. Indeed, initiating an antidepressant before adequate mood stabilization has been achieved could worsen the anxiety symptoms by exacerbating the BPD. The efficacy of typical and atypical antipsychotics in the treatment of primary or comorbid AD or anxiety symptoms in major depressive or bipolar disorders was recently reviewed [109]. Six trials in primary generalized anxiety disorder (GAD), 15 in refractory OCD, 8 in posttraumatic stress disorder (PTSD), 6 in neurosis with the HAM-A, 1 in SoP and 2 in anxiety symptoms in bipolar depression were identified. Gao et al. [109] concluded that, except for trifluoperazine, there is no large, well-designed study of antipsychotics in the treatment of primary or comorbid anxiety symptoms or disorders. Most of the less welldesigned studies showed that other typical antipsychotics might be superior to placebo or as effective as benzodiazepines in the treatment of GAD and other anxiety conditions. In most studies, risperidone, olanzapine and quetiapine augmentation to antidepressants was superior to placebo in treating refractory OCD and PTSD. Both olanzapine and quetiapine significantly reduced anxiety, compared to placebo in studies of bipolar depression. The efficacy of these agents in various anxiety conditions needs to be further investigated with large, well-designed comparison studies.

In the treatment of comorbid BPD and PD, it appears reasonable to utilize as a first choice mood stabilizers who have been shown to possess some antipanic efficacy, such as valproate or adjunctive gabapentin. In patients with persistent and disabling ADs, the combination with antidepressants can be considered. Less information is available for comorbid BPD and SoP. A small positive study on gabapentin in SoP seems indicate the possible efficacy of this drug [103]. The combination of mood stabilizers such as lithium, valproate and carbamazepine with SSRIs, RIMAs or IMAOs might reduce the number of switches in these patients. However, there is almost no information on long-term outcome of patients with comorbid BPD and SoP treated with drug combinations. Bipolar OCD are amongst the most difficult patients to treat. No mood stabilizers has been shown to exert any antiOCD activity, and the effective anti-OCD pharmachological treatments (high doses of clomipramine or SSRIs) have high potential for inducing (hyo)manic switches and increasing cyclicity in BPD patients. Combination of different mood stabilizer (lithium plus antiepileptics) is often necessary, and in some cases the combination with antidepressants supposed less likely to induce rapid-cycling (i.e. MAOIs) can be utilized. However, many of these patients present residual OCD symptomatology and very severe manic or mixed episode (aggressive, hostile mood) that may require hospitalization. In some cases the combination with atypical antipsychotics (risperidone, olanzapine, quetiapine or aripiprazole) can be taken into account. Indeed, even if in some cases atypical antipsychotics has been reported to exacerbate OCD symptomatology [110,111], in others these drugs display a mood-stabilizing, anti-aggressive activity, which permit also an effective treatment of OCD symptoms. In summary, the coexistence of anxiety and bipolar spectrum disorders is a substantial clinical issue affecting a large number of patients. The frequent comorbidity between BPD and ADs has also been reported in epidemiologic samples and primary care setting, indicating that clinical referral bias is unlikely to be the main explanation for this phenomenon. Accurate diagnosis is a central concern, in patients presenting with BPD, the clinician must screen for all ADs. Likewise, clinicians must investigate whether or not BPD is a comorbid condition in patients presenting with AD. The suspicion of bipolar comorbidity should be even greater if patients presented multiple ADs, alcohol or substance abuse or have been previously refractory to treatment. The correct identification of anxious-bipolar comorbidity has relevant clinical implications as far as BPD symptomatology, course and complications are concerned. Symptomatological instability, multiple comorbidity, in particular alcohol and substance abuse, and suicidality appear as the

Comorbidity in Bipolar Disorder

most relevant consequences of anxious-bipolar coexistence. No firm recommendations can be made as to which mood stabilizer would be best for which BPD patient, based on his or her particular comorbid AD. Nonetheless, several impressions emerge from the available literature. Generally, the data support the use of valproate as the mood-stabilizer of choice for patients with comorbid PD and possibly OCD, especially if associated with prominent anxiety symptoms, mixed features and/or rapid cycling. Antidepressants, while proven effective in PD, OCD and SP, may worsen the course of BPD, especially if initiated before treatment with a moodstabilizer. If antidepressants are to be used in patients with concurrent BPD and ADs, adequate mood stabilization should first be achieved, and antidepressants then added cautiously while patients are monitored carefully for emerging symptoms of hypomania or mania. Atypical antipsychotics are widely utilized as mood stabilizing agents. On the other hand, they have not yet been systematically studied in AD, and have been hypothesized to exacerbate PD and OCD because of their serotonergic antagonistic properties.

Conclusion The use of the term comorbidity in psychiatry is questionable and raises fundamental questions regarding the validity of the utilized diagnostic criteria and classification system. The study of comorbidity in BD, however, provides an opportunity to address important clinical and research questions. Epidemiological and clinical studies have documented the high lifetime rates and risks related to substance use and AD comorbidity in BD patients. This triad of diagnoses is associated with several indices of BD severity such as earlier age at onset, mixed presentations, severity of symptoms, poor symptomatic and functional recovery, suicidal behaviour, diminished acute response to pharmacological treatment, decreased quality of life and an unfavourable course and outcome. Comorbidity of BPD with substance use disorders and AD can be challenging to diagnose and optimally treat. Further work is encouraged to study these specific patterns (i.e. rapid cycling, dysphoric mania) and aetiology of comorbidity directionality (primary vs. secondary drug use) in controlled clinical trials. The identification of temporal priority in comorbid BD may provide a more refined view of the association between BD and comorbid syndromes. Coexisting conditions, whose onset precedes BD, often occurring with AD, may obscure essential elements of the primary diagnosis, thus diminishing the possibility of early detection and timely intervention. A question yet to be answered is whether an earlier and/or accurate diagnosis of BPD can

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prevent or at least attenuate the degree of subsequent substance use disorder or whether bipolar symptoms at onset that are diagnosed and treated can in fact attenuate or minimize the development of addiction as a later manifestation of bipolar illness. Finally, despite intensified efforts to clinically characterize substance use and anxiety comorbidity in BD, the empirical base informing therapeutic decisions in the comorbid bipolar patient remains largely inadequate, as a consequence of the routine exclusion of patients with such a comorbidity from the largest randomized clinical trials for all phases of bipolar illness.

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population but do not necessarily hamper smoking cessation. J. Clin. Psychiat., 65 (2), 169–176. Hirschfeld, R.M., Williams, J.B., Spitzer, R.L. et al. (2000) Development and validation of a screening instrument for bipolar spectrum disorder: the Mood Disorder Questionnaire. Am. J. Psychiatry, 157, 1873–1875. Shoaib, A.M. and Dilsaver, S.C. (1995) Panic disorder in subjects with pure mania and depressive mania. Anxiety, 1, 302–304. Perugi, G., Toni, C. and Akiskal, H.S. (1999) AnxiousBipolar comorbidity: diagnostic and treatment challenges. Psychiat. Clin. N. Am., 22 (3), 565–583. Perugi, G., Akiskal, H.S., Ramacciotti, S. et al. (1999) Depressive comorbidity of panic, social phobic and obsessive-compulsive disorders re-examined: is there a bipolar connection? J. Psychiat. Res., 33, 53–61. Chen, Y.W. and Dilsaver, S.C. (1995) Comorbidity for obsessive-compulsive disorder in bipolar and unipolar disorders. Psychiatric Res., 59, 57–64. Kessler, R. (1999) Comorbidity of unipolar and bipolar depression with other psychiatric disorders in a general population survey, in Comorbidity in Affective Disorders (ed. M. Tohen), Marcel Dekker Inc., New York, pp. 1–25. Rihmer, Z., Szadoczky, E., Furedi, J. et al. (2001) Anxiety disorders comorbidity in bipolar I, bipolar II and unipolar major depression: results from a populationbased study in Hungary. J. Affect. Disord., 67 (1–3), 175–179. Manning, J.S., Haykal, R.F., Connor, P.D. and Akiskal, H.S. (1997) On the nature of depressive and anxious states in a family practice setting: The high prevalence of bipolar II and related disorders in a cohort followed longitudinally. Compr. Psychiatry, 38, 102–108. MacQueen, G.M., Marriott, M., Begin, H. et al. (2003) Subsyndromal symptoms assessed in a longitudinal, prospective follow-up of a cohort of patients with bipolar disorder. Bipolar Disord., 5, 349–355. Dilsaver, S.C. and Chen, Y.W. (2003) Social phobia, panic disorder and suicidality in subjects with pure and depressive mania. J. Affect. Disord., 77, 173–177. McElroy, S.L., Altshuler, L.L., Suppes, T. et al. (2001) Axis I psychiatric comorbidity and its relationship to historical illness variables in 288 patients with bipolar disorder. Am. J. Psychiatry, 158, 420–426. Bauer, M.S., Altshuler, L., Evans, D.R. et al. (2005) for the VA Cooperative Study # 430 Team. Prevalence and distinct correlates of anxiety, substance and combined comorbidity in a multi-site public sector sample with bipolar disorder. J. Affect. Disord., 85, 301–315. Goodwin, R.D., Stayner, D.A., Chinman, M.J. et al. (2002) The relationship between anxiety and substance use disorders among individuals with severe affective disorders. Compr. Psychiatry, 43, 245–252. Masi, G., Perugi, G., Millepiedi, S. et al. (2007) Clinical and research implications of panic-bipolar comorbidity in children and adolescents. Psychiatry Res., 153 (1), 47–54.

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74. Savino, M., Perugi, G., Simonini, E. et al. (1993) Affective comorbidity in panic disorder: is there a bipolar connection? J. Affect. Disord., 28, 155–163. 75. Rhimer, Z., Barsi, J., Belso, N. et al. (1996) Antidepressant induced hypomania in obsessive-compulsive disorder. Int. Clin. Psychopharm., 11, 203–205. 76. Kruger, S., Cooke, R.G., Hasey, G.M. et al. (1995) Comorbidity of obsessive-compulsive disorder in bipolar disorder. J. Affect. Disord., 34, 117–120. 77. Perugi, G., Akiskal, H.S., Pfanner, C. et al. (1997) The clinical impact of bipolar and unipolar affective comorbidity on obsessive-compulsive disorder. J. Affect. Disord., 46, 15–23. 78. Dunner, D.L. and Kai Tay, L. (1993) Diagnostic reliability of the history of hypomania in bipolar II patients with major depression. Compr. Psychiatry, 34, 303–307. 79. Perugi, G. and Akiskal, H.S. (2002) The soft bipolar spectrum redefined: focus on the cyclothymic, anxious-sensitive, impulse-dyscontrol and binge-eating connection in Bipolar II and related conditions. Psychiatr. Clin. North Am., 25 (4), 713–737. 80. Gaudiano, B.A. and Miller, I.W. (2005) Anxiety disorder comorbidity in bipolar I disorder: relationship to depression severity and treatment outcome. Depress Anxiety, 21, 71–77. 81. Henry, C., Bulke, D., Bellivier, F. et al. (2003) Anxiety disorders in 318 bipolar patients: prevalence and impact on illness severity and response to mood-stabilizers. J. Clin. Psychiatry, 64, 331–335. 82. Boylan, K.R., Bieling, P.J., Marriott, M. et al. (2004) Impact of comorbid anxiety disorders on outcome in a cohort of patients with bipolar disorder. J. Clin. Psychiatry, 65, 1106–1113. 83. Perugi, G., Akiskal, H.S., Toni, C. et al. (2001) The temporal relationship between anxiety disorders and (hypo)mania: a retrospective examination of 63 panic, social phobic and obsessive-compulsive patients with comorbid bipolar disorder. J. Affect. Disord., 67, 199–206. 84. MacKinnon, D.F., McMahon, F.J., Simpson, S.G. et al. (1997) Panic Disorder with familial bipolar disorder. Biol. Psychiatry, 42, 90–95. 85. Perugi, G., Akiskal, H.S., Gemignani, A. et al. (1998) Episodic course in obsessive compulsive disorder. Eur. Arch. Psychiatr. Clin. Neurosci., 248, 240–244. 86. Dilsaver, S.C. and White, K. (1986) Affective disorder and associated psychopathology: a family history study. J. Clin. Psychiatry, 47, 162–169. 87. Klein, D.N., Depue, R.A. and Slater, J.F. (1985) Inventory identification of cyclothymia. IX. Validation in offspring of bipolar I patients. Arch. Gen. Psychiatry, 43, 441–445. 88. Coryell, W. (1981) Obsessive compulsive disorder and primary unipolar depression. J. Nerv. Ment. Dis., 169, 220–224. 89. Himmelhoch, J.M. (1998) Social Anxiety, hypomania and the bipolar spectrum: data, theory and clinical issues. J. Affect. Disord., 50, 203–213. 90. Perugi, G., Toni, C., Frare, F. et al. (2002) Effectiveness of adjunctive gabapentin in resistant bipolar disorder: is it due to anxious-alcohol abuse comorbidity? J. Clin. Psychopharmacol., 22 (6), 584–591.

91. Perugi, G., Frare, F., Madaro, D. et al. (2002) Alcohol Abuse In Social Phobic Patients: Is There A Bipolar Connection? J. Affect. Disord., 68, 33–39. 92. Himle, J.A., Abelson, J.L., Haghightgou, H. et al. (1999) Effect of alcohol on social phobic anxiety. Am. J. Psychiatry, 156, 1237–1243. 93. Young, L.T., Cooke, R.G., Robb, J.C. et al. (1993) Anxious and non-anxious bipolar disorder. J. Affect. Disorder, 29, 49–52. 94. Feske, U., Frank, E., Mallinger, A.G. et al. (2000) Anxiety as a correlate of response to the acute treatment of bipolar I disorder. Am. J. Psychiatry, 157, 956–962. 95. Swann, A.C., Bowden, C.L., Morris, D. et al. (1997) Depression during mania: treatment response to lithium or divalproex. Arch. Gen. Psychiatry, 54, 37–42. 96. Lum, M., Fontaine, R., Elie, R. and Ontiveros, A. (1990) Divalproex sodium’s anti-panic effect in panic disorder: a placebo-controlled study. Biol. Psychiatry, 27, 164A–165. 97. Calabrese, J.R. and Delucchi, G.A. (1990) Spectrum of efficacy of valproate in 55 patients with rapid-cycling bipolar disorder. Am. J. Psychiatry, 147, 431–434. 98. Deltito, J.A. (1994) Valproate pretreatment for the difficultto-treat patient with OCD. J. Clin. Psychiatry, 55, 500. 99. Cora-Locatelli, G., Greenberg, B.D., Martin, J.D. and Murphy, D.L. (1998) Valproate monotherapy in an SRI-intolerant OCD patient. J. Clin. Psychiatry, 59, 82. 100. Uhde, T.W., Stein, M.B. and Post, R.M. (1988) Lack of efficacy of carbamazepine in the treatment of panic disorder. Am. J. Psychiatry, 145, 1104–1109. 101. Koopowitz, L.F. and Berk, M. (1997) Response of obsessive compulsive disorder to carbamazepine in two patients with comorbid epilepsy. Ann. Clin. Psychiatry, 9, 171–173. 102. Swinson, R.P. and Joffe, R.T. (1987) Carbamazepine in obsessive-compulsive disorder. Biol. Psychiatry, 22, 1169–1171. 103. Pande, A.C., Davidson, J. and Jefferson, J. (1999). Treatment of social phobia with gabapentin: a placebo controlled study. J. Clin. Psychopharm., 19, 341–348. 104. Pollack, M.H., Matthews, J. and Scott, E.L. (1998) Gabapentin as a potential treatment for anxiety disorders. Am. J. Psychiatry, 155 (7), 992–993. 105. Ghaemi, S.N., Wingo, A.P., Filkowski, M.A. and Baldessarini, R.J. (2008) Long-term antidepressant treatment in bipolar disorder: meta-analyses of benefits and risks. Acta Psychiatr. Scand., 118 (5), 347–356. 106. Sholomskas, A.J. (1990) Mania in a panic disorder patient treated with fluoxetine. Am. J. Psychiatry, 147, 1090–1091. 107. Jann, M.W., Bitar, A.H. and Rao, A. (1982) Lithium prophylaxis of tricyclic-antidepressant-induced mania in bipolar patients. Am. J. Psychiatry, 139 (5), 683–684. 108. Kane, J.M., Quitkin, F.M., Rifkin, A. et al. (1982) Lithium carbonate and imipramine in the prophylaxis of unipolar and bipolar II illness. Arch. Gen. Psychiatry, 39, 1065–1069. 109. Gao, K., Muzina, D., Gajwani, P. and Calabrese, J.R. (2006) Efficacy of typical and atypical antipsychotics for primary

Comorbidity in Bipolar Disorder and comorbid anxiety symptoms or disorders: a review. J. Clin. Psychiatry, 67 (9), 1327–1340. 110. Baker, R.W., Chengappa, K.N., Baird, J.W. et al. (1992) Emergence of obsessive compulsive symptoms during treatment with clozapine. J. Clin. Psychiatry, 53 (12), 439–442. 111. de Haan, L., Beuk, N., Hoogenboom, B. et al. (1997) Obsessive-compulsive symptoms during treatment with olanzapine and risperidone: a prospective study of 113 patients with recent-onset schizophrenia or related disorders. J. Clin. Psychiatry, 58, 119–122.

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112. Niaura R, Britt DM, Shadel WG, Goldstein M, Abrams D, & Brown R. (2001). Symptoms of depression and survival experience among three samples of smokers trying to quit. Psychology of Addictive Behaviors, 15, 13–17. 113. Angst, J. (1998) The emerging epidemiology of hypomania and bipolar II disorder. J. Affect. Disord., 50 (2-3), 143–151. 114. Himmelhoch, J.M. (1998) Social anxiety, hypomania and the bipolar spectrum: data, theory and clinical issues. J. Affect. Disord., 50 (2–3), 203–213.

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DSM-V Perspectives on Classification of Bipolar Disorder Jan Fawcett Department of Psychiatry, University of New Mexico School of Medicine, Albuquerque, NM, USA

It is customary to periodically revise our diagnostic system in the field of psychiatry. This custom is justified on the assumption that over a period of time new information is developed. DSM classifications have been updated over time, periods ranging from 7 to 12 years or more in response to new information concerning the course, treatment response and more recently the familial transmission, genetic factors, biological markers and even neural substrates associated with specific diagnostic categories, as research efforts at all levels yield more information. There is also an implicit assumption that from use of the established criteria in clinical practice and research over time, ‘design flaws’ inherent in any system will become evident and call for revision to further enhance the clinical utility, reliability and validity of the diagnostic categories.

An overall view of the DSM-V process Thus, the effort to revise the present DSM-IV classification for a planned DSM-V classification intended for publication in 2012, was undertaken in 2007 by the American Psychiatric Association under the direction of David Kupfer MD and Darrel Regier MD. Having been assigned the task of addressing the area of mood disorders, a Mood Disorders Work Group of knowledgeable volunteers was formed, which has been meeting both face-to-face and more frequently by conference calls reviewing the DSM-V classification and relevant scientificclinical literature. Where deemed necessary, we would elect to conduct secondary data analyses directed at specific questions, identify issues for possible revision as well as to recommend field trials to test the feasibility of certain proposed changes. We have also been challenged to reconsider the structure of the overall DSM-V, and to consider new ways to classify disorders that would reflect changes in clinical knowledge or practice as well as emerging knowl-

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edge from neurogenetic, neuroimaging and clinical research findings. Our task is to come up with a revised diagnostic classification that reflects emerging information relevant to validity of disorders and improves clinical utility in a format that, in an age of rapidly emerging new information, will not become obsolete by the time of its publication and will lend itself to the incorporation of emerging findings. We proceeded with this awe-inspiring charge. There is a hope that the resulting DSM-V would be in the greatest possible harmony with the emerging ICD 11 classification of psychiatric disorders. An effort was made to form groups of individuals, with expertise in the study of each group of disorders, into members of diagnostic category workgroups. Suggested revisions and changes reached by consensus in the workgroups will be passed on to a task force chaired by Drs Kupfer and Regier, which will be made up of Diagnosis Work Group Chairs, and various leaders and consultants in psychiatry. which have the task of visualizing the overall structure of the merging DSMV classification for approval, deferral or modification. The Mood Disorders Workgroup covers the categories major depressive disorder and bipolar disorder and all related diagnoses. We divided into sub-workgroups to more effectively work on these sub-categories in parallel. In this process, it was determined that other relevant behavioural dimensional candidates, such as suicide risk, the role of comorbid anxiety and several related categories such as seasonal affective disorder and premenstrual dysphoric disorder deserved thoughtful consideration. To deal with these issues, further sub-workgroups made up of members of the Mood Disorders Workgroup, as well as liaison members from other overlapping workgroups, such as anxiety, personality and psychotic disorders, were sought, supplemented with appointed advisors with specific expertise and research experience in these clinical areas who could make specific valuable contribution to our deliberations and recommendations, were all recruited to participate in this multilayered process. Each sub-workgroup, such as the Bipolar Sub-workgroup, regularly report their areas of discussion, and preliminary

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recommendations to and receives feedback from the entire membership of Mood Disorders Workgroup on conference calls and in face-to-face meetings as the process moves forward. This creates an iterative process where preliminary decisions are revisited by the sub-workgroups and periodically discussed in the entire mood workgroup and when approved, will be forwarded to the task force as recommendations to be considered for inclusion in the new DSM-V structure. This complex and iterative process of seeking and discussing information on questions raised by a review of the overall structure, that is the possibility and feasibility of adding a suicide risk dimension or severity dimension for anxiety to a mood disorder diagnosis, or raised by review of possible specific criteria changes such as the required duration of a symptom, for example the required duration of hypomania for bipolar II disorder and the definition of a mixed depressive state, is proceeding and being discussed by both the major depression and bipolar sub-workgroups, as well as the overall Mood Disorders Workgroup. Because of the resulting six sub-workgroups, with conference calls ranging from every two to four weeks, as well as various related group calls and adding in the task force group calls, an average of two to four calls each week occur in this process. The workgoups meet for face-to-face discussions for two days about every six months.

Ongoing work on bipolar disorder for DSM-V Understanding the review process should make it clear that there is much discussion and evaluation of possible changes for bipolar disorder in DSM-V, though few final decisions have been made at this point in the process. The members of the Bipolar Sub-workgroup include the Sub-workgroup Chairperson Trish Suppes MD, Jules Angst MD, Ray DePaulo MD, Ellen Frank PhD, Ellen Leibenluft MD, who are members of the full Mood Disorders Workgroup, which includes Bill Coryell MD, Lori Davis, MD, David Goldberg MD, James Jackson PhD, Ken Kendler MD, Mario Maj MD, Michael Phillips MD, Carlos Zarate MD and myself, as well as liaisons members from other work groups and advisors, such as Alan Swann MD who had input concerning the issue of mixed states in the Bipolar Subworkgroup and Norman Rosenthal who wrote a review of seasonal affective disorder. Liaison members from other groups, such as Kimberly Yonkers, Uli Witchen and Joen Oldham, also participated at various stages.

Criteria for recommending a change in DSM-IV The Mood Disorders Workgroup agreed on a memorandum that described criteria for recommending a change in

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DSM-IV to the task force. In summary form, this memorandum stated that a recommendation for a signuifiucant change must be sponsored by a workgroup member who would provide a rationale for the change and a review of the literature or other database analyses supporting the change. The greater the significance of the change proposed, the greater the data required to support the change. Unintended consequences of any change and how those changes would be offset by the advantages of the change would be considered. A two-thirds vote of the workgroup would be required for the proposal to be forwarded to the task force for their consideration of the recommendation.

Bipolar disorder Based on discussions of the Bipolar Sub-workgroup and the Mood Disorders Workgroup some interesting issues have emerged. This work is going on at more than one conceptual level. A review of the DSM-IV criteria, such as the possible need to include increased energy or overactivity in the diagnostic criteria and how that could best be accomplished, has been discussed [18].

Bipolar spectrum A consideration of the meaning and relevance of the distinction of mania from hypomania, as well as the utility and validity of the concept of bipolar spectrum disorder, is going on simultaneously and receiving discussion. These discussions are occurring with an awareness of a plethora of articles published over the past 15 years, raising the question of sub-threshold manic symptoms not being recognized by DSM-IV, which would alter the balance of patients diagnosed on the bipolar spectrum, increasing the rate of bipolar spectrum patients to approach the rates of patients diagnosed with true unipolar disorder [1–8,10–12,14–16,18–21,33,35,36,38,40,44,45,50,57,60,62] Some of these articles have suggested that the four-day requirement for the diagnosis of bipolar II disorder in DSM-IV, has resulted in many bipolar spectrum patients being diagnosed as unipolar depression as opposed to a two-day duration of hypomanic symptoms [4,12,16,43,62]. These publications remind us that the original concept of manic depressive disorder included patients on the basis of recurrent affective episodes and not only the occurrence of a full syndrome manic episode [5]. The literature on bipolar spectrum has also pointed out that by having criteria that are too restrictive for the recognition of manic symptoms, may lead patients to suffer from symptoms for years without a correct diagnosis of bipolar disorder and effective treatment [21,36]. For example, the criteria requiring a fourday duration of hypomania has been criticized as a barrier to the correct and timely diagnosis of bipolar disorder by some authors [4,12,62]. Studies have pointed out the negative

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consequences in many patients of ineffective responses and increased risk for suicidal behaviour from the use of antidepressant medications, without consideration of the need for concomitant treatment with mood-stabilizing medications [4,16,19,43,62]. On the other hand, a problem of overdiagnosis of bipolar disorder diagnosis has been raised by Zimmerman et al. [65]. These investigators present results of 700 patients interviewed with the SCID, which is based on DSM-IV criteria. They found that fewer than half of the patients, who reported they had been diagnosed previously with bipolar disorder, were diagnosed with bipolar disorder based on a SCID interview. Patients who self-reported a previous diagnosis of bipolar disorder that was not confirmed by the SCID did not have a significantly higher morbid risk for bipolar disorder than the patients who were negative for bipolar disorder by self-report and the SCID. This finding does not answer the question of what are the best supported criteria for a bipolar diagnosis, but addresses the manner in which various clinicians apply the criteria.

could be improved at the borders of major depression and mild or moderate manifestations of mania, hypomania or mixed states, so that patients who are actually suffering from a bipolar spectrum disorder could be earlier diagnosed and treated. On the other hand, a very high proportion of patients diagnosed with major depression may have isolated (not concurrent) manic symptoms over their course without developing bipolar disorder. In addition, with respect to a bipolar spectrum, it has been found that the clinical outcome of bipolar I and bipolar II patients is distinct enough to merit designation into these categories.

Rapid cycling bipolar disorder Thus far, the specifier of rapid cycling bipolar disorder with the DSM-IV criteria of four affective episodes in the past year has been found to be clinically useful without need of modification by the workgroup.

Bipolar depression Mixed episodes The issue of mixed manic-hypomanic and depressive states is being considered with a trend toward extending mixed states across the entire severity range of bipolar bisorder. According to DSM-IV, a mixed episode occurs only as a part of bipolar disorder, and it requires the presence of full major depression and full mania, although the literature suggests that mixed depressive states are being found throughout the spectrum of bipolar patients, as well as in patients diagnosed with unipolar depression [9,13,17,22,24,27,30,33,37,42,52,58]. Of course, there are questions of the borders between bipolar and recurrent unipolar disorder. It has been found that the incidence of unipolar depression is as great or greater than bipolar disorder in family members, while the incidence of bipolar disorder is greater in families with bipolar disorder than those without [8,25,38,63]. The issues of bipolar spectrum, and sub-threshold bipolar states, as well as the capturing of episodes of mixed states, could have a significant effect on the proportion of patients diagnosed as in the bipolar spectrum versus unipolar depression. However, a report of an analysis comparing the course of BP I versus BP II patients concluded that the phenotypes of bipolar I and bipolar II disorder are likely to exist in a disease spectrum, but since they are sufficiently distinct in their long-term outcomes (more severe episodes in BP I patients and more chronic course with a predominance of depression in BP II patients), they are best classified as two separate subtypes in official classification syndromes [39]. It appears that a significant proportion of patients classified as unipolar major depressive may ultimately be found to be in the bipolar spectrum, and perhaps they could be classified on a severity spectrum. It seems that diagnosis

Bipolar depression and its clinical characteristics relative to treatment outcome is also a concern. Is it the same as unipolar major depression or are there differences that should be recognized? The data from the large STEP-BD study showing that adjunctive SSRI antidepressants or buprorion versus placebo added double blind to mood stabilizers or atypical antipsychotics in bipolar depressed patients, showed that the efficacy as measured by durable recovery of these antidepressants was only 23% versus a 27% response for placebo over 26 weeks [53]. Further reports from STEP-BD find that anidepressants do not assist in depressive recovery in bipolar depression accompanied by symptoms of mania, and are likely to increase symptoms of dysphoria, irritablity and middle waking, [34]. The STEPBD studies of antidepressant efficacy and effectiveness certainly raise questions as to differences in treatment response, particularly in those patients with the presence of depression with manic symptoms (mixed depression) or a history of mood switching in past trials of antidepressants [6,34,48]. Another study of self reported mood switching, within 12 weeks of starting antidepressant medications, found that 44% reported at least one episode in the 338 bipolar patients studied [49]. The risk of treatment-emergent mania was found to be greatest in bipolar patients with a short duration of illness, multiple past antidepressant trials and a past history of switch with at least one antidepressant. A treatment study of 176 adult outpatients with bipolar depression over 10 weeks found that 85 responded to treatment, 45 did not respond and 46 patients had treatment-emergent mania or hypomania [30]. YMRS items of increased motor activity, pressured speech and racing thoughts were significantly associated with the outcome of mood switching in this sample. This chapter suggests that

DSM-V Perspectives on Classification

screening for mild manic symptoms would help predict patients likely to develop manic symptomatology in response to antidepressant treatment. It is interesting that some of the same symptoms are noted in patients diagnosed with unipolar major depression who later develop manic or hypomanic behaviour. Perhaps more sensitive criteria for mixed depressive and mixed manic or hypomanic states would help to sort out candidates with bipolar depression from those with unipolar depression more accurately and earlier in their course. Is bipolar depression really the same condition as unipolar depression? If not, is there a difference in symptom criteria? The Collaborative Depression Study, reported an 11-year follow-up of major depression revealing an 8.6% rate of conversion to bipolar II disorder and a 3.9% conversion rate to bipolar I Disorder – total conversion rate 12.5% [6]. The patients who converted were found to have early onset of depression, high rates of substance abuse and a high incidence of social turmoil and antisocial acts. Mood labiality alone was the most sensitive predictor (86%), though of lower sensitivity (42%). ‘Habitual self’ descriptions of temperamental instability attained a predictive sensitivity of 91%. A study reported in 2007 of 744 outpatients followed since 1981–1986, found an incidence of lifetime mania of 27%, significantly associated with three factors: age of onset of depression, family history of mania and increased psychotic symptoms [48]. Another study reported on a 15-year follow-up of 74 patients with an average age of 23, were hospitalized for major depression and found that 27% had developed on or more distinct patterns of hypomania, while an additional 19% had at least one episode of bipolar I mania [26]. These investigators found that young patients with psychotic features were at particularly high risk for eventually developing mania. A recent study of 269, predominantly outpatients diagnosed as unipolar major depression and followed over 5 years, reported that 8.9% of patients diagnosed with unipolar major depression that then had a switch into symptoms of mania or hypomania and 2.8% switched to Type I when treated with antidepressant medications, also contribute to this issue [59]. One treatment study of unipolar depressed inpatients found a manic/hypomanic switch rate of 13.1%, and then compared these patients with 245 patients who did not show any switch [49]. The patients who developed a switch in response to antidepressants tended to be male and to have a higher proportion of family history of bipolar disorder. Mitchell and colleagues [45] have pointed out that while there is no ‘point of rarity’ between bipolar depression and unipolar major depression, there are clinical characteristics that are more common in each form of depression. Features more common in patients who ‘convert’ or later develop hypo/manic symptoms are: ‘atypical’ symptoms such as hypersomnia, hyperphagia, and leaden paralysis, psychomotor retardation, psychotic features and/or path-

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ological guilt and lability of mood. Bipolar depressed patients are more likely to have an earlier age of onset of their first depressive episode, to have more prior episodes of depression, to have shorter episodes of depression and a family history of bipolar disorder. Unipolar depression patients were found to have initial insomnia/reduced sleep, appetite or weight loss, normal or increased activity levels, somatic complaints, later age of onset of first episodes, prolonged episodes and no family history of bipolar disorder. The authors suggest that a ‘probabilistic’ approach to the diagnosis of bipolar/unipolar depression be developed, based on the appearance of these clinical characteristics. A subsequent study by the same group [46,47] of 217 patients with bipolar disorder with standardized interviews with a comparison with a Stanley Foundation Bipolar Disorders Network (SFBN) sample, as well as a STEP-BD sample, found sociodemographic similarities across the three samples, between samples for positive family history of bipolar disorder (40%) and unipolar depression (55%). The comparison also found similar proportions with the STEP-BD sample reporting earlier age of onset and the SFBN sample reporting higher numbers of overall episodes, but psychotic episodes and suicide attempts were less common than in the Australian sample. A recent study by Goldberg et al. [35], of 1380 STEP-BD bipolar patients with depressive episodes, found that two-thirds of this sample had concurrent manic symptoms, most often distractibility, flight of ideas, or racing thoughts and psychomotor agitation. Patients with mixed features were more likely to have an early age of onset, rapid cycling in the past year, suicide attempts and more days in the preceeding year with irritability or mood elevation. The authors conclude that manic symptoms often accompany bipolar depression, but are often overlooked when they appear less prominent than depressive features and subsyndromal manic symptoms during bipolar I or II depression demarcate a more common, severe and complex clinical state than pure bipolar depression.

Schizoaffective disorder The diagnosis of schizo-affective disorder is a contentious problem shared by the Mood Disorders Workgroup and the Psychosis Workgroup. While in its current form it has turned out to have rather low reliability, it has been found by Tohen et al. to be the most commonly used second diagnosis in a group of patients initially diagnosed as psychosis NOS. Currently, it seems that the Psychosis Workgroup is recommending that it be dropped and diagnosed by using the diagnosis of schizophrenia with a behavioural dimension of mania or depression. Because schizoaffective disorder is one of the most frequently used diagnoses, at this point it has been decided that the diagnosis will be retained in DSM-V changes in the wording of

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the criteria which will hopefully increase the reliability of this diagnosis. The psychosis Workgroup has currently proposed to retaine the diagnosis because of the frequency of its use, with changes in the diagnostic criteria aimed at making the diagnosis more reliable than it currently is.

Paediatric bipolar disorder The issue of diagnosing bipolar disorder in children is also a major issue. Bipolar disorder has a serious prognosis and often requires treatment with powerful medications that may have serious side effects and in some cases long-term medical risks, so when relying on symptom presentations and history as contrasted with laboratory tests, having the most effective diagnostic criteria is of great concern. It appears that irritability, although certainly common in bipolar disorder at all ages, is quite a promiscuous symptom across a range of diagnoses and may not be very useful in discriminating bipolar disorder from other disorders. Separating bipolar disorder from ADHD and Oppositional Defiant Disorder in children is a concern [55]. A recent study of 637 youths with a 10 item scale demonstrated good discrimination between bipolar disorder and attention deficit disorder, and showed that parents most notice elated mood, high energy, irritability and rapid changes in mood and energy as the prominent features of juvenile bipolar disorder [56,64]. The question has been raised whether children with bipolar disorder manifest shorter (as short as four hours) episodes occurring frequently over periods such as four days. This would suggest the possibility of different criteria for paediatric bipolar disorder than those currently in place for adults. On the other hand, there are obvious concerns for overdiagnosis as there must be a balance of overdiagnosis versus Underdiagnosis of paediatric bipolar disorder. A field test of criteria and further discussions with the Developmental/Lifespan Issues Task Force Committee will be required to decide this issue. A recent eight-year follow-up study of children diagnosed with bipolar disorder, showing an over 40% of recurrent mania once they are over the age of 18, provides a much needed confirmation of the potential for the accurate diagnosis of bipolar disorder in children [32]. However, concern has been expressed regarding the method of diagnosis utilized for the over-18 group in this study. It is also of great interest and importance that this study also documented a very high incidence (over 90%) of ultradian cycling (cycles of a minimum of four-hour switches) with an interview that is sensitive to this phenomenon, suggesting that it is common, but often not captured in clinical interviews. A study critically reviewing the phenomenology of paediatric bipolar disorder, the specificity of symptoms and the validity of the diagnostic construct found good support, but areas of disagreement over the use of elated mood versus irritability, and the limitations of the entity of bipolar dis-

order NOS in children [31,64]. A recent report, looking at the relative incidence of childhood-onset bipolar disorder reported by adult bipolar patients, found a 61% incidence in US patients compared with 30% report of childhood in the Netherlands or Germany [30,51]. This study found twice the genetic/familial risk for affective disorder and twice the incidence in childhood adversity in the United States. In a group of 480 adult outpatients carefully diagnosed with bipolar disorder, 14% reported an onset before age 12 and 36% reported onset in adolescence. The childhood-onset group reported an average 16-year delay until they received treatment, and both the childhood-onset and adolescentonset group had more episodes, more comorbidity and a more severe course [41]. It appears that childhood-onset bipolar onset diagnosis may not be made early enough, but that there might be disagreement around the milder forms (bipolar disorder NOS) that require attention to assure accurate, but timely diagnosis and treatment.

Behavioural dimensions In addition to an ongoing review of criteria for the diagnosis of bipolar mania, hypomania, depression, mixed states and various age-related presentations, the concept of being able to convey more useful clinical information by combining behavioural dimensions with diagnostic categories and how to do this and at the same time maintain clinical utility, is under consideration [7,61]. One candidate is a universal behavioural dimension, which might be rated as a severity dimension across diagnoses, is the presence of comorbid anxiety that emerges with the disorder, rather than as a primary comorbid anxiety disorder. Even the presence of a comorbid anxiety disorder might mean more if rated on a simple severity scale as done using the SADS-C psychic anxiety scale, which rates severity using both the intensity experienced by the patient as well as the time of the patient’s day dominated by anxiety [27]. The basis for this consideration is the fact that comorbid severe anxiety is not widely recognized as a high priority treatment target, while recent studies show that it is a robust predictor of poor outcome and suicidal behaviour in bipolar disorder and the range of affective disorders. Studies have shown it is very prevalent (40–50%) in bipolar disorder. If the patient meets criteria for a diagnosable anxiety disorder, this diagnosis can be made as a comorbid Axis I diagnosis, but not uncommonly the anxiety symptoms may emerge with the bipolar symptomatology and be ignored diagnostically and by under-treatment of a bipolar patient with comorbid anxiety, resulting in poor outcomes and an elevation of suicide risk [55,56]. It has also been reported that a comorbid anxiety disorders diagnosis predicts an increased risk of suicide (HR ¼ 1.81) in bipolar patients [54]. Fawcett et al. [29] found that severity of psychic anxiety in both bipolar and unipolar patients was signifi-

DSM-V Perspectives on Classification

cantly correlated with suicide risk over one year from the time of assessment. (See Chapter 7, Suicide and Bipolar Disorder). Recently, Coryell et al., studied the severity of psychic and somatic anxiety measured at baseline by the SADS-C rating scale, which was found significantly linearily correlated with time spent in a depressive episode stepwise by severity rating, over a 20-year follow-up period. Psychic anxiety severity was the strongest single correlate of time spent in depressive episodes of a 20-year follow-up [23]. It is interesting that a similar report concerning poor outcomes with antidepressant treatment has been recently made from the STAR
D study of treatment outcome in patients with unipolar major depression. Anxiety severity has also be related to poor outcome in unipolar depressive patients treated in the STAR
D Study [28]. This data supports the addition of a psychic anxiety dimension to all of the mood disorder diagnoses, including bipolar spectrum disorder has well as perhaps across other diagnostic categories. This clinically significant behavioural dimension, which is extrinsic to criteria for the diagnosis, would call attention to the need for treatment of anxiety symptoms and further collection of data on the significance of co-existing anxiety severity for each diagnostic category, without prematurely changing criteria for the diagnostic category. A simple scale, such as the SADS-C, would lend itself to easy use by clinicians that would not be a burden, but would increase the data available for treatment planning. A decision to add extrinsic (supraordinate) as well as intrinsic (criteria symptom severity dimensions) dimensional severity measures would be a major change in the conceptual structure of DSM-V, if adopted. Adding certain extrinsic behaviour dimensions, such as severity of psychic anxiety and severity and immediacy of suicide risk, could result in an important increase in relevant clinical information conveyed and improve the treatment of patients as well as lead to further valuable research outcome data, which could result in further progress. It has become clearer that the criteria presently used for the diagnosis of bipolar disorder as well as other diagnoses may limit our clinical perspective, by limiting the focus of our treatment efforts in such a way as to ignore important clinical dimensions presently not included in the diagnostic criteria, but which are critical to our patient’s clinical outcome. These issues are complex and raise the issue of clinical utility, which is a major consideration in the DSM-V process. A concept of bipolar disorder as a spectrum spanning a range of severity from very severe, psychotic behaviour to a recurrent disorder with subtle and short-lived 1–2 day bouts of hypomania followed by long episodes of depression, to traits of mood instability and periodic flamboyant behaviour that may not require treatment, may be more effective in arriving at severity cut points. True severity may also depend on comorbid symptomatology, such as substance

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abuse or anxiety severity as well as measures of disability. Such a choice might expand the numbers of patients formerly diagnosed with unipolar depression who receive an early bipolar diagnosis and result in a considerable increase in bipolar spectrum diagnoses in patients with recurrent mood disorders, relative to unipolar major depression. Adding behavioural dimensions across bipolar disorder and other diagnostic categories might considerably expand our treatment efforts and provide new targets for treatment and treatment development, resulting in improved outcomes for mood disorder and patients with other disorders. The DSM-V will need to be able to serve many masters. Busy clinicians will want it to be as simple and easy to use as possible and will not want to be burdened with changes that do not result in an obvious improvement in their practice. Research investigators will guard against changes that will diminish the value of previously collected large datasets resulting from any major changes in criteria and will set a high threshold of data driven support for proposed changes. Others will be wedded by years of hard work to certain clinical concepts and will demand solid empirical support for changes. Insurers and health care payers will be sensitive to changes, which might increase utilization and treatment expense. Ultimately, it is my hope that DSM-V can move the field ahead, with a diagnostic system that will improve treatment and encourage research in areas that need the greatest attention, by addressing newly developed knowledge and the inevitable ‘design flaws’ that result in any diagnostic system. Hopefully, we can help clinicians to be more responsive to important facets and contribute to more effective treatment of the disorders we treat.

References 1. Akiskal, H.S. (2007) The emergence of bipolar spectrum: Validation among Clinical-Epidemiologic and FamilialGenetic Lines. Psychopharmacol. Bull., 40 (4), 99–115. 2. Akiskal, H.S. (1996) The prevalent spectrum of bipolar disorders:beyone DSM-IV. J. Clin. Psychopharmacol., 16 (2 suppl 1), 48–148. 3. Akiskal, H.S., Aksikal, K.K., Lancrenon, S. and Hantouche, E. (2006) Validating the soft bipolar spectrum in the French National EPIDEP Study: the prominence of BP II1/2. J. Affect. Disord., 96 (3), 207–213. 4. Akiskal, H.S. and Benazzi, S. (2005) Optimizing the detection of bipolar II disorder in outpatient practice: toward a systemization of diagnostic wisdom. J. Clin. Psychiatry., 66 (7), 914–921. 5. Akiskal, H.S., Bourgeois, M.L., Angst, J. et al. (2000) Reevaluating the prevalence and diagnostic composition within the broad clinical spectrum of bipolar disorders. J. Affect. Disord., 59 (Suppl 1), S5–S30. 6. Akiskal, H.S., Maser, J.D., Zeller, P.J. et al. (1995) Switching from ‘unipolar’ to bipolar II. An 11-year prospective study of

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Chapter 5

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D report. Am. J. Psychiatry., 165 (3), 342–351, Epub 2008 Jan 2. Fawcett, J., Scheftner, W.A., Fogg, L. et al. (1990) Time-related predictors of suicide in major affective disorder. Am. J. Psychiatry, 147 (9), 1189–1194. Frye, M.A., Helleman, G., McElroy, S.L. et al. (2008) Correlates of treatment-emergent mania associated with antidepressant treatment in bipolar depression. Am. J. Psychiatry., (2009) Feb; 166 (2),164–72. Galanter, C.A. and Leibenluft, E. (2008) Frontiers between attention deficit hyperactivity disorder and bipolar disorder. Child Adolesc. Psychiatr. Clin. N. Amer., 17 (2), 325–346, viii–ix. Geller, B., Tillman, R., Bolhofner, K. et al. (2008) Prospective continuity with adult bipolar I disorder; characteristics of second and third episodes; predictors of 8-year outcome. Arch. Gen. Psychiatry, 65 (10), 1125–1133. Goldberg, J.F., Harrow, M. and Whiteside, J.E. (2001) Risk for bipolar illness in patients initially hospitalized for unipolar depression. Am. J. Psychiatry, 158 (8), 1265–1270. Goldberg, J.F., Perlis, R.H., Ghaemi, S.N. et al. (2007) Adjunctive antidepressant use and symptomatic recovery among bipolar depressed patients with concomitant manic symptoms: findings from the STEP-BD. Am. J. Psychiatry, 164 (9), 1348–1355. Goldberg, J.F., Perlis, R.H. Bowden, C.L. et al. (2009) Manic symptoms during depressive episodes in 1380 patients with bipolar disorder: findings from the STEP-BD. Am. J. Psychiatry, 166 (2), 173–181. Hirschfeld, R.M. (2001) Bipolar spectrum disorder: improving its recognition and diagnosis. J. Clin. Psychiatry, 62 (Suppl 14), 5–9. Holma, K.M., Melartin, T.K., Holma, I.A. and Isometsa, E.T. (2008) Predictors for switch from unipolar major depressive disorder to bipolar disorder type I or II: a 5-year prospective study. J. Clin. Psychiatry, 69 (8), 1267–1275. Joyce, P.R., Doughty, C.J., Wells, J.E. et al. (2004) Affective disorders in the first-degree relatives of bipolar probands: results from the South Island Bipolar Study. Compr. Psychiatry, 45 (3), 168–174. Judd, L.L., Akiskal, H.S., Schettler, P.J. et al. (2003) The comparative clinical phenotype and long-term longitudinal episode course of bipolar I and II: a clinical spectrum or distinct disorders? J. Affect. Disord., 73 (1–2), 19–32. Kessler, R.C., Akiskal, H.S., Angst, J. et al. (2006) Validity of the assessment of bipolar spectrum disorders in the WHO CIDI 3.0. J. Affect. Disord., 96 (3), 259–269.

DSM-V Perspectives on Classification 41. Leverich, G.S., Post, R.M., Keck, P.E. Jr et al. (2007) The poor prognosis of childhood-onset bipolar disorder. J. Pediatr., 150 (5), 485–490. 42. Maj, M., Pirozzi, R., Magliano, L. et al. (2006) Agitated “unipolar” major depression: prevalence, phenomenology, and outcome. J. Clin. Psychiatry, 67 (5), 712–719. 43. Mak, A.D. (2009) Prevalence and correlates of bipolar II disorder in major depressive patients at a psychiatric outpatient clinic in Hong Kong. J. Affect. Disord., 112 (1–3), 201. 44. McElroy, S. (2008) Understanding the complexity of bipolar mixed episodes. J. Clin. Psychiatry, 69 (2), e06. 45. Merikangas, K.R., Akiskal, H.S., Angst, J. et al. (2007) Lifetime and 12-month prevalence of bipolar spectrum disorder in the National Comorbidity Survey replication. Arch. Gen. Psychiatry, 64 (5), 543–552. 46. Mitchell, P.B., Goodwin, G.M., Johnson, G.F. and Hirschfeld, R.M. (2008) Diagnosic guidelines for bipolar depression: a probabilistic approach. Bipolar Disorder, 10 (1 Pt 2), 144–152. 47. Mitchell, P.B., Johnson, A.K., Corry, J. et al. (2009) Characteristics of bipolar disorder in an Australian specialist outpatient clinic: comparison across large datasets. Aust. NZ Psychiatry, 43 (2), 109–117. 48. Othmer, E., Desouza, C.M., Penick, E.C. et al. (2007) Indicators of mania in depressed outpatients: a retrospective analysis of data from the Kansas 1500 study. J. Clin. Psychiatry, 68 (1), 47–51. 49. Perlis, R.H., Brown, E., Baker, R.W. and Nierenberg, A.A. (2006) Clinical features of bipolar depression versus major depressive disorder in large multicenter trials. Am. J. Psychiatry, 163 (2), 225–231. 50. Perugi, G. and Akiskal, H.S. (2002) The soft bipolar spectrum redefined: focus on the cyclothymic, anxious-sensitive, impulse-dyscontrol, and binge-eating connection in bipolar II and related conditions. Psychiatr. Clin. North Am., 25 (4), 713–737. 51. Post, R.M., Luckenbaugh, D.A., Leverich, G.S. et al. (2008) Incidence of childhood-onset bipolar illness in the USA and Europe. Br. J. Psychiatry, 192 (2), 150–151. 52. Rihmer, A., Gonda, X., Balazs, J. and Faludi, G. (2008) The importance of depressive mixed states in suicidal behavior. Neuropsychopharmacol. Hung., 10 (1), 45–49. 53. Sachs, G.S., Nierenberg, A.A., Calabrese, J.R. and Marangell, L.B. (2007) Effectiveness of adjunctive antidepressant treatment for bipolar depression. N. Engl. J. Med., 356 (17), 1711–1722, Epub 2007 Mar 28.

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54. Simon, G.E., Hunkeler, E., Fireman, B. et al. (2007) Risk of suicide attempt and suicide death in patients treated for bipolar disorder. Bipolar Disord., 9 (5), 526–530. 55. Simon, N.M., Otto, M.W., Weiss, R.D. et al. (2004) STEP-BD investigators. Pharmacotherapy for bipolar disorder and comorbid conditions: baseline data from STEP-BD. J. Clin. Psychopharmacol., 24 (5), 512–520. 56. Simon, N.M., Zalta, A.K., Otto, M.W. et al. (2007) The association of comorbid anxiety disorders with suicide attempts and suicidal ideation in outpatients with bipolar disorder. J. Psychiatr. Res., 41 (3–4), 255–264, Epub 2006 Oct 18. 57. Smith, D.J., Ghaemi, S.N. and Craddock, N. (2008) The broad spectrum of bipolar disorder: implications for research and practice (Clinical report). Journal of Psychopharmacology, 22.4, 397. 58. Suppes, T., Mintz, J., McElroy, S.L. et al. (2005) Mixed hypomania in 908 patients with bipolar disorder evaluated prospectively in the Stanley Foundation Bipolar Treatment Network: a sex-specific phenomenon. Arch. Gen. Psychiatry, 62 (10), 1089–1096. 59. Truman, C.J., Goldberg, J.F., Ghaemi, S.N. et al. (2007) Selfreported history of manic/hypomanic switch associated with antidepressant use: data from the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD). J. Clin. Psychiatry, 68 (10), 1472–1479. 60. Vieta, E. (2008) Defining the bipolar spectrum and treating bipolar II disorder. J. Clin. Psychiatry, 69 (4), e12. 61. Vieta, E. and Phillips, M.L. (2007) Deconstructing bipolar disorder: a critical review of its diagnostic validity and a proposal for DSM-V and ICD-11. Schizophren Bull., 33 (4), 886–892, Epub 2007 Jun 11. 62. Vieta, E. and Suppes, T. (2008) Bipolar II disorder: arguments for and against a distinct diagnostic entity. Bipolar Disord., 10 (1 Pt 2), 163–178. 63. Weissman, M.M., Gershon, E.S., Kidd, K.K. et al. (1984) Psychiatric disorders in the relatives of probands with affective disorders. The Yale University-National Institute of Mental Health Collaborative Study. Arch. Gen. Psychiatry, 41 (1), 13–21. 64. Youngstrom, E.A., Birmaher, B. and Findling, R.L. (2008) Pediatric bipolar disorder: validity, phenomenology, and recommendations for diagnosis. Bipolar Disord., 10 (1 Pt 2), 194–214. 65. Zimmerman, M., Ruggero, C.J., Chelminski, I. and Young, D. (2008) Is bipolar disorder over-diagnosed? J. Clin. Psychiatry, 69 (6), 935–940.

CHAPTER

6

Update on the Epidemiology of Bipolar Disorder Kathleen R. Merikangas and Tracy L. Peters Genetic Epidemiology Research Branch, Mood and Anxiety Program, Intramural Research Program, National Institute of Mental Health, National Institute of Health, Bethesda, MD, USA

Introduction During the past decade, the results of numerous international epidemiologic surveys using contemporary diagnostic criteria have strengthened the evidence base on the magnitude, correlates and consequences of bipolar disorder in representative samples of the general population. This work has highlighted the dramatic personal and societal impact of bipolar disorders I and II (DSM IV). The estimated disability-adjusted life years of bipolar disorder outrank all cancers and primary neurologic disorders such as epilepsy and Alzheimer’s disease, primarily because of its early onset and chronicity across the life span [1]. The aims of this chapter are: (1) to provide a background on epidemiology; (2) to summarize the epidemiology of bipolar disorder in adults and youth; (3) to summarize the risk factors for bipolar disorder; and (4) to discuss the family genetics of bipolar disorder.

Background on epidemiology Epidemiology is defined as the study of the distribution and determinants of diseases in human populations. Epidemiologic studies are concerned with the extent and types of illnesses in groups of people and with the factors that influence their distribution. Epidemiologists investigate the interactions that may occur amongst the host, agent and environment (the classic epidemiologic triangle) to produce a disease state. The important goal of epidemiologic studies is to identify the aetiology of a disease in order to prevent or intervene in the progression of the disorder. To achieve this goal, epidemiologic studies generally proceed from studies that specify the prevalence and distribution of a disease within a population by person, place and time (i.e. descriptive epidemiology) to more focused studies of the determinants of the disease in specific groups (i.e. analytic epidemiology) [2].

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Descriptive epidemiologic studies are important in specifying the rates and distribution of disorders in the general population. The two major estimates of rates in epidemiology are prevalence and incidence. Both are based on the goal of identifying the proportion of cases of a particular index disease in a defined population. Prevalence rates are the number of existing cases in a defined population during a specified time period; incidence rates are the number of new cases of a disorder in a defined population during a specified time period of observation. Incidence rates are derived from prospective cohort studies. Most prevalence estimates in psychiatry include lifetime (the number of cases at any time in the lifetime of respondents, irrespective of whether the disorder is current), 12-month (the number of cases in the population during the past year) and point prevalence (the number of cases at the time of the survey). The most common estimates of prevalence in children are either point or one-year, because of the lack of reliability of lifetime estimates. Prevalence and incidence rates are generally adjusted for sex and age of the base population [2]. Epidemiologic studies are also designed to identify risk factors that influence the base rates of diseases in the general population. Differential distribution by sex, age, ethnicity, geographic site or by exposure to particular risk factors provides clues that may be tested systematically with casecontrol designs. These studies compare the association between a particular risk factor or disease correlate and the presence or absence of a given disease, after controlling for relevant confounding variables. Case-control studies generally proceed from retrospective designs defined by the presence or absence of a disease in the cases and controls, in order to identify potential associations between a particular risk factor or set of risk factors, and prospective cohort studies where the cases and controls are defined by the presence or absence of a putative risk factor, and followed prospectively to examine differential incidence of the disease. Community study data can also be applied to identify biases that may exist in treated populations and to construct case registries from which persons may serve as probands

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Update on the Epidemiology

for analytic epidemiologic studies. Such attention to sampling issues is a major contribution of the epidemiologic approach, as individuals identified in clinical settings often constitute the top of the iceberg of the disease, and may not be representative of the general population of similarly affected individuals with respect to demographic, social or clinical characteristics [2].

Epidemiology of bipolar disorder in adults Prevalence rates Comprehensive summaries of international studies of the prevalence of bipolar disorder over the past 25 years have been provided in several subsequent published reviews [3–8]. The aggregate cross-study estimate of the lifetime prevalence of bipolar disorder is about 1.0%. Only one of the reviews of the epidemiology of bipolar disorder includes Bipolar II (BP II) and bipolar spectrum disorders [4]. As expected, it was found that the median rates increase with successively less restrictive definitions of bipolar disorder; the median lifetime prevalence rate of BP II was 1.2%, and of bipolar spectrum was 2.9%. The only systematic difference that has been found to explain the variation in rates is the actual diagnostic interview employed to generate the criteria for bipolar disorder [7]. A summary of the 12-month and lifetime prevalence rates of BP I and BP II, as defined by DSM-IV criteria, is presented in Table 1. The aggregate cross-study estimate of the lifetime

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prevalence of bipolar disorder is 1.2%, with a range of 0.0% in Nigeria [9] to 3.3 in the United States [10]. Despite these outliers, the prevalence rates of bipolar I disorder are highly consistent across studies. The lifetime prevalence rates cluster at about 1.0%, whereas the average 12-month prevalence rate is only slightly lower with a median of 0.8%, with a range from 0.2–1.8%. The prevalence of BP II was only assessed in a few studies [11–13]. Two recent studies also reported on prevalence of bipolar disorder defined by ICD10 criteria. The lifetime prevalence of ICD-10 BP I was 1.8 in Ethiopia [14] and the 12-month prevalence in Ireland was 0.2 [15]. Finally, the lifetime prevalence of DSM-III defined BP I and BP II combined was 1.6 in the NHANES survey in the United States [16]. With increased interest in evaluating the validity of the thresholds of mania and its core components, investigators are beginning to test different thresholds in general community samples. Application of the concept of sub-threshold bipolarity to the Zurich Cohort Study demonstrated the enormous consequences of varying definitions of diagnostic criteria for symptoms, duration and impairment. The broader criteria yielded rates of 5.3% for bipolar II disorder, 3.2% for minor bipolar disorder and 3.3% for hypomania [17]. Similar rates emerged from a re-analysis of the Epidemiologic Catchment Area study by Judd et al. (2003), who reported that 5.1% of the population met criteria for lifetime sub-threshold mania/hypomania [18]. Likewise, expansion of the definition of hypomania in the NCS-R study yielded a lifetime prevalence rate of 4.5% [12,19].

Table 1 Rates of DSM-IV bipolar disorders in community samples of adults. LOCATION

Study

AGE

Sample size

Method

Diagnosis

Lifetime prevalence (%)

12-Month prevalence (%)

Male Female Total Male Female Total China Germany Iraq Israel Japan Lebanon Mexico New Zealand Nigeria Switzerland United States

Lee et al. [70] Jacobi et al. [71] Alhasnawi et al. [72] Levinson et al. [73] Kawakami et al. [74] Karam et al. [75] Medina-Mora et al. [76] Baxter et al. [38] Gureje et al. [9] Angst et al. [77] Grant et al. [10] Ford et al. [78] Merikangas et al. [12]

18–70 18–65
18
21
20
18 18–65

5201 4181 4332 4859 1664 2857 5826

WMH-CIDI/DSM-IV M-CIDI/DSM-IV WMH-CIDI/DSM-IV WMH-CIDI/DSM-IV WMH-CIDI/DSM-IV CIDI 3.0/DSM-IV WMH-CIDI/DSM-IV

Bipolar I/Bipolar II Any Bipolar Bipolar Disorder Bipolar Disorder Bipolar I/Bipolar II Bipolar Disorder Bipolar I/Bipolar II

— 0.8 — — — 2.6 —

— 1.2 — — — 2.3 —

0.1 1.0 0.2 0.7 — 2.4 1.9

— 0.6 — — — — —

— 1.1 — — — — —

— 0.8 0.2 0.1 0.1 — —

16–64
18 40
12
55
18

12 992 4984 591 43 093 6082 9282

CIDI 3.0/DSM-IV WMH-CIDI/DSM-IV SPIKE/DSM-IV NESARC/DSM-IV WMH-CIDI/DSM-IV CIDI/DSM-IV

Bipolar Disorder Bipolar I/Bipolar II Bipolar I, II Bipolar I Bipolar I/Bipolar II Bipolar I

— — — 3.2 — 0.8

— — — 3.4 — 1.1

— 0.0 2.6 3.3 0.8 1.0

— — — 1.8 — —

— — — 2.2 — —

1.8 0.0 — 2.0 0.4 0.6

Bipolar II Subthreshold BPD

0.9 2.6

1.3 2.1

1.1 2.4

— —

— —

0.8 —

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Chapter 6

Evidence for the validity of the expanded definition was provided by the clinical significance, severity, and impairment associated with sub-threshold bipolar disorder. Of particular interest, the severity of symptoms of depression and mania associated with sub-threshold bipolar disorder, suggested that the latter category did tap clinically significant manifestations of bipolar disorder that were comparable to people seeking treatment for these conditions in outpatient settings [19].

Incidence rates Most of the evidence on incidence rates (e.g. new cases in a defined population over a specified time period) of bipolar disorder has been derived from information on first admissions for bipolar disorder. Sherazi et al. (2006) reported a range of annual incidence rates of first-episode mania and bipolar I disorder from 1.7–6.5 per 100 000 per year [6]. Though some studies did report that men and women had different incidence rates, there are no consistent patterns of sex difference across studies.

Epidemiology of bipolar disorder in youth Although there has been substantial research on the epidemiology of mental disorders in children and adolescents in specific regions of the United States, there is still a striking lack of information on the national estimates of the prevalence and distribution of mental disorders in children in the US population. There is also a lack of data on the prevalence of bipolar disorder in youth from international studies. Most of the information on bipolar disorder in adolescents can be derived from ongoing longitudinal studies that have followed a sample of youth from adolescence through adulthood. These studies include community surveys of children and adolescents in New York State [20], North Carolina [21] and Oregon [22] in the United States, and in Munich, Germany [13] and Dunedin, New Zealand [23]. However, very few of these studies had sufficient sample sizes to identify cases of bipolar disorder. There are also a limited number of international population surveys that have provided information on the magnitude of bipolar disorder in youth.

Prevalence There is still a striking lack of information on the magnitude of bipolar disorder in youth. Even though there is an increasing number of population-based surveys of children and adolescents, many of these studies do not include assessment of the symptoms of mania because it is believed to be so rare [24,25]. To date, there is also a lack of data on the prevalence of bipolar disorder in youth in a nationally representative sample of US youth. The results of the

existing cross-sectional or short–term prospective studies of youth that applied DSM-IV criteria are shown in Table 2. The 12-month prevalence rates of mania range from 0.8 to 1.9%, and hypomania from 0.4–0.9% to age 18 [26–28]. A recent population survey of adolescents in Mexico City reported the highest prevalence rate of bipolar disorder in youth to date, with a one-year prevalence of 2.5% with bipolar disorder [28]. The most valid information on the prevalence and patterns of onset of bipolar disorder can be derived from prospective follow-up studies of youth through adulthood. Studies in New York State [20], North Carolina [21] and Oregon [22] in the United States, and in Munich, Germany [13] and Dunedin, New Zealand [23] have monitored prevalence of mental disorders through early adulthood. The lower half of Table 2 shows the prevalence of bipolar disorder in these studies. The results of these studies converge in estimating the prevalence of bipolar disorder at between 1.4 and 2.1%, which approximates cross-sectional prevalence rates of bipolar disorder in adult samples.

Incidence rates Prospective studies of child and adolescent samples from population surveys are the best source of incidence rates of bipolar disorder. Lewinsohn et al. (2002) found that the incidence of bipolar disorder peaks at age 14 in both males and females and decreases gradually thereafter [29]. By age 21, the rate of bipolar disorder rose to 2% in the prospective cohort studies of youth who were followed for several years [29,30]. There are also a growing number of studies that evaluate the incidence of first onset mania in clinical samples of youth. Incidence rates from these studies range from 1.7 to 2.2 per 100 000 per year, with a weighted average of 1.4% [31].

Age of onset and treatment rates in both adults and youth with bipolar disorder Age of onset Although estimates of the average age of onset of bipolar disorder from clinical samples was believed to occur in the third decade of life, retrospective estimates from the population surveys reveal that the average first onset of manic episodes occurs in the late teens to early 20s [12]. Emerging evidence from prospective studies of adolescents converges in demonstrating that the first onset of bipolar disorder generally begins in adolescence (possibly pre-adolescence) or early adulthood, with a mean age of onset of 18 years [32]. Waraich et al. (2004) showed that there was remarkable stability in the lifetime prevalence of bipolar disorder across adulthood, thereby demonstrating the chronicity of this condition across the lifespan [7].

Update on the Epidemiology

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55

Table 2 Rates of bipolar disorders in community samples of children and adolescents. Design

Authors

N

Age

Mania

Hypomania

Bipolar

13–18

1.9% (6 Mo)

0.9% (6 Mo)

—

1015

9, 11, 13

—

0.1%

0.2%

4175

11–17

0.4% (12 Mo)

0.8% (12 Mo)

—

3005

12–17

—

—

2.5% (12-Mo)

3021

14–24

—

0.4% (12Mo)

1.3% (12 Mo)

0.4% (LT)

1.4% (LT)

— —

—

Cross-Sectional Dutch Adolescent Study Verhulst et al. [27] Smoky Mountains Study Costello et al. [79] Teen Health 2000 Roberts et al. [80] Mexican Adolescent Mental Health Survey Benjet et al. [28]

760

Longitudinal (into Adulthood) Early Developmental Study of Psychopathology Wittchen et al. [13] Dunedin Longitudinal Study Cannon et al. [30] New York Longitudinal Study Velez et al. [81] Cohen et al. [20] Pine et al. [82] Oregon Adolescent Depression Project Lewinsohn, Klein, & Seeley [83]

980

26

2.0% (12Mo) —

776 760 716 1709

9–18 11–20 17–26 14–18

1507

15–19

1.0% (LT)

24

2.1% (LT)

865

—

Treatment rates

Risk factors

The studies summarized in Tables 1 and 2 have also provided substantial information about differential treatment patterns amongst samples identified from the general population. The findings indicate that about 60% of those with BPI in US community samples receive mental health treatment. Though more variable, more than half of those with BP in other countries receive treatment as well. This also suggests that half of those with bipolar disorder in the general population are not represented in mental health treatment, thereby limiting the generalizability of research conducted in these settings. Treatment rates in children have also been reported from prospective surveys. Newman et al. (1996) [23] found that approximately half of those youth in New Zealand with a 12-month episode of mania had received treatment. Moreno et al. (2007) examined data from the National Ambulatory Medical Care Survey to show that most visits by both youth and adult patients with a diagnosis of bipolar disorder included the prescription of at least one psychotropic medication, with use of mood stabilizers (generally anticonvulsants) in approximately two-thirds of the visits, and antidepressants in approximately one-third of the visits [33].

Sex

—

2.0% (T1 or T2) 1.4% 0.9% (LT)

The finding of equal rates of bipolar disorder in men and women from epidemiologic surveys was confirmed in all of the recent US population surveys [10,12,16]. Although there is consistentevidenceforanequalsexratioforbipolarIdisorder, several studies have shown that more women manifest the BP II subtype [34]. The lack of a sex difference demonstrates one of the sources of bias in clinical samples, which tend to have a greater proportion of women in psychiatric care for bipolar disorder [35]. Studies of youth also confirm the lack of sex differences in the rates of bipolar disorder and its components during adolescence [31]. However, caution should be exercised in drawing conclusions regarding the lack of sex differences in prevalence rates, because there may be differential manifestations of bipolar disorders in males and females. Whereas males may be more likely to exhibit mania, females are more likely to present with depression [36].

Other demographic factors Although many early studies of treated samples suggest that bipolar disorder was more common in upper

56

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socio-economic classes, the most recent US epidemiologic studies have consistently found that there are higher rates amongst those with lower income and education [10,12,16]. Likewise, rates of bipolar disorders are greater amongst those who were separated, divorced or widowed compared to those who are married or never married in all of the recent US population surveys. In contrast, a comparison of rates of bipolar disorder in high income and low income countries from the World Mental Health Survey showed that bipolar disorder was more common in high income than in low income countries (1.4 vs. 0.7%), as was disability associated with bipolar disorder [37]. Moreover, people from high income countries were nearly three times more frequently likely to enter treatment than their low income counterparts. No ethnic or racial differences in the rates of bipolar disorder have been reported in recent population surveys of the United States, including the NHANES, NCS-R and NESARC. However, there are only a limited number of studies that can truly distinguish ethnic differences because of the inclusion of sufficiently large multiethnic samples. The large sample size of the NESARC study enabled inclusion of several distinct ethnic subgroups in the US population. This study found that Native Americans reported higher rates of bipolar I disorder [10] than the other subgroups included in the survey. Another study that examined cultural subgroups is the New Zealand Mental Health Survey [38] that yielded higher rates of bipolar disorder amongst the Maori (3.4%) and Pacific people (2.7%), compared to European and other whites (1.9%).

Comorbidity Recent epidemiologic surveys have highlighted the striking magnitude of comorbidity between bipolar disorder and other Axis I DSM-IV disorders. Several population surveys confirm the strong link between anxiety disorders and bipolar disorder described in clinical samples (NCS R; NESARC, ESEMED). Data from the NCS-R revealed that more than 90% of those with lifetime BP I or BP II disorder also meet criteria for another lifetime disorder, and that 70% of those with bipolar spectrum disorders have a history of three or more disorders [12]. The disorders that are most strongly associated with bipolar disorder are anxiety disorders and substance use disorders. The NCS-R study revealed that more than 80% of those with bipolar disorder also have a lifetime history of DSM IV anxiety disorders, particularly panic attacks (e.g. 70%) and social phobia (e.g. 50%) [12]. Prospective studies of community samples provide valuable information on the temporal patterns of association between bipolar disorder and comorbid conditions. Followup studies of children have shown that bipolar disorder is associated with multiple other disorders including attention-deficit/hyperactivity disorder (ADHD) [29,33,39,40],

anxiety disorders and/or oppositional defiant disorder (ODD) [39] and conduct disorder [29]. An eight-year follow-up study of a population sample of youth from New York state revealed that childhood anxiety disorders and depression, and to a lower extent disruptive behaviour disorders, were significantly associated with the development of bipolar disorder in early adulthood [41,42]. Recent results of a high risk study of bipolar disorder confirm the anxiety-bipolar link. Duffy et al. (2007) found that rates of anxiety disorders and sleep disturbances were significantly elevated amongst offspring of bipolar probands compared to those of controls [43]. The latter work suggests that anxiety disorders may constitute an early form of expression of the developmental pathway of bipolar disorders. Future studies should attempt to distinguish whether anxiety disorders represent manifestations of the same aetiologic factors or independently elevate the risk for development of bipolar disorder. For example, one possible explanation for comorbidity in high risk samples could be parental concordance for these disorders, for example, paternal bipolar disorder and maternal anxiety disorder. The strong association between bipolar disorder with substance use disorders has also been widely described in both community and clinical samples. Retrospective research has shown that the onset of bipolar disorder generally precedes that of the substance use disorder. For example, [44] used data from a 20-year prospective cohort study to demonstrate the dramatic increase in risk of alcohol dependence associated with symptoms of mania and bipolar disorder in early adulthood. Thus, bipolar disorder can be considered a risk factor for the development of substance use disorders. Table 3 shows the strength of evidence that Table 3 Association between bipolar disorder with mental and physical disorders. Mental Disorders

Physical disorders

Disorder

Strength Disorder of evidence

Strength of evidence

Panic Attacks/ Disorder Specific Phobia Social Phobia Obsessive Compulsive Disorder Generalized Anxiety Disorder Drug Abuse/ Dependence

þþþ

þþþ

þþþ þþþ þþþ

Cardiovascular Disease Migraine Diabetes Asthma

þþ

Allergies

þþ

þþ

Back and Neck Pain Arthritis

þþ

þþþ Strong Evidence. þþ Moderate Evidence. þ Weak Evidence.

þþþ þþþ þþ

þ

Update on the Epidemiology

bipolar disorder is comorbid with different mental disorders and physical disorder.

Physical disorders Comorbidity of physical diseases with bipolar disorder has been well-recognized in clinical settings [45,46]. The recent generation of large psychiatric epidemiology studies has begun to include assessment of medical conditions that can be used to examine whether the associations that have been reported in clinical samples are associated with biases associated with either sampling or treatment. The disorders that have been most strongly associated with bipolar disorder in clinical settings include cardiovascular disorders, diabetes and migraine. Several studies of population-based samples and the recent results of the NCS-R have confirmed the strong association between migraine and bipolar symptoms/disorder [47,48]. Evaluation of physical-mental comorbidity in World Mental Health countries showed that heart disease, hypertension and back/neck pain are associated with bipolar disorder in both high and low income countries, whereas associations with arthritis, asthma and cancer are limited to high income countries. In contrast, severe headaches/migraine are more strongly associated with bipolar disorder in low income countries [37]. Health information collected in the NHANES data showed that those with bipolar disorder were more likely to rate themselves as in fair or poor health than those without affective disorders; however, other subtypes of mood disorders, including major depression and dysthymia, tended to have even stronger associations with poor health than bipolar disorder [16]. In the same study, associations emerged between all mood disorder subtypes with hypertension, but asthma was only significantly associated with major depression [16]. Although there is scant information on medical comorbidity in children with bipolar disorder, some studies of children have reported links between bipolar disorder and diabetes and cardiovascular diseases [49]. There also are several studies of systematic samples, such as the Veteran’s Administration [50] and health insurance claims data [51] bases, that provide strong evidence that people with bipolar disorder have high rates of physical disorders [52]. The study of health care claims by Carney and Jones (2006) found that nearly every medical disorder was more common amongst those with bipolar disorder; however, the extremely large database, lack of correction for multiple comparisons and failure to conduct multivariate analysis reduced the ability of this study to address the specificity of these associations [51].

Family history/genetics A family history of bipolar disorder is one of the strongest and most consistent risk factors for the development of this

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57

disorder. Controlled family studies yield an average 10-fold increased risk of bipolar disorder amongst adult relatives of probands with this disorder, compared to relatives of controls [53], as well as a 3.5-fold increased risk of bipolar disorder amongst relatives of probands with non-bipolar major depression. Results of a small number of twin studies yield an aggregate estimate of 3 fold greater risk amongst monozygotic compared to dizygotic twins, indicating that a significant proportion of the familiality of bipolar disorder can be attributed to genetic factors [54]. However, there is a remarkable lack of twin studies of bipolar disorder defined by modern diagnostic criteria [53]. Existing twin studies yield an average concordance rates for monozygotic twins of 40% compared to 5% for dizygotic twins, thereby suggesting a complex mode of inheritance of this condition [55]. Despite the strong evidence for familial and genetic factors underlying bipolar disorder, there is still a lack of information on susceptibility genes that have been consistently shown to have significant predictive value for the development of bipolar disorder. Although there have been many studies designed to identify candidate genes underlying bipolar disorder through either linkage (segregating within family) or association (differences between cases and controls), there are still no replicated genetic markers for bipolar disorder. The results of recent genome-wide association studies did not identify any of the candidate genes found in earlier studies, but it is anticipated that combined results of several large studies now under way may yield more presumptive evidence for susceptibility genes for in the next few years [55]. Irrespective of whether the family history represents increased genetic or environmental risk, or more likely elements of both, it is one of the most important predictors of the development of bipolar disorders in particular and mood and anxiety disorders in general youth.

Studies of offspring of bipolar probands The potential contribution of the family study can be enhanced by inclusion of a high-risk component, where individuals with a high probability for developing a specific disorder are compared to controls and followed over time. This design permits identification of the components and processes underlying disorders, early patterns of expression of these disorders, determinants of disorder progression, order of onset of comorbid disorders, and the longitudinal course and stability of symptoms and disorders. Following early studies by Meyer et al. [56], there are a growing number of studies of offspring of parents with bipolar disorder (Table 4) [57–60]. Controlled studies of offspring of parents with bipolar disorder have revealed an increased risk of a range of disorders including depression, anxiety disorders and ADHD, suggesting a lack of specificity of early manifestations of bipolarity [61]. Rates of mania and bipolar disorder

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Chapter 6

Table 4 High risk studies of bipolar disorder. Authors

N Cases

N Controls

Age

Parent group

Bipolar

Other

Controls

Bipolar Mood Anxiety ADHD Conduct/ODD Bipolar Mood Anxiety ADHD Conduct/ODD Bipolar Mood Anxiety ADHD Conduct/ODD Bipolar

10.6 21.1 25.8 24.5 19.1 16.0 32.0 32.9 32.0 22.0 20.4 52.8 23.2 10.2 0.8 8.8

— — —

— — 1.7

0.8 4.4 10.8 16.7 8.0 0 0 14.0 0 0 0 1.3 7.8 1.6 0 0

13.4 5.2 2.3 1.5 2.4 — — 2.3 — — — 14.7 6.2 6.4 — 5,2

Mood Anxiety ADHD Conduct/ODD

14.7 44.1 23.5 26.5

6.7 25.1 8.4 12.9

2.1 4.2 4.2 4.2

7.0 10,5 5.6 6.4

Birmaher et al. [60]

233

113

6–18

Singh et al. [58]

37

29

8–17

Duffy et al. [59]

207

87

8–25

Hirshfeld-Becker et al. [57]

34

179 Panic/Anx

4–10

98 Control

are generally low due to the young age of adolescent offspring in these studies; however, children of bipolar parents show greater specificity of transmission of affective disorders than do children of parents with unipolar depression [62]. The increased rates of ADHD that have been reported in some studies have been interpreted as evidence that symptoms of ADHD may be manifestations of a common underlying diathesis with bipolar disorder [40,63–66]. The prospective design of many of these studies will enable investigators to evaluate the prognostic significance of the symptoms and syndromes manifested by these children across development.

— — — — — — —

Risk ratio

unaffected subjects than in the general healthy population [67]. Table 5 lists the most promising endophenotypes that underlie bipolar disorder, including: cognitive endophenotypes, abnormal regulation of circadian rhythms (the sleep/wake cycle, hormonal rhythms, etc.), response to sleep deprivation, P300 event-related potentials, behavioural responses to psychostimulants and other medications, brain imaging endophenotypes (specifically, an increase in white matter hyperintensities (WHM)), and biochemical alterations in peripheral mononuclear cells [68,69].

Summary Endophenotypes/components of bipolar disorder Because psychiatric disorders have disparate manifestations, recent research has begun to investigate the symptoms and indices of their core underlying processes [67]. It has been proposed that these core components of diagnostic entities, or endophenotypes, are more likely to represent manifestations of the genetic factors involved in these disorders. Before a marker can be used as an endophenotype in genetic analysis, certain criteria need to be met: (1) the marker has to be associated with the illness in the population; (2) the marker has to be heritable; (3) the marker has to be state independent (i.e. present during remission); and (4) the marker also has to co-segregate with the disease within the family and have higher prevalence in high-risk

This chapter provides a comprehensive review of the magnitude of bipolar disorder in adults (DSM-IV) and children across the world. The lifetime prevalence rates, of bipolar I, cluster at about 1.0%, whereas the average 12-month

Table 5 Endophenotypes/Components of bipolar disorder. Cognitive deficits in verbal explicit memory and executive functioning. Brain Imaging: White matter hypertensities Abnormal Regulation of Circadian Rhythms Increased Latency in P300 Event-Related Potentials Behaviour Responses to Psychostimulants and Other Medications Biochemical Alterations Peripiheral Mononuclear Cells

Update on the Epidemiology

prevalence rate is only slightly lower with a median of 0.6%, with a range from 0–1.8%. There is a lack of data on the prevalence and magnitude of bipolar disorder in youth. The age of onset in bipolar disorder generally begins in adolescence, with a mean age of 18. About 60% of those with bipolar disorder I receive mental health treatment. Higher rates of bipolar disorder have been found in those with lower income and education. Comorbidity is pervasive amongst both adolescents and adults with bipolar disorder in the general population. Researchers have found bipolar to be comorbid with anxiety disorders, substance use disorders, panic attacks, social phobia and others. Family history of bipolar disorder is one of the strongest risk factors. Endophenotypes in bipolar disorder consist of abnormal regulation of circadian rhythm, imaging endophenotypes, cognitive endophentypes amongst others.

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45. McIntyre, R.S. and Keck, P.E. Jr (2006) Comorbidity in bipolar disorder: clinical and research opportunities. Bipolar Disord., 8 (6), 645–647. 46. McIntyre, R.S., Konarski, J.Z., Soczynska, J.K. et al. (2006) Medical comorbidity in bipolar disorder: implications for functional outcomes and health service utilization. Psychiatr. Serv., 57 (8), 1140–1144. 47. Merikangas, K.R. and Stevens, D. (1997) Comorbidity of migraine and psychiatric disorders. Neurol. Clin., 15 (1), 115–123. 48. Saunders, K., Merikangas, K., Low, N.C.P. et al. (2008) Impact of comorbidity on headache-related disability. Neurology, 70 (7), 538–547. 49. Scheffer, R.E. and Linden, S. (2007) Concurrent medical conditions with pediatric bipolar disorder. Curr. Opin. Psychiatry, 20 (4), 398–401. 50. Kilbourne, A.M., Cornelius, J.R., Han, X.Y. et al. (2004) Burden of general medical conditions among individuals with bipolar disorder. Bipolar Disord., 6 (5), 368–373. 51. Carney, C.P. and Jones, L.E. (2006) Medical comorbidity in women and men with bipolar disorders: A population-based controlled study. Psychosom. Med., 68 (5), 684–691. 52. McIntyre, R.S., Soczynska, J.K., Mancini, D. et al. (2007) Comparing features of bipolar disorder to major depressive disorder in a tertiary mood disorders clinic. Ann. Clin. Psychiatry, 19 (4), 313–317. 53. Merikangas, K. and Yu, K. (2002) Genetic epidemiology of bipolar disorder. Clin. Neurosci. Res., 2 (3–4), 127–141. 54. Smoller, J.W. and Gardner-Schuster, E. (2007) Genetics of bipolar disorder. Curr. Psychiatry Rep., 9 (6), 504–511. 55. Smoller, J.W. and Finn, C.T. (2003) Family, twin, and adoption studies of bipolar disorder. Am. J. Med. Genet. C Semin. Med. Genet., 123C (1), 48–58. 56. Meyer, S.E., Carlson, G.A., Youngstrom, E. et al. (2009) Longterm outcomes of youth who manifested the CBCL-Pediatric Bipolar Disorder phenotype during childhood and/or adolescence. J. Affect. Disord., 113 (3), 227–235. 57. Hirshfeld-Becker, D.R., Biederman, J., Henin, A. et al. (2006) Psychopathology in the young offspring of parents with bipolar disorder: a controlled pilot study. Psychiatry Res., 145 (2–3), 155–167. 58. Singh, M.K., DelBello, M.P., Stanford, K.E. et al. (2007) Psychopathology in children of bipolar parents. J. Affect. Disord., 102 (1–3), 131–136. 59. Duffy, A., Alda, M., Crawford, L. et al. (2007) The early manifestations of bipolar disorder: a longitudinal prospective study of the offspring of bipolar parents. Bipolar Disord., 9 (8), 828–838. 60. Birmaher, B., Axelson, D., Monk, K. et al. (2009) Lifetime psychiatric disorders in school-aged offspring of parents with bipolar disorder: the Pittsburgh Bipolar Offspring study. Arch. Gen. Psychiatry, 66 (3), 287–296. 61. Duffy, A. (2007) Does bipolar disorder exist in children? A selected review. Can. J. Psychiatry, 52 (7), 409–417. 62. Merikangas, K.R. and Angst, J. (1995) Comorbidity and social phobia – evidence from clinical, epidemiologic, and geneticstudies. Eur. Arch. Psy. Clin. N., 244 (6), 297–303.

Update on the Epidemiology 63. Hirschfeld, R., Calabrese, J.R., Weissman, M. et al. (2002) Prevalence of bipolar spectrum in US adults. Eur. Neuropsychopharm., 12, S218–S318. 64. Biederman, J., Makris, N., Valera, E.M. et al. (2008) Towards further understanding of the comorbidity between attention deficit hyperactivity disorder and bipolar disorder: a MRI study of brain volumes. Psychol. Med., 38 (7), 1045–1056. 65. Biederman, J., Faraone, S., Mick, E. et al. (1996) Attentiondeficit hyperactivity disorder and juvenile mania: an overlooked comorbidity? J. Am. Acad. Child Adolesc. Psychiatry, 35 (8), 997–1008. 66. Chang, K.K.D., Steiner, H. and Ketter, T.A. (2000) Psychiatric phenomenology of child and adolescent bipolar offspring. J. Am. Acad. Child Psy., 39 (4), 453–460. 67. MacQueen, G.M., Hajek, T. and Alda, M. (2005) The phenotypes of bipolar disorder: relevance for genetic investigations. Mol. Psychiatry, 10 (9), 811–826. 68. Lenox, R.H., Gould, T.D. and Manji, H.K. (2002) Endophenotypes in bipolar disorder. Am. J. Med. Genet., 114 (4), 391–406. 69. Glahn, D.C., Bearden, C.E., Niendam, T.A. and Escamilla, M. A. (2004) The feasibility of neuropsychological endophenotypes in the search for genes associated with bipolar affective disorder. Bipolar Disord., 6 (3), 171–182. 70. Lee, S., Tsang, A., Zhang, M.Y. et al. (2007) Lifetime prevalence and inter-cohort variation in DSM-IV disorders in metropolitan China. Psychol. Med., 37 (1), 61–71. 71. Jacobi, F., Wittchen, H.U., Holting, C. et al. (2004) Prevalence, comorbidity and correlates of mental disorders in the general population: results from the German Health Interview and Examination Survey (GHS). Psychol. Med., 34 (4), 597–611. 72. Alhasnawi, S., Sadik, S., Rasheed, M. et al. (2009) The prevalence and correlates of DSM-IV disorders in the Iraq Mental Health Survey (IMHS). World Psychiatry, 8 (2), 97–109. 73. Levinson, D., Zilber, N., Lerner, Y. et al. (2007) Prevalence of mood and anxiety disorders in the community: results from the Israel National Health Survey. Isr. J. Psychiatry Relat. Sci., 44 (2), 94–103.

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74. Kawakami, N., Takeshima, T., Ono, Y. et al. (2005) Twelvemonth prevalence, severity, and treatment of common mental disorders in communities in Japan: preliminary finding from the World Mental Health Japan Survey 2002–2003. Psychiatry Clin. Neurosci., 59 (4), 441–452. 75. Karam, E.G., Mneimneh, Z.N., Dimassi, H. et al. (2008) Lifetime prevalence of mental disorders in Lebanon: First onset, treatment, and exposure to war. PLoS Med., 5 (4), 579–586. 76. Medina-Mora, M.E., Borges, G., Benjet, C. et al. (2007) Psychiatric disorders in Mexico: lifetime prevalence in a nationally representative sample. Brit. J. Psychiat., 190, 521–528. 77. Angst, J., Gamma, A., Neuenschwander, M. et al. (2005) Prevalence of mental disorders in the Zurich Cohort Study: a twenty year prospective study. Epidemiologia E Psichiatria Sociale, 14 (2), 68–76. 78. Ford, B.C., Bullard, K.M., Taylor, R.J. et al. (2007) Lifetime and 12-month prevalence of Diagnostic and Statistical Manual of Mental Disorders. Fourth Edition disorders among older African Americans: Findings from the national survey of American life. Am. J. Geriatr. Psychiatry, 15 (8), 652–659. 79. Costello, E.J., Angold, A., Burns, B.J. et al. (1996) The Great Smoky Mountains Study of Youth. Goals, design, methods, and the prevalence of DSM-III-R disorders. Arch. Gen. Psychiatry, 53 (12), 1129–1136. 80. Roberts, R.E., Roberts, C.R. and Xing, Y. (2007) Rates of DSMIV psychiatric disorders among adolescents in a large metropolitan area. J. Psychiatr. Res., 41 (11), 959–967. 81. Velez, C.N., Johnson, J. and Cohen, P. (1989) A longitudinal analysis of selected risk factors for childhood psychopathology. J. Am. Acad. Child Adolesc. Psychiatry, 28 (6), 861–864. 82. Pine, D.S., Cohen, P., Gurley, D. et al. (1998) The risk for earlyadulthood anxiety and depressive disorders in adolescents with anxiety and depressive disorders. Arch. Gen. Psychiatry, 55 (1), 56–64. 83. Lewinsohn, P.M., Klein, D.N. and Seeley, J.R. (2000) Bipolar disorder during adolescence and young adulthood in a community sample. Bipolar Disord, 2 (3), 281–293.

CHAPTER

7

Suicide and Bipolar Disorder
n Rihmer1 and Jan Fawcett2 Zolta 1

Department of Clinical and Theoretical Mental Health, and Department of Psychiatry and Psychotherapy, Semmelweis Medical University, Ku´tv€ olgyi Clinical Centre, Budapest, Hungary 2 Department of Psychiatry, University of New Mexico School of Medicine Albuquerque, NM, USA

Introduction Despite the great clinical and public health significance of bipolar disorder, an illness with markedly elevated premature mortality, it is still underreferred, underdiagnosed and undertreated or mistreated [1,2]. This elevated risk of early death of patients with bipolar disorder is predominantly due to suicide. Up to 15% of bipolar patients die by their own hands and about half of them make one or more suicide attempts during their lifetime [3–7]. Although suicidal behaviour is very rare in the absence of current major mental illnesses [3,7,8], suicide is not the linear consequence of psychiatric disorders. It is a very complex and multicausal human behaviour involving also several psycho-social and cultural components. This chapter summarizes the clinically most important suicide risk and protective factors in bipolar disorders.

Suicide and attempted suicide in major mood disorders Harris and Barraclough [9] analysed separately the risk of completed suicide in patients with index diagnosis of unipolar major depression or bipolar disorder (37 reports and more than 11 000 patients), the patients having been followed in some studies for many decades and found that the standardized mortality ratio (SMR) for completed suicide was about 20-fold for patients with index diagnosis of unipolar major depression, and the same figure for bipolar disorders was 15. However, it should be noted that this type of analysis cannot provide a precise estimate of separate risk of suicide in unipolar depression and bipolar disorders (i.e. it overestimates the risk for unipolar and underestimates the risk of bipolar disorders). The main reason of this is that the index diagnosis often changes over the long-term course from unipolar depression to bipolar I or bipolar II illness [7,10] and in the studies reviewed by Harris and Bipolar Disorder: Clinical and Neurobiological Foundations Edited by Lakshmi N. Yatham and Mario Maj © 2010 John Wiley & Sons, Ltd. ISBN: 978-0-470-72198-8

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Barraclough [9], the distinct diagnostic category of bipolar II depression (major depressive episode with history of hypomania but not with mania), which is the most common clinical manifestation of bipolar disorders [1,7], was not considered separately. Consequently it is very likely that the majority of bipolar II patients in these studies were included into the unipolar major depressive group. Indeed, the most recent meta-analysis of 28 reports, published between 1945 and 2001 (including only patients with index diagnosis of bipolar disorder without long-term lithium treatment) by Tondo et al. [3], have found that during an average 10 years of follow-up, the SMR for completed suicide in bipolar patients was as high as 22. These authors also calculated that suicide rates in bipolar disorder patients average 0.4% per year, which is more than 25 times higher than the rate for the general population. In addition, in their very recent long-term prospective follow-up study (average 11 years) on 1983 unipolar major depressives and 843 bipolar (I þ II) patients, Tondo et al. [4] found much (5-fold) higher rate of completed suicide in bipolar I and II than in unipolar patients (0.25% of patients/ year vs. 0.05% of patients/year). This study also showed that the ratio of attempted to completed suicide in bipolar II, bipolar I and unipolar depression was 5, 11 and 10, respectively, indicating that the lethality of suicide attempts was far highest in bipolar II patients. This is in good agreement with a previously published psychological autopsy study, which showed that bipolar II patients were markedly overrepresented amongst consecutively investigated suicide victims with major depressive episode at the time of suicide [11]. On the other hand, in a 40–44 years’ prospective followup study of 406 formerly hospitalized (186 unipolar and 220 bipolar) major mood disorder patients, in which study the unipolar-bipolar conversion was carefully considered during the follow-up, Angst et al. [10] found that 14.5% of unipolar and 8.2% of bipolar (I þ II) patients committed suicide, and the SMR for suicide in unipolar and bipolar patients were 26 and 12, respectively. Previous suicide attempt is the most powerful predictor of completed suicide, particularly in patients with major

Suicide and Bipolar Disorder

mood disorder [7–9,12]. Considering only the 10 clinical studies (including more than 3100 patients), in which unipolar and bipolar (I þ II) patients were analyzed separately, it has been found that the lifetime rate of prior suicide attempt(s) was much higher in bipolar (I þ II) patients (mean: 28%, range: 10–61%) than in unipolar depressives (mean: 13%, range: 9.30%) [5]. A recent long-term prospective study also found that the rate of suicide attempts during the follow-up was more than double in bipolar (I þ II) than in unipolar patients [4]. Community-based epidemiological studies [13,14] also showed that the lifetime rate of prior suicide attempts was 1.5–2.5 higher in bipolar (I þ II) than in unipolar patients.

Suicide risk and protective factors in bipolar disorders Completed suicide, suicide attempt and suicidal ideation in patients with bipolar disorders occur mostly during the severe major depressive episode and less frequently in mixed affective episode and dysphoric mania, but very rarely during euphoric mania, hypomania and euthymia [6,8,12,15,16], indicating that suicidal behaviour in bipolar patients is a state- and severity-dependent phenomenon. However, since the majority of bipolar patients never commit (and up to 50% of them never attempt) suicide [3,7,12,16], risk factors, other than the major mood episode itself, such as special clinical characteristics as well as some personality, familial and psychosocial risk and protective factors, should also play a significant contributory role [3,8,12]. Most of the suicide risk factors in patients with bipolar disorders are related to the acute major (mainly depressive) episodes but there are several historical and personality factors that can help clinicians identify highly suicidal patients.

Suicide risk factors in patients with bipolar disorders The clinical conditions most alarming and associated with suicidal behaviour in bipolar disorder patients are the recent suicide attempt and the current severe (melancholic) major depressive episode, frequently accompanied by hopelessness, severe psychic anxiety, guilt, few reasons for living and suicidal ideations, agitation, insomnia and psychotic features [5–8,10,12,17–19]. Recent results also suggest that mixed depressive episode (major depression plus 3 or more co-occurring intra-depressive hypomanic symptoms, which highly corresponds to the category of ‘agitated depression’) that accounts for between 30 and 60% of major depressive episodes [19–21], substantially increases the risk of both attempted and committed suicide [15,19,22–25]. These results can explain, at least in part, the rarely occurring ‘antidepressant-induced’ suicidal behaviour:

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antidepressant monotherapy, unprotected by mood stabilizers or atypical antipsychotics, particularly in bipolar and bipolar spectrum disorder (including ‘unipolar’ depressive mixed state) can induce not only hypomanic/manic switches and rapid cycling, but also worsen the pre-existing mixed state or generate de novo mixed conditions, making the clinical picture more serious and ultimately leading to self-destructive behaviour [12,25,26]. Suicidal behaviour in bipolar patients, however, is not exclusively restricted to depressive episodes. In contrast to classical (euphoric) mania, where suicidal tendencies are extremely rare, suicidal thoughts and attempts are relatively common in patients with mixed affective episode and dysphoric mania, supporting the common clinical observation that suicidal behaviour in bipolar patients is linked to depressive symptomatology [6,7,10,15]. Bipolar patients show a high frequency of psychiatric and medical comorbidities [1,7,27] and it is well documented that comorbid anxiety/anxiety disorders, substance-use disorders, personality – mainly borderline personality – disorders and serious medical illnesses, particularly in the case of multiple comorbidities, also increase the risk of all forms of suicidal behaviour [5–8,12,27–30]. As the majority of bipolar suicide victims and attempters are not pharmacologically treated [5,7,12,28] and successful acute and longterm treatment of bipolar disorder substantially (by
80%) reduces the risk of both completed and attempted suicide [3,7,31], lack of medical and family support as well as the first few days of the therapy, when antidepressants usually do not work (or rarely can worsen the depression) [25], also should be considered as suicide risk factors. As for suicide risk factors related to prior course of bipolar disorders, previous suicide attempt(s), particularly in the case of violent or more lethal methods, is the most powerful single predictor of future attempts and fatal suicide [3,7,8,12]. Other historical variables, like early onset and early stage of the mood disorder [4,7,10,12,29,30], as well as rapid cycling course, predominant depressive polarity and more prior hospitalizations for depression [3,6,8,27,32] have been also shown to increase the risk of both attempted and completed suicide. Certain personality features also play a significant role in suicidal behaviour: aggressive/impulsive personality traits especially in combination with current hopelessness and pessimism [18,33–36] markedly increases the risk of suicidal behaviour in patients with bipolar disorder. The interaction between personality features and illness’ characteristics in suicidal behaviour was best formulated by Mann et al. [33] in their ‘stress-diathesis model’, which suggests that the suicidal behaviour in psychiatric patients is determined not only by the stressor (acute major psychiatric illness), but also by a diathesis (impulsive, aggressive, pessimistic personality traits). Cyclothymia/cyclothymic temperament also seems to be a predisposing factor for suicidal behaviour,

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as in patients with major depressive episode, cyclothymic personality was significantly related to lifetime and current suicidal behaviour (ideation and attempts) both in adult and in a paediatric sample [37–39]. Although the vast majority of suicide victims in the general population are males and the opposite is true for suicide attempters [7,9,25], this difference is much smaller amongst suicidal patients with bipolar disorder [3,8,10,29,30], suggesting that gender is not a significant predictor for committed and attempted suicide in this otherwise high-risk population. As for suicide risk factors related to personal history, early negative life events (e.g. loss of parents, living alone, emotional, physical and sexual abuse) [5,8,12,27,33], permanent adverse life situations (e.g. unemployment, disabling medical disorders), as well as acute psycho-social stressors (e.g. loss events, financial disasters), [5,8,12,27,40] are the most important and clinically useful indicators of possible suicidality, primarily if other risk factors are also present. However, acute psycho-social stressors are commonly dependent on the victim’s own behaviour, particularly in the case of bipolar I disorder [40]. It may be that hypomanic and manic periods can easily lead to aggressiveimpulsive behaviour, financial extravagance or episodic promiscuity, thus generating several interpersonal conflicts, marital breakdown and new negative life events, all of which have a negative impact on the further course of the illness. Family history of suicidal behaviour and/or major mood disorders in first- and second-degree relatives is also a strong risk factor for both attempted and completed suicide [8,12,27,33,34]. However, the familial component of suicidal behaviour seems to be partly independent of psychiatric disorders, as suicidal persons are over 10 times more likely than relatives of comparison subjects to attempt or complete suicide after controlling for psychopathology [41]. The clinically explorable suicide risk factors in mood disorders are listed in Table 1.

Comorbid anxiety: an imminent risk factor for suicide Over the past 20 years, the importance of the role of comorbid anxiety as a risk factor for suicide in patients with mood disorders has become increasingly clear. This evidence has recently focused on the importance of anxiety disorders and comorbid anxiety severity as a risk factor for suicide or suicide attempts in patients with bipolar disorder. The findings in this area are of clinical importance for two reasons: (1) severe psychic anxiety may be an acute or imminent risk factor for suicide, when most risk factors for suicide such as prior suicidal behaviour and hopelessness tend to predict suicide over an indefinite period of time. Clinicians are in great need of information that will help

Table 1 Clinically detectable suicide risk factors in bipolar disorders 1. Risk factors related to acute mood episodes a/Severe major depressive episode - Current suicide attempt, plan, ideation - Hopelessness, guilt, few reasons for living - Agitation, depressive mixed state (three or more intradepressive hypomanic symptoms) - Severe psychic anxiety, insomnia - Psychotic features - Bipolar II diagnosis - Comorbid Axis I (anxiety, substance-related), Axis II and serious Axis III disorders - Lack of medical treatment and family/social support - First few days of the treatment (particularly if appropriate care and co-medication is lacking), first few weeks and months after hospital discharge b/Mixed affective episode (simultaneously occurring manic and major depressive episode) c/Dysphoric mania (mania and three or more intramanic depressive symptoms) 2. Risk factors related to prior course of the illness - Previous suicide attempt/ideation (particularly the violent/highly lethal methods) - Early onset/early stage of the illness/predominantly depressive course - Rapid cycling course 3. Risk factors related to personality features - Aggressive/impulsive personality traits - Cyclothymic temperament - Same-sex orientation, bisexuality 4. Risk factors related to personal history and/or family history - Early negative life events (separation, emotional, physical and sexual abuse) - Permanent adverse life situations (unemployment, isolation) - Acute psychosocial stressors (loss events, financial catastrophe) - Family history of mood disorders (1- and 2-degree relatives) - Family history of suicide and/or suicide attempt (1- and 2-degree relatives).

them detect acute suicide risk; (2) severe psychic anxiety, when diagnosed is treatment modifiable, which raises the potential to reduce acute and chronic suicide risk with medication treatment focused on anxiety symptoms. What is the evidence relating to severe anxiety as a risk factor for suicide in bipolar disorder? In 1990, a long-term follow-up study of 954 patients with major affective disorder, including 299 patients with bipolar I and II disorder, as well as 46 with bipolar schizoaffective disorder, provided the rare opportunity for a prospective study of suicide, since 85% of the patients followed were recruited while hospitalized [17]. This study recorded that 13 (6 bipolar) patients in this group died by suicide within 12 months of hospital discharge, while at 10 years of follow-up 34 (15 bipolar) patients in this group died by suicide. Baseline symptom

Suicide and Bipolar Disorder

severity was rated on the study patients on the SADS-C scale [42], by raters who were trained and had established rating reliability across sites. Comparing symptom severity levels at baseline showed that 13 patients who had committed suicide within one year of entry into the study had significantly higher severity of psychic anxiety, panic attacks and severe (global – unable to fall asleep, mid-wakening and early awakening) insomnia than the majority who survived. Interestingly, there was no difference in the presence of ‘standard’ risk factors’, such as suicidal ideation (greater numerically, but not significant in the non-suicide group), prior and recent suicide attempts and hopelessness. From years 2–10 of follow-up, a history of suicidal ideation, past suicidal behaviour and severity of hopelessness did significantly correlate with an outcome of suicide. The 13 suicides occurring over one year were composed of roughly half bipolar patients, even though bipolar patients made up about only one-third of the total of patients with major affective disorder. This study found that severe psychic anxiety, panic attacks and severe (global) insomnia may be imminent or acute risk factors (weeks to a few months) for suicide compared with standard risk factors such as suicidal ideation, past suicide attempts and severe hopelessness, which may more often be long-term (months to years) risk factors for suicide. Comorbid severe anxiety may be rapidly treatment modifiable with pharmacologic intervention, reducing risk levels before a depressive episode responds to treatment. Furthermore, over the past five years, several epidemiological studies have reported a significant relationship of comorbid anxiety, especially with affective disorders and increased suicidal behaviour [43,44]. More recently findings by [30], from the STEP-BD study found from a sub-sample of 120 bipolar patients manifesting suicidal thoughts, related later suicidal behaviour to the presence of significant anxiety symptoms in this patient group. It is more difficult to study suicide rates across specific disorders because of the huge numbers of subjects required to achieve the statistical power to compare rates of suicide, which occurs about once for ever 30 attempts in the United States, and once for every three to four attempts in bipolar patients. A recent study by Simon et al. [29] of two managed care databases totalling over 32 000 bipolar patients, found that males (HR 2.7) and patients with a diagnosis of comorbid anxiety disorders had an elevated risk for suicide (HR 1.8) and suicide attempts (HR 1.4). It was of special interest that while comorbid anxiety disorders designated risk for suicide and attempts, comorbid substance abuse was able to predict elevated rates of suicide attempt (HR 2.5), but not increased rates of suicide (HR 1.02). The risk of suicide attempts was increased in youth, while suicide rates were unrelated to age. A recent analysis by Coryell et al. [45], of data from a 20-year follow-up of over 300 bipolar patients,

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has shown that severe anxiety measured by SADS-C rated psychic and somatic anxiety items at baseline predicts a significant stepwise increase in duration of time spent in depressive episodes over 20 years in patients diagnosed with bipolar disorder according to severity levels of baseline anxiety. Stordal et al. [46], looking at monthly ratings of depression and anxiety from the Hospital Anxiety and Depression rating scale in over 60 000 people, including 10 670 male and 3833 female suicides, found a correlation in the Norweigen national suicide rate and monthly variation of anxiety and depression (p < 0.001). These studies all show a general relationship between affective disorders, severe comorbid anxiety and suicide behaviours and suicide.

Suicide protective factors In contrast to several suicide risk factors, only few circumstances are known to have a protective effect against suicidal behaviour. Good family and social support, pregnancy and postpartum period, having a great number of children, holding strong religious beliefs and restricting lethal suicide methods (e.g. to reduce domestic and car exhaust gas toxicity and to introduce stricter laws on gun control) whenever possible, seem to have some protective effect [5,7,12,47,48]. The most extensively studied suicide protective factor in bipolar disorders is the acute and longterm pharmacological treatment that results in a marked decline in all forms of suicidal behaviour in this high-risk patient piopulation [3,5,10,12,31,49]. However, targeted psycho-social intervention improves the efficacy of pharmacotherapy [7,50,51]. In spite of the fact that suicide risk is the highest in patients with bipolar disorders, appropriate pharmacotherapy can reach the greatest risk reduction exactly in this patient-population. Both open clinical studies and randomized controlled trials consistently have found that long-term treatment with lithium (in some studies in combination with antidepressants and antipsychotics) markedly (by >80%) reduced the risk of competed and attempted suicide in bipolar I, bipolar I and schizoaffective patients [10,31,49,52]. Antiepileptic mood stabilizers, such as divalproex and carbamazepine, have weaker, but clinically still significant, antisuicidal effect [7,49,52]. The marked anti-suicidal effect of lithium seems to be more than the simple result of its episode-prophylactic effect, as a significant reduction in the number of subsequent suicide attempts was found not only in excellent responders (93%), but also in moderate responders (83%) and in nonresponders (49%) [53]. The clinical implication of this finding is that in case of lithium nonresponse, when the patient is at high risk of suicidal behaviour, instead of switching from lithium to another mood stabilizer, the clinician should retain lithium (even at a lower level) and combine it with another mood stabilizer.

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As for antidepressants, administered particularly in monotherapy, they hardly work in bipolar depression and sometimes they can worsen the cross-sectional clinical picture via inducing or aggravating depressive mixed states/agitation and this can lead to increased suicidality [7,22,25,54]. There is also a growing body of evidence suggesting that antidepressant and (tipycal) antipsychotic monotherapy (unprotected by mood stabilizers) can also worsen the long-tem course and outcome of bipolar disorder that may also contribute to increased suicidal risk [25,49,54,55]. However, as bipolar patients with long-term pharmacotherapy sometimes need (and more frequently receive) antidepressants and/or antipsychotics in addition to their mood stabilizers to treat breakthrough depression or mania for shorter or longer period of time, clinicians should keep their patients on these supplementary medications as short a time as possible and the main component of the acute and long-term pharmacotherapy should be the mood stabilizer monotherapy [25,49,56,57].

Suicide risk assessment and prevention Although suicide is a rare event in the community, it is frequent amongst patients with mood disorder. Most suicides would have had contact with different levels of health care some weeks and months before their death [3,5,7,12], but more than half of bipolar suicide victims were pharmacologically untreated at the time of their death [2,3,5,7]. This underlines the priority role of health care workers in suicide prevention. All patients with bipolar disorders must be carefully assessed for suicide risk (see Table 1). It is important to note that the data reviewed above suggests that severe anxiety may be an indicator of more imminent suicide that should alert a clinician, while most risk factors as suicide ideation (excluding a suicide plan), past suicide attempts and hopelessness relate to increased risk for suicide over an undetermined time frame in the presence of affective symptoms. Medications, such as the long-acting benzodiazepine, clonazepam and sedating second-generation antipsychotics, such as olanzepine and quetiapine, have been shown to significantly reduce anxiety and agitation as well as suicidal ideation in depressive, bipolar depressive and bipolar mixed states [58–63]. Careful ongoing assessment of the severity of anxiety symptoms and their treatment using a relatively simple severity scales, such as the SAD-C psychic anxiety scale in bipolar patients, may assist the clinician in reducing suicide risk and perhaps suggest a treatment intervention for acute suicide risk, in the short term and reduce long-term risk. Other treatments, such as lithium, other mood stabilizing

medications, atypical antipsychotic medications for mood stabilization and anxiety symptoms as well as psychotherapies, such as cognitive therapy and dialectical behavioural therapy, may be helpful in the long-term management of bipolar patients at high chronic risk (based on prior suicidal episodes and behaviour) for suicide. Clinicians need as much information as possible to assess suicide risk, particularly imminent risk. They also need to address treatment targets that will reduce both short-term and long-term suicide risk. Comorbid anxiety may be one valuable treatment target that is worth more careful assessment and more treatment focus in bipolar and other major mood disorder patients. A recent study by Marangell et al. [55] from the STEP-BD study, found a significant association of SSRI treatment with 93 suicidal events, including eight completed suicides (p < 0.0001). While these findings require careful interpretation, because SSRI treatment could have been a marker for depressive severity, they could also be interpreted to show that antidepressant treatment alone may not be sufficient for the prevention of suicidal behaviour and suicide in bipolar patients [49]. This suggests that attention to other risk factors, such as comorbid anxiety, may be warranted as one approach to reduce suicidal behaviour in the management of bipolar disorder. Severe, agitated and/or anxious major depression, particularly in the presence of past suicide attempt and current insomnia, is the clinical constellation that indicates the highest risk of imminent suicidal behaviour, even in the absence of direct or indirect communication of wish to die. Discussing the possibility of suicidal behaviour with the patient and family members as a common but preventable complication of acute severe bipolar and other psychiatric disorders, is particularly important and always needed. Doctors should declare that depressive disorders can be successfully treated, and that suicidal tendencies will vanish after (or even before) the recovery from depression. Patients with acute suicidal danger usually need inpatient treatment, even of an involuntary nature. In the case of severe agitation, anxiety and insomnia prompt anyiolysis with benzodiazepines and sedating atipycal antipsychotics, as well as close observation is highly recommended. Although short screening instruments are useful in clinical practice for detecting actual suicide risk, no one screening instrument can replace the optimal doctor-patient relationship, including asking the right questions at the right time, accompained by a highly professional and emphatic atmosphere. The careful estimation of all suicide risk factors (see Table 1) allows detection of suicide risk at the earliest possible time and opportunity for intervention prior to the patient making the first suicide act.

Suicide and Bipolar Disorder

References 1. Rihmer, Z. and Angst, J. (2005) Epidemiology of bipolar disorder, in Handbook of Bipolar Disorder (eds S. Kasper and R.M.A. Hirschfeld), Taylor and Francis, New York, pp. 21–35. 2. Dunner, D.L. (2003) Clinical consequences of under-recognized bipolar spectrum disorder. Bipol. Disord., 5, 456–463. 3. Tondo, L., Isacsson, G. and Baldessarini, R.J. (2003) Suicidal behaviour in bipolar disorder. CNS Drugs, 17, 491–511. 4. Tondo, L., Lepri, B. and Baldessarini, R. (2007) Suicidal risk among 2826 Sardinian major affective disorder patients. Acta. Psychiat. Scand, 116, 419–428. 5. Rihmer, Z. (2005) Prediction and prevention of suicide in bipolar disorder. Clin. Neuropsychiatry, 2, 48–54. 6. Valtonen, H., Suominen, K., Mantere, O. et al. (2005) Suicidal ideation and attempts in bipolar I and bipolar II disorders. J. Clin. Psychiat., 66, 1456–1462. 7. Goodwin, F.K. and Jamison, K.R. (2007) Manic-Depressive Illness: Bipolar disorders and recurrent Depression, Oxford University Press, New York. 8. Hawton, K., Sutton, L., Haw, C. et al. (2005) Suicide and attempted suicide in bipolar disorder: A systematic review of risk factors. J. Clin. Psychiat., 66 693–704. 9. Harris, E.C. and Barraclough, B. (1997) Suicide as an outcome for mental disorders: A meta-analysis. Brit. J. Psychiat., 170, 205–228. 10. Angst, J., Angst, F., Gerber-Werder, R. and Gamma, A. (2005) Suicide in 406 mood-disorder patients with and without long-term medication: A 40 to 44 years’ follow-up. Arch. Suic. Res., 9, 279–300. 11. Rihmer, Z., Barsi, J., Arato´, M. and Demeter, E. (1990) Suicide in subtypes of primary major depression. J. Affect. Disord., 18, 221–225. 12. Rihmer, Z. (2007) Suicide risk in mood disorders. Curr. Opin. Psychiat., 20, 17–22. 13. Kessler, R.C., Borges, G. and Walters, E.E. (1999) Prevalence and risk factors for lifetime suicide attempts in the National Comorbidity Survey. Arch. Gen. Psychiat., 56, 617–626. 14. Sz
ado´czky, E., Vitrai, J., Rihmer, Z. and F€ uredi, J. (2000) Suicide attempts in the Hungarian adult population. Their relation with DIS/DSM-III-R affective and anxiety disorders. Eur. Psychiat., 15, 610–617. 15. Valtonen, H.M., Suominen, K., Haukka, J. et al. (2008) Differences in incidence of suicide attempts during phases of bipolar I and bipolar II disorders. Bipol. Disord., 10, 588–596. 16. Sokero, P., Eerola, M., Rytsala, H. et al. (2006) Decline in suicidal ideation among patients with MDD is preceded by decline in depression and hopelessness. J. Affect. Disord., 95, 95–102. 17. Fawcett, J., Scheftner, W.A., Fogg, L. et al. (1990) Time related predictors of suicide in major affective disorder. Am. J. Psychiatry, 147 (9), 1189–1194. 18. Oquendo, M.A., Galfalvy, H., Russo, S. et al. (2004) Prospective study of clinical predictors of suicidal acts after a major depressive episode in patients with major depressive disorder and bipolar disorder. Amer. J. Psychiatry, 161, 1433–1441. 19. Akiskal, H.S., Benazzi, F., Perugi, G. and Rihmer, Z. (2005) Agitated “unipolar” depression re-conceptualized as a depre-

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ssive mixed state: Implications for the antidepressant-suicide controversy. J. Affect. Disord., 85, 245–258. Maj, M., Pirozzi, R., Magliano, L. and Bartoli, L. (2003) Agitated depression in bipolar I disorder: Prevalence, phenomenology, and outcome. Amer. J. Psychiatry, 160, 2134–2140. Benazzi, F. (2006) Mood patterns and classification in bipolar disorder. Curr. Opin. Psychiat., 19, 1–8. Benazzi, F. (2005) Suicidal ideation and depressive mixed states. Psychother Psychosom., 74, 107–108. Sato, T., Bottlender, R., Kleindienst, N. and M€ oller, H.-J. (2005) Irritable psychomotor elation in depressed inpatients: A factor validation of mixed depression. J. Affect. Disord., 84, 187–196. Bal
azs, J., Benazzi, F., Rihmer, Z. et al. (2006) The close link between suicide attempts and mixed (bipolar) depression: Implications for suicide prevention. J. Affect. Disord., 91, 133–138. Rihmer, Z. and Akiskal, H.S. (2006) Do antidepressants t(h)reat(en) depressives? Toward a clinically judicious formulation of the antidepressant-suicidality FDA advisory in light of declining national suicide statistics from many countries. J. Affect. Disord., 94, 3–13. Benazzi, F. (2003) How could antidepressants worsen unipolar depression? Psychother Psychosom, 72, 107–108. Leverich, G.S., Altshuler Frye, M.A., Suppes, T. et al. (2003) Factors associated with suicide attempts in 684 patients with bipolar disorder in the Stanley Foundation Bipolar Network. J. Clin. Psychiat., 64, 506–515. Bal
azs, J., Lecrubier, Y., Csisz
er, N. et al. (2003) Prevalence and comorbidity of affective disorders in persons making suicide attempts in Hungary: Importance of the first episode and of bipolar II diagnosis. J. Affect. Disord., 76, 113–119. Simon, G.E., Hunkeler, E., Fireman, B. et al. (2007) Risk of suicide attempt and suicide death in patients treated for bipolar disorder. Bipol. Disord., 9, 526–530. Simon, N.M., Zalta, A.K., Otto, M.W. et al. (2007) The association of comorbid anxiety with suicide attempts and suicidal ideation in outpatients with bipolar disorder. J. Psychiatr. Res., 41 (3–4), 255–264. Baldessarini, R.J., Tondo, L., Davis, P. et al. (2006) Decreased risk of suicides and attempts during long-term lithium treatment: A meta-analytic review. Bipol. Disord., 8, 625–639. Valtonen, H.M., Suominen, K., Mantere, O. et al. (2007) Suicidal behaviour during different phases of bipolar disorder. J. Affect. Disord., 97, 101–107. Mann, J.J., Waternaux, C., Haas, G.L. and Malone, K.M. (1999) Toward a clinical model of suicidal behavior in psychiatric patients. Amer. J. Psychiatry, 156, 181–189. MacKinnon, D.F., Potash, J.B., McMahon, F.J. et al. The National Institutes of Mental Health Bipolar Disorder Genetics Initiative (2005) Rapid mood switching and suicidality in familial bipolar disorder. Bipol. Disord., 7, 441–448. Zalsman, G., Braun, M., Arendt, M. et al. (2006) A comparison of the medical lethality of suicide attempts in bipolar and major depressive disorder. Bipol. Disord., 8, 558–565.

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36. Swann, A.C., Moeller, F.G., Steinberg, J.L. et al. (2007) Manic symptoms and impulsivity during bipolar depressive episode. Bipol. Disord., 9, 206–212. 37. Akiskal, H.S., Hantouche, E.G. and Allilare, J.F. (2003) Bipolar II with and without cyclothymic temperament: ‘Dark’ and ‘sunny’ expressions of soft bipolarity. J. Affect. Disord., 73, 49–57. 38. Kochman, F.J., Hantouche, E.G., Ferrari, P. et al. (2005) Cyclothymic temperament as a prospective predictor of bipolarity and suicidality in children and adolescents with major depressive disorder. J. Affect. Disord., 85, 181–189. 39. Pompili, M., Rihmer, Z., Akiskal, H.S. et al. (2008) Temperament and personality dimensions in suicidal and nonsuicidal psychiatric inpatients. Psychopathology, 41, 313–321. 40. Isometsa, E., Heikkinen, M., Henriksson, M. et al. (1995) Recent life events and completed suicide in bipolar affective disorder: A comparison with major depressive disorder in Finland. J. Affect. Disord., 33, 99–106. 41. Kim, C.D., Seguin, M., Therrien, N. et al. (2005) Familial aggregation of suicidal behavior: A family study of male suicide completers from the general population. Amer. J. Psychiatry, 162, 1017–1019. 42. Endicott, J. and Spitzer, R.L. (1978) A diagnostic interview: the schedule for affective disorders and schizophrenia. Arch. Gen. Psychiatry, 35 (7), 837–844. 43. Wunderlich, U., Bronisch, T. and Wittchen, H.U. (1998) Comorbidity patterns in adolescents and young adults with suicide attempts. Eur. aRch. Psychiatry Neurosci., 248 (2), 87–95. 44. Foley, D.L., Goldston, D.B., Costello, E.J. and Angold, A. (2006) Proximal psychiatric risk factors for suicidality in youth: the Great Smoky Mountains Study. Arch. Gen. Psychiatry, 63 (9), 1017–1024. 45. Coryell, W., Dervic, K., Oquendo, M.A. et al. (2004) Religious affiliation and suicide attempt. Amer. J. Psychiatry, 161, 2303–2308. 46. Stordal, E., Morken, G., Mykletun, A. et al. (2008) Monthly variation in prevalence of comorbid depression and anxiety in the general population at 63–65 degrees North: the Hunt study. J. Affect. Disord., 106 (3), 273–278. 47. Marzuk, P.M., Tardiff, K., Leon, A.C. et al. (1997) Lower risk of suicide during pregnancy. Amer. J. Psychiatry, 154, 122–123. 48. Driver, K. and Abed, R. (2004) Does having offspring reduce the risk of suicide in women? Int. J. Psychiat. Clin. Pract., 8, 25–29. 49. Rihmer, Z. (2007) Pharmacological prevention of suicide in bipolar patients – A realizable target. J. Affect. Disord., 103, 1–3. 50. Rucci, P., Frank, E., Kostelnik, B. et al. (2002) Suicide attempts in patients with bipolar I disorder during acute and maintenance phases of intensive treatment with pharmacotherapy and adjunctive psychotherapy. Amer. J. Psychiatry, 159, 1160–1164.

51. Michalak, E.E., Yatham, L.N. and Lam, R.W. (2004) The role of psychoeducation in the treatment of bipolar disorder: A clinical perspective. Clin. Appr. Bipol. Disord., 3, 5–11. 52. Cipriani, A., Pretty, H., Hawton, K. and Geddes, J.R. (2005) Lithium in the prevention of suicidal behavior and all causemortality in patients with mood disorders: A systematic review of randomized controlled trials. Amer. J. Psychiatry, 162, 1805–1819. 53. Ahrens, B. and Muller-Oerlinghausen, B. (2001) Does lithium excert an independent antisuicidal effect? Pharmacopsychiatry, 34, 132–136. 54. McElroy, S.L., Kotwal, R., Kaneria, R. and Keck, P.E. Jr (2006) Antidepressants and suicidal behavior in bipolar disorder. Bipol. Disord., 8, 596–617. 55. Marangell, L.B., Dennehey, E.B., Wisniewski, S.R. et al. (2008) Case-control analyses of the impact of pharmacotherapy on prospectively observed suicide attempts and completed suicides in bipolar disorder: Findings from the STEP-BD. J. Clin. Psychiatry, 69, 916–922. 56. Akiskal, H.S. (2007) Targeting suicide prevention to modifiable risk factors: Has bipolar II been overlooked? (Editorial) Acta Psychiat. Scand., 116, 395–402. 57. Sondergard, L., Lopez, A.G., Andersen, P.K. and Kessing, L.V. (2008) Mood stabilizing pharmacological treatment in bipolar disorders and the risk of suicide. Bipol. Disord., 10, 87–94. 58. Smith, W.T., Londborg, P.D., Glaudin, V. and Painter J.R. (1998) Short-term augmentation of fluoxetine withclonazepam in the treatment of depression: a double-blind study. Am. J. Psychiatry, 155, 1339–1345. 59. Smith, W.T., Londborg, P.D., Glaudin, V. and Painter J.R. (2002) Is extended clonazepam cotherapy of fluoxetine effective for outpatients with major depression? J. Affect. Disord., 70, 251–259. 60. Londborg, P.D., Smith, W.T., Glaudin, V. and Painter J.R. (2000) Short-term cotherapy with clonazepam and fluoxetine: anxiety, sleep disturbance and core symptoms of depression. J. Affect. Disord., 61, 73–79. 61. Hirschfeld, R.M., Weisler, R.H., Raines, S.R. and Macfadden, W. (2006) Quetiapine in the treatment of anxiety in patients with bipolar I or II depression: a secondary analysis from a randomized, double-blind, placebo-controlled study. J. Clin. Psychiatry. 67, 355–362. 62. McIntyre, A., Gendron, A. and McIntyre A. (2007) Quetiapine adjunct to selective serotonin reuptake inhibitors or venlafaxine in patients with major depression, comorbid anxiety, and residual depressive symptoms: a randomized, placebo-controlled pilot study. Depress Anxiety. 24, 487–494. 63. Houston, J.P., Tohen, M., Degenhardt, E.K. et al. (2009) Olanzapine-divalproex combination versus divalproex monotherapy in the treatment of bipolar mixed episodes: a double-blind, placebo-controlled study. J. Clin. Psychiatry, 70, 1540–1547.

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8

Neurocognition in Bipolar Disorder Ivan J. Torres1,2 and Gin S. Malhi3 1

Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada Riverview Hospital, British Columbia Mental Health and Addictions Services, Coquitlam, BC, Canada 3 Discipline of Psychiatry, Sydney Medical School, University of Sydney; CADE (Clinical Assessment Diagnostic Evaluation) Clinic, Royal North Shore Hospital, Sydney, Australia 2

Introduction Bipolar disorder has traditionally been conceptualized as a dynamic illness involving the alternation between transient periods of mood instability and periods of symptom remission. Early conceptions posited that in between mood episodes, patients returned to a normal functional state, and this was an important basis for differentiating mood disorders such as bipolar disorder from schizophrenia. The idea that patients with bipolar disorder indeed return to a fully functional state in between mood episodes is no longer accepted as truth, and much of this is based on findings from the rapidly emerging literature on cognitive functioning in bipolar disorder. Specifically, this body of research has revealed that cognitive impairment is a prevalent clinical feature of bipolar disorder, and that it persists even in patients who are in a remitted or euthymic state. Cognitive impairment thus appears to occur independently of mood state and represents a core clinical feature of bipolar illness. Given the increasing recognition of the importance of impaired cognition as a clinical feature of bipolar disorder [1], the purpose of this chapter is to provide an update on the current understanding of neuropsychological functioning in bipolar illness. The organizational strategy involves first providing an evaluation of the nature and extent of cognitive dysfunction across the various mood states and across potential subtypes of the illness. This is followed by consideration of the degree to which cognitive deficits might at least partly be produced by medication side effects. In the next general section we provide a brief review of cognitive neuroimaging studies and what they are beginning to reveal about the faulty brain systems that underlie the cognitive deficits in bipolar disorder. This is followed by a discussion of likely aetiologic factors associated with the cognitive impairment. The final portion of the chapter high-

Bipolar Disorder: Clinical and Neurobiological Foundations Edited by Lakshmi N. Yatham and Mario Maj © 2010 John Wiley & Sons, Ltd. ISBN: 978-0-470-72198-8

lights the clinical significance of cognitive impairment in bipolar disorder, as is illustrated by the ability of cognitive variables to predict everyday functional outcome. We also provide a clinically focused summary of strategies for assessment of cognitive deficits, and cover the understudied area of treatments targeting cognitive deficits in bipolar illness. Before delving into the main subject matter, however, we provide a brief primer on neuropsychological assessment to serve as background for subsequent discussion throughout the chapter.

Brief overview of neuropsychological assessment The field of clinical neuropsychology concerns itself with the understanding of brain/behaviour relationships in clinical populations with documented or suspected brain dysfunction. Although the discipline’s roots can be traced to work with neurosurgical and neurological patient populations, in more recent decades, clinical neuropsychology has shown increasing convergence with the field of psychiatry. This has undoubtedly been facilitated by the explosion in biological psychiatry and the universal recognition that many primary psychiatric disorders are manifestations of brain disease or illness. Even though research into neurocognitive functioning in bipolar disorder and other psychiatric disorders has been embraced by neuroscience researchers from varying disciplines and training backgrounds, the clinical practice of neuropsychology has largely remained a subspecialty of clinical psychology. The settings for clinical neuropsychological practice vary widely. Within a psychiatric context the main goals of neuropsychological assessment frequently include assistance with differential diagnosis, understanding and prediction of adaptive or real-world functioning and tracking of cognitive status across time, often in an effort to assist with assessing clinical outcome in response to treatment. The primary tool for cognitive assessment consists of the use of psychometrically validated cognitive tests, often paper and pencil, but increasingly computer-based, which have 69

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also been applied to large numbers of healthy individuals for the purpose of normative development and comparison. In this way, a given test score obtained by an individual can be compared to a reference group of healthy individuals with the same demographic characteristics (e.g. age, gender, education). Two of the key psychometric indicators of the utility of a cognitive measure include its reliability, which refers to the test’s consistency of measurement, as well as the measure’s validity, which refers to the test’s demonstrated ability to measure a particular psychological or cognitive construct. Attention to a cognitive measure’s psychometric properties thus forms an important basis for selection and interpretation of neuropsychological test results. Based on a patient’s performance on a range of such tests, inferences can be made about the individual’s functioning across different cognitive domains. This forms the basis for making conclusions about differential diagnosis, aetiology of cognitive impairments and the patient’s adaptive or functional capabilities. Neuropsychological assessment results may also provide indirect evidence of underlying dysfunction in various brain systems. Table 1 provides a summary of some of the major cognitive domains and representative types of tasks that are frequently sampled during the course of a neuropsychological evaluation [2]. The majority of research into cognitive functioning in bipolar disorder has been conducted within the framework of clinical neuropsychology, and thus many studies have employed clinically derived psychometrically validated

cognitive tests. However, increasingly the field has also embraced methodologies from a broader cognitive neuroscience perspective, and thus newer experimental tasks and paradigms have also been used in an effort to more accurately identify the cognitive components that may be implicated in the disorder. Thus, at this point the accumulated knowledge regarding neurocognitive functioning in bipolar disorder is based on research findings from multiple and varied perspectives.

Nature of cognitive impairment in bipolar disorder Because bipolar disorder is a disorder involving experience of abnormal mood states, any effort to characterize the nature of cognitive impairment associated with the illness requires consideration of the underlying mood state. Research into neurocognitive functioning in bipolar illness has thus been conducted in symptomatic patients (in depressed, manic or mixed states) and in individuals who are free or relatively free of mood symptoms.

Cognitive deficits associated with mood symptoms Early research suggested that bipolar patients in acute depressive or manic states demonstrate disproportionate impairment on tests of cognitive functioning. Not surpris-

Table 1 Neuropsychological domains sampled in a typical neuropsychological evaluation. Cognitive domain

Specific type of cognitive task

Premorbid Intelligence Intelligence/Reasoning

Single-word reading Verbal: vocabulary, reasoning, abstraction Nonverbal: reasoning, problem solving Verbal: list, story learning and recall Nonverbal: learning, recall visual designs Auditory attention span, spatial span Sustained attention Speeded visual-motor tasks Speeded cognitive tasks Visual/spatial perception, discrimination, recognition Drawing, block construction Expressive, receptive language Confrontation Naming, repetition Attentional/set shifting, working memory Mental flexibility, perseveration Response inhibition Verbal, nonverbal fluency Organization, sequencing, dyspraxia Tactile, visual, auditory perception Fine motor speed, coordination, grip strength

Memory Attention/Concentration Processing Speed Visual-Spatial/Visual Constructional Language Executive Function

Sensory Perceptual/Psychomotor

Based on Lezak et al., 2004.

Implicated brain regions

Diffuse Medial Temporal Lobe Diencephalon Diffuse: Frontal/Parietal Diffuse Right Hemisphere Left Hemisphere, Peri-sylvian Prefrontal, Parietal, Subcortical

Pre, Post-Central Gyrus, Occipital, Superior Temporal

Neurocognition in Bipolar Disorder

ingly, this finding has been confirmed in cross-sectional studies that evaluate groups of patients in euthymic or active mood states and compare their neuropsychological performance to each other and/or to healthy individuals. A number of test-retest studies evaluating patients in symptomatic and asymptomatic mood states also support the idea that cognitive performance worsens in the midst of a depressive or manic state. In mania, patients demonstrate widespread neuropsychological impairment that includes broad deficits in sustained attention (both inattention and impulsivity), memory recall and recognition (verbal and nonverbal), executive function, judgement and decision making [3,4]. These findings implicate global dysfunction in multiple brain systems, including dorsal and ventral prefrontal brain regions in mania. Although some of the deficits subside or diminish with symptomatic resolution, other impairments persist into the euthymic state (see section on cognitive deficits in euthymia below). In a depressive state, patients with bipolar disorder also show preferential decline in attention, concentration, memory, psychomotor speed and visual-spatial function, and again, these cognitive impairments improve with resolution of the depressive episode [4]. A summary of the major cognitive deficits observed in manic and depressed states in bipolar disorder is presented in Table 2. Although the finding that patients perform worse on cognitive tasks during a mood episode is established, the source or aetiology of the poor performance in such patients is far from clear and likely multiply determined. Cognitive deficits observed in depressed or manic individuals may reflect persistent neuropsychological impairments that are inherent to the illness, or they may be secondary and more intimately linked to or represent a by-product of the mood episode itself. For example, patients in a mood state may be unable or unwilling to concentrate on a cognitive task

Table 2 Cognitive impairments associated with mood states in bipolar disorder. Depression

Mania

Sustained Attention

Sustained Attention with impulsivity Selective Attention Verbal Learning Verbal Memory including recognition Visuospatial Memory

Verbal Learning Verbal Memory Visuospatial Memory Problem Solving Verbal Fluency Cognitive Flexibility

Psychomotor Speed Based on Malhi et al., 2008.

Verbal Fluency Inhibitory Control Cognitive Flexibility Judgement Decision Making

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because of poor effort, a tendency to give up, lack of interest, irritability or distractibility arising from other preoccupations. Because patients show improved cognitive performance as mood symptoms resolve, it is likely that at least a portion of the cognitive impairment observed in symptomatic patients represents mood-state dependent impairment. From a clinical perspective, the optimistic view is that when patients in severe mood states are treated effectively, it can be expected that their cognitive deficits will likely improve to a certain degree.

Cognitive deficits in euthymic patients In the past few years there has been a surge in research studies that have attempted to further elucidate the source of cognitive impairment in bipolar disorder, by evaluating the degree to which cognitive deficits represent more persistent or trait features of the illness. The strategy has been to restrict the study of neuropsychological deficits to samples of patients who are in remitted or euthymic, rather than symptomatic mood states. The finding of cognitive impairment even in asymptomatic patients would provide some evidence that cognitive deficits at least partly represent persistent, trait-related deficits that are mood independent. To date, there have been four published meta-analytic reviews that have aimed to quantify the severity and pattern of cognitive impairment across studies that have assessed remitted patients with bipolar disorder and compared their neuropsychological performance to a healthy comparison group [5–8]. Figure 1 illustrates the aggregate findings from these meta-analytic data by plotting the mean patientcontrol effect size differences that are observed across a range of neuropsychological tests. The meta-analytic data reveal that patients show a variable pattern of performance across different cognitive domains. First, individuals with bipolar disorder show minimal to no impairment on standard measures of current or estimated premorbid intellectual functioning, such as vocabulary and single-word reading ability. This finding suggests that the cognitive deficit profile in bipolar disorder does not involve gross intellectual decline, and this likely distinguishes patients with bipolar disorder from individuals with schizophrenia [9]. Euthymic bipolar patients also show relative sparing on spatial tasks involving ability to copy geometric designs, although it should be acknowledged that these functions have been studied relatively infrequently. In addition, patients show relatively intact performance on measures of simple auditory attention span such as digit span forwards. In contrast, deficits of considerable magnitude are observed on virtually all measures of verbal learning and recall (excluding recognition), on multiple aspects of executive function (response inhibition, auditory working memory, category fluency, attentional and mental set shifting ability), on measures of visual-motor processing speed and on

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1.0

Effect Size

0.8

0.6

0.4

indices of sustained attention involving inattention (rather than impulsivity as indexed by commission errors). Even though these deficits are not likely to be attributed to global intellectual decline, it remains unclear whether the diminished performance across multiple tests reflects multiple cognitive deficits or whether there is a core cognitive deficit that impacts performance on multiple cognitive tasks. One of the inherent difficulties of using clinically derived neuropsychological tests is that they frequently rely on multiple cognitive domains for successful performance. Thus, it is difficult to isolate any core cognitive deficit(s) that may be at play. Although seemingly compelling, the meta-analytic data do not rule out the possibility that the magnitude of cognitive impairment is at least partially influenced by several moderators or confounds, the most likely candidates being presence of residual mood symptoms and effects of medications. To help rule out that cognitive impairments may be due to residual mood symptoms, several well conducted studies assessing cognitive differences between euthymic patients and controls have incorporated rigorous inclusion criteria for mood rating scores into their designs, and they have statistically covaried out the influence of mood ratings when assessing cognitive group differences [10,11]. When these steps are undertaken, cognitive deficits in the domains identified above continue to be present in patients relative to controls. In addition, in the meta-analytic study conducted by Bora et al. (2008), meta-regression techniques failed to find an association between depression rating scores and cognitive functioning across samples of euthymic patients with bipolar disorder [6]. Together, these data suggest that residual mood symptoms are not likely responsible for the considerable cognitive deficits that are observed in euthymic patients. The question of whether medication variables

CPT Commission

CPT Reaction Time

CPT Hits/Ommission

Trailmaking A

Forward Span

Spatial

Digit Symbol

Visual Delay Recall

Verbal Recognition

Verbal Delay Recall

Verbal Learning

Verbal Immed Recall

WCST categories

Stroop Interference

Trailmaking B

WCST perseveration

Fluency-Letter

Backward Span

IQ

0.0

Fluency-Category

0.2

Fig. 1 Summary of 4 meta-analyses illustrating the mean effect size differences between euthymic bipolar patients and healthy controls. Note: if an effect size for a given measure was reported in more than one meta-analysis, then the mean value was calculated. WCST ¼ Wisconsin Card Sorting Test; CPT ¼ Continuous Performance Test.

may account for some or all of the cognitive deficits observed in bipolar disorder is addressed in more detail in a subsequent section.

Cognitive deficits in subsets of patients The data presented above show that cognitive impairments are common in bipolar disorder; however, as currently conceptualized, the illness still reflects a heterogeneous disorder. It is thus possible and even probable that specific subsets of patients may be biologically distinct from others, and that these biological distinctions may also be manifested in differential cognitive impairment across subgroups of patients. A common sub-classification of bipolar disorder makes the distinction between patients who show a history of at least one prior manic or mixed episode (bipolar I) and those who present with a history of hypomanic rather than manic episode, coupled with at least one, but frequently multiple depressive episodes (bipolar II). To date, only a few studies have evaluated neuropsychological functioning in patients with bipolar I versus bipolar II. Despite some mixed results, findings from this literature show preliminary evidence of better neuropsychological functioning in patients with bipolar II relative to bipolar I. Whereas patients with bipolar I show more severe and widespread deficits in memory, attention and executive functioning, patients with bipolar II show a more restricted and less severe pattern of impairment [12,13]. Thus, in addition to other possible clinical differences between these subtypes (e.g. course, genetics, neurobiology), patients with bipolar I and II may show distinct neurocognitive profiles as well. Clearly, more research on this topic is needed, and potential confounds, such as differential illness burden between patients with bipolar I and II, need to be controlled.

Neurocognition in Bipolar Disorder

Another clinical variable that may provide a meaningful distinction amongst patients diagnosed with bipolar disorder is history of psychosis. The clinical, anatomical/ physiological and cognitive similarities between patients diagnosed with bipolar disorder and schizophrenia are substantial, and current conceptualizations posit that rather than representing distinct entities, these disorders likely lie on a continuum and share common aetiologic factors [14]. The phenotypic overlap between these two disorders is revealed by estimates that greater than half of all patients with bipolar experience psychotic symptoms. However, because not all patients with bipolar disorder experience psychosis, it is possible that the presence of psychosis may identify a distinct subset of patients that may be ‘closer’ neurobiologically to patients in the schizophrenia spectrum. In order to evaluate whether these putative differences may manifest in differential neurocognitive performance, several studies have evaluated cognitive functioning in patients with and without a history of psychosis. Although findings are not universal, most studies point to evidence of preferential executive and working memory deficits in patients with a history of psychotic symptoms relative to bipolar patients without psychosis [15,16]. Moreover, in some instances, the more pronounced cognitive deficits are comparable to the more severe cognitive deficits observed in schizophrenia spectrum disorders. As is the case with the comparison between patients with bipolar I and bipolar II, several confounds including severity of illness and differential course and treatment need to be ruled out to further establish the robustness of the finding of preferential cognitive impairment in psychotic bipolar disorder. Moreover, even if such a link exists, the question of whether there is specificity to particular types of psychosis (e.g. mood congruent vs. incongruent psychosis, presence vs. absence of Schneiderian symptoms, etc.) also requires further study.

Effects of medication Because the large majority of both clinical and research patients with bipolar disorder are treated with psychotropic medications, assessment of the magnitude and pattern of neuropsychological impairment in bipolar disorder requires understanding of the potential influence of these agents upon neuropsychological functioning. Moreover, the possibility that medications may have a deleterious (this section) or a positive effect (see section at end of chapter) upon cognition should be considered. Increased understanding of the cognitive effects of psychotropic agents used to treat the illness also allows for more accurate specification of the cognitive deficits that are more likely to be inherently associated with the illness and those that are likely related to secondary factors. The influence of medication on cognitive functioning is ideally evaluated through appropriately conducted pro-

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spective randomized clinical trials in patients with bipolar disorder, or through neuropsychological studies that assess medication-free patients with bipolar disorder. Unfortunately, clinical trials aimed at assessing clinical change in bipolar disorder seldom include cognitive outcome variables, and there are relatively few existing neuropsychological studies designed specifically to evaluate drug influences on cognition in bipolar patients. Such studies aimed at assessing medication influences on cognition may also be confounded by change in the patient’s mood state. Thus, if an agent is observed to show cognitive improvement in the presence of improved mood, it remains unclear whether the cognitive improvement is directly associated with the treating agent or indirectly results from the improved mood. For ethical reasons it is also challenging to evaluate patients cognitively while in the unmedicated state. Moreover, patients that are untreated are more likely to exhibit mood symptoms. As a result, cognitive impairments observed in such patients might arise from the acute symptomatic state rather than from a more stable feature of the illness. Given these barriers, much of the information that is known about psychotropic effects upon cognition in bipolar disorder has been gleaned from either correlational crosssectional studies that evaluate relationships between cognitive measures and medication variables in samples with bipolar disorder, or from research investigating the influence of various agents used to treat bipolar disorder upon cognition in other neurological disorders and in healthy controls. Goldberg (2008) provides a comprehensive review of the common medications that are used to treat bipolar disorder and their effects on neuropsychological functioning in bipolar disorder [17]. Historically, lithium represents the most frequently used mood-stabilizer in bipolar illness, and there is a reasonable literature on the effects of this pharmacological agent upon cognitive functioning in psychiatric patients and healthy individuals. Based on this body of research, it appears that lithium has a reversible and subtle negative effect upon psychomotor speed and a trend toward impaired verbal memory, yet no effect on visual-spatial ability or attention and concentration, and little evidence of prolonged cumulative effect [18]. In terms of the anticonvulsant mood stabilizers that are used to treat the illness, the overall cognitive side-effect profile also appears to be relatively benign. Divalproex has been associated with subtle effects upon attention and memory ability that appear to be dose related and that are also reversible with cessation of treatment [17]. In addition, divalproex treated patients show similar cognitive functioning relative to those treated with lithium [19]. The cognitive impact of carbamazepine has been shown to include mild effects upon learning and reaction time, although these findings have been based primarily on reports on patients with epilepsy and healthy individuals [17]. Oxcarbazepine, a derivative of

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carbamazepine, compares favourably in terms of a cognitive side-effect profile in relation to carbamazepine. With the exception of topiramate, other newer anticonvulsant mood stabilizers show minimal to absent cognitive side effects. In particular, lamotrigine appears to have a favourable side-effect profile and bipolar patients treated with this agent may perform better than those treated with divalproex or carbamazepine [20]. Clearly, the most significant negative cognitive side effects have been reported with topiramate, and cognitive symptoms include diminished word finding, attention and concentration, processing speed, fluency, working memory and perceptual ability [17]. Because of this robust finding, topiramate treated patients presenting with suspected or documented cognitive difficulties should be considered candidates for medication review and/or modification. The other major class of psychotropics used to treat bipolar includes antipsychotics, most frequently the second-generation or atypical antipsychotics. Even though much of the suggestion that these agents have a minimal negative or even beneficial effect on cognition is based on evidence from patients with schizophrenia, considerably less work has evaluated the cognitive effects of these medications on patients with bipolar disorder [21]. Ironically, in samples of patients with bipolar disorder, there is some cross-sectional correlational evidence that treatment with antipsychotics may be associated with mild cognitive side effects, unlike that observed in schizophrenia [17]. Whether this may be an artefact of poorer baseline cognitive scores and thus increased room for improvement in schizophrenia remains unclear. In addition, it is possible that poorer cognitive performance in bipolar patients treated with antipsychotics reflects poorer performance in psychotic bipolar patients rather than preferential cognitive side effects resulting from the antipsychotics. Extrapolating from work that has been conducted primarily in schizophrenia, there is strong evidence that use of anticholinergic agents is associated with clinically significant reductions in attention and memory functioning [17]. Considering other less frequently employed psychotropic medications, specific serotonin reuptake inhibitors (SSRI) antidepressants appear to have minimal negative impact and in some cases may have beneficial impacts upon neuropsychological functioning; however, these findings are almost exclusively based on patients with major depression, as studies in bipolar disorder are lacking [17]. On the other hand, tricyclic antidepressants exert a significant negative impact upon verbal learning and memory that is likely associated with the anticholinergic properties of these agents [17]. A final consideration for the treatment of patients with bipolar disorder concerns the use of benzodiazepines, as these medications have known deleterious cognitive effects upon attention, memory and disinhibition. In summary, although the various medications used to treat

bipolar disorders exert a somewhat variable range of cognitive side effects, their overall impact upon cognitive functioning is relatively minor and in many cases transient. Therefore, it is unlikely that the influence of these medications accounts for the magnitude of cognitive impairment that is observed in bipolar disorder.

Neuroimaging bipolar disorder cognition Advances in neuroimaging over the past 3 decades have progressively afforded unprecedented access to the structure and function of the ‘working brain’. Arguably, magnetic resonance imaging (MRI) has undergone the greatest evolution and currently provides the most diverse and pertinent tools for examining brain processing and the ability to ‘question the mind’ in a manner beyond what is possible with bedside neuropsychological testing [22]. In this section we briefly, and somewhat selectively, review some of the broad emerging insights from functional MRI studies that have examined aspects of bipolar disorder, and discuss their potential clinical salience and implications for future research in the context of cognition. A more comprehensive analysis of neuroimaging findings in bipolar disorder can be found in other chapters contained within this volume. In bipolar disorder research the problems surrounding a lack of consensus as regards diagnostic classification have made less of an impact on neuroimaging research than other fields, possibly because most studies have been conducted relatively recently over the past decade. A review of fMRI studies in bipolar disorder published in 2004 [23] noted the potential for identifying functional markers of bipolar disorder as findings from different groups [24–27] appeared to be implicating overlapping brain regions in the dysfunctional processing associated with bipolar disorder as compared to healthy controls. Since then, a number of influential models to explain bipolar disorder processing have been posited [28–30] and, though these have provided a useful framework for the interpretation of findings, many aspects of the functional differences seen in patients cannot be fully explained. Over the past five years, many more fMRI studies examining bipolar disorder [26,27,31–68] have been conducted. Most of these have been conducted in adults; however, an increasing number have examined younger populations [32,40,41,44,61–63], reflecting the heightened interest in identifying the early markers of bipolarity. In addition to the obvious population differences, the studies vary considerably in terms of the fMRI stimuli used, the paradigms employed for analysis and the extent to which potential confounds have been controlled. Medication is a prominent concern but one that is extremely difficult to manage ethically given that unmedicated bipolar patients are at greater risk of relapse. However, a few groups have attempted to identify the effects of medication by adopting longitudinal

Neurocognition in Bipolar Disorder

designs, but retention in these studies, and the numbers that are successfully scanned on two or more occasions, is extremely small (<10). In fact, samples in the majority of studies are modest (<20) and consequently most findings remain speculative. The array of stimuli that have been used in bipolar disorder fMRI studies is extensive and varied, and as such many cannot be meaningfully compared, either to each other, or indeed to the bedside neuropsychological tests from which they have been derived and adapted for the MRI environment. Clearly, the latter is also not a true reflection of ‘reality’ and has by its very nature many constraints that introduce further confounds that need to be borne in mind when considering fMRI data, such as the extreme noise of the scanner and the need to remain very still during the whole procedure. Nevertheless, the findings from fMRI experiments in bipolar disorder are proving to be extremely interesting and are providing unique insights into bipolar brain processing [22]. Functional MRI studies in bipolar disorder have basically attempted to explore both state (related to periods of mood disturbance) and trait (related to personality and genetic factors) markers of the illness. In order to do this, researchers have examined bipolar patients both when they are acutely unwell, namely when suffering from symptoms of depression or mania/hypomania, and when reasonably ‘recovered’ and symptom-free, namely euthymic. Across each of these groups, essentially two broad neuropsychological domains have been probed; emotion and cognition. The range of cognitive paradigms that have been used have been designed primarily to probe executive control functions such as working memory, response generation, response inhibition and sustained attention. It should be noted that in many instances the cognitive and emotional components are difficult to separate and the tests that have been utilized may in fact not be able to partition these functions. Functional MRI studies have attempted to investigate aspects of cognitive and emotional processing in bipolar disorder, using a wide variety of stimuli across the phases of the illness. These studies have been conducted predominantly in adult samples of subjects but there are a number of studies examining adolescent/paediatric populations that have demonstrated some interesting insights into the putative evolution of functional changes in bipolar disorder [32,40,41,44,61–63]. Thus far, the vast majority of studies have been cross-sectional; however, a number of ambitious studies have attempted to scan patients longitudinally with variable success [39,41,48,58,59]. The studies can be summarized according to mood state or paradigm-focus; however, the findings are not so easy to coalesce. The majority of studies have examined euthymic patients (though earlier studies, prior to 2004, began by examining depressed bipolar and indeed unipolar patients) using in particular cognitive paradigms [32,33,43,

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44,47,49–51,58–61,64–66]. Studies across each of the phases consistently show that there are functional differences in bipolar patients as compared to healthy controls and that the regions implicated are those involved in executive functioning and emotional processing, specifically the prefrontal cortex and limbic system. What is perhaps surprising is that the distinction between phases is not self-evident with many functional differences (as compared to healthy subjects) still present in euthymia. For example, a relatively consistent finding across all mood states and euthymia is increased subcortical limbic activity (amygdala, ventral striatum, hippocampus) to emotional stimuli in patients with bipolar disorder, as well as abnormal activation in prefrontal cortical areas that modulate these limbic regions. Studies that have attempted to differentiate the various mood states of bipolar disorder have shown both underactivity and hyperactivity that is not necessarily related to bipolar polarity but does distinguish illness from wellness. However, the extent to which these putative functional changes perceived on fMRI are unique to bipolar disorder remains unknown, as few studies have successfully examined comparable unipolar and bipolar depressed populations in significant numbers using the same paradigms. In conjunction with findings from neuropsychological studies, it is likely that both mood states and the very essence of having bipolar disorder contribute to significant changes in brain processing that are reflected in cognitive and emotional compromise. In this respect, studies that have examined younger populations have shown that the patterns are quite possibly different to those found in adults, and that the ‘adult fMRI picture’ emerges sometime during adolescence. This is important because in addition to using fMRI to partition bipolar disorder from major depression and schizophrenia and better understand the pathophysiology of the disorder in adults, it can potentially be used to identify the emergence and early-onset of bipolar disorder and to this end it is necessary to know the pattern of MRI changes in younger years and how these evolve. Discussion of specific findings from each of the imaging studies in both adults and younger populations is beyond the scope of this chapter; however, in summary, the findings appear to implicate abnormalities in the regulation of prefrontalsubcortical circuits that subserve emotion with generally heightened activity as compared to healthy controls in these regions during youth that then diminishes with advancing years and progression of the illness. These tentative findings raise tantalizing possibilities but need to be reaffirmed and established in patients without the potentially significant confounds of medication. Large longitudinal studies coupled with even larger cross-sectional studies are needed, using perhaps standardized fMRI stimuli and paradigms. Emotional dysregulation that is perhaps a consequence of diminished cognitive control is certainly observed in bipolar patients when unwell. In adults,

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fMRI imaging studies suggest that there is a diminution of the regulatory control exerted by prefrontal structures of the brain coupled with either primary or secondary hyperactivity in subcortical structures. This pattern has not been shown to reliably change with treatment and whether it is a state or trait-marker is unclear. However, cognitive impairment is often noted in patients with bipolar disorder and it is possible that this is the primary deficit in patients that leads to corticalsubcortical neurocircuit dysfunction [24,28–30]. The next step in neuroimaging research (once initial findings have been adequately clarified and corroborated) is to localize the cognitive deficits seen neuropsychologically using imaging and to link these findings to genetic markers.

the cognitive performance of healthy first-degree relatives of patients with the illness. Because unaffected relatives share substantial genetic overlap with bipolar probands, observed cognitive deficits in healthy relatives (relative to appropriately matched healthy controls) could indicate that identified cognitive deficits have a genetic basis associated with vulnerability for the illness. This is particularly the case when cognitive abilities with high heritability are considered [70]. Identification of cognitive deficits in unaffected relatives may in turn facilitate the search for specific genetic and causal mechanisms underlying the illness. Such cognitive deficits may turn out to represent endophenotypes that are more genetically discoverable due to their presumed closer link to genes as well as their lesser biological complexity when compared to psychiatric phenotypes. Another advantage of studying high risk samples is that unlike patients, relatives of patients with the illness are free of medications and prominent mood symptoms, which as described above could exert some influence on cognitive functioning. In the past few years, an increasing number of cognitive studies in high risk populations have been published, and as of this writing there are two very recent meta-analytic studies that have been conducted on this literature [5,6]. Figure 2 summarizes these meta-analytic data by plotting the mean effect size cognitive differences between healthy first-degree relatives of patients with bipolar disorder and matched healthy controls. Although considerably attenuated relative to patients with bipolar illness (see Figure 1), healthy relatives of patients with bipolar disorder nonetheless show significant declines in the primary domains of verbal learning and memory, executive functioning (set shifting, response inhibition) and sustained attention (inattention rather than impulsivity). These data provide

Aetiology of cognitive impairment Because cognitive deficits in bipolar disorder are not likely to be fully explained by variables such as residual mood symptoms or medication effects, and because they likely at least partly reflect underlying brain dysfunction, the question of the aetiology of these core neuropsychological deficits becomes central. Two possibilities (not mutually exclusive) that have been considered are that cognitive impairments at least partly result from genetic vulnerability associated with the illness, and that cognitive impairments are the result of progressive deficits associated with increased illness burden [30,69].

Genetic vulnerability A major strategy for investigating whether cognitive impairment in bipolar disorder results from genetic susceptibility associated with the illness consists of evaluating 1.0 0.8

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Fig. 2 Summary of 2 meta-analyses illustrating the mean effect size differences between first-degree relatives of patients with bipolar disorder and healthy controls. Note: if an effect size for a given measure was reported in more than one meta-analysis, then the mean value was calculated. WCST ¼ Wisconsin Card Sorting Test; CPT ¼ Continuous Performance Test.

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evidence that at least a portion of the cognitive impairment associated with bipolar disorder is likely to be due to genetic vulnerability to the illness, and that the described deficits may serve as primary candidate endophenotypes of bipolar disorder. In addition, based on the cognitive deficits identified in relatives, the brain systems implicated include frontal-temporal-limbic brain regions. At this point, the search into the genetic basis of potential cognitive endophenotypes in bipolar disorder is in its infancy. This effort will require continued refinement of the appropriate endophenotype(s) for bipolar disorder and discovery of their genetic basis. A further approach to determining the genetic basis of the bipolar disorder phenotype is to assess whether specific candidate genes and their known or suspected biological functions are abnormally represented in bipolar disorder, and whether these genetic variants are associated with clinical features of the illness such as cognitive impairment. Although these studies are more prevalent in the context of schizophrenia, they are beginning to emerge in bipolar disorder. Burdick et al. (2007) reported an association between diagnosis of bipolar I disorder and a specific single nucleotide polymorphism (SNP) on the catechol O-methyltransferace (COMT) gene, which has been linked to prefrontal dopamine metabolism and availability [71]. Importantly, they also found an association between presence of the risk allele in patients and verbal memory performance. Similarly, the Val66Met polymorphism of the BDNF gene, which has been implicated to be involved in various mood disorders, has also been found to associate with Wisconsin Card Sorting Test performance in patients with bipolar disorder [72]. In addition, in a large cohort of families with bipolar disorder, specific allelic variants of the disrupted-in-schizophrenia-1 (DISC-1) gene, which encodes for a multifunctional protein involved in neurodevelopment and synaptic modulation, were associated with either presence of psychosis or bipolar spectrum diagnosis [73]. Moreover, these genetic variants were associated with cognitive functioning, including perseveration (psychosis) as well as processing speed and verbal fluency (bipolar spectrum). These and similar studies may provide preliminary insights into the genetic basis of bipolar disorder and its clinical features. However, the aetiology of psychiatric disorders such as bipolar disorder is likely complex and determined by multiple genetic and environmental factors [70]. Nevertheless, efforts to link genetic variants to bipolar illness and associated clinical features, such as cognitive impairment and psychosis, may help to clarify this complexity and identify the overlap between disorders such as bipolar disorder and schizophrenia.

of whether deficits may progress throughout the course of illness. The potential underlying causes of progressive decline are varied, and could include toxicity resulting from increased illness duration, chronicity, multiple episodes or cumulative treatment side effects. One indirect method of addressing whether cognitive deficits may be progressive has been to evaluate correlations between cognitive impairment and illness burden variables such as duration of illness, number of hospitalizations and number of episodes in samples of patients with bipolar disorder. In a review of this literature, Robinson et al. (2006) evaluated existing studies of cognitive functioning in bipolar disorder and compiled the correlations between neuropsychological variables and multiple illness burden variables, including number of affective episodes (manic, depressive, total), number of hospitalizations, age at illness onset, duration of illness and length of time in euthymia [69]. Their analysis revealed that poor cognitive function, especially verbal memory, was frequently associated with multiple burden variables, including previous number of affective episodes, illness duration and number of hospital admissions. Regarding mood episodes, an increasing number of manic episodes was associated with diminished delayed verbal memory and some aspects of executive function, whereas an increasing number of depressive episodes was less strongly associated with a wider range of cognitive impairment. The implication of these findings is that cognition declines as a result of an increasing number of mood episodes, hospitalizations and illness duration. However, these observations should be interpreted cautiously because of their cross-sectional correlational nature, and because of the possibility that the path of causation could be in the reverse direction. That is, it is possible that patients with poorer cognitive impairment to begin with follow a trajectory of poorer outcome that includes more mood episodes and a higher number of hospitalizations. As the authors point out, there are also other potential confounds inherent in this literature, including a likely bias for reporting positive cognition-burden correlations as well as the failure to control for other potentially important variables such as age and current symptom ratings in these correlations. As a result, although existing data provide some preliminary support for the hypothesis that cognition declines throughout the course of illness, a stronger test will need to come from longitudinal studies that track neuropsychological function in patients across time.

Progressive cognitive decline

In light of the converging evidence that cognitive impairment is highly prevalent in bipolar disorder, a further question that arises is whether these cognitive deficits have a significant impact on patient’s everyday functioning. If

A second major line of enquiry regarding the aetiology of cognitive deficits in bipolar disorder involves investigation

Clinical significance of cognitive impairments

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indeed cognitive impairment in bipolar disorder is predictive of an individual’s real-world adaptive functioning, this underscores the urgency to identify and treat these cognitive deficits in the hope of improving functional outcome and quality of life.

cognitive assessment [78]. By linking cognition, not only to present but future psychosocial functioning, such longitudinal studies may provide further insight into the causal direction of the association between cognition and psychosocial functioning.

Cognition and functional outcome

Neuropsychological assessment in bipolar disorder

Establishing a link between the cognitive impairments observed in bipolar disorder and indices of everyday functioning, serves to reinforce the importance of detecting and understanding cognitive impairments in this population. In the same way that multiple measures have been developed for assessing cognitive impairment, there are multiple ways of measuring everyday psychosocial functioning in patients. One of the simplest and most frequent methods for measuring everyday function consists of using global ratings such as the DSM based Global Assessment of Functioning (GAF) scale or similar scales. A number of studies have been conducted, aimed at assessing the correlation between scores on global functioning scales and a range of cognitive measures. In general, these studies have revealed a consistent association between global psychosocial functioning and cognitive functioning, primarily in the domains of (verbal) memory functioning and several aspects of executive function [74]. Other investigators have also evaluated the cognitive correlates of more specific functional domains, such as occupational status. These studies also support a robust association between cognitive functioning and work status in similar cognitive domains. Importantly, the association between cognitive and functional outcome does not appear to be a function of symptomatic status, as when psychiatric symptom variables are controlled the cognition-function association persists. Nevertheless, associations between cognition and functional outcome may be stronger in symptomatic rather than euthymic samples [75]. In addition, the correlation between cognition and psychosocial functioning may be more evident in studies where functional status is derived from objective rather than subjective outcome measures. The basis for this is unclear, but may be associated with diminished insight in patients with bipolar disorder [74]. Although the large majority of studies in this area have investigated cognitive and psychosocial functioning concurrently, at least two studies have measured these outcomes longitudinally. Jaeger et al. (2007) reported that baseline measures of attention and ideational fluency were predictive of psychosocial functioning after 1 year, even after control of residual symptoms at both time points [76]. In our own work, we have recently reported that cognitive deficits are present in clinically stable patients after they have experienced their first lifetime manic episode [77]. Moreover, such early cognitive deficits observed in these patients, particularly in the memory domain, appear predictive of psychosocial functional outcome 6 months after

In light of the relevance of cognitive impairment to bipolar disorder, cognitive assessment should be considered a key element of standard of care in contemporary practice. In patients who present with diminished psychosocial functioning, neuropsychological assessment can be a useful means to help sort out the underlying determinants of dysfunction and evaluate whether cognitive factors may be contributing to poor daily function. In instances where neuropsychological deficits are minimal or absent, difficulties in functioning may then be attributed to other potential underlying factors such as mood symptoms, comorbidity, personality variables, situational factors and other variables that require attention. Due to the weak correlation between subjective patient reports of cognitive symptoms and objective testing results [79], clinicians should not exclusively rely on patient reports as the sole basis for investigating potential cognitive impairments. Similarly, self-report of cognitive complaints may not always reflect objective cognitive impairment, but instead may be associated with mood states, particularly depression. A comprehensive neuropsychological evaluation should be guided by knowledge of the cognitive functions that are most frequently implicated in bipolar disorder (Figure 1). Brief cognitive screening approaches may have some utility in initial screening of patients, but are limited by diminished psychometric properties and reduced sensitivity to cognitive impairment. This may result in increased false negative rates, particularly in individuals presenting with less severe cognitive deficits. Based on the increasing recognition that deficits are likely present at illness onset [77,80], neuropsychological evaluation is warranted early in the course of illness so that strengths and weaknesses can be identified and rehabilitative and treatment recommendations can be made. Early assessments can also establish baseline levels of neuropsychological functioning that can be used to assess longitudinal changes in cognitive functioning. Unless the goal is to assess short-term treatment effects upon cognition, neuropsychological referrals should be made when patients are relatively clinically stable and asymptomatic.

Treatment strategies for cognitive deficits At this point, the utility of neuropsychological assessment in bipolar disorder primarily lies in the delineation of

Neurocognition in Bipolar Disorder

cognitive strengths and weaknesses and in contributing to the formulation of treatment, rehabilitative and disposition plans. However, identified cognitive deficits should be increasingly considered legitimate targets for treatment interventions, and neuropsychological measures should be used as clinical outcome measures for quantifying change in patient’s neurocognitive status. To date there have been remarkably few controlled clinical trials assessing either the positive or negative effects of pharmacological treatments on cognition in bipolar disorder. As a result, there are no established rational or evidence based treatments for cognitive deficits in bipolar disorder [81,82]. Of the current mood stabilizers used to treat bipolar disorder, lamotrigine appears to be associated with the most positive cognitive profile, and there is at least scant evidence that this agent may lead to some improvement in cognitive function in bipolar disorder [83]. The effects of atypical antipsychotics on cognition in bipolar disorder have also been understudied, making it difficult to assess whether the modest cognitive enhancement properties that are periodically observed in schizophrenia also apply to bipolar disorder. There is some evidence suggesting possible cognitive enhancement resulting from treatment with risperidone relative to a conventional antipsychotic [84]; however, clearly more work is needed to assess the potential cognitive enhancing role of antipsychotics. The use of procholinergic cognitive enhancers has primarily been evaluated in the context of dementia and age-associated cognitive impairment, so the utility of these agents in bipolar disorder is largely unknown. Several case studies indicate that galantamine may have some positive effects on cognition, but this requires further study in controlled clinical trials [82]. It is also too early to tell whether there is a role for treatment with psychostimulants in boosting cognitive function in bipolar disorder. Pramipexole, a D2/D3 receptor agonist that increases the availability of dopamine, has been shown to have potential cognitive enhancing properties when used as an adjunctive treatment in bipolar disorder [81]. In another experimental study, there is some evidence that mifepristone, a glucocorticoid receptor antagonist, may have a positive influence on executive and memory functions based on its actions on a dysfunctional HPA system [85]. To summarize, despite the fact that treatment studies targeting cognitive deficits in patients with bipolar disorder are in their early stages, there is some cause for optimism that interventions will be developed to target this important clinical feature of bipolar disorder.

Conclusions The pace of research into cognitive functioning in bipolar disorder has accelerated rapidly within the past few years, and it is now recognized that cognitive impairment represents an important clinical feature of bipolar disorder.

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Although individuals diagnosed with bipolar disorder demonstrate a wide range of cognitive functioning, a significant proportion of patients with the diagnosis can be expected to show clinically significant cognitive impairment. Cognitive dysfunction occurs independently of mood state and is most frequently expressed through diminished performance on neuropsychological tests of attention, memory and executive functioning. Although cognitive ability in patients is influenced by acute psychiatric symptoms and medications, these variables do not account for the persistent underlying deficits observed in the illness. Increasingly, cognitive impairments have been linked to dysfunctional brain systems; however, cognitive imaging studies have employed diverse methodologies and small patient samples, thus limiting the ability to make firm conclusions. Nevertheless, these studies implicate the involvement and dysregulation of a complex distributed network of cortical, subcortical and limbic brain regions underlying abnormal cognition and emotion in the illness. Preliminary work suggests that subsets of patients with psychotic symptoms and with the bipolar I subtype may show preferential cognitive impairment; however, the validity of these findings and of putative bipolar disorder subtypes requires further study. Although the underlying cause(s) of neuropsychological deficits have yet to be revealed, it is likely that impairments reflect both fixed and progressive components, and that both genetic and neurotoxic or deteriorative influences may be present. The clinical urgency to both identify and treat neuropsychological deficits in bipolar disorder is highlighted by the consistent finding that cognitive deficits reliably predict everyday psychosocial functioning. However, there is currently a paucity of research into treatments approaches aimed at enhancing cognitive abilities in bipolar disorder, and this represents an important area for future research.

References 1. Goldberg, J.F. and Burdick, K.E. (2008) Cognitive Dysfunction in Bipolar Disorder: A Guide for Clinicians, American Psychiatric Press, Washington, DC. 2. Lezak, M.D., Howieson, D.B. and Loring, D.W. (2004) Neuropsychological Assessment, 4th edn, Oxford University Press, New York. 3. Clark, L., Iversen, S.D. and Goodwin, G.M. (2001) A neuropsychological investigation of prefrontal cortex involvement in acute mania. Am. J. Psychiatry, 158, 1605–1611. 4. Malhi, G.S., Cahill, C.S. and Mitchell, P. (2008) Impact of mood, anxiety, and psychotic symptoms on cognition in patients with bipolar disorder, in Cognitive Dysfunction in Bipolar Disorder: A Guide for Clinicians (eds J.F. Goldbergand K.E. Burdick), American Psychiatric Press, Washington, DC, pp. 89–111. 5. Arts, B., Jabben, N., Krabbendam, L. and van Os, J. (2008) Meta-analyses of cognitive functioning in euthymic bipolar

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patients and their first-degree relatives. Psychol. Med., 38, 771–785. Bora, E., Yucel, M. and Pantelis, C. (2009) Cognitive endophenotypes of bipolar disorder: A meta-analysis of neuropsychological deficits in euthymic patients and their firstdegree relatives. J. Affect. Disord., 113, 1–20. Robinson, L.J., Thompson, J.M., Gallagher, P. et al. (2006) A meta-analysis of cognitive deficits in euthymic patients with bipolar disorder. J. Affect. Disord., 93, 105–115. Torres, I.J., Boudreau, V.G. and Yatham, L.N. (2007) Neuropsychological functioning in euthymic bipolar disorder: A meta-analysis. Acta. Psychiatr. Scand., 116 (Suppl 434), 17–26. Krabbendam, L., Arts, B., van Os, J. and Aleman, A. (2005) Cognitive functioning in patients with schizophrenia and bipolar disorder: A quantitative review. Schizophr. Res., 80, 137–149. Martınez-Aran, A., Vieta, E., Colom, F. et al. (2004) Cognitive impairment in euthymic bipolar patients: Implications for clinical and functional outcome. Bipolar Disord., 6, 224–232. Thompson, J.M., Gallagher, P., Hughes, J.H. et al. (2005) Neurocognitive impairment in euthymic patients with bipolar affective disorder. Br. J. Psychiatry: The Journal of Mental Science, 186, 32–40. Simonsen, C., Sundet, K., Vaskinn, A. et al. (2008) Neurocognitive profiles in bipolar I and bipolar II disorder: Differences in pattern and magnitude of dysfunction. Bipolar Disord., 10, 245–255. Torrent, C., Martinez-Aran, A., Daban, C. et al. (2006) Cognitive impairment in bipolar II disorder. Brit. J. Psychiat., 189, 254–259. Murray, R.M., Sham, P., Van Os, J. et al. (2004) A developmental model for similarities and dissimilarities between schizophrenia and bipolar disorder. Schizophr. Res., 71, 405–416. de Almeida Rocca, C.C., de Macedo-Soares, M.B., Gorenstein, C. et al. (2008) Verbal fluency dysfunction in euthymic bipolar patients: A controlled study. J. Affect. Disord., 107, 187–192. Glahn, D.C., Bearden, C.E., Barguil, M. et al. (2007) The neurocognitive signature of psychotic bipolar disorder. Biol. Psychiatry., 62, 910–916. Goldberg, J.F. (2008) Adverse cognitive effects of psychotropic medications, in Cognitive Dysfunction in Bipolar Disorder: A Guide for Clinicians (eds J.F. Goldbergand K.E. Burdick), American Psychiatric Press, Washington, DC, pp. 137–158. Pachet, A.K. and Wisniewski, A.M. (2003) The effects of lithium on cognition: An updated review. Psychopharmacology (Berl.), 170, 225–234. Senturk, V., Goker, C., Bilgic, A. et al. (2007) Impaired verbal memory and otherwise spared cognition in remitted bipolar patients on monotherapy with lithium or valproate. Bipolar Disord., 9 (Suppl 1), 136–144. Daban, C., Martinez-Aran, A., Torrent, C. et al. (2006) Cognitive functioning in bipolar patients receiving lamotrigine: Preliminary results. J. Clin. Psychopharmacol., 26, 178–181. Macqueen, G. and Young, T. (2003) Cognitive effects of atypical antipsychotics: Focus on bipolar spectrum disorders. Bipolar Disord., 5 (Suppl 2), 53–61.

22. Malhi, G.S. and Lagopoulos, J. (2008) Making sense of neuroimaging in psychiatry. Acta Psychiatr. Scand., 117, 100–117. 23. Malhi, G.S., Lagopoulos, J., Owen, A.M. and Yatham, L.N. (2004) Bipolaroids: functional imaging in bipolar disorder. Acta Psychiatr. Scand., 110 (Suppl 422), 46–54. 24. Blumberg, H., Leung, H., Skudlarski, P.E.A. et al. (2003) A functional magnetic resonance imaging study of bipolar disorder: state- and trait-related dysfunction in ventral prefrontal cortices. Arch. Gen. Psychiatry, 60, 601–609. 25. Yurgelun-Todd, D.A., Gruber, S.A., Kanayama, G. et al. (2000) fMRI during affect discrimination in bipolar affective disorder. Bipolar Disord., 2, 237–248. 26. Malhi, G.S., Lagopoulos, J., Ward, P.B. et al. (2004) Cognitive generation of affect in bipolar depression: an fMRI study. Eur. J. Neurosci., 19, 741–754. 27. Malhi, G.S., Lagopoulos, J., Sachdev, P. et al. (2004) Cognitive generation of affect in hypomania: an fMRI study. Bipolar Disord., 6, 271–285. 28. Phillips, M.L., Drevets, W.C., Rauch, S.L. and Lane, R.D. (2003) Neurobiology of emotion perception I: The neural basis of normal emotion perception. Biol. Psychiatry, 54, 504–514. 29. Phillips, M.L., Drevets, W.C., Rauch, S.L. and Lane, R.D. (2003) The neurobiology of emotion perception II: Implications for major psychiatric disorders. Biol. Psychiatry, 54, 515–528. 30. Strakowski, S.M., Delbello, M.P. and Adler, C.M. (2005) The functional neuroanatomy of bipolar disorder: a review of neuroimaging findings. Mol. Psychiatry, 10, 105–116. 31. Abler, B., Greenhouse, I., Ongur, D. et al. (2008) Abnormal reward system activation in mania. Neuropsychopharmacology, 33, 2217–2227. 32. Adler, C.M., Delbello, M.P., Mills, N.P. et al. (2005) Comorbid ADHD is associated with altered patterns of neuronal activation in adolescents with bipolar disorder performing a simple attention task. Bipolar Disord., 7, 577–588. 33. Adler, C.M., Holland, S.K., Schmithforst, V. et al. (2004) Changes in neuronal activation in patients with bipolar disorder during performance of a working memory task. Bipolar Disord., 6, 540–549. 34. Altshuler, L., Bookheimer, S., Proenza, M.A. et al. (2005) Increased amygdala activation during mania: a functional magnetic resonance imaging study. Am. J. Psychiatry, 162, 1211–1213. 35. Altshuler, L., Bookheimer, S., Townsend, J. et al. (2008) Regional brain changes in bipolar I depression: a functional magnetic resonance imaging study. Bipolar Disord., 10, 708–717. 36. Altshuler, L., Bookheimer, S., Townsend, J. et al. (2005) Blunted activation in orbitofrontal cortex during mania: a functional magnetic resonance imaging study. Biol. Psychiatry, 58, 763–769. 37. Blumberg, H.P., Donegan, N.H., Sanislow, C.A. et al. (2005) Preliminary evidence for medication effects on functional abnormalities in the amygdala and anterior cingulate in bipolar disorder. Psychopharmacology (Berl.), 183, 308–313. 38. Caligiuri, M.P., Brown, G.G., Meloy, M.J. et al. (2006) Striatopallidal regulation of affect in bipolar disorder. J. Affect. Disord., 91, 235–242.

Neurocognition in Bipolar Disorder 39. Caligiuri, M.P., Brown, G.G., Meloy, M.J. et al. (2004) A functional magnetic resonance imaging study of cortical asymmetry in bipolar disorder. Bipolar Disord., 6, 183–196. 40. Chang, K., Adleman, N.E., Dienes, K. et al. (2004) Anomalous prefrontal-subcortical activation in familial pediatric bipolar disorder: a functional magnetic resonance imaging investigation. Arch. Gen. Psychiatry, 61, 781–792. 41. Chang, K.D., Wagner, C., Garrett, A. et al. (2008) A preliminary functional magnetic resonance imaging study of prefrontal-amygdalar activation changes in adolescents with bipolar depression treated with lamotrigine. Bipolar Disord., 10, 426–431. 42. Chen, C.H., Lennox, B., Jacob, R. et al. (2006) Explicit and implicit facial affect recognition in manic and depressed States of bipolar disorder: a functional magnetic resonance imaging study. Biol. Psychiatry, 59, 31–39. 43. Curtis, V.A., Thompson, J.M., Seal, M.L. et al. (2007) The nature of abnormal language processing in euthymic bipolar I disorder: evidence for a relationship between task demand and prefrontal function. Bipolar Disord., 9, 358–369. 44. Dickstein, D.P., Rich, B.A., Roberson-Nay, R. et al. (2007) Neural activation during encoding of emotional faces in pediatric bipolar disorder. Bipolar Disord., 9, 679–692. 45. Elliot, R., Ogilvie, A., Rubinszetin, J.S. et al. (2004) Abnormal ventral frontal response during performance of an affective go/no go task in patients with mania. Biol. Psychiatry, 55, 1163–1170. 46. Foland, L.C., Altshuler, L.L., Bookheimer, S.Y. et al. (2008) Evidence for deficient modulation of amygdala response by prefrontal cortex in bipolar mania. Psychiatry Res., 162, 27–37. 47. Gruber, S.A., Rogowska, J. and Yurgelun-Todd, D.A. (2004) Decreased activation of the anterior cingulate in bipolar patients: an fMRI study. J. Affect. Disord., 82, 191–201. 48. Haldane, M., Jogia, J., Cobb, A. et al. (2008) Changes in brain activation during working memory and facial recognition tasks in patients with bipolar disorder with Lamotrigine monotherapy. Eur. Neuropsychopharm., 18, 48–54. 49. Kronhaus, D.M., Lawrence, N.S., Williams, A.M. et al. (2006) Stroop performance in bipolar disorder: further evidence for abnormalities in the ventral prefrontal cortex. Bipolar Disord., 8, 28–39. 50. Lagopoulos, J., Ivanovski, B. and Malhi, G.S. (2007) An eventrelated functional MRI study of working memory in euthymic bipolar disorder. J. Psychiatr. Neurosci., 32, 174–184. 51. Lagopoulos, J. and Malhi, G.S. (2007) A functional magnetic resonance imaging study of emotional Stroop in euthymic bipolar disorder. Neuroreport, 18, 1583–1587. 52. Lawrence, N.S., Williams, A.M., Surguladze, S. et al. (2004) Subcortical and ventral prefrontal cortical neural responses to facial expressions distinguish patients with bipolar disorder and major depression. Biol. Psychiatry, 55, 578–587. 53. Lennox, B.R., Jacob, R., Calder, A.J. et al. (2004) Behavioural and neurocognitive responses to sad facial affect are attenuated in patients with mania. Psychol. Med., 34, 795–802. 54. Malhi, G.S., Lagopoulos, J., Owen, A.M. et al. (2007) Reduced activation to implicit affect induction in euthymic bipolar patients: an fMRI study. J. Affect. Disord., 97, 109–122.

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78. Torres, I.J., DeFreitas, C.M., DeFreitas, V.G. et al. (submitted) Relationship between cognitive functioning and six month clinical and functional outcome in patients with first episode Bipolar I Disorder. 79. Burdick, K.E., Endick, C.J. and Goldberg, J.F. (2005) Assessing cognitive deficits in bipolar disorder: Are self-reports valid? Psychiatry Res., 136, 43–50. 80. Gruber, S.A., Rosso, I.M. and Yurgelun-Todd, D. (2008) Neuropsychological performance predicts clinical recovery in bipolar patients. J. Affect. Disord., 105, 253–260. 81. Burdick, K.E., Braga, R.J., Goldberg, J.F. and Malhotra, A.K. (2007) Cognitive dysfunction in bipolar disorder: Future place of pharmacotherapy. CNS Drugs, 21, 971–981. 82. Goldberg, J.F. and Young, L.T. (2008) Pharmacologic strategies to enhance neurocognitive function, in Cognitive Dysfunction in Bipolar Disorder: A Guide for Clinicians (eds J. F. Goldbergand K.E. Burdick), American Psychiatric Press, Washington, DC, pp. 159–194. 83. Khan, A., Ginsberg, L.D., Asnis, G.M. et al. (2004) Effect of lamotrigine on cognitive complaints in patients with bipolar I disorder. J. Clin. Psychiat., 65, 1483–1490. 84. Reinares, M., Martinez-Aran, A., Colom, F. et al. (2000) Longterm effects of the treatment with risperidone versus conventional neuroleptics on the neuropsychological performance of euthymic bipolar patients. Actas Espanolas De Psiquiatria, 28, 231–238. 85. Young, A.H., Gallagher, P., Watson, S. et al. (2004) Improvements in neurocognitive function and mood following adjunctive treatment with mifepristone (RU-486) in bipolar disorder. Neuropsychopharmacology, 29, 1538–1545.

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The Genius-Insanity Debate: Focus on Bipolarity, Temperament, Creativity and Leadership Hagop S. Akiskal1,2,3 and Kareen K. Akiskal3 1

University of California at San Diego, San Diego, CA, USA San Diego Veterans Administration Medical Center (UCA), USA 3 International Mood Center, La Jolla, CA, USA 2

Why is it that all those who have become eminent in philosophy or politics or poetry or the arts are clearly melancholics and some of them to such an extent as to be affected by diseases caused by black bile?. . . Aristotle (Problema XXX)

A great deal of new data [1–8] and several major monographs [9–14] have been published during the first decade of this century alone, documenting the relationship between mental disorders and creative achievement. Can our field bear yet another review of this topic? Like the editors of this book, we feel a new synthesis of how this complex literature is shaping up is useful, but ultimately defer the question to the judgement of the reader.

History Since at least the time of the ancient Greeks, eminence in various professions – including artistic domains – has been linked to mental disorders [15]. Socrates thought that mental illness was a divine gift, and Plato linked creativity to the inspiration deriving from madness which, interestingly, he distinguished from ‘clinical madness’. Aristotle (in our opening quote), in a more nuanced statement, observed that eminence had something to do with the melancholic temperament, and in some instances to diseases arising from the black humour (whose exact nature still escapes us!). It is important to point out that melancholia in those days did refer to a broader group of illnesses than clinical depression in contemporary psychiatry. Beyond depressive withdrawal, the Problemata described mood instability, impulsivity, alcoholism and suicidality. In Roman times, Seneca went one step further and posited that ‘no great mind is immune from a little insanity’ [16].

Bipolar Disorder: Clinical and Neurobiological Foundations Edited by Lakshmi N. Yatham and Mario Maj © 2010 John Wiley & Sons, Ltd. ISBN: 978-0-470-72198-8

The foregoing concepts are reflected in more modern times in the ‘genius-insanity’ thesis put forward by Cesare Lombroso [17]. According to his theory, genius and insanity had a common genetic ancestry. It is of interest that the pathology described was typified by passion, preoccupation with glory, as well as inspiration and energy followed by exhaustion. There have been data-based investigations of the nature of ‘insanity’ of creative individuals in contemporary psychiatry, which will be reviewed throughout this chapter. Before doing so, it is relevant to point out that there have always been sceptics about such a relationship.

Methodologic issues Eliot Slater [18], the famed British psychiatrist, based in part on Adele Juda’s research on geniuses of German music, art, literature and science [19], observed that in this group, psychotic disorders overall were ‘only slightly greater than would have been expected from a sample of ordinary men’. Weisberg wrote a monograph in which the genius is considered a ‘myth’ [20]. Pathography, the discipline that relates creative output to life experiences, typically those with negative valence, tends to focus on selected individuals. For instance, a book advancing the notion of ‘creative malady’ [21] examined the lives of Charles Darwin, Florence Nightingale, Mary Baker Eddy, Sigmund Freud, Marcel Proust and Elizabeth Barrett Browning. On the other hand, Dean Simonton, the dean of scientific research on eminence, who investigated all major historical figures [22] and scientists [23], found common positive strengths in the psychologic make-up of his more representative sample. Finally, Don Goodwin narrowly focused on a cohort of American literary figures awarded Nobel Prizes, most of whom had extensive histories of alcoholism [24]. Charlotte Waddell, a Canadian psychiatrist, observed that there was ‘limited scientific evidence to associate creativity with mental illness’ [25]. Paul Wolff, a California pathologist, went even further to suggest that ‘if clinical 83

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chemistry had existed then. . .’ the mental illnesses of various historical figures in art, music and political life could have been instead diagnosed with well-known physical illnesses [26]. We would add to these critiques the methodologic point that there may well be a selective bias in biographical and media reports towards those eminent individuals who were mentally ill and confirmed the popular notion that suffering is needed for artistic creativity; the ‘healthy artist’ [27] appears to have been neglected and perhaps even attained less notoriety. Although biographical studies of well-known individuals are not necessarily the most unbiased forms of information, they have been a favourite source for scholarly work [21,24,28]. The landmark development in this field that lent historic credibility to all genres of inquiries on creativity is Sir Francis Galton’s Hereditary Genius [29]. A more contemporaneous work by Runyan [30] has focused on four biographies – those of Abraham Lincoln, Sigmund Freud, Vincent Van Gogh and Virginia Wolf – to illustrate how objective, verifiable information can be gathered from existing records. This monograph also provides useful methodologic insights in the examination of narratives of the lives of Jesus of Nazareth, Samuel Johnson, Benjamin Franklin, King George III of England, Daniel Paul Schreber and Malcolm X.

Is psychosis relevant to creative genius? This question is not central to our main theme on bipolarity and creativity. However, given that the role of psychosis and schizophrenia [17,31,32] has long dominated the literature on creativity, a brief discussion of it is therefore a necessary background to our theme. The first question one needs to ask is how ‘psychosis’, ‘creativity’ and ‘eminence’ should be defined? The question already indicates the broad nature of the inquiries undertaken historically and contemporaneously, and the relative lack of precision that has muddled some of the early studies. More often than not, ‘psychosis’ and ‘madness’ have not been further characterized or else relegated to the domain of ‘schizophrenia’. As far as subjects studied, it has ranged from individuals known to be mentally ill, well-known artists in the community, professionals in high national office, to students enrolled in various colleges and universities. More sophisticated and imaginative developments have evolved recently. Psychologists have explored whether psychosis identifies eminent individuals or constitutes their familial background. This brings up the interesting possibility that certain familial traits, rather than the fullblown psychosis, might be what are involved in eminence and creativity. A variant of this perspective is that the eminent individual might suffer serious bouts of disease, but

produces his or her most distinguished work in periods free from major illness, during which they would presumably be exhibiting the desired trait of the condition. In an important methodologic advance, the Chapmans [33–34] and others [35] have operationalized the latter trait and developed instruments to test it. In doing so, they have based themselves on Meehl’s concept of ‘schizotypy’ [36]. To summarize a complex literature on creativity and psychosis, suffice it to mention the following considerations and substantive advances: 1 The similarity of primary process thinking of the schizophrenic and the free associations exhibited by artistic expressions [31]. However, Andreasen and Powers [37] have shown that such a conceptual style is more characteristic of mania than schizophrenia. 2 ‘Janusian thinking’ [38,39], operationalized as the psychotic patients’ and creative individual’s receptivity to a broad range of stimuli, which makes it possible for them to simultaneously consider mutually exclusive and contradictory ideas. 3 It has been proposed that psychedelic experiences [40,41] too can enhance a richness of perceptual experiences and associations. 4 Although schizotypy has been recently linked to visual and related artistic expressions [5], the gift most clearly familially linked to psychosis and schizophrenia is mathematics and related academic pursuits [2]. 5 The autistic spectrum [11], though distinct from schizotypy, must also be mentioned in this context, because it appears relevant to creativity in mathematical philosophy, related computer sciences and beyond. Such observations have led to the hypothesis that relatives of schizophrenic patients have a creative edge [32] which might account for their mating success [42].

Affective temperaments and achievement We return to Aristotle, who wondered whether creative eminence derived from temperament and its excesses [15]. In modern parlance, he appears to have placed the query on exceptional greatness within the dimensional space between temperament and affective disease (see Figure 1) as conceptualized by Kretschmer [43]. This conceptualization tends to address the paradox, posed by Heidi Northwood [44] on how the Greek ideal of the ‘golden mean’ (i.e. a temperament) – which predisposes to a diseased pathological state (i.e. melancholia) – can be juxtaposed. This is indeed the philosophical virtue embodied in the concept of the bipolar spectrum, which extends from normative temperament to bipolar psychosis [45]. Genetically, the assumption is one of oligogenic inheritance leading to overlapping phenotypes separated by degrees of severity [47]. This concept is schematically shown in Figure 1.

Temperament

Population frequency

The Genius-Insanity Debate

Bipolar

Genetic loading Fig. 1 Temperament and bipolar disease in a spectrum concept.

In a sample of 750 affectively ill patients, even with a liberal definition of creative output, such output was largely limited to 8% of those with bipolar II and III [48]; the corresponding rate in bipolar and schizoaffective psychoses was <0.5. Investigations on eminence in the United States [49] and France [50] have shown that professional success is significantly higher in the clinically well relatives compared to bipolar probands: the same finding holds up for creativity which appears mediated in the main by the cyclothymic temperament [3,13,48]. Although creative samples have a significant excess of bipolarity (see review in [51]), with the exception of Jamison’s sample [52–54], full-blown manic-depressive illness is relatively uncommon. Such data are compatible with our hypothesis that it is the ‘dilute’ temperamental form of bipolarity that subserves eminence and creativity. Our collaborative study in Milan [3] has supported the role of cyclothymia in artistic creativity and of hyperthymic temperamental traits in eminence. The fact that obsessive-compulsive traits in the Milan study had a moderating influence on these traits suggests that creativity and temperament and eminence are related in a complex fashion. A perusal of the traits constituting the cyclothymic and hyperthymic temperaments is relevant to their achievements, respectively, in artistic and leadership domains: The cyclothymic Temperament [54]: labile with rapid shifts in mood, unstable in energy, self-esteem and socialization, unevenly gifted and dilettante, yet keen in perception, intense in emotions and romantic. The hyperthymic Temperament [54]: outgoing, upbeat, fun-loving, sexually driven, jocular, optimistic, confident, full of ideas, eloquent, on the go, short-sleeper, tireless, likes to be the boss, single-minded, risk-taker, and unlikely to admit to his/her meddlesome nature. Traits reported by Feist [55] – openness to experience, unconventional, self-confidence, driven, ambitious, dominant and impulsive – in meta-analytic studies of creative scientists and artists are compatible with subthreshold bipolarity, that is the traits of the cyclothymic and hyperthymic individuals listed above. Feist’s work, in turn, derives from the conceptual framework and landmark research by Dredvhal and Cattell [56], Barron [57] and Mackinnon [58].

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Schizotypy, in our view, to the extent it involves trait deficits in experiencing pleasure, is expected to be negatively correlated with creative output [59]. We respectfully submit that the penchant for unusual experiences in the spectrum of measures related to ‘positive schizotypy’ reported amongst artists might in part reflect traits shared and/or captured by cyclothymia. We have elsewhere documented the excesses so characteristic of cyclothymic individuals in their personal, social and occupational life [60], as well as their evolutionary advantages in mating, including multiple marriages, and especially hypergamy (marrying above their social class). In blues musicians and Parisian painters and writers, our data to date published only in part [61], do suggest that creativity and eminence are associated, respectively, with the cyclothymic and hyperthymic temperaments rather than full-blown manic depressive illness per se. Ruth Richard’s research group [62] at Harvard has also shown the crucial role of cyclothymia in creativity. The foregoing findings and considerations are further borne out by new research from Stanford [4,6,7]. They are also compatible with earlier findings from the Iowa writers’ workshop by Andreasen and colleagues [63,64] – where cyclothymia and bipolar II were more prevalent than bipolar I – and Kretschmer’s classical treatise on the Psychology of Men of Genius [65]. In terms of how temperament enhances the creative process, we would submit it may involve both the biographic ups and downs of the cyclothymic, the energy and confidence of the hyperthymic, as well as the cognitive and perceptual changes of cyclothymia and mixity. It is wellknown that the melancholic and cyclothymic temperaments belong to the same factorial structure [66]. It is finally relevant in this context to also cite Stanghellini [67], who reported some degree of overlap between the melancholic and hyperthymic temperaments. This paradox might be understood if one considers the work-orientation of melancholic individuals between affective episodes and the habitual high energy of the hyperthymic [68].

Toward a synthesis Aristotle’s Problemata XXX, may have laid the foundations for much of subsequent research on creativity, achievement and eminence. As a footnote to his insight, we submit that the reason why creativity and professional eminence are associated with melancholia may arise from the fact that cyclothymic and hyperthymic temperaments constitute the foundations of melancholia [66], and the melancholia Aristotle is referring to is possibly bipolar II, or some territory in between. It is individuals with such temperaments who are possessed by intense passion and cognitive abilities for novelty and are willing to risk journeys into new realms, whether

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that be in philosophy, aesthetics, letters, science, politics or leadership in various professional domains [3]. Pies [69] provides a compelling description of Aristotle’s vacillation between melancholia and frenzy and, interestingly, suggests that in the passage attributed to him, the Stagirian implied that ‘those who excel in the arts may be blessed by . . . a humoral. . .effect. . . not too hot . . . not too cold, but just right (eukraton)’. Such a ‘balanced’ mental state implicates bipolar temperament, a condition close to health rather than the disease, in the creative process. We have elsewhere [51] suggested that artists may well be considered ‘healthier’ than ‘normal’ individuals. ‘Healthier’ in this context refers to a value system, whereby being eminent and creative is the ultimate mental state, which trumps the conventional notion of health as ‘average’ or ‘stable’. Creativity and eminence by their very nature are exceptional and beyond the statistical definition of normality – they are outliers [14]. Temperaments by their very nature occupy the terrain between normality and disease. Creativity and leadership are related, but distinct aspects of eminence, a relationship which is in need of new research vistas. Emerging data-based investigations suggest that creativity and eminence and leadership in different professional domains are related to distinct optimal mixes of temperamental and cognitive profiles [1,3,4,6,7] including, but not limited to obsessive-compulsive traits, cyclothymia, sensation-seeking, novelty-seeking and openness to experience. We further submit that talent is a necessary ingredient. How all such factors and others interact with the unique biography of the artist is one of the most fascinating, multidimensional challenges in bridging modern neurobiology and art. The interaction of these diverse factors with unique biography is perhaps where the mystery of genius lies, appearing unpredictably in time and locale. The fact that Terman’s IQ children grown up [70] do not necessarily turn out to be creative, suggests that high intelligence is not one or the necessary ingredients of creative achievement. In collaborating with clinical scientists and epidemiologists from many countries to validate the concept of affective temperaments [66], our instrument, the Temperament Evaluation of Memphis, Pisa, Paris and San Diego (TEMPS). has been translated into at least 25 languages, and validated in 12. One of the most provocative findings pertains to the hyperthymic, which we consider the temperament of leadership [48,71]. For instance, in Italy [72], Lebanon [73] and Argentina [74], the hyperthymic is largely situated within the first and the second standard deviation. Such data imply that at least in those specific cultures (i.e. Mediterranean or having their origins there), the hyperthymic is considered a highly desirable super-normal trait. It may represent the most ‘balanced’ of all temperaments; hence, given its energy, confidence, generosity and eloquence, the hyperthymic emerges as most suitable for leadership roles. Another instrument (the CEATS), conceptually in part derived from

TEMPS-A, has also shown that the hyperthymic is superadaptive, whereas the cyclothymic is more prone to emotional instability [75]. Overall, this literature tends to indicate that leadership and creativity are relatively distinct domains of eminence. The question of melancholia and intellectual and/or artistic eminence which has so preoccupied Western thought and art history may hinge on mixity [76], the coexistence of hypomanic elements in melancholia, which itself derives from the intrusion into or intersection of cyclothymia and hyperthymia with melancholia. This is, properly speaking, the domain of the bipolar spectrum. The co-existence of opposite emotional poles, while agonizing, might simultaneously provide ‘access to negative affect’, which could yield ‘benefits with respect to providing energy for creative achievement’ [77,78], while at the same time perturb their interpersonal relationships and love life, so typical of the biography of artists. The price of greatness [28] is costly, but seems to reside in the subpsychotic interface of bipolar temperaments and affective disease, what geneticists call balanced polymorphism, whereby the condition remains prevalent, despite selection pressures against it. Thus, full-blown manicdepressive illness, rather than representing what is exceptional in human beings, appears to serve as the genetic reservoir of greatness [51].

Implications for clinical practice Consistent with our reading of the literature and our own work, temperament is intimately involved in creativity, achievement and eminence. There appears, in the current literature, greater recognition of affective [13,52,79,80], especially bipolar, traits in creativity. Jamison’s classic treatise [81] has had a major influence worldwide in the shift of the creativity literature from schizophrenia to bipolar disorder. This monumental work, apart from its intellectual interest, has helped in destigmatizing manic-depressive illness. Instability of mood has long been recognized as a risk amongst creative and eminent individuals [82], but only recently have we had scientifically credible studies in its support. Clinicians must note these new developments. That lithium, the most established mood-stabilizer, is not acceptable to a substantial subgroup of artists [83] represents a clinical challenge for the psychiatrist. The fact that periods of acute mental illness are generally incompatible with creative output [84], emphasizes the need for acute and preventive interventions for artists and prominent individuals. Tragedies have occurred, such as Ernest Hemingway leaving the hospital against medical advice, and shooting himself to death, are not rare events. Caring for the mental health needs of artists and eminent individuals – handling their special psychology – is a challenging clinical endeavour

The Genius-Insanity Debate

for which, to the best of our knowledge, there has never been systematic training and preparation. It is also relevant to raise a more generic, albeit rhetorical, question: Why should practising psychiatrists be interested in the relationship of creativity and mental’ disorder? The subject should prove to be intellectually stimulating to the clinician, and as for the patient, it helps in opening up channels of emotional expression otherwise unavailable. We summarize from a paper by Perldringer and Krambeck [85], who have expressed this process as follows: (1) permission to create without constraint is a liberating experience; (2) discovering one’s hidden talents; (3) feedback by peers about one’s artistic expressions serves as a form of group therapy; (4) creation of art boosts one’s self-esteem and mood; and (5) ‘Training of the generally underdeveloped nondominant hemisphere in order to be able in the future to plan and act emotionally and from a synthetic view’. Given our focus on eminent individuals in this chapter, the most serious therapeutic challenge in caring for such individuals is to give in to their sense of entitlement and either omit or permit a course of treatment one would not have considered for more ‘ordinary’ patients. This certainly is a therapeutic domain in need of creative approaches. Whether the temperament factors given the greater space in this chapter – which are in line with literary trends [86] – or neurobiologic considerations [87] – will ultimately illuminate the ‘mystery’ of creativity is a matter of scientific progress. Since in being creative man partakes in one of the most essential attributes of God, we may never know the answer to this question.

8.

9. 10. 11. 12. 13. 14. 15.

16.

17. 18.

19.

20. 21.

References 1. Wills, G.I. (2003) Forty lives in the bebop business: mental health in a group of eminent jazz musicians. Br. J. Psychiatry, 183, 255–259. 2. Karlsson, J.L. (2004) Psychosis and academic performance. Br. J. Psychiatry, 184, 327–329. 3. Akiskal, K.K., Savino, M. and Akiskal, H.S. (2005) Temperament profiles in physicians, lawyers, managers, industrialists, architects, journalists, and artists: a study in psychiatric outpatients. J. Affect. Disord., 85, 201–206. 4. Nowakowska, C., Strong, C.M., Santosa, C.M. et al. (2005) Temperamental commonalities and differences in euthymic mood disorder patients, creative controls, and healthy controls. J. Affect. Disord., 85, 207–215. 5. Burch, G.St.J., Pavelis, C., Hemsley, D.R. and Corr, P.J. (2006) Schizotypy and creativity in visual artists. Br. Psychol. Soc., 97, 177–190. 6. Santosa, C.M., Strong, C.M., Nowakowska, C. et al. (2007) Enhanced creativity in bipolar disorder patients: A controlled study. J. Affect. Disord., 100, 31–39. 7. Strong, C., Nowakowska, C., Santosa, C.M. et al. (2007) Temperament-creativity relationships in mood disorder

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31. Arieti, S. (1979) From schizophrenia to creativity. Am. J. Psychotherapy, 33, 490–505. 32. Karlsson, J.L. (1966) The Biologic Basis of Schizophrenia, Charles C. Thomas, Springfield, Ill. 33. Chapman, L.J., Chapman, J.P. and Raulin, M.L. (1976) Scales for physical and social anhedonia. J. Abnorm. Psychol., 87, 374–382. 34. Chapman, L.J., Edell, W.W. and Chapman, J.P. (1980) Physical anhedonia, perceptual aberration, and psychosis proneness. Schizophr. Bull., 6, 639–656. 35. Mason, O., Claridge, G. and Jackson, M. (1995) New scales for the assessment of schizotypy. Person. Individ. Diff., 18, 7–13. 36. Meehl, P.E. (1962) Schizotaxia, schizotypy, schizophrenia. Am. Psychol., 17, 827–838. 37. Andreasen, N.J.C. and Powers, P. (1975) Creativity and psychosis: an examination of conceptual style. Arch. Gen. Psychiatry, 32, 70–73. 38. Rothenberg, A. (1971) The process of janusian thinking in creativity. Arch. Gen. Psychiatry, 24, 195–205. 39. Rothenberg, A. (1983) Psychopathology and creative cognition. A comparison of hospitalized patients, Nobel laureates, and controls. Arch. Gen. Psychiatry, 40, 937–942. 40. Sessa, B. (2008) Is it time to revisit the role of psychedelic drugs in enhancing human creativity? J. Psychopharmacol., 22, 821–827. 41. Ward, J., Thompson-Lake, D., Ely, R. et al. (2008) Synaesthesia, creativity and art: What is the link? Br. J. Psychol., 99, 127–141. 42. Nettle, D. and Clegg, H. (2006) Schizotypy, creativity and mating success in humans. Proc. R. Soc. B., 273, 611–615. 43. Kretschmer, E. (1936 trans.) Physique and Character; an Investigation of the Nature of Constitution and of the Theory of Temperament, Kegan, Paul, Trench, Trubner and Co. Ltd, London. 44. Northwood, H.(May 1998) The Melancholic Mean: the Aristotelian Problema XXX. 1. Paper presented at World Congress of Philosophy, Boston, MASS. 45. Akiskal, H.S. (2003) Validating “hard” and “soft” phenotypes within the bipolar spectrum: continuity or discontinuity? J. Affect. Disord., 73, 1–5. 46. Akiskal, H.S. (2004) De la Folie circulaire (
a double forme) au spectre bipolaire: la tendance chronique
a la recidive depressive. [From circular insanity (in double form) to the bipolar spectrum: chronic tendency for depressive recurrence]. Bull. Acad. Natl. Med., 88, 285–296. 47. Kelsoe, J.R. (2003) Arguments for the genetic basis of the bipolar spectrum. J. Affect. Disord., 73, 183–197. 48. Akiskal, H.S. and Akiskal, K. (1988) Re-assessing the prevalence of bipolar disorders: Clinical significance and artistic creativity. Psychiatrie et Psychobiologie (European Psychiatry), 3, 29s–36s. 49. Coryell, W., Endicott, J., Keller, M., et al. (1989) Bipolar affective disorder and high achievement: a familial association. Am. J. Psychiatry, 146, 983–988. 50. Verdoux, H. and Bourgeois, M. (1959) Comparative study on the occupational levels of unipolar and bipolar probands and relatives. Ann. Med. Psychol., 153, 67–70.

51. Akiskal, H. and Akiskal, K. (2007) In search of Aristotle: Temperament, human nature, melancholia, creativity and eminence. J. Affect. Disorders, 100, 1–6. 52. Jamison, K.R. (1989) Mood disorders and patterns of creativity in British writers and artists. Psychiatry, 2, 125–133. 53. Jamison, K.R. (1995) Manic depressive illness and creativity. Sci. Am., 272, 62–67. 54. Akiskal, H.S., Akiskal, K., Allilaire, J.F. et al. (2005) Validating affective temperaments in their subaffective and socially positive attributes: Psychometric, clinical and familial data from the French national study. J. Affect. Disord., 85, 29–36. 55. Feist, G.J. (1988) A meta-analysis of personality in scientific and artistic creativity. Pers. Soc. Psychol. Rev., 2, 290–309. 56. Drevdahl, J.E. and Cattell, R.B. (1958) Personality and creativity in artists and writers. J. Clin. Psychol., 14, 107–111. 57. Barron, F.A. (1972) Artists in the Making, Seminar Press, New York. 58. Mackinnon, D.W. (1965) Personality and the realization of creative potential. Am. Psychol., 20, 273–281. 59. Schuldberg, D. (1990) Schizotypal and hypomanic traits, creativity, and psychological health. Creativity Res. J., 3, 218–230. 60. Akiskal, H.S., Khani, M.K. and Scott-Strauss, A. (1979) Cyclothymic temperamental disorders. Psychiatr Clin. North Am., 2, 527–554. 61. Akiskal, H.S. and Akiskal, K. (1994) Temperaments et Humeur des Musiciens de Blues. Nervure, 8, 28–304. 62. Richards, R., Kinney, D.K., Lunde, I. et al. (1988) Creativity in manic-depressives, cyclothymes, their normal relatives, and control subjects. J. Abnorm. Psychology, 97, 281–288. 63. Andreasen, N. and Canter, A. (1974) The creative writer: psychiatric symptoms and family history. Compr. Psychiatry, 15, 123–131. 64. Andreasen, N. and Glick, I.D. (1988) Bipolar affective disorder and creativity: implications and clinical management. Compr. Psychiatry, 29, 207–217. 65. Kretschmer, E.(trans 1931) Psychology of Men of Genius, Kegal Paul, Trench, Trubner & Co., London. 66. Akiskal, H.S. and Akiskal, K.K.(eds) (2005) TEMPS: Temperament Evaluation of Memphis, Pisa, Paris and San Diego. J Affect Disord, Special Issue. 85, 1–242. 67. Stanghellini, G. (2007) Exploring the margins of the bipolar spectrum: Temperamental features of the typus melancholicus. J. Affect. Disord., 100, 13–21. 68. Akiskal, H.S. and Akiskal, K. (1992) Cyclothymic, hyperthymic and depressive temperaments as subaffective variants of mood disorders, in Annual Review, vol. 11 (eds A. Tasmanand M.B. Riba), American Psychiatric Press, Washington, DC, pp. 43–62. 69. Pies, R. (2007) The historical roots of the “bipolar spectrum”: did Aristotle anticipate Kraepelin’s broad concept of manicdepression? J. Affect. Disord., 100, 7–11. 70. Terman, L.W. (1920–59) Genetic Studies of Genius, vol. 6, Stanford University Press, Stanford. 71. Akiskal, K.K. and Akiskal, H.S. (2005) The theoretical underpinnings of affective temperaments: implications for evolutionary foundations of bipolarity and human nature. J. Affect. Disord., 85, 231–239.

The Genius-Insanity Debate 72. Placidi, G.F., Signoretta, S., Liguori, A. et al. (1998) The SemiStructured Affective Temperament Interview (TEMPS-I): Reliability and psychometric properties in 1010 14–26 year students. J. Affect. Disord., 47, 1–10. 73. Karam, E.G., Mneimneh, Z., Salamoun, M. et al. (2005) Psychometric properties of the Lebanese-Arabic TEMPS-A: a national epidemiologic study. J. Affect. Disord., 87, 169–183. 74. Vazquez, G., Nasetta, S., Mercado, B. et al. (2008) Validation of the TEMPS-A Buenos Aires: Spanish psychometric validation of affective temperaments in a population study of Argentina. J. Affect. Disord., 108, 25–32. 75. Lara, D., Lorenzi, T.M., Borba, D.L. et al. (2008) Development and validation of the combined emotional and affective temperament scale (CEATS): towards a brief self-rated instrument. J. Affect. Disord., 111, 320–333. 76. Akiskal, H.S. and Akiskal, K.K. (2007) A mixed state core for melancholia: an exploration in history, art and clinical science. Acta Psychiatr. Scand., 115, s44–s49. 77. Simeonova, D.I., Chang, K.D., Strong, C. et al. (2005) Creativity in familial bipolar disorder. J. Psychiatr. Res., 39, 623–631.

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78. Akinola, M. and Mendes, W.B. (2008) The Dark side of creativity: biological vulnerability and negative emotions lead to greater artistic creativity. Pers. Soc. Psychol. Bull., 34, 1677–1680. 79. Janka, Z. (2004) Muveszi kreativitas es bipolaris kedelyzavar. Evforyam, 145, 1709–1718. 80. Rihmer, Z., Gonda, X. and Rihmer, A. (2006) Creativity and mental illness. Psychatr. Hung., 21, 288–290. 81. Jamison, K. (1993) Touched with Fire, Free Press, New York. 82. Post, F. (1994) Creativity of psychopathology: A study of 291 world-famous men. Br. J. Psychiatry, 165, 22–34. 83. Schou, M. (1979) Artistic productivity and lithium prophylaxis in manic-depressive illness. Br. J. Psychiatry, 135, 97–103. 84. Herbert, P.S. (1959) Creativity and mental illness. Psychiatr. Quart., 33, 534–547. 85. Poeldinger, W. and Krambeck, K. (1987) The relevance of creativity for psychiatric therapy and rehabilitation. Compr. Psychiatry, 28, 384–388. 86. Steptoe, A.(ed.) (1998) Genius and the Mind: Studies of Creativity and Temperament, Oxford University Press, Oxford. 87. Zeki, S. (1999) Inner Vision: An Exploration of Art and the Brain, Oxford University Press, Oxford.

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Economics of Bipolar Disorder R. Sabes-Figuera1, D. Razzouk2 and Paul E. McCrone1 1

Centre for the Economics of Mental Health, Health Service and Population Research Department, Institute of Psychiatry, King’s College, London, UK 2 Department of Psychiatry, Universidade Federal de Sao Paulo (UNIFESP), Sao Paulo, Brazil

Introduction Bipolar disorder (BD) is the fifth leading cause of disability in young people, and amongst mental disorders is the fourth highest cause of burden [1]. Patients with BD may delay seeking treatment, and 30–70% of patients do not access treatment [2]. The lack or delay of treatment for BD contributes to the economic and social burden; as the disorder progresses the response to treatment decreases and increases the impairment in patients’ global functioning. Patients with BD are more likely to have higher rates of health service use (including hospitalization) and comorbidity with physical diseases, as well as increased suicide attempts, absenteeism and unemployment, substance misuse, sexual risk behaviour and social dysfunction [3–10]. The aims of this chapter are: (1) to examine the economic impact of BD; and (2) to assess the evidence surrounding the cost-effectiveness and cost-utility of different interventions to treat BD.

Economic cost of bipolar disorder Methodological considerations Cost of illness (COI) studies do not determine how decision makers should choose between treatments and interventions, as such studies are not evaluative [11]. Nevertheless, they do provide useful information on the economic burden that the disease imposes on a society. This information can highlight processes of care and aspects of the disease where improvements and more research are needed. COI studies should consider all costs that fall on individuals and organizations. These costs can be divided into: (1) direct costs, which are those that arise from treating the disease and its consequences; and (2) indirect costs, which are those caused by reduced productivity or engagement in leisure activities.

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There are two basic approaches used in COI studies. The prevalence approach is used to assess the costs generated by the condition over a certain period of time, usually one year. Alternatively, the incidence approach can be used, in which the lifetime costs of new cases occurring within a year are calculated [12]. In addition, there are two main methods to obtain estimations of the costs. One possibility (top-down approach) is to assign a percentage of total health and other expenditures to the condition of interest. The second option (bottom-up approach) consists in evaluating the average use of services by individuals with the condition through surveys and/or medical records and extrapolating these data to the overall population affected by the condition. While there is not much disagreement about how to estimate the direct costs of care, there is much more debate as to the most appropriate way of estimating indirect costs, specifically unemployment and absenteeism. The human capital method uses the level of an individual’s earnings to indicate the productivity losses caused by reduced work time. This has been criticized as it suggests greater productivity losses for those who earn more (and it is known that earnings inequalities arise for a variety of reasons). Furthermore, it may be that in the presence of unemployment someone who stops work is replaced by someone who was previously unemployed; any production loss would therefore be confined to the friction period during which recruitment takes place [13].

COI estimates One of the earliest studies was by Wyatt and Henter [14]. They established that in 1991 the cost of BD in the United States was $45 billion, based on estimations of utilization of health care and other services by BD patients. Most of the costs were indirect costs (83%), and around half of these were productivity losses of the workforce affected by the disease. The remaining indirect costs included lost productivity of homemakers, people in institutions and people who had committed suicide. Using a different approach, Begley et al. estimated the present value of lifetime societal costs of

Economics of Bipolar Disorder

persons with the onset of BD in the year 1998 in the United States [15]. They obtained data from expert opinion, employment surveys, published literature and health insurance claims and reported a lifetime cost per person of $252 212, with much variation according to severity ($11 220 for patients with single manic episodes and $624 785 for non-responsive chronic patients). The total cost for the country was estimated at $24 billion with 44% accounted for by indirect costs. Bryant-Comstock et al., analysing the same health insurance claims database used by Begley et al., compared the annual health care cost of BD patients with non-BD patients for the year 1997 [16]. This database included the health claims of 2.7 million privately insured patients. The study estimated an annual cost for the BD group of $7663 per patient, compared to $1962 for the comparator group. One limitation was that data from patients with only one episode were not included and therefore the costs may be overestimated. In a very different health care system, Das Gupta and Guest calculated the cost of BD in the United Kingdom in 1998 to be £2.1 billion [17]. Data were drawn from health care utilization databases, published data and expert opinion. As with the studies from the United States, indirect costs accounted for a substantial amount of the total (86%). Amongst the direct costs, the most costly elements were hospital admissions (35%) and community mental health care (27%). Given that they assumed a lifetime prevalence of BD of 0.5%, the estimation for the cost per person with BD was £6919 (I$10 455). In a recent study, McCrone et al. have made estimates of the cost of BD for England [18]. Attaching costs from secondary sources to prevalence estimates, they calculated total service costs in 2007 to be £1.6 billion. With the inclusion of lost employment costs the total rose to £5.2 billion. Another approach to conducting COI studies is to use survey data. From these it is possible to obtain information about the prevalence of the disease, the use of services and how the condition affects the work productivity of the individuals. In the Netherlands, Hakkart-van Roijen et al. identified participants from a national survey with a diagnosis of BD or unipolar major depressive disorder and re-interviewed them [19]. Forty individuals had a confirmed diagnosis of BD. Based on this relatively small number, the societal cost of was estimated to be D 1.9 billion for 2002. Based on a prevalence rate of 5.2%, the cost per person was D 4527. The results again revealed that indirect costs represent the most significant part of the overall costs (80%). The small sample of the study may have affected the validity of the results. For instance, there were no hospitalization costs included, because none of the respondents had reported an admission in the 4-week period before the interview.

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In a similar survey-based study in Australia, Fisher et al. reported an excess cost per person with BD of A$9878 in 2004, compared with people without BD [20]. Indirect costs represented 86% of the total cost, and the estimation of the total excess costs for the entire country based on these data was in the range of A$4.0–5.0 billion. Some costs were excluded, such as those for patients living in institutions or residential care settings. Furthermore, the authors did not find excess pharmaceutical drug costs for the BD group. The direct costs of health care borne by the government reported by this study, A$1325, can be compared with the figures provided by Sanderson et al. in their article on the costeffectiveness of specific interventions for affective disorders [21]. Analysing a large household survey of mental disorders, n ¼ 10 641, they reported a direct health care cost of A$1294 per treated case in the year 1998. A number of studies have focused just on the direct health care costs of BD. For example, Knoth et al. found that these costs in the first year after diagnosis were more than four times higher than the health care cost of the average member of the managed care plan analysed [22]. Elsewhere, Stensland et al. showed that health care costs associated with BD were $2908 higher than those for depression [23]. Other studies have focused on explaining these higher health care costs. Several studies have found that the misdiagnosis of BD, which delays appropriate treatment for these patients, increases health care costs. For instance, McCombs et al. analysed Medicaid data and found that costs increased by $91 for each month of delayed diagnosis [24]. Li et al. reported that only 5.5% of the patients in a Medicaid programme used a mood stabilizer consistently for one year [25]. The relationship between such suboptimal use of medication and higher costs was demonstrated in that study and others [26]. The influence of comorbid conditions on the health care costs of BD patients was highlighted by Guo et al., who showed that comorbidity accounted for 70% of the total cost of BD in another analysis of Medicaid data [27]. Amongst the studies that have estimated costs at the national level, only Wyatt and Henter and McCrone et al. have examined caregiver costs [14,18]. There is evidence that these carers report more physical and mental health problems, therefore increasing their own health service use [28]. Other studies have focused on the lost employment costs associated with BD. For example, Kleinman et al., in a study from the United States, found that there were on average 11.5 additional lost working days per year per employee with BD compared to those without this condition [29]. Furthermore, it has been reported by Goetzel et al. that of all mental health problems, BD generated the greatest loss of productivity to employers [30]. This review has identified a number of studies that have attempted to estimate the economic cost of BD in specific countries. The costs appear substantial in most countries.

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A common finding is that the indirect costs associated with lost employment are substantial. However, comparisons across, and even within, countries is problematic for a number of reasons. First, the total economic burden of BD clearly depends on which costs are included, the prevalence figures used and the methods that are used to estimate indirect costs. Second, different studies collect data from different sources and this can cause difficulties. For example, while those based on large administrative databases provide good information on health care costs for those in contact with services, they provide little information on those not in contact. An alternative is to use survey data. This should result in a more representative sample but the numbers tend to be low and therefore this may result in imprecise cost estimates. This is illustrated by some studies not including inpatient costs, because those included in the survey did not use this form of care. Third, quite different estimates will be produced, depending on whether topdown or bottom-up approaches are used. Each requires specific assumptions to be made.

Economic evaluations of interventions for bipolar disorder Cost of illness studies are informative but they do not tell us about the efficiency of different treatments for BD. For this, the cost of services needs to be combined with information on their outcomes. Various ways of doing this exist, with the two most common being cost-effectiveness analysis (CEA) and cost-utility analysis (CUA). In CEA, costs are linked to condition specific measures (e.g. scales to measure depression). This makes CEA clinically meaningful but does not allow interventions in one clinical area to be compared to those elsewhere. These decisions do though have to be made at a local or national level. CUA is similar to CEA but uses generic measures of outcome to enable such comparisons, with the most commonly used measure being the quality adjusted life year (QALY). With QALYs, the length of time spent in a particular health state is multiplied by a number anchored by 1 (full health) and 0 (death), to reflect the quality of life experienced during that time.

Economic evidence for the treatment of acute manic episodes Several economic studies have evaluated the cost-effectiveness of different drug treatments for acute manic or mixed episodes in BD patients. Most of these studies were sponsored by the pharmaceutical industry and analysed the efficiency of atypical antipsychotics in relation to conventional antipsychotics and/or mood-stabilizers. A number of studies have focused on the use of the drug olanzapine. In a pre-post study, Namjoshi et al. concluded that compared to the year prior to the treatment, olanzapine

resulted in improved quality of life and reduced costs for 76 patients [31]. However, given the lack of a control group, it is unclear whether these patients would have improved anyway, or whether their gains were any greater due to drug treatment. Elsewhere, Revicki et al. did use a double blind randomized design in their comparison of olanzapine with valproate [32]. Quality of life deteriorated for both groups over a short 12-week period. Costs for out-patient care were significantly higher for the olanzapine group, but this was due to the cost of medication itself. Overall health care costs were not significantly different, but this was largely because the sample all started off as inpatients and these costs dominated the others. Societal costs were not included. This study was limited by the small sample size, which was reduced further by the lack of follow-up data for many patients. In a similar study, Zhu et al. did not find significant differences in the medical costs between the same two pharmacological agents, while clinical outcomes were reported to favour olanzapine [33]. Revicki et al. compared the effectiveness and medical costs associated with valproate and lithium in a group of patients hospitalized for an acute manic or mixed episode [34]. The analysis was based on a pragmatic, multicentre open-label randomized controlled trial with a followup of 12 months. They did not find significant differences between the two treatments in terms of effectiveness nor medical costs. Klok et al. analysed the economic consequences of the use of the atypical antipsychotic quetiapine in monotherapy and in combination with lithium through a decision model [35]. The authors showed that the combination of quetiapine and lithium was more costly, but prevented more serious adverse events than other combinations of lithium with olanzapine or risperidone. As a part of a National Health Service Health Technology Assessment, Bridle et al. developed an economic model to evaluate different drug treatments for treating mania associated with BD [36]. The time horizon of the model was three weeks and the third-party payer (i.e. National Health Service) was the perspective adopted. They found that haloperidol, a conventional antipsychotic, was less costly and more effective than lithium, valproate and quetiapine. Olanzapine was more effective and more costly than haloperidol, with an incremental cost effectiveness ratio equal to £7179 per additional responder. The authors concluded that if decision makers were willing to pay this amount (or more) for each additional responder, then olanzapine would be the optimal decision. Otherwise treatment with haloperidol would be the optimal strategy. The authors acknowledged that the analysis had some limitations, including the use of secondary data, not evaluating combination therapies and not considering the costs and effects of adverse events. A study of electroconvulsive therapy (ECT) for treatment resistant BD in adolescents and young adults found that

Economics of Bipolar Disorder

outcomes were significantly better for those receiving ECT compared to those who declined it [37]. Hospital costs were less for the ECT patients due to a shorter length of stay. However, this was not a randomized comparison and the group willing to undergo ECT may have shown more improvement anyway. In addition, the sample size was very small.

Economic evidence for maintenance treatment in bipolar disorder Two different studies have analysed the economic implications of maintenance therapy with olanzapine compared to lithium treatment. In an industry-sponsored study, McKendrick et al. constructed a Markov model, relying on a single clinical trial for the effectiveness data, to assess the cost-effectiveness of these treatments from the perspective of the National Health Service in England and Wales [38]. The model showed that olanzapine prevented acute mood (manic) events with lower costs after 1 year, although this difference in costs was not statistically significant. In the United States, Zhang found opposite results in an retrospective analysis of private sector insurance claims data from health plans [39]. After controlling for other variables that could affect medical spending, it was found that compared to similar patients taking lithium, patients with BD taking olanzapine spent $5600 more each year on health care services. Calvert et al. also used a Markov model to assess the cost-effectiveness of lamotrigine treatment compared to olanzapine, lithium and no treatment in patients recently stabilized after resolution of a manic episode [40]. They ‘populated’ the effectiveness part of the model with data from four clinical trials, and they adopted the perspective of the third-party payer. Lamotrigine was found to be less costly and more effective than olanzapine and no treatment. Compared with lithium, the incremental cost-effectiveness was $2400 per episode avoided, $30 per euthymic day gained, and $26 000 per QALY. These results were influenced by the low rate of depressive episodes in patients being treated with lamotrigine. In an economic evaluation alongside a clinical trial, Lam et al. evaluated the cost-effectiveness of adding cognitive therapy to standard care in the prevention of relapse in BD [41]. This study benefited from a follow-up period of 30 months. The group that received psychological treatment spent 110 fewer days with bipolar episodes and had lower health and care costs, although these differences were not statistically significant. Besides the small sample size, another limitation of the study was that the standard care group received any one of a range of pharmaceutical treatments and therefore it is not possible to compare the cost-effectiveness of therapy against any particular drug treatment.

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A economic decision model was developed as part of a clinical guideline process in the United Kingdom, using the results of a meta-analysis of RCTs to inform this model [42]. The treatments evaluated were lithium, valproate and olanzapine and these were compared to no treatment. The use of health care resources associated with the different health states of the Markov model, in the five-year period analysed, was based mainly on expert opinion. Using averted episodes as the outcome measure, the results showed that olanzapine was dominated (i.e. more expensive and less effective) by valproate, while the option of no treatment was dominated by both valproate and lithium. Valproate was more costly and more effective than lithium, with an incremental cost of £260 and £341 per additional averted episode for men and women, respectively. Nevertheless, when health benefits were measured in QALYs, the results were different, with olanzapine not being a dominated strategy. The incremental cost-effectiveness ratio (ICER) per QALY gained for valproate over lithium was £1725 for men and £1985 for women. The ICER per QALY gained for olanzapine over valproate was £5902 for men and women (for this population subgroup, after excluding valproate, the ICER per QALY gained for olanzapine over lithium was £4805). The assumptions regarding service use in this study created some uncertainty about the results. Furthermore, the contradictory results depending on the outcome measure used could be explained by the method to obtain the utility values as the basis for the QALYs. A similar decision analytic model was developed by Soares-Weiser et al. [43]. They included a more complete range of comparators (lithium, valproate, lamotrigine, carbamazepine, imipramine, olanzapine, and lithium plus imipramine) and the method to obtain clinical evidence was more refined. This Markov model estimated costs from the perspective of the UK National Health Service and health outcomes in terms of QALYs using a lifetime horizon. Two separate analyses were carried out, one for patients who had recently experienced a depressive episode and another for the ones who had suffered a manic episode. In the former, valproate was the cheapest, non-dominated alternative and lithium and the combination treatment of lithium plus imipramine were both more costly and more effective than valproate (the other alternatives were dominated). The results showed that the ICER of lithium compared with valproate was £10 409 per additional QALY. The ICER of the combination treatment compared with lithium monotherapy was £21 370 per additional QALY. In the analysis of the patients who had recently experienced a manic episode, olanzapine dominated all of the strategies with the exception of lithium monotherapy, this alternative being more costly and more effective. The ICER of lithium compared with olanzapine was estimated to be £11 359 per additional QALY.

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Economic evidence of multicomponent intervention care programmes Two different studies, both looking at interventions based in the United States, evaluated the cost-effectiveness of care programmes with multiple components that had the objective of improving quality of care and long-term outcomes for persons with BD. Simon et al. assessed outcomes and costs (with a follow-up period of two years) of a systematic care programmeprovidedbynursecaremanagers that comprised several interventions plus usual care (“a structured group psychoeducational programme,monthlytelephonemonitoring of mood symptoms and medication adherence, feedback to treating mentalhealth providers,facilitationofappropriate follow-up care, and as-needed outreach and crisis intervention”) [44]. The patients were recruited at mental health clinics of a group-model prepaid health plan. They were assigned randomly to the intervention group or to the usual care group. The clinical outcomes showed a positive effect of the intervention in the mean level of time with significant mania symptoms, with no significant effects on level of depression. After controlling for confounding variables, the incremental cost of the intervention was $1251. In a very similar study, Bauer et al. found similar clinical outcomes but in a highly ill, frequently hospitalized sample with a follow-up period of three years. In addition, the intervention group was less costly, although this difference was not significant [45].

Conclusions This chapter has demonstrated that the costs associated with BD are substantial. A disproportionate amount of the cost is due to lost employment and therefore interventions that can maintain people in the workplace would have potential economic benefits. A reasonable number of economic evaluations have now been conducted. These have generally been of pharmacological interventions and have shown mixed results. An increasing number of evaluations have used QALYs as outcome measures which is important if interventions for BD are to be compared to those in other health care areas. Future work needs to examine the impact of treatments on employment and more evaluations of psychological therapies are clearly required.

References 1. World Health Organization (WHO) (2001) The World Health Report 2001: Mental Health: New Understanding New Hope, World Health Organization, Geneva. 2. Kohn, R., Saxena, S., Levav, I. and Saraceno, B. (2004) The treatment gap in mental health care. Bulletin of the World Health Organization, 82, 858–866. 3. Woods, S.W. (2006) The economic burden of bipolar disease. J. Clin. Psychiat., 61 (suppl 113), 38–41.

4. Birnbaum, H.G., Shi, L., Dial, E. et al. (2003) Economic consequences of not recognizing bipolar disorder patient: A cross-sectional descriptive analysis. J. Clin. Psychiat., 64 1201–1209. 5. Calabrese, J.R., Hirschfeld, R.M., Reed, M. et al. (2003) Impact of a bipolar disorder on a US community sample. J. Clin. Psychiat., 64, 425–432. 6. Kilbourne, A.M., Cornelius, J.R., Han, X. et al. (2004) Burden of general medical conditions among individuals with bipolar disorder. Bipolar Disord., 6, 368–373. 7. Adling-Sobocki, P. and Wittchen, U. (2005) Cost of affective disorders in Europe. Eur. J. Neurology, 12 (suppl 1), 34–38. 8. Hirschfeld, R.M.A. and Vornik, L.A. (2005) Bipolar disorder – Costs and comorbidity. Am. J. Manag. Care, 11 (Suppl), S85–S90. 9. Matza, L.S., Rajagopalan, K.S., Thompson, C.L. and Lissovoy, G. (2005) Misdiagnosed patients with bipolar disorder: Comorbidities, treatment patterns and direct treatment costs. J. Clin. Psychiat., 66, 1432–1440. 10. Ranga, K. and Krishnan, R. (2005) Psychiatric and medical comorbidities of bipolar disorder. Psychosom. Med., 67, 1–8. 11. Drummond, M. (1992) Cost of illness studies: major headache? PharmacoEconomics, 2, 1–4. 12. Hartunian, N.S., Smart, C.N. and Thompson, M.S. (1981) The Incidence and Economic Costs of Major Health Impairments, Lexington Books. 13. Koopmanschap, M.A. and van Ineveld, B.M. (1992) Towards a new approach for estimating indirect costs of disease. Soc. Sci. Med.., 34, 1005–1010. 14. Wyatt, R.J. and Henter, I. (1995) An economic evaluation of manic-depressive illness. Soc. Psych. Psych. Epid., 30, 213–219. 15. Begley, C.E., Annegers, J.F., Swann, A.C. et al. (2001) The lifetime cost of bipolar disorder in the US: an estimate for new cases in 1998. Pharmacoeconomics, 19, 483–495. 16. Bryant-Comstock, L. et al. (2002) Health care utilization and costs among privately insured patients with bipolar I disorder. Bipolar Disord., 4, 398–405. 17. Das Gupta, R. and Guest, J.F. (2002) Annual cost of bipolar disorder to UK society. Brit. J. Psychiat., 180, 227–233. 18. McCrone, P., Dhanasiri, S., Patel, A. et al. (2008) Paying the Price, King’s Fund, London. 19. Hakkaart-van Roijen, L., Hoeijenbos, M.B., Releer, E.J. et al. (2004) The societal cost and quality of life of patients suffering from bipolar disorder in the Netherlands. Acta Psychiatr. Scand., 110, 383–392. 20. Fisher, L.J., Goldney, R.D., Dal Grande, E. et al. (2007) Bipolar disorders in Australia. A population-based study of excess costs. Soc. Psychiatry Psychiatr. Epidemiol., 42 (2), 105–109. 21. Sanderson, K., Andrews, G., Corry, J. and Lapsley, H. (2003) Reducing the burden of affective disorders: is evidencebased health care affordable? J. Affect. Disord., 77 (2), 109–125. 22. Knoth, R.L., Chen, K. and Tafesse, E. (2004) Datapoints: Costs associated with the treatment of patients with bipolar disorder in a managed care organization. Psychiatr. Serv., 55 (12), 1353. 23. Stensland, M.D., Jacobson, J.G. and Nyhuis, A. (2007) Service utilization and associated direct costs for bipolar disorder in

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An Introduction to the Neurobiology of Bipolar Illness Onset, Recurrence and Progression Robert M. Post1 and Marcia Kauer-Sant’Anna2 1 2

George Washington University Medical School, Bipolar Collaborative Network, Bethesda, MD, USA Molecular Psychiatry Laboratory, Department of Psychiatry, Hospital de Clinicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Brazil

Introduction The neurobiology of bipolar illness is increasingly more precisely delineated and understood. Well-replicated findings have emerged in multiple areas of study, ranging from alterations in blood and cerebrospinal fluid to direct abnormalities in brain. These are seen by a variety of brain imaging techniques in patients, as well as in discrete biochemical and structural changes delineated in autopsy specimens of patients dying with a diagnosis of bipolar disorder compared with controls. Subsequent chapters in this volume will deal with many of these topics in great detail; instead, here, we wish to give a broad overview and delineate some of the many pathological mechanisms by which these changes might occur and evolve. Until recently, pathophysiological mechanisms have been viewed as largely dichotomous – residing in those related to genetic inheritance or environmental alterations. Instead, it is becoming increasingly clear that the development of the central nervous system (CNS) relies on an exquisite interplay between genetic and environmental factors and that this process continues throughout the lifetime of the individual. Thus, a fundamental question emerges as to how the pathophysiology of a complex psychiatric illness such as bipolar disorder not only may have its origins in genetic and environmental vulnerabilities, but how the illness course and its response to treatment may also depend on an intricate and ongoing interaction of these dual mechanisms. Normal processes of learning and memory and responses to environmental stressors involve short- and long-term changes in gene expression, some of which are mediated by changes in gene structure, but not gene sequence. DNA itself can be methylated and histones (around which the DNA is wrapped) can be acetylated or methylated. These

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epigenetic changes alter DNA’s availability for transcription and provide new conceptual mechanisms for understanding lifelong alterations in neurobiology and behavioural responsivity based on environmental events. Recent findings also suggest that these epigenetic changes themselves may have considerable plasticity and may be amenable to alterations that could ultimately lead to new therapeutic approaches to illness vulnerability and progression. Bipolar illness is fundamentally a recurrent and potentially progressive illness requiring not only acute intervention for episodes but, in the vast majority of instances, long-term prophylactic measures to ward off manic and depressive episode recurrences. Considerable evidence suggests that episode recurrence itself may be a mediator of illness progression, further complicated by accumulating neurobiological alterations induced by stressors, substances of abuse and other environmental influences. This view leads to a fundamental reconceptualization of the illness, not only as a progressive neurobiological and somatic medical illness, but one which can be slowed or halted altogether if appropriate treatment intervention is instituted. Yet, disappointingly, all too often the illness is not recognized or well-treated in its earliest phases, and even after multiple severe episodes have occurred, appropriate long-term prophylaxis is not consistently given or accepted. Thus, it is a secondary hope that not only will this chapter help orientate the reader to subsequent, more detailed expositions of the neurobiology of bipolar illness, but further the understanding of some of the fundamental mechanisms of illness onset, progression, treatment and prevention. This information may help foster the institution of adequate treatment earlier and in a more consistent fashion in an attempt to slow or halt illness progression.

Clinical evidence for bipolar illness progression Emil Kraepelin, a century ago, delineated several aspects of the tendency for manic-depressive illness to progress:

An Introduction to the Neurobiology

(a) that successive episodes tend to recur with shorter well-intervals; and (b) that episodes later in the course of illness emerge more autonomously compared to early episodes that are often precipitated by psychosocial stressors [1]. In most studies, in which these variables were appropriately assessed, these general tendencies, which we have labelled (a) episode-sensitization [2] and (b) stress-sensitization, have been replicated [3–8] with few exceptions. Multiple other components of illness progression are manifest as well (c–g). (c) There is a general tendency for the illness to become more poorly responsive to most treatments as a function of number of prior episodes [9,10]. Similarly, there are a wealth of data demonstrating that even euthymic bipolar patients have substantial cognitive deficits; and (d) that the deficits are proportional to the number of prior episodes or duration of depressive illness [11–13]. The progressive emergence of increasing frequency, severity or duration of episodes during continuous treatment, which had previously been highly effective in preventing episodes is a (e) tolerance pattern that is indicative of another type of illness progression. This tolerance phenomenon can occur, even when full doses and adequate blood levels are maintained, suggesting that it is a pharmacodynamic rather than a pharmacokinetic tolerance process. This pattern of progressive increases in morbidity occurring during treatment often bears some resemblance to the initial progressive development of affective episodes that occurs at the beginning of the illness when it is unmedicated [14,15]. Another way in which treatment-refractoriness [14,16,17] can develop is in instances in which the illness has remained in remission on a given prophylactic treatment, but treatment is discontinued, new episodes re-emerge, and the drug is no longer effective once it is re-administered. This phenomenon has been most notably demonstrated with lithium discontinuation-induced refractoriness, but we have also seen other instances of it in patients with unipolar depression with traditional antidepressants in long-term prophylaxis [16]. This phenomenon of (f) discontinuationinduced treatment resistance, too suggests that the illness is progressive in that the occurrence of new episodes, in this case in the medication-free condition, is sufficient to change pharmaco-responsivity in the direction of treatment nonresponsiveness. This latter process may be, to some extent, analogous to that observed in treatment of malignancies, wherein the primary tumour is highly responsive to chemotherapy, but once the tumour has evolved and metastasized, it is no longer responsive to those primary agents. In bipolar disorders, a number of mechanisms could account for this phenomenon. For example, the new episode that occurs off medication may engender the typical decrements in neuroprotective factors, such as brain derived neurotrophic factor (BDNF) [18] and increases in neurotoxic factors such as oxidative stress and free radical produc-

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tion [19]. However, these episode-related changes are now occurring in the absence of the neuroprotective effects of a treatment such as lithium, which is known to induce BDNF and neurogenesis and a variety of other neuroprotective processes on its own [20]. Thus, the emergence of an episode of relatively similar severity during the offlithium period may cause a greater pathophysiologic disturbance than that which would ordinarily occur from an episode breaking through ongoing treatment. Regardless of the exact mechanisms involved, this phenomenon of additional episodes engendering treatment-refractoriness in the off-medication period is further evidence for the potential for illness progression as a function of number of episodes. (g) Many systemic manifestations of BD occur as a function of number of episodes or duration of illness. Recent studies have reported that 55–74% of bipolar patients are overweight or obese [21–23], and that they are more likely to be so compared to the general population [24]. Furthermore, the prevalence of obesity in bipolar disorder appears to be increasing with time. While obesity is a common feature of a number of psychiatric illnesses, a large epidemiologic study including 9125 patients suggested that the association between obesity and bipolar disorder was greater than that for major depressive disorder or anxiety disorders [24]. An increased prevalence of medical conditions associated with obesity, such as diabetes mellitus, hypertension, ischaemic heart disease and stroke, have been documented in bipolar patients [25,26]. Standardized mortality rates due to cardiovascular disease, are approximately twice that of the general population [26]. The cumulative effect of increased oxidative stress during mood episodes and chronic stress may in part explain the increased medical morbidity in bipolar disorder. These multiple reflections of illness progression (a–g) raise the idea of using medical staging models in BD [27,28]. Such models could guide specific, stage orientated therapeutic approaches; earlier stages would be associated with better prognosis and a higher likelihood of response, while later stages would demand more complex and potentially risky treatments. Furthermore, validation of these models could help to emphasize the need for early intervention and preventive strategies in BD. In this way, staging models for BD could optimize guidelines and algorithms, refining treatment according to an individualized, need-based management plan.

Potential neurobiological mechanisms for illness progression Given the substantial evidence that without effective treatment there is a tendency for the illness to increase in frequency, severity or duration of episodes and show increasing levels of treatment resistance, it is apparent that a

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variety of neurobiological processes could account for these phenomena. Hereditary genetic vulnerability could, itself, potentially be sufficient. This would be apparent from analogies to an illness process such as Huntington’s chorea which, once the disease process is initiated, it progresses inexorably to neurological and psychological decline, resulting in premature death. Such pure genetic determinism is highly unlikely to occur in bipolar illness for multiple reasons, including the evidence that there are many gene/environment interactions. For example, environmental insults such as the occurrence of stresses early in life interact with genetic and familial vulnerability to be associated with an earlier age of onset of illness [29–31] and a more severe course, as reflected in an increased incidence of suicidality [32] compared with those with the illness not suffering from these early life stressors. Similarly, those with a history of substance abuse have a more adverse course of illness than those without, suggesting an additional impact of neurobiological mechanisms associated with substance abuse on the pathophysiology of bipolar disorder. These clinical observations of a progressive course of BD are in line with findings of changes in brain biochemistry, function and structure between patients with early and late stages of BD [33]. For instance, morphometric studies have shown that patients with BD have changes in many brain structures in comparison to controls [34–36]. Notably, some authors reported that such neuroanatomical changes tend to be more pronounced with repeated episodes and correlate with length of illness [34,37]. Consistent with this, recent studies suggest that those that recently had their first manic episode have minimal alterations in brain structures [38]. Decreased neurotrophins and increased mediators of inflammation are amongst the potential mechanisms for neuronal and glial deterioration and progressive cognitive impairment in BD [18,39,40]. For instance, a recent report showed that TNF-alpha and IL-6 cytokines were increased in the early and late stage of BD, while BDNF levels were decreased in the late stage, but not in the early stage, when compared to controls [41]. The levels of the anti-inflammatory cytokine IL10 additionally declined in late stage of the disorder. These and other findings [42] indicate that patients with BD are likely to be in a pro-inflammatory state, which worsens in the later stages of the illness. In parallel, there is a decrease in the protective mechanisms, as indicated by a reduction in BDNF levels. One could hypothesize that BDNF levels decrease during mood episodes, but the restoration of the levels may be less likely with multiple episodes. In addition, some parameters of oxidative stress, such as 3-nitrotyrosine, are altered in the early stages of BD, while others, such as glutathione-s-transferase and glutathione reductase differ from controls only in those patients with multiple episodes, in later stages of BD [43].

Emerging data also suggests that the lowering of BDNF levels in acute episodes occurs in parallel with increased oxidative stress, suggesting that such changes occur in an orchestrated way [44]. Furthermore, there is emerging evidence of accelerated ageing process in BD, as indicated by telomere shortening and greater age-related decreases in BDNF levels in bipolar patients when compared to controls [27]. For instance, the telomere length, which has been used as a marker of ageing, was significantly shorter in those with mood disorders, representing as much as 10 years of accelerated ageing [24]. Indirect evidence also comes from studies showing increased oxidative stress in BD, which is also known to increase with ageing [45]. Notably, oxidative stress is associated with DNA damage, endothelial dysfunction and telomere shortening. These findings of accelerated agerelated processes provide further support for investigating more aggressive preventative measures.

Genetic mechanisms Large-scale whole genome studies suggest that there are reliable associations of a calcium channel (CACNA1C) and a neurotransmitter release mechanism (ANK 3) involved in vulnerability to bipolar illness. The involvement of a calcium channel is of considerable interest in regard to the overwhelming data, indicating increases in baseline and provoked levels of intracellular calcium in blood elements of patients with unipolar, and in particular, bipolar illness. Whether these relate to altered calcium channel dynamics on the membrane, or a very large body of data implicating alterations in mitochondrial dynamics and mitochondrial regulatory genes, remains to be further assessed. A particular mechanism of interest is that of two different alleles for proBDNF. The val-66-val allele of proBDNF occurs in a larger portion of the population and is the better functioning allele compared with the val-66-met allele or the met-66-met allele, which occur in smaller portions of the normal population and are less efficient [46]. These met alleles show limited transport to dendritic areas and are associated with decreased long-term potentiation in hippocampal slices, and subtle memory deficits in both normal volunteers and patient populations. The met alleles are also associated with decrements in hippocampal volume and activation as well as reduced prefrontal volumes in even normal volunteer controls [46]. What is particularly surprising, however, is that there is considerable evidence that the val-66-val allele of proBDNF is associated with an increased incidence of bipolar illness and/or earlier onsets, or the rapid cycling variant [18]. While it remains to be directly demonstrated in clinical studies, one could postulate that the better functioning val-66-val allele of proBDNF could be associated with the

An Introduction to the Neurobiology

increased pressure of speech and hyperassociativity, as well as creativity in those with mania and a diagnosis of bipolar illness in general. Moreover, Benson et al. [47] have recently demonstrated that bipolar patients, in contrast to those with unipolar illness and normal volunteer controls, have an increase in functional connectivity amongst brain regions. The usual inverse relationships between frontal cortex and amygdala or frontal cortex and cerebellum are not only not present in those with bipolar illness, but the correlations of metabolism between these and many other regions are now positive – that is, increases in one area are associated with increases in the other, and vice-versa, decreases are associated with decreases. Again, whether this hyperconnectivity and hyperassociativity seen in bipolar illness relates to the increased presence of the val-66-val allele, or some other mechanism, remains for future ascertainment. However, hypothetically, it is relatively easy to envision that such a hyper-positive associativity of multiple brain regions could, in part, account for the exaggerated overswings in mood and behaviour associated with both mania and depression, that is, the normal inverse modulatory effects of one region upon another and, particularly, prefrontal cortical suppression of amygdala and perilimbic and ventral striatal mechanisms, which appear to be hyperactive in patients with bipolar illness, does not occur [48]. However, as we make clear below, it is equally possible that such hyperassociativity is environmentally induced and potentially related to epigenetic mechanisms and not those inherent in our DNA code. Another area of promising findings in the realm of genetics is that of alterations in the CLOCK genes and related circadian rhythm genes in patients with bipolar illness. These data are now supported by the compelling studies of McClung et al., [49] and Roybal et al., [50], showing that disruptions of the clock gene are associated with behaviours in mice that are highly similar to human mania including: hyperactivity, decreased sleep, and increased reward value for cocaine, sucrose and even medial forebrain bundle stimulation. Remarkably, chronic administration of the mood stabilizer, lithium, returns many of these behavioural responses to normalcy. In addition, clock mutant mice have an increase in dopaminergic activity in the ventral striatal area and the associated behavioural abnormalities that are rescued by expressing a functional clock protein into the VTA. These data suggest inherent genetic connections between essential genes mediating circadian rhythms in the suprachiasmatic area (and in other areas of the brain) and dopaminergic transmission and cocaine reward. Mice lacking the functional clock gene also display not only an increasing cocaine reward, but also in the excitability and burst of firings of dopaminergic neurons in the VTA. These genetic data, like those discussed below for epigenetic mechanisms,

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provide a potential linkage between bipolar illness and the greatly increased proclivity for substance abuse.

Epigenetic mechanisms Long lasting effects of maternal rearing behaviour on adult neurochemistry, behaviour and stress responsivity Studies in the laboratory of M.J. Meaney [51,52] indicated that maternal licking and grooming behaviour in the immediate neonatal period is associated with long-lasting characteristics in the adult. For example, low licking and grooming is associated with increases in anxiety-like behaviour, hypersecretion of glucocorticoids and increased stress responsivity in the HPA axis. However, if offspring of low-licking mothers are cross-fostered by those with high licking and grooming traits, the offspring bear the differential signature of the high-licking mother of decreased anxiety-like behaviour and stress responsivity. This investigative group has demonstrated that such a life-long maternal programme of stress responsivity in the adult offspring is related to epigenetic mechanisms, that is low licking and grooming experiences of the neonate are associated with lower levels of the glucocorticoid receptor (GR), which is mediated by hypermethylation of the exon-17 of the GR promoter and is also associated with hyperacetylation of histone H 3-lysine-9, which reduces binding to nerve growth factor-inducible protein-A(NGF I-A). While it had initially been thought that these behavioural and biochemical characteristics were permanent, it now appears that central infusion of the histone-deacetylase inhibitor (HDAC) trichostatin A (TSA) can enhance histone H3K9 acetylation of the exon 17 of the GR promoter and change levels of hippocampal GR expression and HPA responsivity to stress. This has been further confirmed with reversal of some of these maternal-induced behavioural programmes with methionine infusions to alter the state of DNA methylation. These long-lasting, epigenetic-mediated, stable changes in adult offspring related to subtle differences in maternal licking and grooming behaviour make it clear that even very small alterations in appropriately timed maternal behaviour can induce long-lasting and life-long behavioural and biochemical characteristics, and more profound abuse or neglect could have even more major consequences. The clinical relevance of these findings has now been documented with the observations of parallel increased DNA methylation in the GR promotor in human brain. This occurred only in suicide victims who had experienced child abuse and neglect and not in those without these environmental adversities [53]. The new evidence indicating that some epigenetic mechanisms may also be potentially reversible with appropriate pharmacotherapeutic interventions raises hope for the possibility of ameliorating

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some of the long-lasting consequences of environmental adversity.

Defeat stress induced alterations in BDNF and behaviour The defeat stress paradigm provides a potentially homologous model to not only many of the behavioural characteristics of clinical depression in humans, but has parallels in terms of inducing principles (defeat stress) and pharmacotherapeutic mechanisms (antidepressants). In the defeat stress paradigm, an intruder mouse is introduced into the home cage of a resident animal, who viciously defends its territory and repeatedly defeats the intruder upon repeated presentations to the cage. This is associated with the induction of depressive-like behaviours including: social withdrawal, increased anxiety behaviour, weight loss, anhedonia (loss of preference for sucrose) and so on, as well as decrements in hippocampal BDNF and increases in BDNF in the dopaminergic pathway from the VTA to the nucleus accumbens [54,55]. Pretreatment with antidepressants reverses the defeat stress signature of low hippocampal BDNF and depressive-like behaviours. If the BDNF decreases are prevented with other genetic manipulations, the BDNF and defeat stress behaviours do not occur, indicating that the BDNF changes are critical to the resulting defeat stress behaviours. What makes these findings in adult animals of particular interest is that the repeated neonatal stresses can also change the signature of hippocampal and fronto-cortical BDNF and anxiety behaviour and stress responsivity in the adult [56]. Thus, similar to the subtle differences in maternal licking and grooming behaviour, more extreme stress experiences in an appropriate timed neonatal window can also affect neurochemistry and behaviour in a long-lasting fashion in the adult. Human data parallel these findings; adult bipolar patients who experienced serious early life adversity and trauma show lower serum BDNF levels than those without these environmental stressors [57]. Increases in BDNF in the dopaminergic pathway induced by defeat stress and cocaine sensitization In contrast to the stress-induced decrements of BDNF in the hippocampal-tri-glutamatergic neuronal circuit, defeat stress behaviours are associated with increases in BDNF in the nucleus accumbens, and such increases, if they are prevented by appropriate genetic manipulations, prevent the emergence of defeat stress behaviours [54,58]. Parallel increases in BDNF occur with chronic cocaine administration, again revealing environmentally-induced mechanisms linking depressive-like behaviours and the proclivity for substance abuse acquisition and progression [55]. This linkage is analogous to the genetically mediated mechanisms for the proclivity to substance abuse and manic-like behaviour associated with deficits in the clock gene [49,50].

The molecular mechanisms underlying the epigenetic changes induced by stress and cocaine are now being revealed. They involve not changes in the DNA sequence, but in its relative conformational openness yielding greater or lesser ease of initiating transcriptional activity [58]. This occurs at two different levels. DNA is tightly wrapped around histones and if histones are acetylated, this increases DNA openness and facilitates transcription. In contrast, if histones are methylated and phosphorylated, this can either activate or repress transcription. In addition to these histone modifications, DNA itself can be methylated and this is almost universally associated with repression of transcription. S-adenosyl methionine (SAM) is acted upon by DNA methyltransferases (DNMTs) to make methyl groups available for cytosine residues in the DNA. Most of the findings have so far revealed epigenetic mechanisms acting through histone modifications. Histone acetyl transferases (HATs) put acetyl groups on the histones and open DNA conformation, while histone deacetylases (HDACs) tighten or close the structure, making DNA less available for transcription. There is an entire group of histone deacetylase inhibitors (HDACIs), which keep the acetyl groups on the histones and maintain the open conformation, one of which is the mood stabilizing anticonvulsant valproate. Moreover, a recent study showed that treatment with an inhibitor of histone desacetylase, butyrate, reversed the hyperlocomotion induced by d-amphetamine in an animal model of mania, similarly to the effect of valproate [59]. Kumar and colleagues [60] have shown that acute cocaine or an acute electroconvulsive seizure hyperacetylates histone H4 acutely and transiently, suggesting dynamic changes in gene transcription. In contrast, chronic cocaine and chronic ECS hyperacetylate H3, inducing a chronic and stable state. This hyperacetylation of promoters 3 and 4 of BDNF are mediated by increases in the transcription factor DFOS-B and alterations in cdk5. It is interesting that acetylation of H3 builds increasingly during a week of cocaine withdrawal, resulting in the late increase in BDNF in the nucleus accumbens, which correlate with the time-frame of maximal behavioural-sensitization. Thus, changes in the degree of hyperacetylation of histone H3 account for the increases in BDNF in the nucleus accumbens and accompanying respective behaviours with both chronic cocaine and defeat stress behaviours. Krishnam et al., [61] report that they have also found increases in BDNF in the nucleus accumbens in autopsy specimens of patients with a history of depression. One could speculate that the BDNF decreases in the hippocampus noted above are related to alterations in the conscious or declarative memory system associated with amygdalo-hippocampal pathways, while the BDNF increases in the ventral striatum might be those associated with more automatic responses engaging the habit memory

An Introduction to the Neurobiology

system in the striatum [62]. This inherent, automatic, unconscious mechanism in the nucleus accumbens could account for the high risk of relapse in animals and humans, even after they have been desensitized or extinguished from cocaine cues. Similarly, with repeated episodes of affective illness, episodes can emerge not only following the triggers of psychosocial stressors, but also in a more autonomous fashion as well. It has proven difficult to prevent or ward off by conscious or volitional behaviour, both recurrent affective episodes and re-instatement of substance abuse.

Only partial reversal of defeat stress epigenetic modifications by antidepressants As noted above, defeat stress results in sustained down regulation of two splice variants in the hippocampus – BDNF 3&4. This is mediated by dimethylation of histone H3 lysine 27 (H3K27) [58]. Interestingly, while antidepressants increase BDNF in the hippocampus by other pathways, the H3K27 dimethylation changes are not reversed by chronic treatment with antidepressants. Thus, this type of environmentally-induced histone modification may represent one aspect of the molecular memory or neurobiological scar that mediates the long-term increases in vulnerability that we postulate occurs and accumulates with each successive depressive episode [5,17]. It is noteable that cancer progression is likely mediated by trimethylation of H3K27, also leading to epigenetic silencing of target genes, potentially by an over expression of EZH2 a histone methyltranferase [63]. In the case of cancer progression, the over expression of EZH2 is mediated by a progressive genomic loss of a microRNA (miR-101) that normally inhibits EZH2, thus leading to dysregulaion of epigenetic pathways involved in cancer progression. The complexity of epigenetic mechanisms related to bipolar illness vulnerability and therapeutics remains to be more fully explored. In contrast to the persistence of the H3K27 dimethylation changes, the decreased BDNF levels in the hippocampus and associated defeat stress behaviours are reversed by antidepressants that remove the repression of the BDNF gene by inducing H3 acetylation and H3K4 methylation [58]. Chronic antidepressants down regulate HDAC 5 in the hippocampus only in chronic defeat stressed animals, leading to the increases in H3 acetylation (as well as H3 and K4 methylation activity in parallel) and prevention of the defeat stress behaviours. Thus, the H3K27 dimethylation induced by defeat stress is not reversed by antidepressants, even though these drugs reverse the depressive-like behaviours. To the extent that the H3K27 dimethylation leaves a permanent residue of illness vulnerability, further attempts at reversal of this epigenetic alteration are of great interest; this more complete reversal of the epigenetic effects of stressors could render the animal (or human) less vulnerable to further

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recurrences. Likewise, modifying EZH2-like methyltransferases and their regulation by microRNAs, as in cancer progression, are potential new targets of therapeutics.

Overview of the neurobiology of bipolar disorder Prefrontal cortical deficits and hypofunctions versus paralimbic hyperfunction The emerging neurobiology of bipolar illness has yielded some general patterns of the neurochemical, physiological and anatomical substrates involved. As illustrated in Figure 1, there appears to be a host of evidence of both neuronal and glial deficits yielding biochemical and physiological indices of hypo-function in prefrontal cortex of patients with bipolar disorder [9]. This stands in general contrast to considerable evidence for amygdala overactivity, hyper-reactivity and, in adults with the illness, volume increases. Parallel changes may be occurring in the extended amygdala, which merges into the ventral striatum (nucleus accumbens) with its evidence for over activity in the illness and paradoxical increases in BDNF and dopaminergic burst firing. Perhaps in concert with these opposite effects in anatomy, physiology, biochemistry and function of cortex versus mesolimbic regions are the findings that the normal inverse relationship of functional metabolic activity between prefrontal cortex and amygdala and other paralimbic areas of the brain in patients with bipolar illness, have shifted the valance towards uniform positive associativity [47]. The causative mechanisms underlying these shifts in associativity patterns are not known and the direction of causality – either episodes driving some neurobiological changes or the opposite that the severity of baseline alterations in connectivity are driving illness progression – remains to be further delineated.

Neurobiological alterations based on the environment However, the preclinical and animal model data noted above yield conclusive evidence that ill-timed and recurrent psychosocial stressors of sufficient emotional significance can change the neuro-behavioural signature of an adult animal in a stable and long-lasting fashion. D Fos B is a transcription factor that, in contrast to the immediate early genes (Fos, Jun and Ziff 268, etc.) is extremely long-lasting and thus yields the property of showing additive accumulation in relationship to the recurrence of stressors or repeated bouts of substance abuse. Thus, not only does D Fos B provide a cumulative marker for some recurrent stressors and substances of abuse, but distinguishing the patterns of histone acetylation and DNA modulation as a consequence

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Convergence of Structural, Biochemical, & Functional Abnormalities in Bipolar Illness: Cortical Deficits & Limbic Hyperactivity Imaging: Structural and Postmortem

Biochemistry & Function

DL-Pfc ↓ Gray ( Lim, Coffman) ↓ NAA (Winsberg/Ketter) ↓ Neurons esp Layer

DL-Pfc ↓ metabolism (dep.) ↓ CaCMK IIα (Xing) ↓ reelin (Costa/Guidotti) ↓ GAD67 (Guidotti) ↓ GFAP mRNA & protein ↑ cortisol ↓ MR (Xing)

DLPfc BA9 ↓ glial

III Glia esp BA24

↓ BG ↑volume (Pearlson) Hippocampus ↓ NAA (Bertolino) ↓ neuronal and synaptic markers (Eastwood & Harrison) Temporal Cortex ↓ Gray Volume (Altshuler, Hauser) ↓ NP & Spatial Navigation

BG ↑ PET metabolism

Hyp.

(Rajkowska)

BG

Pit.

C

A

H

LC

Hypothalamus ↑ CRF Pituitary

ACTH

Adrenal ↑ cortisol

↑ Amygdala (A) Volume ( Altshuler, Strakowski, Pearlson, Soares) ↓ Glial density in A (Bowley) ↑ Lateral and ↑ Third ventricle size

Fig. 1

¼ decreased and

(Ketter

H. ↓ cognitive and spatial memory Cerebellum (C) ↑Associativity, i.e., loss of reciprocal pfc-cerebellar function (Benson)

Locus Coeruleus (L.C.) ↑ # Ne cells (Baumann) ↑ Ne turnover, Ctx (Young) ↑ CSF Ne in Mania (Post) ↑ Amygdala (A) metabolism (Ketter) ↑ reactivity fMRI (Altshuler) ↓ response to Procaine (Ketter) ↑,↓ fear responses to stimuli Proportional to Neuropsychological (NP) Deficits

¼ increased.

of the accumulation of this transcription factor may yield important insights about the pathophysiology of bipolar illness and its treatment. It now appears that D Fos B and CDK5 influences on BDNF and subsequent histone H3 acetylation is one pathway leading to stable epigenetic events [58]. Distinguishing which of the pathological changes that have been revealed in the brains of bipolar patients are mediated by environmental-induced mechanisms and which are related to hereditary genetic mechanisms, may not only yield new understanding of the illness, but new approaches to targeting these alterations for therapeutics and developing new treatment strategies. While the search for single major genetic loci in bipolar disorders has been discouragingly negative, the lack of strong and replicateable findings can at the same offer an optimistic view about the lack of inevitability of illness onset and progression, despite ones genetic endowment. Whereas the single gene illnesses, such as Huntington’s chorea, convey a relatively immutable course of illness as a function of number of triple repeat sequences, the contrast in bipolar illness appears to include a panoply of modifying factors that can result in no illness at all in a relatively highly genetically vulnerable person, to a devastatingly progressive course. To the extent that more environmentally-induced epigenetic mechanisms become revealed in the bipolar illnesses, such information should yield the illness increasingly

malleable and responsive to treatment. The brain, as described by Edelson, has enormous capacity for plasticity and resilience, given its 12 billion neurons (each with an approximate average of 100 000 synapses) and four times as many glial elements. Viewing bipolar illness as a potentially progressive but highly modifiable illness, with no certain or irrevocable course or outcome, should convey a much more hopeful and optimistic view of the potentials for illness intervention and prevention.

Early onset illness as an added risk for neurobiological alterations and illness progression There is disturbing evidence that the earlier the age of onset of bipolar illness assessed retrospectively in adults (about average age 42), the more severe and disabling is the illness over the lifespan, as reported retrospectively [64] and as observed prospectively [65]. However, what remains to be seen is whether earlier, more effective intervention would yield more benign outcomes in those with early-onset bipolar illness. This is suggested by the observations that there is an inverse relationship between early age of onset and increasing duration of the lag to first treatment for mania and depression. Those with childhood onsets (before the age of 13) had an average of 15 years’ delay to first treatment, and adolescent-onset patients (before age 19) had an average of 10 years’ delay from illness onset to first

An Introduction to the Neurobiology

treatment, while those with early and late adult-onset illnesses had much shorter five and three years’ delay, respectively. The delay to first treatment has been found to be an independent predictor of poor outcome in prospectively treated adults with bipolar disorder [66]. During these long periods of lack of treatment, those with child- and adolescent-onsets had increasing numbers of affective episodes and also had an increased amount of psychosocial adversity, as well as the new onset of substance abuse comorbidity [67]. To the extent that these factors provide additive or potentiative neurobiological mechanisms fundamental to bipolar illness at the level of epigenetic mechanisms, one can readily envision the multiple liabilities conveyed by lack of early and adequate treatment. Not only are there extremes of affective dysregulation yielding marked impairment in social and academic and, ultimately, employment roles, but one misses out on the acquisition of adequate neural and psychosocial development. These empirically observed and known consequences of poorly treated early-onset bipolar illness are now compounded by the very real possibility that a whole new level of pathophysiological processes can occur by epigenetic mechanisms and propel further stressors, episodes and abuse of substances. Childhood-onset bipolar illness appears to go through an accelerated rate of illness stage evolution compared with that of the adult variety. As such, it is even more critical from a developmental, psychosocial, and now, neurobiological perspective that adequate treatment is instituted early to avoid the wide range of adverse outcomes now observed to occur throughout childhood and adulthood. In these instances, the old adage that an ounce of prevention is worth a pound of cure not only rings true, but appears to be an underestimation of the potential difficulties a youngster with bipolar illness might encounter in the face of no or inadequate treatment. This illness on its own can be severe enough, but in the face of acquisition of a substance abuse disorder, which is 8fold more likely to occur in an adolescent with a bipolar diagnosis compared with others [68], leaves an individual with two very difficult to treat chronic recurrent illnesses, that is bipolar affective disorder and substance abuse disorder. Their additive negative psychosocial impact may be reflected in additive or new pathophysiological mechanisms. This can occur not only in basic CNS mechanisms, reviewed above, but also in peripheral mechanisms, related to accumulating allostatic loads ([69], which further increases the likelihood of the eventual onset or increased severity of a variety of medical comorbidities as well. These can ultimately have a catastrophic impact on the number of years of potential life expectancy lost in those with serious mental disorders, ranging from 13 years in the United States in states like Virginia to 25–30 years in some western states [70].

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Clinical implications for illness progression This dual view of (1) the strong empirical clinical evidence for the potential for bipolar illness progression in concert with (2) the newly revealed epigenetic putative pathophysiological mechanisms, together provides very compelling evidence for the need for dramatic reassessment of approaches to bipolar illness and its earlier intervention with preventative treatment [3,71]. These environmentally-mediated epigenetic mechanisms could be interacting with genetic mechanisms that each mediate earlier onset or a more fulminate course of illness. As noted in the Introduction, each episode of mania and depression clinically is associated with decrements in BDNF in serum (in proportion to the severity of either type of episode) [18] and decreases in platelet BDNF has now been demonstrated in childhood-onset bipolar illness as well [72]. To the extent that these changes in the periphery reflect BDNF alterations in brain as some have suggested, one could see how each episode might increase vulnerability to further neurobiological alterations associated with the illness, by virtue of decrements in BDNF and related neuroprotective factors. At the same time that there are decreases in BDNF, each episode appears to be associated with increases in oxidative stress and the ratio of pro inflammatory to anti-inflamatory cytokines. Thus, there appear to be interacting mechanisms for episode-induced illness progression by way of both increases in free radicals and other toxic substances endangering neurons and glia, as well as lack of adequate protection by neurotrophins such as BDNF. Based on the defeat stress model cited above, one would postulate that transient episode-related alterations would be mediated in part by changes in H4 acetylation, while the chronic, more longlasting consequences could be mediated by changes in H3 acetylation [58].

Cross-sensitization amongst stressors, episodes and substances of abuse such as cocaine Repetition of many different types of stressors will lead to stress sensitization or increases in behavioural reactivity, at times being manifest even when there is evidence of down regulation to the endocrine effects of the stressor. Interestingly, a variety of stressors seem to cross-sensitize to the stimulants cocaine or amphetamine [3,73–75]. That is, a stress-sensitized animal is more hyper-reactive to not only cocaine and amphetamine, but stress predisposes them to the acquisition of stimulant self-administration more readily than their non-stressed litter-mate controls. In addition, stresses are associated with the reactivation of cocaine selfadministration behaviour, even in animals and humans that have had their reactivity to cocaine cues and cravings

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extinguished. Thus, there appears to be not only the discrete phenomenon of stress-sensitization and cocaine sensitization, but cross-sensitization between these two as well. In addition, we have seen that there is a general tendency for episodes to beget further episodes in a phenomenon we have generically called ‘episode sensitization’. Bipolar and unipolar affective episodes are associated with a highly increased risk of engaging in substance abuse and also, in some instances, appear to convey the risk for increasing stress exposure, if not reactivity. Thus, we postulate there is a cross-sensitization amongst all three phenomena, that is sensitization to episodes, substances of abuse and stressors. BDNF decreases in hippocampus and in the serum clinically of humans may be part of the common mechanism of crosssensitization. At the same time, the increases in BDNF in the nucleus accumbens may be part of the over-learned or habit system over-representation of memory-like events for episodes, stressors and substances of abuse such as cocaine.

Passive and active mechanisms of illness progression Therefore, one might postulate two different types of mechanisms of sensitization to affective episodes, one a passive one associated with increase in free radicals and the other neurotoxic substances in the context of decreased neuroprotection, which could then endanger nonspecifically neuronal and glial function, or even survival. Then, in addition, there may be an active component of sensitization based on over-learned behavioural responsivity mediated, potentially in a condition- or context-dependent fashion, via BDNF and other changes in the nucleus accumbens. Given the new viewpoint about how each of these alterations could be mediated by epigenetic factors (in particular, changes in histone acetylation or methylation, and changes in DNA methylation), one begins to see how various environmental occurrences could alter DNA structure and associated transcription or repression (silencing of a large series of transcriptional events), while not altering the fundamental inherited DNA sequences [58].

Neurobiology informing clinical therapeutics The clinical empirical data for the adverse clinical, cognitive, functional and neural consequences of repeated episodes is quite clear. The empirical evidence itself supports a new view of the recurrent affective disorders as potentially progressive illnesses partially mediated by the accumulation of recurrent environmental events, including episodes themselves, as well as stressors and substances of abuse. This theoretical or kindling-like sensitization effect of the affective disorders raises a new level of concern about the importance of early institution of preventive strategies, not only

to limit illness-related morbidity and disability, but also potentially to avoid long-term course of illness alterations.

The importance of medications is thus based on a three fold rationale Effective pharmacoprophylaxis with lithium, carbamazepine or valproate will: (1) help prevent episodes and their associated morbidity; (2) prevent episode-related decreases in BDNF and increases in oxidative stress and other neurotoxic phenomena; and (3) likely mediate direct neurotrophic, neuroprotective effects on their own via their ability to increase BDNF and, with lithium and valproate, also neurogenesis. In addition, two of the atypicals, quetiapine and ziprasidone, prevent stress-induced decreases in hippocampal BDNF, and quetiapine also increases BDNF directly [76,77]. Importantly, these atypicals act in an opposite fashion on BDNF compared with the typical antipsychotic haloperidol, which exacerbates the stress-induced reduction in BDNF in the hippocampus. While the role of the unimodal antidepressants in the treatment of bipolar depression is controversial and undergoing revision with regard to an accumulation of data suggesting less than desirable efficacy and increased risk of mania induction and cycle acceleration, in the unipolar recurrent affective disorders the role of antidepressants is unequivocal in enhancing long-termprophylaxis [78,79]and, in animals, increasing both BDNF and neurogenesis. These putative mechanisms for enhancing neuroprotection have now been validated in the clinic with evidence that patients with unipolar depression who were on antidepressants more of the time do not have the hippocampal volume loss with ageing, in contrast to those on antidepressants less of the time who showed decrements in hippocampal volume [80]. Likewise, a number of studies have indicated that lithium in bipolar patients is associated with increases in markers of neuronal integrity such as NAA, as well as direct increases in cortical grey matter as revealed on the MRI [81,82].

Epigenetic effects reemphasize the need for early prevention The new data on epigenetic changes mediated by stressors and substances of abuse add to the potential long-term consequences of repeated affective illness recurrences and, at the same time, offer potential new avenues for therapeutic exploration. Previously, one recognized intermediate-term duration of neurochemical changes associated with an episode of affective illness, such as state dependent cortisol hypersecretion or BDNF decrements, likely mediated by changes in gene transcription. Given the new view of how stressors and cocaine could lead to lifelong alterations in histone and DNA conformation

An Introduction to the Neurobiology

and availability for transcription, one is given even greater theoretical imputus for preventing affective episodes, their associated proclivity for substance abuse and avoiding or modulating stressor occurrence. These epigenetic-mediated changes may, on the one hand, represent episode, stressinduced and substance-induced neurobiological scars leading to illness progression, but may, in addition, mediate more active processes of illness progression associated with the appropriation or usurping of the habit learning system in the ventral striatum for accretion of behavioural pathology. Preventive approaches to the long-term management of the illness thus become of paramount importance.

Positive therapeutic potential of the convergent epigenetic effects Given the potential convergence of at least some mechanisms underlying stress sensitization, cocaine sensitization and episode-induced sensitization, a single therapeutic manoeuvre could have widespread implications for all three target systems. One potential example of this phenomenon is seen with the therapeutic approaches to substance abuse pioneered by Kalivas and associates using N-acetylcysteine (NAC) [83,84]. They observed that nucleus accumbens glutamate secretion was hyper-responsive in animals exposed to prior cocaine sensitization and put them at high risk for relapse to cocaine reinstatement (reinitiation of acquisition) upon stressor or cocaine exposure. They found that N-acetylcysteine(NAC), which alters the cysteine/glutamate exchanger in the nucleus accumbens and dampens the glutamate overactivity reduced cocaine reinstatement behaviour in animals, and subsequently showed that it had positive effects in cocaine addicts. NAC also showed positive effects in heroin and gambling addiction as well as trichotillomania. At the same time, Berk and associates [85] viewed NAC as an antioxidant and a glutathione precursor and showed that it had long-term benefit over placebo at 3 and 6 months in the treatment of residual symptoms of bipolar illness, with particularly prominent effects on bipolar depression. While it is unclear whether dampening glutamate hyper-responsivity in the nucleus accumbens or the antioxidant effects of NAC are responsible for its therapeutic effects in the affective disorders, the data on NAC make the point that a single pharmacological manipulation carries the potential dual or triple therapeutic benefit. Thus far, there is no evidence that treatment of episodes of mania and depression and preventing their recurrence in the long term alters vulnerability to the underlying mechanisms for illness recurrence; that is there are no cures. However, to the extent that epigenetic changes play a prominent role in the accumulation of illness vulnerability, potentially making whatever inherited genetic vulnerability cross the threshold for illness activation and reactivation, targeting

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epigenetic changes directly could theoretically have promise for altering some of the fundamental mediators of longterm vulnerability to recurrence. In this regard we know that valproate is a histone deacetylase inhibitor and it and other more specific HDAC inhibitors could ultimately play a role in altering some of the environmentally-induced epigenetic changes associated with the illness. Interestingly, the congener of valproate, valpromide, while it is a potent anticonvulsant, is not a HDAC inhibitor, thus raising the possibility of controlled clinical trials to show whether anticonvulsant versus epigenetic mechanisms play a role in whatever therapeutic effects are observed with these two agents. Similarly, the ability to reverse behavioural and biochemical alterations in neonatal maternal programming of adult behaviour, as well as in the defeat stress paradigm, also raises the possibility of TSA and other substances directly targeting epigenetic mechanisms that could also alter or reverse some of the long-lasting increases in illness vulnerability previously viewed as inherent in the illness and its progression.

An evolving neurobiology of bipolar disorder Pathological versus adaptive mechanisms We hope the foregoing discussion has shed some conceptual light on the rich variety of potential mechanisms involved in the neurobiology of bipolar disorder. At any level of analysis, it will be of critical importance to discern which changes are related to the primary pathology of the illness and its progression versus which are potentially endogenous adaptations and compensatory mechanisms [14]. This is essential in attempting to develop new therapeutic approaches, which could either: (1) be aimed at inhibiting the pathological processes; or (2) enhance the adaptive ones. Neurochemical alterations mediated by inherited genetic variation are at the moment not subject to amelioration, although they may be in the not-so-distant future. On the other hand, all of the environmentally-induced changes become major targets for therapeutics and more immediate attempts at intervention, prevention and reversal of those alterations.

Bipolar illness pleiomorphy and state versus trait abnormalities One of the struggles in conceptualizing the neurobiology of the affective disorders has been the difficulty in dealing with the behaviour and neurobiological over-swings occurring in opposite directions in both manic and depressive episodes and their co-occurrence in mixed states, as well as the

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almost infinite variety of frequencies of episode recurrence and cyclicity. This extreme illness pleiomorphy, further exacerbated by its multiplicity of comorbidities, makes bipolar illness particularly difficult to understand and treat. The problem is further exacerbated by the current limited understanding of the neuropathology of the illness at multiple separate levels of analysis. These include changes that reside at the level of a single gene and its protein product to a large array of multiple candidate genes and proteins successively reflecting upwards into larger regional neurochemical and physiological changes to alterations in pathways and circuits, which ultimately lead to behavioural dysregulation. The following chapters update our knowledge of the neurobiology of bipolar illness at each of these many different levels of analysis. The new view of the potential role of epigenetics in the neuropathology of bipolar illness and its therapeutics give us hope that it will yield new leverage points in better understanding and treating the illness. Transcription factors themselves can transiently induce gene activation or repression, and this level of understanding is now much further amplified by the knowledge of histone and DNA conformational modifications that make whole segments of the genome more or less accessible for gene transcription on a short- or long-term basis. Thus, common underlying mechanisms could mediate the apparent disparate neurochemical events associated with bipolar illness. These ultimately may yield common targets of therapeutics as well. If there is a general regulatory lack of control and resultant hyperactivity in systems modulating the excesses of mania, some of the same principles may apply to those modulating the excesses in the opposite direction of depressive affect and immobilization. The new findings of clock genes alterations and the pertinent animal models of mania derived from them further suggest mechanisms for the inherent connections between affective dysfunction and substance abuse comorbidity, and at the same time, potential links to the diverse alterations in frequency and cyclicity that are manifest across different individuals with bipolar disorder. Such linkages of changes in gene transcription and histone and DNA modifications also may yield new insights into factors underlying the stages of bipolar illness development and progression. These sequentially involve the: (1) baseline vulnerability state; (2) presymptomatic interval; (3) prodrome; (4) full syndrome; (5) episode recurrence; (6) illness progression; (7) treatment refractoriness; and (8) end-stage illness and premature death. Each of these stages may be reflected in differences in neurochemistry, physiology and neuroanatomy, so that assessing discrete changes as a function of illness course progression appears essential to a full understanding of the neurobiology of bipolar illness and its treatment. We know that affective illness patterns may progress from isolated intermittent episodes to more rapid and

regular recurrences and, ultimately, to continuous cycling without a well interval [16]. These can be spontaneous illness transitions or occur in association with some treatments, such as the adverse effects of unimodal antidepressants. The fact that antidepressants not only increase BDNF and neurogenesis, but also facilitate histone acetylation, could help in the conceptualization of how such a positive treatment for unipolar depression could, paradoxically, produce too much of an antidepressant drive and induce the illness to a new stage of progression. To the extent that histone and DNA modifications are involved in such transitions, this further raises the importance of not only early effective treatment of bipolar illness, but the avoidance of inappropriate treatment that could have lasting adverse effects via epigenetic mechanisms. Baldessarini et al. [86] reviewed treatment practices in a very large network of bipolar patients seen in private practice settings and, disturbingly, found that about 50% of those with new onset bipolar diagnoses were treated with antidepressant monotherapy, while many fewer patients were treated with lithium, anticonvulsants or atypical antipsychotics. Thus, prevention of both induced and spontaneous illness stage progression by dealing optimally with stresses and maximally preventing episodes and their associated high risk for substance abuse, are three critical and highly modifiable targets of not only pharmacotherapeutic but psychotherapeutic interventions as well. The early phases of understanding the complex and evolving neurobiology of bipolar disorders are continuing to reveal putative pathophysiological mechanisms not only for illness vulnerability and onset, but also their recurrence and progression to new stages of treatment refractoriness. To gain further detailed understanding of bipolar illness neurobiology, it will be increasingly important to assess it in relationship to the stage of illness evolution, as this may help explain some of the discrepant and at time apparently contradictory findings. We are used to examining neurobiology in relationships to manic and depressive states versus underlying trait vulnerability; to this we now must add the stage of illness evolution as well. Hopefully, this reconceptualization of the constantly changing and evolving pathophysiology of bipolar illness and the potential interactions of genetic and epigenetic factors driving it, will clarify some apparently discrepant findings reviewed in the following chapters. Hopefully, it will also help create a shift towards earlier and more effective treatment intervention and prevention in this paradoxical illness which, on the one hand, appears highly treatable and on the other hand potentially crippling and lethal. The insights already gained into the neurobiology of the illness may help us begin to intervene more effectively in making the course of illness a much more benign one for a larger majority of patients with the disorder.

An Introduction to the Neurobiology

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Genetics of Bipolar Disorder Falk W. Lohoff and Wade H. Berrettini University of Pennsylvania School of Medicine, Philadelphia, PA, USA

Introduction The search for bipolar disorder (BPD) susceptibility genes is the subject of this chapter. As indicated by family, twin and adoption studies, BPD has substantial heritability, estimated from twin studies as approximately 65–80% of the risk [1]. Consistent with this heritability, BPD family studies demonstrate substantial familial aggregation: children of BPD parents have
9-fold increase in lifetime BPD risk, compared to the approximately 2–3% general population risk [2–10]. These same studies note a significant increase in risk for recurrent unipolar disorders (RUP) amongst the first-degree relatives of individuals with BPD. For RUP, the lifetime prevalence is at least 10% [11–13] and twin studies suggest a heritability of 40–50% [14–19]. Family studies indicated a two to three-fold increase in lifetime risk to develop RUP for first-degree relatives [4,9,20]. The familial aggregation and high heritability estimates generated early optimism that molecular genetic linkage and association techniques (useful for Mendelian disorders) would be similarly helpful in understanding the substantial genetic influence on BPD risk. As with nearly all common disorders (e.g. cardiovascular disease, alcoholism) however, unequivocal gene localization and identification has been a slow and labour intensive process. For BPD, as with all complex human disease traits, primary difficulties include: (1) no single gene is necessary and sufficient; (2) a single vulnerability allele conveys a small fraction of the total genetic risk; and (3) tremendous heterogeneity of risk alleles, meaning that large numbers of susceptibility alleles (which interact with each other and the environment) predispose to disorders, which are indistinguishable by phenotype (clinical presentation). Because the inherited susceptibilities for BPD are explained by multiple alleles, each of small effect, consistent confirmation of these risk alleles cannot be expected due to power issues, sampling variation (variations in risk allele frequencies in distinct ethnic groups) and genetic

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heterogeneity (distinctly different risk alleles occurring in indistinguishable syndromes). With this introduction, several promising linkages of BPD to genomic regions are reviewed, including some which may be shared with schizophrenia (SZ). It is highly probable that psychiatric nosology will be re-written to be consistent with genetics of the myriad diseases, which are currently subsumed under the rubric, BPD.

Genetic epidemiology of bipolar disorders Twin studies Evidence for a genetic component to BPD has been documented consistently using family, twin and adoptions studies and is summarized in Table 1. The first genetic studies of mood disorders were conducted over 70 years ago and included assessment of concordance rates for monozygotic and dizygotic twins with mood disorders [21–27]. The early studies did not distinguish between BPD and RUP; however, in nearly all these reports, RUP illness in the co-twin of a BPD index case was grounds for categorizing the twin pair as concordant. Bertelsen et al. [22] and Allen et al. [21] report that approximately 20% of concordant monozygotic twin pairs were constituted by a BPD index twin and a RUP cotwin. These older results are consistent with the more recent studies of BPD [16,28], reporting significantly higher monozygotic twins’ concordance rates, compared to those for dizygotic twins.

Family studies Family studies of BPD show that a spectrum of mood disorders is found amongst the first-degree relatives of BPD probands: BPI, BPII with major depression (hypomania and RUP illness in the same person), schizoaffective disorders and RUP illness [2–9,29,30]. The family studies suggest shared liability for BPD and RUP disorders. No BPD family study, conducted in an optimal manner (meaning simultaneous and blind interview of first-degree relatives of patients and controls), reports increased risk for SZ amongst

Genetics of Bipolar Disorder Table 1 Genetic epidemiology of mood disorders.

Lifetime prevalence (%) Lifetime risk for first degree relatives (fold increase) Proband-wise MZ twin concordance (%) Heritability estimate (%)

Bipolar disorder

Unipolar depression

2–3 9–10

10–15 2–3

45–70

40–50

65–80

33–42

relatives of BPD probands. Similarly, no SZ family study reports increased risk for BPD amongst relatives of SZ probands. Most importantly, these family studies were probably underpowered to detect a small increase in risk for a disorder with a base rate of 1–2% in the general population. However, several SZ family studies report increase risk for RUP and schizoaffective disorders amongst relatives of SZ probands [8,29,31,32]. These family studies are consistent with some degree of overlap in susceptibility to RUP and schizoaffective disorders for relatives of BPD probands and relatives of SZ probands. Kendler et al. [32] specifically note an increase in risk for psychotic affective disorders amongst the relatives of SZ probands. Potash et al. reported that psychotic affective disorders cluster in families [33,34]. Risk for psychotic affective disorders was significantly higher amongst the relatives of psychotic BPD probands, compared to the risk for relatives of non-psychotic BPD probands. This raises the possibility that the partial overlap in risk for BPD and SZ nosological categories is due to a subset of BPD characterized by psychotic symptoms. This subset of BPD is probably quite common, as the majority of BPD probands from the Potash et al. [33] study were psychotic. Recently, an epidemiological sample from Sweden, including 2 million nuclear families and using registry diagnoses, reported increased risk for SZ amongst relatives of BPD probands and increased risk for BPD amongst relatives of SZ probands [35]. This paper is remarkable for the size of the study population. Its main difficulty is reliance on registry diagnoses, as opposed to reliance on semistructured, in person interview data.

Adoption studies Mendlewicz and Rainer [36] reported a controlled adoption study of BPD probands, including a control group of probands with poliomyelitis [36]. The biological relatives of the BPD probands had a 31% risk for BPD or UP disorders, as opposed to 2% in the relatives of the control probands. The risk for affective disorder in biological relatives of adopted BPD patients was similar to the risk in relatives of BPD

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patients who were not adopted away (26%). Adoptive relatives do not show increased risk compared to relatives of control probands. Wender et al. [37] and Cadoret [38] studied RUP and BPD probands. Although evidence for genetic susceptibility was found, adoptive relatives of affective probands had a tendency to excess affective illness themselves, compared with the adoptive relatives of controls [37,38].

Linkage studies of bipolar disorders While linkage studies have nominated several genomic regions that might contain BPD risk alleles, inconsistent confirmation has been the rule, due to those factors mentioned earlier, including power, genetic heterogeneity and ethnic differences. The term, linkage, refers to the observation that two genetic loci, found near one another on the same chromosome, tend to be inherited together more often than expected by chance within families. Two such loci are said to be linked. The key concept of linkage is that chromosomal fragments that might harbour vulnerability genes are inherited with an illness more often then expected by chance in families. LOD (the logarithm of the odds ratio) scores refer to the probability that observed co-segregation of alleles at two loci within a family has occurred because the two loci are linked. A LOD score of more than 3 is evidence (not proof) that two DNA sequences are linked. The numerical value of the LOD score is dependent on the proposed mode of inheritance (dominant, recessive, sexlinked) and penetrance. Because the LOD score is dependent on these parameters (mode of inheritance and penetrance), it is sometimes termed a parametric statistic. This dependence on inheritance mode and penetrance distinguishes the LOD score from non-parametric statistics (including affected sibling pair and affected pedigree member methods), because such statistics are not dependent on mode of inheritance or penetrance. What level of statistical significance should be required for declaring linkage? A recommended level of statistical significance for an initial report (p 
0.00 002) is a stringent criterion, based on simulations that indicate that this level of significance would occur less than five times randomly in 100 genome scans for linkage [39]. This statistical criterion assumes that all the genetic information within the pedigrees studied would be extracted, an assumption that is not true in practice. Typically, no more than approximately 80% of the genetic information in a pedigree series is extracted through genotyping. As in any other area of science however, no single report of linkage should be accepted as valid without independent confirmation. The requirement for independent confirmations (at p  0.01) is not waived, no matter what level of statistical significance has been achieved in a single report. This confirmation requirement

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should be seen within the context that valid linkages will not be confirmed in some studies. Indeed, non-confirmations should be expected, intuitively, because of population (ethnic) differences, sampling procedures and genetic heterogeneity. Suarez et al. [40] have examined the probability of confirmation in simulations. Suarez et al. [40] simulated a disorder caused by any one of six loci, and determined that a large sample size and substantial time will be required for an initial linkage to be confirmed in a second sample. From his simulations, it is clear that consistent detection of a locus of moderate effect cannot be expected. Non-confirmatory studies will always occur when an initially detected linkage is valid [40]. One of the most critical issues in confirmation of reported linkages is power. Attempts at confirmation of a reported susceptibility locus should state what power has been achieved to detect the locus initially described. For example, if a locus increases risk for BPD by a factor of 2, it may be necessary to study approximately 200 affected sibling pairs in order to have adequate (90%) power to detect such a locus [41]. Unfortunately, few studies address this key issue. If 200 affected sibling pairs are required to achieve adequate (90%) power to detect a previously described locus, then a publication with less than 150 sibling pairs does not address the central issue of confirmation. However, such power-limited publications may have an important role in meta-analyses, in that they identify invaluable sources of additional data. Comprehensive scans of the human genome have been completed with sufficient numbers (e.g. >100) of BPD individuals [42–50]. If a major locus (explaining >50% of the risk in >50% of BPD persons) existed, it would have been detected in many of these studies. Thus, no such major locus exists for BPD. There are several confirmed reports of loci of smaller effect, which can be termed susceptibility loci. These loci are neither necessary nor sufficient for disease, but increase risk for the disorder in a non-Mendelian manner. Confirmed linkage loci are summarized in Table 2. From these genome scans and from additional, smaller studies, a picture has emerged in which there are several confirmed BPD linkage regions across the genome. It is highly probable that additional confirmed BPD linkages will be identified through future linkage studies. These BPD linkage regions are confirmed by virtue of at least one study with strong statistical significance (p < 0.0001) and at least two confirmatory studies (p < 0.01). As noted elsewhere [51], in some cases, these confirmed BPD linkage regions overlap with SZ linkage reports, suggesting that the same loci may be involved in some aspects of both disorders. In an attempt to further elucidate possible BPD linkage regions, two meta-analyses of BPD genome scans have been conducted [52–54]. Badner and Gershon [52] analysed linkage results using a multiple scan probability approach, in which p values are combined across studies, after adjusting

Table 2 Linkage studies of bipolar disorder. Location

Primary report

Independent confirmations/ supportive evidence

4q32 4p15 6q16-24 8q24 12q23 13q21-32 16p12 18p11.2 18q22 21q22 22q11-13

[46] [64] [68] [43] [67] [44] [65] [81] [85] [92] [47]

[48,49,62,63] [43,44,65–67] [45,50,63,65,69–71] [45,49,54,59,72] [46,65,73–77] [47,48,60,78,79] [45,46,80] [42,82–86] [49,69,87–91] [67,93–96] [44,97,98]

Evidence from meta-analyses for genome wide significance

[55] [55] [52]

[52]

Only primary linkage studies are shown with genome-wide significance according to [39]. Negative studies are not shown.

for the size of the linkage region. These authors concluded that two genomic regions, 13q32 and 22q11-13, were the most promising loci for BPD. Segurado et al. [54] used the method of Levinson et al. [53], which ranks the p values across the genome of each study, then sums the rankings for each genomic ‘bin’. In this approach, no genomic region reached genome-wide significance, although the regions that seemed most promising were 9p, 10q, 14q and the pericentromeric region of chromosome 18 [54]. A combined analysis of 11 previous linkage scans was carried out by McQueen et al. [55]. In contrast to the two previous meta-analyses, the authors used original genotyping data and showed genome wide significant linkage for BPD on chromosomes 6q and 8q [55]. It is likely that several additional linkage loci will be identified in the future, in particular when large enough sample sizes will allow the analyses of clinical subtypes like psychotic BPD, early onset of illness or BPD with comorbid panic disorder. These subtypes have been suggested to have a strong heritable component to them [33,34,56,57]. For example, recent genome scans of psychotic BPD showed promising results to chromosome 9q31 and 8p21 [58,59] and 13q21-33 and 2p11-q14 [60]. Interestingly, 8p21 and 13q overlap with SZ, further substantiating the concept of shared genomic regions, which harbour shared susceptibility factors between BPD and SZ [61].

Candidate gene studies of bipolar disorder The human genome consists of about three billion base pairs of DNA [99]. The recent completion of draft genomic sequences of the human genome [99] is consistent with about 30 000 genes. Physical distance along the linear sequence of

Genetics of Bipolar Disorder

DNA can be expressed in terms of base pairs of DNA. The most common sequence variation in the human genome is a single nucleotide polymorphism (SNP), where there are two different nucleotides (from the possible four, adenine [A], guaine [G], thymidine [T] and cytosine [C]) found amongst homo sapiens at the same position on different chromosomes. SNPs with a common minor allele (frequency of
20%) occur approximately every 1000 base pairs of DNA [99]. Analysis of closely-spaced SNPs in outbred populations suggests a complex pattern of inheritance in which recombination is inhibited in a small region of DNA, such that blocks of DNA (containing multiple SNPs) tend to be inherited intact over many generations [100]. Thus, blocks of DNA are shared amongst present-day individuals who may have had a common ancestor 10 000 generations ago. These DNA blocks vary in length across ethnic groups [100], with typical lengths of 10–20 000 base pairs (containing multiple SNPs), but amongst outbred human populations, the block length rarely exceeds approximately 100 000 base pairs. Alleles of SNPs within a block form a haplotype (a set of alleles) that are usually inherited together across many generations. The alleles of such SNPs are said to be in strong linkage disequilibrium (LD) with each other, or ‘associated’ with each other. LD refers to the fact that two (or more) alleles can be found together in unrelated individuals more often than predicted by chance. The interested reader is referred to primary reports concerning LD [100]. LD is a useful tool to investigate the relatively small genomic regions that have been implicated in the genetic origins of BPD through linkage studies (see Table 2). In this process, SNPs spaced across genes in the linkage region are assessed in large groups (ideally several hundred at least) of ethnically-matched cases and controls. Investigators compare allele and genotype frequencies amongst

Allele

1 2

3 4

RUP 5 6

7 8

9 10 11 12 13 14 15 16 17 18 19 20

Individual A Individual B Affected

Individual C Individual D Individual E Individual F

Not Affected

Individual G = risk allele

= protective allele

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groups of cases and controls. If nominally significant differences in allele or genotype frequencies are found between groups, the investigators might conclude that the tested SNP or a variant in close proximity influences risk for BPD. There have been a multitude of association studies in BPD over the past decade. Most studies have focused on neurotransmitter, neuroendocrine, neurotrophic and cellular signalling systems. Unfortunately, the nearly complete absence of pathophysiological data in BPD makes the process of rational candidate gene selection difficult. In addition, these studies have typically involved smaller numbers of BPD patients than is optimal, given that the effect size of individual alleles on risk must be small. While the lack of adequate power of some studies might explain the high degree of non-replication, other factors such as genetic heterogeneity and population differences further complicate matters. As indicated by the findings of multiple linkage loci, it is likely that there are several candidate genes that in combination contribute to the clinical phenotype of BPD. This paradigm is illustrated in Figure 1. Assume that there are 20 risk alleles, each only contributing a small fraction to the overall risk. In order to develop BPD, let us suppose we need five risk alleles. As shown, both individual A and B have BPD but share only one risk allele. Individual C has also five risk alleles but shares one risk allele with individual A and one risk allele with individual B. Individual D has also BPD risk alleles but falls in the SZ continuum. This genetic heterogeneity can explain why it is difficult to find universal risk alleles. It is more likely that several sets of risk alleles will contribute to the clinical phenotype. The degree and amount of risk alleles might explain why we observe a continuum or spectrum of the BPDs, or psychiatric disorders in general.

BPD SZ

|

Fig. 1 Model of risk and protective alleles involved in psych.

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As shown for the unaffected group, there are several scenarios which could explain unaffected status. One simple explanation is the lack of risk alleles (individual E) but another possibility includes the presence of protective alleles (as shown for individual F and G in green). While the majority of past studies have investigated risk alleles, it is becoming increasing clear that complex interactions of genetic risk and protective factors in concert with environmental stimuli contribute to the development of BPD. This observation has been made for example, in cancer genetics, with the identification of oncogenes and tumour suppressor genes [101,102]. Investigation of interaction of protective and susceptibility factors, in addition to complex gene-gene (epistatic) and gene-environment interactions, will be necessary in order to elucidate the genetic basis of complex behaviours [103]. Furthermore, epigenetic regulation and mechanisms might influence gene expression without altering the genetic code and could mediate stable changes in brain function [104]. Despite these difficulties and complexities, there are several candidate genes which deserve mention. On a general note, many candidate genes discussed here show also positive results for other psychiatric illnesses such as anxiety disorders, attention deficit hyperactivity disorder, psychotic disorders and substance use disorders, supporting the concept of shared susceptibility factors and comorbidities across diagnostic categories (Figure 1).

D-AMINO acid oxidase activator DAOA (G72)/G30 One promising candidate gene is the G72/G30 locus on 13q32, the site of a confirmed linkage in BPD (see Table 2) and SZ [52,82,105–112]. G72 is a primate-specific brainexpressed gene that activates D-amino acid oxidase [113] and was recently renamed D-amino acid oxidase activator (DAOA) (UCSC genome browser; Ensemble genome browser; National Centre for Biotechnology Information, http:// www.ncbi.nlm.nih.gov). D-amino acid oxidase may control levels of D-serine, which regulates glutamatergic receptors [114], implicated in the pathophysiology of SZ and BPD. Chumakov et al. [113] identified a haplotype from G72 SNPs (without obvious functional significance), which were in LD with SZ in a French-Canadian sample. This has been confirmed in distinct SZ populations, [113,115–117], although different haplotypes have been associated in different ethnic populations. Similarly, in BPD there have been several positive findings with distinct haplotypes in different populations [115–119]. A recent meta-analysis combined the published results at this locus and further substantiated the association of G72/G30 with BPD and SZ [120]. Although the G72/G30 locus is arguable amongst the best replicated association findings in psychiatric genetics, no clear functional variants have been yet defined at this locus and the biological relevance of this susceptibility locus remains elusive.

Brain-derived neurotrophic factor (BDNF) A second promising candidate gene is brain-derived neurotrophic factor (BDNF). BDNF is located on chromosome 11p13, a region of suggestive linkage for BPD [44,90]. Two family-based association studies showed an overtransmission of Val-allele of the functional Val66Met polymorphism [121,122]. This finding was confirmed in a large case-control association study of unrelated BPD subjects from the NIMH Genetics Initiative [123]. Additional evidence for an association of the Val allele was reported in three small childhood-onset samples: two using a family-based design [124,125] and one employing a case-control approach [126]. Furthermore, two studies report the Val allele associated with rapid cycling [127,128]. However, there are also several negative findings [127,129–135]. While some of these studies were likely underpowered, another explanation would be ethnic and clinical differences between samples. Recently, Liu et al. (2008) [213] reported results for a large sample of BPD cases and controls, concluding that the several BDNF SNPs may convey risk for BPD, including the Val allele, but the odds ratio is very modest (
1.2). Most of the mentioned studies only investigated the Val66Met polymorphism. The BDNF gene structure is complex and might harbour several risk alleles in addition to the Val allele, as suggested by Liu et al. (2008). The functional consequences of the Val66Met are substantial and incompletely understood. Egan et al., demonstrated allele specific effects on intracellular trafficking and activity-dependent secretion of BDNF protein [136]. Recent studies demonstrate a role of the BDNF Val66Met polymorphism in cognition [136–140], brain structures [141] and BDNF serum levels [142]. Growing evidence suggests that BDNF is involved in the aetiology of mood disorders [143,144] and depressive personality traits [145]. Serum levels of BDNF were decreased in depressed patients when compared to controls [146–149] and postmortem brain studies in patients with BPD show decreased BDNF protein when compared to controls [150]. The use of antidepressants, electroconvulsive therapy and mood stabilizers such as lithium increase BDNF gene transcription [151–153] and infusion of BDNF into rat brain has a direct antidepressant effect in animal models of depression [154,155]. Taken together, the convergent evidence from genetic, preclinical and clinical studies makes BDNF a strong candidate for mood disorder.

Monoamine oxidase A (MAOA) There have been numerous independent association studies of BPD and RUP and an MAOA (CA)n repeat polymorphism in European [156–165] and Asian populations [166–168]. Those studies reporting a positive association [157–159, 162,166] generally detect an over-representation of allele 5 or

Genetics of Bipolar Disorder

6 of the MAOA (CA)n repeat amongst BPD patients, compared to controls, an observation that may be particularly evident amongst women [162,169–172]. The effect size is small, the odds ratio being 1.49 [162] and the sample size required for adequate power to detect is larger than most of the negative studies [156–165]. There is also an MAOA promoter polymorphism [167]. These studies involve multiple ethnic groups, case-control methods and family-based designs, with some studies having limited power to detect a small effect size. Thus, it is understandable that conflicting studies are reported.

Serotonin transporter (5HTT) Another intensively-studied candidate gene is the serotonin transporter (5HTT/SLC6A4), a functional candidate gene for which multiple BPD LD studies have been published. The 5HTT represents a logical candidate gene, as many antidepressants act through binding to the 5HTT protein [173]. There are two variants of the 5HTT that have been studied in BPD, and both have functional significance, based on in vitro analysis of these non-coding polymorphisms. The first variant is an insertion/deletion polymorphism in the promoter region (5HTTLPR). The shorter allele has much less transcriptional activity than the longer allele [174,175]. Moreover, the shorter allele has been associated with anxiety-related personality traits in humans [176]. The second variant is a variable number of tandem repeats (VNTR) polymorphism in intron 2. The two most common alleles are the 10 and 12 repeats, which confer differential transcriptional activity in an embryonic stem cell line [177]. Collier et al. [178] first reported that the 5HTT intron 2 VNTR allele 12 was in LD with BPD amongst patients from the United Kingdom [178]. Collier et al. also reported that the short allele of the 5HTT promoter variant was more common amongst 454 European BPD and recurrent unipolar patients, compared to 570 European controls, although the statistical significance was marginal (p ¼ 0.03), emphasizing the small effect size involved [174]. Analysis by genotype suggested that homozygosity for the short allele was associated with BPD (p < 0.05) and RUP (p < 0.01). Since this initial report there have been numerous replication studies with positive [179–183] and negative results [184–194]. Sampling variation and the small effect size, coupled with limited power of this sample size are probable explanations for these mixed results. Furlong et al. [195] reported results of a meta-analysis for approximately 1400 individuals of European origin, including 772 controls, 375 bipolar and 299 unipolar patients. Although there was no evidence for LD with affective disorders for the VNTR, a marginally significant result was found for the short allele of the 5HTT promoter polymorphism. This result is important, because it suggests that samples in the thousands will be necessary to draw firm

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conclusions, due to the small effect sizes involved. In another large European study, Mendlewicz et al. [191] examined the genetic contribution of the 5HTT promoter polymorphism in a case-control sample, including 539 RUP patients, 572 BPD patients and 821 controls. No evidence of LD was found for RUP or BPD, and subdividing the sample according to family history, suicidal attempts or psychotic features did not reveal any role of the promoter variant in the genetic susceptibilities to these disorders. A recent meta-analysis of published population-based and family-based association studies in BPD, investigating the 5HTTLPR and the VNTR polymorphism, showed a small effect (OR ¼ 1.12) of both SNPs [196]. Lasky-Su et al. [197] performed a meta-analysis of these SNPs for BPD and RUP and could only document a small effect (OR ¼ 1.13) of the insertion/deletion polymorphism with BPD [197]. A recent large-scale study of the 5HTTLPR promoter polymorphism failed to show an association for neuroticism, major depression or recurrent major depression [198]. Taken together, these data suggest a small but significant effect of the 44-bp insertion/deletion polymorphism (5HTTLPR) in BPD, while the role in major depression remains unclear. Several other candidate genes have been investigated in BPD, with some positive results for COMT, DAT, HTR4, DRD4, DRD2, HTR2A, DISC1, P2RX7 [199,200]. Most of these candidate genes were selected based on ‘a priori’ hypotheses regarding their neurobiological function. This approach of candidate gene selection has obvious limitation, given our lack of understanding the pathophysiology of mood disorders.

Genome-wide association studies Risch and Merikangas (1996) [214] showed that association had greater power to detect causative alleles of small effect, and they argued for the genome-wide association study (GWAS) design. GWAS research is now feasible, with the discovery of over three million SNPs and the development of microarray genotyping. Because GWAS research involves testing for allele frequency differences as about 1 000 000 SNPs in large samples of cases and controls, a statistical level of p ¼
10-7 is the equivalent of p ¼ 0.05 when searching the entire genome for association [201,202]. The stringent statistical correction for multiple-testing might mask true signals from genes that confer only modest risk of disease [203,204], although in theory this limitation could be overcome by larger sample sizes. The sample size required to achieve adequate power for expected effects sizes (odds ratios <1.5), given the correction for a genome-wide search, is the greatest limitation of this approach, as detailed in the power analysis shown in Table 3.

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Table 3 Sample Size for 80% Power in GWAS. Allele Freq.

OR 1.10

OR 1.30

OR 1.50

Additive 0.5 0.3 0.1

44 900 19 600 16 800

5580 2530 2240

2230 1050 954

Recessive 0.5 0.3 0.1

43 700 98 800 809 000

5570 12 200 99 100

2280 4860 39 000

Dominant 0.5 0.3 0.1

45 700 33 600 52 900

6320 4470 6680

2760 1900 2700

OR ¼ odds ratio Table gives number of case-control pairs needed for 80% power at a causative SNP.  P ¼ 0.0000001 (statistical significance corrected for multiple hypothesis testing).

A few GWAS reports have been published in BPD. Baum et al. [205] published a DNA pooling based study of 500 cases from the NIMH Genetics Initiative, 500 NIMH controls and about 800 cases and about 800 controls collected in Germany. This study identified over 80 SNPs with nominally significant association signals in both samples. The ANK3 SNP, rs9804190, was one of approximately 80 SNPs nominally significant in both the NIMH (p ¼ 0.0020) and German samples (p ¼ 0.0087). Two larger studies employing individual genotyping have also been reported. The Welcome Trust study included 2000 BPD cases; this study reported weak evidence of association with five of the same SNP alleles detected in the Baum et al., study (WTCCC, 2008) [215], although genome-wide significance was not achieved, underscoring the need for large samples. A study of the STEP-BD sample and NIMH controls [206] yielded several SNP association signals at the 10-7 level in myosin 5B (MYO5B) and tetraspanin 8 (TSPAN8). It is noteworthy that the strongest association signals (the ‘top ten’ for example) in each of these three studies were not confirmed in the other two, suggesting that the individual sample sizes lacked sufficient power to detect small effects. This sample size limitation was partially addressed by a collaborative effort, including 4387 cases and 6209 controls, which were analysed jointly using GWAS genotypes [207]. The strongest statistical signal was in the ankyrin 3 (ANK3) gene on chromosome 10q21, with single SNP and haplotype (rs4582919 – rs10994357 – rs7910492, risk haplotype CCT) analyses yielding
P ¼ 109. This statistical level indicates genome-wide significance [208]. The associated SNPs spanned 195 kb in the 50 end of the gene. The odds ratio was 1.4. The characteristics of this study (a single phenotype analysed, careful control of stratification, etc.) are in accord

with those recommended recently by a panel of experts [209]. The 10q21 ANK3 location coincides with a BPD linkage signal [54]. There are several reports of nominally significant p values for SNPs in ANK3 [205,210,211]. Imputation (prediction of unassessed SNPs using genotypes of highly associated SNPs) reveals that the German sample identifies the same alleles as Ferreira et al. [207]. The study of Schulze et al. (2009) [216] was an emandation of the Baum et al. [205] study, including the German sample and additional samples. Finally, Bloss et al. [210] reported on an NIMH sample in which several ANK3 SNPs were nominally positive. Thus, ANK3 is a very promising candidate gene for BPD, although functional variants remain to be discovered. Ankyrins are peripheral membrane proteins thought to interconnect integral proteins with the spectrin-based membrane skeleton. There are three ankyrin genes, ANK1, 2 and 3. Kordeli et al. [212] described the ANK3 cDNA sequence, which has 44 exons, and is widely expressed in brain, as well as a variety of other tissues. The two largest ANK3 protein isoforms, 480 and 270 kD (also known as ankyrin G), contain an unusual serine-rich sequence, and are expressed only in the CNS [212].

Conclusions and future directions Family, twin and adoption studies of BPD are reviewed. They are, in general, consistent with substantial heritable components to risk. Multiple regions of the genome (including 18p11, 18q22, 12q24, 21q21, 13q32, 4p15, 4q32, 16p12, 8q24 and 22q11) have been implicated by several independent linkage studies in the genetic origins of BPD. It is likely that most of these regions will yield susceptibility genes within the near future, through the application of LD mapping methods and WGAS research to large sample sizes. LD approaches to candidate genes have yielded several promising candidate genes, including G72 and BDNF for BPD. In addition, molecular genetic studies of various psychiatric phenotypes document shared genomic regions between disorders, indicating a continuum between diagnostic categories rather then dichotomy. Although the field of psychiatric genetics has been plagued by positive and negative replications, promising robust findings are now emerging, such as ANK3, with the potential to lead to improved diagnosis and treatment.

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Structural Brain Imaging in Bipolar Disorder Paolo Brambilla1,2 and Jair C. Soares3 1

Inter-University Center for Behavioural Neurosciences, Department of Pathology and Experimental and Clinical Medicine, Section of Psychiatry, University of Udine, Udine, Italy

2

Scientific Institute, IRCCS ‘E. Medea’, Udine, Italy Department of Psychiatry and Behavioral Sciences, UT Houston Medical School, Houston, TX, USA

3

Brain imaging studies, specifically with magnetic resonance imaging (MRI), have tried in the last two decades to elucidate the anatomy of bipolar disorder, which is a severe lifelong illness that typically begins in adolescence. Recently, this research has also focused on juvenile-onset bipolar disorder, which is considered a more severe phenotype of the illness [1]. In this chapter, the most consistent findings from structural MRI studies in adult and paediatric bipolar disorder have been reviewed, suggesting future strategies for investigations in this field.

Prefrontal cortex The prefrontal cortex includes three main regions involved in the regulation of cognition and emotions, that is the anterior cingulate, the dorsolateral prefrontal cortex (DLPFC) and the orbitofrontal cortex (OFC) [2,3]. The anterior cingulate (Brodmann’s areas 24, 25, 33) lies between the corpus callosum and the cingulate sulcus [4] and has extensive connections with the amygdala, insula, thalamus and OFC, which also play a role in emotional processing [5,6]. A sub-region of the anterior cingulate called the subgenual prefrontal cortex (SGPFC) (Broadman area 24) is situated ventral to the genu of the corpus callosum and plays a main role in modulating decision making/planning and mood [7,8]. The DLPFC (Broadmann areas 9 and 46) is connected with higher-order association centres in the temporal and parietal lobe and participates in working memory and executive functions [9,10]. Finally, the OFC consists of the ventral-most regions of the prefrontal cortex, extending from the anterior perforated substance to the frontal pole.

Anterior cingulate Abnormally reduced volume [11,12] and grey matter density [13,14] of anterior cingulate cortex, especially in the left

side, have been reported in bipolar patients, including first-episode manic [15] and paediatric [16–18] samples. Interestingly, grey-matter loss over time in anterior cingulate and in the SGPFC has recently been identified in adult [19,20] and juvenile bipolar disorder patients [21]. Also, loss of volume and macromolecular density of the SGPFC have been shown in bipolar patients, particularly in those with a family history of affective illness [22–25], although normal size has been reported in both adult and paediatric patients [26,27]. In addition, post-mortem studies demonstrated synaptic abnormalities [28] and decrease in neural [29,30] and glial density [31] in anterior cingulate in bipolar disorder. Consistent findings support the hypothesis of impaired dysfunction of cingulate neural circuits in bipolar illness, potentially sustaining impairment in executive functions [32,33].

Dorsolateral prefrontal cortex A couple of studies found areas encompassing the DLPFC that were significantly smaller in bipolar disorder patients compared to healthy subjects [34,35]. Such abnormalities have been reported. particularly in the left side and in male patients, even in paediatric samples [36] and may be associated with genetic variability of the interleukin-1 beta gene [37]. Pathology of glial and neuronal size and density and decreased N-acetyl aspartate (NAA) levels have also been shown in the DLPFC of bipolar patients [38–41]. In addition, DLPFC stimulation with transcranial magnetic stimulation appeared to be effective in treating refractory depression in individuals with bipolar disorder [42]. These findings suggest that DLPFC neuroplasticity and cellular resilience may be impaired in bipolar disorder [43].

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Smaller grey matter OFC volumes have been shown in adult and adolescent bipolar disorder patients in comparison to healthy controls [18,44], particularly in

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males [45]. Hypoactivation of the OFC has also been shown in bipolar patients when performing activities involving attention, inhibition and emotional processing [46–48]. This literature suggests that the OFC may be involved in disinhibition and impulsivity in bipolar disorder, considering its role in regulating impulse control and rewardguided behaviour [49,50].

Ventricles Two recent meta-analyses reported that the most consistent structural finding in bipolar disorder was the enlargement of lateral ventricles [51,52]. This correlates with prior number of affective episodes [53,54] and may characterize chronic patients, representing a sign of cortical atrophy [53]. However, several others did not find evidence of size abnormalities for either third or lateral ventricles [54–68].

Limbic structures Hippocampus The ‘declarative memory’, involving the conscious recollection, verbal reflection and explicit expression of facts and events is primarily supported by the hippocampus [69,70], which also plays a major role converting short- into longlasting memory, a process called ‘memory consolidation’. Also, a neural circuitry involving amygdala, OFC, anterior cingulate and hippocampus is crucial in information processing and in creation of emotional memories [71]. Impairment of declarative memory has been shown in bipolar disorder, even during euthymia [72,73], supporting the role of hippocampal alterations in impaired cognition. Although there is one report of right hemisphere hippocampal volume reduction in bipolar patients [74], the majority of studies of patients with bipolar disorder and matched healthy comparison subjects did not find evidence for changes in hippocampal size [53,58,75–80]. Decreased size and accelerated grey matter decline of the hippocampus have been reported in adults with bipolar disorder [74,81–83], particularly in those carrying the met allele of the val-66-met single nucleotide polymorphism (SNP) in the brain-derived neurotrophic factor (BDNF) gene [84]. Such deficits are illustrated by magnetic resonance spectroscopy (1HMRS) studies showing reduced NAA levels [85–87] and increased glutamate concentrations in the hippocampus of adult bipolar patients [88]. Moreover, some [89,90], but not all structural MRI studies [91,92], showed hippocampal atrophy in paediatric samples, predominantly in the subicular region [93]. Hypothetically, dendritic/synaptic maldevelopment or neural degeneration may take place in the bipolar brain. However, other structural MRI studies and meta-analyses reported preserved hippocampal volumes, at least in adult

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patients [52,53,76,94,95]. Discrepancies amongst the studies in adults may in part be explained by the fact that most studies focused on global hippocampus volumes and may not be able to identify differences in specific subregions, which have different developmental trajectories, cortical connections and behavioural functions [96]. Also, there is the possibility that hippocampal deficits shown in juvenile bipolar disorder may be reversed in adult patients by longterm exposure to medications, in particular to lithium [51].

Amygdala The most consistent finding in volumetric analysis of bipolar disorder patients is amygdala enlargement [76,80,97]. However, smaller [78] and normal amygdala size [74] have also been reported. Findings of enlargement of the amygdala are consistent with findings of increased cerebral blood flow and glucose metabolism in this brain structure in bipolar patients [98]. Reports of smaller amygdala volumes in children and adolescents with bipolar disorder have also been published [89,92,99]. Moreover, a direct relationship between age and left amygdala volumes was found in juvenile bipolar patients, whereas in matched healthy controls there was an inverse correlation [92]. Theoretically, abnormal pruning mechanisms in childhood and adolescence could lead to findings of enlargement in adulthood in bipolar disorder patients. Alternatively, compensatory mechanisms might be operating over time and be responsible for the anatomical changes in adulthood. Several authors have proposed that enlargement of the amygdala may represent a trait marker for bipolar disorder; however, longitudinal MR studies in childhood-onset patients and high-risk populations are needed to further characterize amygdala development in bipolar disorder. The amygdala is considered the site where ‘emotional memory’ or memory for emotionally arousing events are formed and stored and is involved in processing fear and emotion in humans [100]. For this purpose, it receives input from the fronto-temporal lobes, and sends information to hippocampus, enthorinal cortex, thalamus and neocortex [101]. The amygdala is therefore believed to be a key region for the pathophysiology of bipolar disorder [102], as confirmed by several studies showing abnormally increased volumes in adult bipolar disorder patients [76,80,97]. In contrast, in paediatric patients, decreases in amygdala size have been reported [36,91,92], with an abnormal direct correlation with age [92]. In this regard, in adult bipolar patients a recent study showed a reduction of amygdala volume with age, which was not present in controls [103]. Therefore, there may be an altered developmental trajectory of the amygdala in bipolar disorder, with larger volumes in adulthood potentially resulting from abnormal neuronal pruning during childhood and adolescence. Alternatively, the neuroprotective effects of

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lithium may in part explain such anatomical changes over time [91,104].

Subcortical structures Thalamus The thalamus is a relay station between cortical and subcortical brain regions, crucial for both motor and cognitive coordination. The thalamus can be divided into multiple subnuclei with different patterns of connections [105–107]. The anterior nuclei is prominently connected with the hippocampus and cingulate gyrus, the mediodorsal nucleus is the main subcortical afferent to the prefrontal cortex, and the dorsomedial nucleus is a major site for serotonergic neurotransmission [108–110]. Some, but not all studies [53,111–114] showed significant thalamic enlargement in bipolar patients [44,80,115], even in first-episode [116]. Few studies examined thalamic size in children and adolescents with bipolar disorder, reporting smaller [117], larger [18,118] and normal size [119]. Inconsistent findings for or against changes in thalamic morphology in bipolar disorder suggests that there is no effect or that the magnitude of the effect size is very small. Future studies with larger samples including individuals across the lifespan may help to explain findings. Also, reliable methods should be developed to determine the size of specific thalamic nuclei.

Corpus callosum The corpus callosum represents the major midline white matter structure connecting the two cerebral hemispheres. It allows inter-hemispheric communication and participates in regulating attention, language and memory [127,128] and increases in size into late adolescence, primarily due to myelination [129,130]. Decreased area/length and impaired signal intensity of the corpus callosum, which is considered a marker of myelination, have been reported in adult bipolar disorder [131–134], as also confirmed by a recent metaanalysis [135]. Furthermore, abnormalities in signal intensity [136], as well as in splenium circularity [137], have been shown in the paediatric population, particularly in males. Circularity is a measure of splenium shape and may be a sign of poor brain maturation. In fact, significant correlation between callosal size and gestational age [138], mostly related to cortical thinning, have been found in the splenium of adolescents who were born prematurely. Taken together, these results suggest that there may a callosal maldevelopment in bipolar disorder patients during adolescence, potentially leading to decrease white matter density in adulthood. Future studies should longitudinally follow a single cohort to identify the development cascade of the corpus callosum in bipolar disorder and to investigate the relationship with the speed and quantity of inter-hemispheric communication.

Cerebellum and vermis Basal ganglia The basal ganglia include the caudate, putamen and globus pallidus, which are structures important for motor and emotional functions. They are connected to cortical and limbic regions by two parallel circuits, and disruption of different nodes in this circuit could result in dysregulation of affective state or mood regulation [120,121]. Larger striatal volumes (i.e. caudate and putamen) have been found in adult [53,80,122,123] and adolescent [18,99,124] bipolar patients type I, compared to healthy subjects and in bipolar twins compared to normal monozygotic twins in a small study [83]. Interestingly, duration of illness was associated with reduced volume in the lenticular nuclei (i.e. putamen and globus pallidus), particularly in bipolar disorder type I, in one study [125], but most investigations have not shown any significant differences in measures of caudate, putamen or lenticular nuclei between bipolar patients and healthy controls [57,112,114,115,125], even in adolescent patients [126]. Although conflicting, the available results suggest an important role for the basal ganglia in the pathophysiology of bipolar disorder, in particular in type I patients. Future longitudinal MRI studies should examine basal ganglia over time, in samples of bipolar I and bipolar II patients, to provide more definitive answers.

The cerebellum has extensive connections with limbic areas and cortical associative areas, supporting its role, along with the vermis, in integrating superior cognitive activities, in regulating language and in modulating mood [139–141]. Abnormally small cerebellum and vermis in bipolar patients have been shown by several [68,142–146], although not all studies [54,55,147]. In particular, those patients with higher numbers of affective episodes seem to have reduced posterior (i.e. limbic cerebellum) and flocculonodular vermis [54,142,148,149], suggesting that the cerebellar vermis may undergo atrophy during the course of bipolar illness due to neurodegenerative consequence of repeated illness episodes. However, further imaging and post-mortem studies are needed to clarify the role of cerebellum and vermis in bipolar disorder.

Conclusions Consistent structural abnormalities have been shown in bipolar disorder, particularly in anterior cingulate, hippocampus, amygdala and corpus callosum, which are all involved in mood and cognitive regulation in humans. Abnormalities in this anterior-limbic network may result in the expression of bipolar disorder by affecting inter- and

Structural Brain Imaging

intra-hemispheric connectivity. In terms of pathogenesis, it is still unclear whether neurodevelopment and neurodegeneration act separately or together in a unitary model of the disease. To this regard, there is evidence that neurodegenerative processes of anterior cingulate, SGPFC and hippocampus may take place over time, potentially in relation with multiple affective episodes. Hypothetically, excessive neuronal pruning/apoptosis during childhood and adolescence may subsequently be followed by neurotoxic mechanisms leading to impaired neuroplasticity and cellular resilience during the progression of the disease. However, current structural imaging studies in bipolar disorder have extensive heterogeneity, include underpowered sample size, and have appreciable chance of making type I and II errors, as pointed out by a couple of recent metaanalyses [51,52]. Also, other confounding variables, such as clinical status, medications and cross-sectional design, limit the available studies. Therefore, it is not yet known whether the reported structural changes reflect abnormal development, the disease process itself or medication exposure. In this perspective, to determine the role of these factors on brain anatomy, future longitudinal studies should follow large samples of first-episode drug-free bipolar patients, paediatric samples and subjects at high risk for the disease. Such studies will be instrumental to systematically examine the role of maldevelopment and neurodegeneration and to minimize potential confounding factors commonly found in adult samples, such as longterm medication effects, chronicity and hospitalizations. Furthermore, future studies should investigate the role of hormones on brain anatomy in bipolar patients, since androgen effects during puberty may have a different impact in males and females. Specifically, male patients seem to have increased vulnerability for developing DLPFC, OFC and corpus callosum deficits, which may be caused by neurotoxic processes driven by testosterone [150]. In fact, neuroprotective effects of oestrogen and progesterone, such as antioxidant action, diminishing of neuroexcitation and stabilization of cell membranes, have been shown [151,152]. Again, the longitudinal recruitment of pre-pubertal bipolar patients would be crucial to explore this issue, since hormonal brain maturation processes are particularly pronounced during adolescence. Indeed, an earlier illness onset, such as in juvenile bipolar patients, may provide a unique opportunity to investigate ongoing brain maturation and attempt to disentangle the impact of neurodevelopmental versus neurodegenerative factors in the pathophysiology of this condition. Finally, the impact of gene-environment interactions on brain development in patients with bipolar disorder remains to be clarified. In this perspective, imaging studies associated with neuropsychological, genetic and post-mortem studies will be extremely valuable to separate state from trait brain abnormalities and to further characterize the genetic/environmental determinants, the

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neuropathological underpinnings and the cognitive disturbances present in bipolar patients.

Acknowledgements Dr Brambilla was partly supported by grants from the American Psychiatric Institute for Research and Education (APIRE Young Minds in Psychiatry Award); the Italian Ministry for University and Research and the Italian Ministry of Health (IRCCS ‘E. Medea’). Dr Soares supported by NIH grants MH 068766, MH 69774, RR 020571.

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Functional Magnetic Resonance Imaging, Diffusion Tensor Imaging, and Magnetic Resonance Spectroscopy in Bipolar Disorder In Kyoon Lyoo1 and Perry F. Renshaw2 1 2

Seoul National University, Seoul, South Korea University of Utah, Salt Lake City, UT, USA

Introduction There have been fervent endeavours for more complete understanding of neurobiological underpinnings of bipolar disorder (BD), ultimately for the development of the better treatment options for this potentially disabling disorder. The technique of magnetic resonance imaging (MRI), developed by Lauterbur and Mansfield, has permitted various functional, chemical and anatomical studies of brain in BD, by enabling researchers to examine structure, function and chemistry of the live human brain. This chapter selectively focuses on the findings from studies using functional magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI) and magnetic resonance spectroscopy (MRS) in patients with BD. For these newer techniques, there have been challenges in technical and image data analytic aspects, to which some inconsistencies in the study results may have been attributed. Some of the challenges in interpreting the data are likely to stem from the variabes in medication history or medication and different clinical characteristics of BD, such as subtypes of BD and mood states at the time of scanning. In spite of these challenges, a substantial amount of studies have successfully been conducted and reported valuable findings that have greatly contributed to a better understanding of the pathophysiology of BD. Converging evidence for altered functions, white matter structure and chemistry in frontal, striatal, thalamic and limbic system of the brain in patients with BD is reviewed and presented [Brain structural changes in BD were reviewed elsewhere in this book]. Implications of these findings are also discussed in this chapter. We show part of the results in the form of tables and figures, in order to better integrate a number of findings.

Bipolar Disorder: Clinical and Neurobiological Foundations Edited by Lakshmi N. Yatham and Mario Maj © 2010 John Wiley & Sons, Ltd. ISBN: 978-0-470-72198-8

Current knowledge from prior studies using fMRI, DTI and MRS, along with future studies with more refined neuroimaging techniques, cutting-edge analytic methods and more sophisticated study designs will not only improve the understanding on the pathophysiology of BD but also contribute to more accurately comprehend the human emotion and behaviour.

Magnetic resonance spectroscopy in bipolar disorder Introduction Recent brain MRS studies have offered the potential for in vivo measurement of brain chemistry and have enhanced our understanding of the biochemical pathophysiology of BD. Hydrogen-1 ð1 HÞ and phosphorous-31 ð31 PÞ are the most widely used nuclei in the clinical application of MRS. Studies using 1 H MRS provides insight into alterations in cerebral concentrations of N-acetylaspartate (NAA), choline-containing compounds (Cho), myoinositol (mI), creatine or phosphocreatine (Cr), glutamate/ glutamine complex (Glx), and lactate in patients with BD, while studies using 31 P MRS can provide information on alterations in cerebral levels of phosphorous containing compounds, including phosphomonoester (PME), phosphodiester (PDE), phosphocreatine (PCr), inorganic phosphate, adenosine triphosphate (ATP) (Figure 1). Changes in phosphorous containing compounds are related to the changes in high-energy phosphate and phospholipid metabolism. Since a decade ago, a substantial amount of MRS studies have examined the neurochemical alterations in BD. Based on the neurochemical and the bioenergetic findings from 1 H MRS and 31 P MRS studies (Figure 2), it has been recently suggested that the mitochondrial dysfunction [1,2], as well as the abnormalities in neuronal and glial cells, play important roles in the pathophysiology of BD. 133

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Fig. 1 Sample magnetic resonance spectroscopy spectra from 31 P MRS at 2T (A) and from 1 H MRS at 3T (B). See also Plate 1. Abbreviations: ATP, adenosine tri-phosphate; MRS, Magnetic Resonance Spectroscopy; PCr, Phosphocreatine; PDE, Phosphodiesters; Pi, Inorganic Phosphate; PME, Phosphomonoesters; T, Tesla. (a) A sample 31 P spectra is shown. Reprinted from [3]. Association between cortical metabolite levels and clinical manifestations of migrainous aura: An MR-spectroscopy study. Brain;130:3102–3110, by permission of Oxford University Press. (b) A sample 1 H spectra is shown. Reprinted from [4]. Abnormal glutamatergic neurotransmission and neuronal-glial interactions in acute mania. Biol. Psych.; 64:718–726, by permission of Elsevier.

Fig. 2 Schematic presentation of the findings from cross-sectional 1 H MRS and 31 P MRS studies that show differences in brain metabolite levels between adult patients with bipolar disorder and comparison subjects. See also Plate 2. Abbreviations: Cho, Choline; Cr, Creatine; Glx, Glutamate, Glutamine and g-amino butyric acid; MRS, Magnetic Resonance Spectroscopy; NAA, N-acetylaspartate; PCr, Phosphocreatine; PME, Phosphomonoesters. Regular triangles represent higher brain metabolite levels or metabolite/Cr þ PCr ratios in patients with bipolar disorder relative to comparison subjects. Inverted triangles represent lower metabolite levels or metabolite/Cr þ PCr ratios in patients with bipolar disorder relative to comparison subjects. Rectangles represent no differences in metabolite levels or metabolite/Cr þ PCr ratios between patients with bipolar disorder and comparison subjects.

Proton (1H) MRS N-acetylaspartate (NAA)(Table 1) The resonance from NAA is the most prominent metabolite peak and occur at 2.02 parts per million (ppm) on the 1 H spectrum. The concentration of NAA is 8–10 mmol/L [38] and NAA is the second abundant amino acid in the brain

following glutamate [1]. Since NAA is mainly located in the neurons, NAA has been regarded as a neuronal marker and the reduction of cerebral NAA levels has been thought to indicate possible neuronal injury or loss [39]. Recent studies have also suggested that NAA plays an important role in cerebral osmoregulation [40,41] and that, more importantly,

Subjects

Gender (M/F)

Mean age (SD)

Patients characteristics (subtype/current episode/ medication/illness durationa)

Bertolino et al. [7]

Cecil et al. [6]

10/7

10/7

17 controls

9/12

21 controls

17 patients

6/11

9/11

17 patients

20 controls

38 (10)

40 (13)

22 (5)

22 (7)

34 (14)

4 manic or hypomanic, 7 depressed, 6 euthymic 6 medication-free for at least 2 wk not available

9 manic, 8 mixed all medicated 5 (4) 17 BD I

PRESS

all medication-free for at least 2 wk 15.0 (12.8) 17 BD I

- each voxel 0.84 cm3

Multi-slice

spin echo sequence

- hippocampus/ DLPFC/STG/ IFG/OC/ACC/ PCC/prefrontal WM/thalamus

- 8 cm3

- # NAA/Cho ratios in bilateral hippocampus

- # NAA/Cr þ PCr ratios in bilateral hippocampus

- # NAA levels in medial prefrontal8 GM

- # NAA/Cho ratios in bilateral DLPFC

- 8 cm3

- medial medial prefrontal8 GM/medial prefrontal8 WM

- # NAA/Cr þ PCr ratios in bilateral DLPFC

Results on NAA/ Cr þ PCr ratio or NAA levelsb

- bilateral DLPFC

Regions of examined/Voxel size

1.5 T

single voxel PRESS

-1.5 T

single voxel

1.5 T

Imaging methods (field strength/ technique/ acquisition)

all euthymic

Findings of reduced NAA/Cr þ PCr or NAA levels in patients with bipolar disorder Winsberg et al. [5] 20 patients 9/11 38 (14) 10 BD I/10 BD II

Study

Table 1 Published 1 H MRS research on NAA/Cr þ PCr and NAA levels in patients with bipolar disorder.

(continued)

- no association between NAA ratios and drug treatment, clinical symptoms, and hippocampal volume

- negative correlation between medial prefrontal l8 GM NAA levels and valproate treatment duration

- positive correlations between NAA/ Cr þ PCr in DLPFC and illness duration and age

Clinical correlations

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Scherk et al. [11]

Bhagwagar et al. [10]

6/7

6/7

13 controls

9/9

18 controls

13 patients

6/10

6/6

12 controls

16 patients

6/6

12 patients

20/0

20 controls

31 (6)

32 (6)

38 (14)

37 (14)

27 (8)

28 (7)

36 (11)

39 (10)

Mean age (SD)

PRESS

12 medicated 18.7 (9.5) 12 BD I

all euthymic

all euthymic all medication-free for at least 3 mo 2 (range 0.5–10.1) 13 BD I

PRESS

not available not available 16 BD I

single voxel

1.5 T

single voxel PRESS

3T

Multi-slice

all manic

1.5 T

CSI

1.5 T

Imaging methods (field strength/ technique/ acquisition)

all euthymic

15 BD I

Patients characteristics (subtype/current episode/ medication/illness durationa)

# NAA/Cr þ PCr ratio in occipital cortex

# NAA/Cho ratios in bilateral hippocampus

- # NAA/Cr þ PCr ratios in bilateral hippocampus

- # NAA levels in bilateral hippocampus

Results on NAA/ Cr þ PCr ratio or NAA levelsb

left hippocampus/ # NAA/Cr þ PCr ratio in left left thalamus/ hippocampus left putamen 3.5 cm3 (hippocampus)/

18 cm3

occipital-parietal region

each voxel 0.84 cm3

- hippocampus

- each voxel 1.1 cm3

- hippocampus

Regions of examined/Voxel size

not examined

no association between NAA ratio and clinical characteristics

- positive correlations between bilateral hippocampal NAA ratios and YMRS scores no association between NAA ratios and illness duration and hippocampal volume

- negative correlation between right hippocampal NAA levels and illness duration - no association between NAA levels and medication dose or concentrations

Clinical correlations

|

Atmaca et al. [9]

15/0

15 patients

Deicken et al. [8]

Gender (M/F)

Subjects

Study

Table 1 (Continued)

136 Chapter 14

Cecil et al. [15]

Olvera et al. [14]

Sassi et al. [13]

Chang et al. [12]

5/4

6/4

10 controls

19/15

36 controls

9 paediatric patients

17/18

9/7

18 controls

35 paediatric patients

6/8

6/5

11 controls

14 paediatric patients

13/2

15 paediatric patients

11 (2)

10 (1)

14 (3)

13 (3)

17 (4)

16 (3)

13 (3)

13 (3)

1 medicated not available

single voxel PRESS

1.5 T

PRESS

24 medicated

4.3 (3.7) 3 BD I, 3 BD II, 1 BD NOS, 2 MDD - all euthymic

single voxel

1.5 T

STEAM

single voxel

not available

1 depressed, 13 euthymic -13 medicated 3.8 (2.4) 23 BD I, 12 BD II

1.5 T

single voxel PRESS

3T

8.2 (6.5) not available

all euthymic 14 medicated not available 10 BD I, 3 BD II, 1 BD NOS

spin echo sequence

all medicated

# NAA/Cho ratio in cerebellar vermis

# NAA levels in early puberty BD patients relative to controls no difference in NAA levels between middle/ advanced puberty BD groups and controls

8 cm3

medial frontal cortex/right frontal WM/ cerebellar vermis 8 cm3

# NAA levels in left DLPFC

# NAA levels in left DLPFC

# NAA/Cr þ PCr and NAA/Cho ratios in right DLPFC

left DLPFC

8 cm3

left DLPFC

8 cm3

-bilateral DLPFC

3.4 cm3 (thalamus)/3.3 cm3 (putamen)

(continued)

not examined

negative correlation between NAA levels and YMRS scores positive correlation between NAA levels and age

no association between NAA levels and clinical characteristics

negative correlation between NAA/ Cr þ PCr ratio in right DLPFC and illness duration

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Subjects

Gender (M/F)

Mean age (SD)

Patients characteristics (subtype/current episode/ medication/illness durationa)

Michael et al. [18]

Hamakawa et al. [17]

6/2

6/2

8 controls

7/13

20 controls

8 patients

8/15

6/14

23 patients

20 controls

41 (15)

40 (14)

37 (10)

45 (11)

44 (10)

all manic 2 medicated not available

all euthymic, 8 subjects were also examined in depressive episode 4 cases medicationfree not available not available

11 and 16 examined in depressive and euthymic states, respectively (some were examined repeatedly) 4 cases medicationfree not available 15 BD I, 8 BD II

27 cm3

single voxel

15.6 cm3

single voxel

left DLPFC

3.4 cm3

1.5 T

single voxel STEAM

STEAM

bilateral frontal cortical regions

1.5 T

STEAM

-left basal ganglia

Regions of examined/Voxel size

1.5 T

Imaging methods (field strength/ technique/ acquisition)

no difference in NAA levels between groups

no difference in NAA levels between groups

no difference in NAA levels and NAA/Cr þ PCr between groups

Results on NAA/ Cr þ PCr ratio or NAA levelsb

not examined

no association between metabolite levels and medication use

-not examined

Clinical correlations

|

Findings of no alterations in NAA/Cr þ PCr or NAA levels in patients with bipolar disorder Hamakawa et al. [16] 18 patients 5/13 46 (13) 8 BD I, 10 BD II

Study

Table 1 (Continued)

138 Chapter 14

Colla et al. [22]

Frey et al. [21]

Brambilla et al. [20]

Dager et al. [19]

10/11

10/22

32 controls

21 patients

11/21

16/16

32 controls

32 patients

2/8

10/14

24 controls

10 patients

13/16

29 patients

54 (2)

34 (9)

34 (10)

35 (10)

37 (14)

32 (8)

30 (11)

7 hypomanic, 17 depressed, 1 mixed, 7 euthymic -ll medication free at least for 2 wk 10.0 (9.6) 21 BD I

3T

bilateral hippocampus

8 cm3 single voxel

PRESS

left DLPFC

STEAM

4 medication-free at least for 2 wk 15.9 (10.3) 20 BD I, 12 BD II

8 cm3

left DLFPC

frontal WM/ cingulate/ caudate/ putamen/ thalamus/ insula/parietal WM (all bilateral)/ midline occipital each voxel 1 cm3

1.5 T

single voxel

1.5 T

PEPSI

CSI

1.5 T

1 depressed, 9 euthymic

all predominantly depressed all medication-free 13.5 (10.2) 8 BD I, 2 BD II

11 BD I, 17 BD II, 1 BD NOS

no difference in NAA levels between groups

no difference in NAA levels between groups

no difference in NAA levels between groups " NAA levels in lithium-treated patients relative to unmedicated patients and controls

no difference in NAA levels in GM and WM between groups

negative correlation between NAA levels and diurnal saliva cortisol levels (continued)

no association between NAA levels and clinical characteristics

negative association between NAA/Cho ratio and prior affective episodes

no association between NAA levels and clinical symptoms

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14 (3)

12 (3)

14 (3)

19/9

17/9

28 with prodromal symptoms 26 controls

non-age matched

22/10

8/2

10 controls

8

34 (10)

32 patient

9/1

10 paediatric patients

11/10

21 controls

36 (12)

55 (2)

Mean age (SD)

28 BD patients medicated not available

not available

PRESS

all medication free at least for 1 wk not available not available

1.5 T

PRESS

single voxel

3T

single voxel

1.5 T

bilateral thalamus

8 cm3

bilateral DLPFC

8 or 27 cm3

bilateral frontal lobes/bilateral basal ganglia

8 cm3

single voxel PRESS

not available

all manic all medicated age of onset, 25.5 (9.5) not available

ACC, parietooccipital cortex

PRESS

all medicated not available 15 BD I

-12 cm3

Regions of examined/Voxel size

3T

single voxel

Imaging methods (field strength/ technique/ acquisition)

all euthymic

Patients characteristics (subtype/current episode/ medication/illness durationa)

Findings of increased NAA/Cr þ PCr or NAA levels in patients with bipolar disorder Deicken et al. [25] 15 patients 15/0 41 (11) 15 BD I

Gallelli et al. [24]

Castillo et al. [23]

7/8

9/10

19 controls

15 patients

Gender (M/F)

Subjects

" NAA levels in bilateral thalamus

no difference in NAA/Cr þ PCr ratio between groups

no difference in NAA/Cr þ PCr ratio between groups

no difference in NAA levels between groups

Results on NAA/ Cr þ PCr ratio or NAA levelsb

no association between NAA levels and clinical characteristics

no association between NAA/Cr þ PCr ratio and medication status

not examined

no association between metabolite levels and medication status

positive correlation between hippocampal NAA and glutamate levels

Clinical correlations

|

€ u € r et al. [4] Ong

Study

Table 1 (Continued)

140 Chapter 14

15/0

38 (11)

all euthymic 13 medicated 22.1 (9.7)

Silverstone et al. [28]d

Moore et al. [27]c

40 (3)

35 (2) (VPA) 31 (3)

9/5 (lithium)

5/6

(VPA)

8/10

- 14 lithium treated patients

- 11 VPA treated patients

18 controls

(lithium)

27

3/6

9 controls

36

31 (5)

5/7

6/3

12 patients

9 controls

all euthymic 14 treated with lithium 11 treated with VPA not available

7 BD I, 4 BD II (VPA)

all depressed all medication free at least for 2 wk not available 7 BD I, 7 BD II (lithium)

4 manic all BD patients treated with lithium not available 11 BD I, 1 BD II

Effects of medication on NAA/Cr þ PCr and NAA levels in patients with bipolar disorder 37 (3) 4 BD, 4 SPR, 1 MDD Sharma et al. [26] 9 patients (4 BD, 3/6 4 SPR, 1 MDD)

15 controls

PRESS

single voxel

3T

single voxel STEAM

1.5 T

single voxel STEAM

1.5 T

Multi-slice spin echo sequence

12 cm3

left temporal cortex

right frontal/left temporal/ central occipital/left parietal regions 8 cm3

15.6 cm3

basal ganglia/ occipital cortex

each voxel 1.5 cm3

" NAA/Cr þ PCr ratio in lithiumtreated patients relative to controls no difference in NAA levels between VPAtreated patients and controls

" NAA levels in all regions with 4wk lithium treatment

" NAA/Cr þ PCr ratio in basal ganglia in lithium-treated BD patients relative to controls

(continued)

not examined

not examined

not examined

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Friedman et al. [31] f 9/12

5/7

12 controls

—

—

21 patients

6/3

9 patients

7/5

12 controls

31 (6)

30 (9)

—

66 (10)

33 (11)

36 (11)

Mean age (SD)

4T

17.4 (10.4) 9 BD I

all predominantly depressed

CSI

1.5 T

single voxel PRESS, ISIS

PRESS

5 medicated

not available all treated lithium not available 8 BD I, 13 BD II

single voxel

1.5 T

Imaging methods (field strength/ technique/ acquisition)

all depressed

BD I or BD II

Patients characteristics (subtype/current episode/ medication/illness durationa)

frontal WM/ cingulate/ caudate/ putamen/ thalamus/ insula/parietal WM (all bilateral)/ midline occipital each voxel 1 cm3

-8 cm3

ACC

27 cm3

medial frontal cortex

Regions of examined/Voxel size

no changes in GM NAA levels with lithium nor VPA treatment

positive correlation between brain lithium levels and ACC NAA levels

no difference in NAA levels between groups at baseline no changes in NAA levels with 12wk lamotrigine treatment # NAA/Cr þ PCr ratios in patients with 12-wk lamotrigine treatment relative to controls

Results on NAA/ Cr þ PCr ratio or NAA levelsb

not examined

significant interaction effect between remission status and baseline NAA levels

Clinical correlations

|

Forester et al. [30] e

17/6

23 patients

Frye et al. [29]

Gender (M/F)

Subjects

Study

Table 1 (Continued)

142 Chapter 14

6/23

9/2

11 controls

28 paediatric patients

9/2

11 paediatric patients

16 (2)

age-matched

11

all depressed all medication free at least for 1 wk (19 with past history of exposure to psychotropic medication) age of onset, 11.4 (4.0)

9 manic, 2 hypomanic 9 medicated at baseline not available 28 BD I

single voxel PRESS

1.5 T

PRESS

single voxel

1.5 T

PEPSI

8 cm3

medial PFC, bilateral prefrontal WM

8 cm3

ACC

# NAA levels in medial PFC with 6-wk lithium treatment

no changes in ACC NAA/Cr þ PCr ratio with 1-wk lithium treatment

not examined

no association between metabolite ratio and serum lithium level after lithium treatment

Abbreviations: ACC, Anterior Cingulate Cortex; BD, Bipolar Disorder; Cr, Creatine; CSI, Chemical Shift Imaging; DLPFC, Dorsolateral Prefrontal Cortex; GM, Grey Matter; IFG, Inferior Frontal Gyrus; ISIS, Image Selective In vivo Spectroscopy; MDD, Major Depressive Disorder; MRS, Magnetic Resonance Spectroscopy; NAA, N-acetylaspartate; NOS, Not Otherwise Specified; PCr, Phosphocreatine; PEPSI, Proton Echo-Planar Spectroscopic Imaging; PFC, Prefrontal Cortex; PRESS, Point Resolved Spectroscopy; SPR, Schizophrenia; STEAM, Stimulated Echo Acquisition Mode; STG, Superior Temporal Gyrus; T, Tesla; VPA, Valproate; WM, White Matter; YMRS, Young Mania Rating Scale. a Years (standard deviation). b All results presented in Table 1 are those of patients with bipolar disorder relative to comparison subjects except where indicated otherwise. c Same cohort as Moore et al. [34]. d Same cohort as Silverstone et al. [35] and Wu et al. [36]. e Lithium MRS was also conducted to measure brain lithium levels. f Participants of this study was a subgroup of subjects studied at baseline in the medication-free state [19]. g Same cohort as Patel et al. [37].

Patel et al. [33]g

Davanzo et al. [32]

12 assigned to lithium treatment/9 assigned to VPA treatment not available 2 BD II, 9 BD mixed

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NAA appears to reflect mitochondrial oxidative phosphorylation [1,42]. Synthesis of NAA from acetyl coenzyme A and aspartate catalyzed by L-aspartate N-acetyl transferase occurs in the mitochondria [43]. This step is energy dependent and is closely linked to mitochondrial activity in ATP production [44]. Until recently, a number of 1 H MRS studies have reported alterations in NAA concentrations in BD patients relative to comparison subjects. Most demonstrated reduced cerebral NAA concentrations in BD patients, while a few studies did not find the alterations in NAA concentrations. Reductions in NAA levels have been observed in the dorsolateral prefrontal cortex as well as in the hippocampus of BD patients relative to comparison subjects. With Cr and PCr as a reference peak, a study by Winsberg et al. [5] demonstrated lower bilateral dorsolateral prefrontal NAA concentrations in BD patients relative to matched comparison subjects. Similarly, lower frontal grey matter NAA concentrations were reported in patients with BD [6]. The grey matter NAA concentrations in BD patients were negatively [6] correlated with the duration of valproate treatment. Reductions in bilateral hippocampal NAA levels, evaluated using 1 H magnetic resonance spectroscopic imaging (MRSI) or 1 H MRS, have been reported in euthymic and manic BD patients [7–9,11]. The lower hippocampal NAA levels were reported to correlate with longer disease duration [8]. Medication-free patients recovered from BD were also demonstrated to have reduced occipital NAA levels relative to comparison subjects [10]. Reduced NAA concentrations in the frontal cortex as well as in the hippocampus have been interpreted to reflect the decreased neuronal integrity or neuronal dysfunction in patients with BD. Based on a recent view that NAA is closely related to mitochondrial energy metabolism, the findings of decreased NAA levels in BD patients relative to comparison subjects could also be interpreted as indirect evidence for mitochondrial dysfunction in BD [1]. In contrast, Brambilla et al. [20] did not find altered dorsolateral prefrontal NAA levels in BD patients. This negative finding was attributed in part to the fact that some of the patients were treated with lithium. Colla et al. [22] reported a similar finding to that of Brambilla et al., that is, the absence of alterations in NAA levels of euthymic BD patients with the chronic lithium treatment relative to comparison subjects. It can be suggested that treatment may normalize cerebral NAA levels of BD patients. However, there have also been studies reporting no differences in NAA levels between antipsychotics- and moodstabilizers-naive and medication-free BD patients and comparison subjects [19]. A few recent studies of manic [4] and depressed [21] BD patients did not find reductions in cerebral NAA levels of BD patients. There has been only one study reporting elevated cerebral NAA levels in BD patients, who were treated with lithium

and valproate, relative to comparison subjects. In euthymic male patients with familial BD, higher NAA levels were observed in the bilateral thalamus [25]. In child and adolescent BD patients, reductions in NAA concentrations have consistently been reported in the dorsolateral prefrontal cortex [12–14] as well as in the cerebellar vermis [15], similar to the findings previously reported in adult BD patients. However, there was no difference in cerebral NAA levels between offspring of BD patients who have a high risk for BD and comparison subjects [24]. This result may suggest, at least in part, that altered NAA levels in BD may be regarded as a disease marker rather than a trait marker. Normalization of abnormally reduced NAA concentrations with treatment, particularly with lithium administration, has been reported in several 1 H MRS studies (Figure 3a). Both longitudinal and cross-sectional studies suggested that lithium treatment may increase the cerebral NAA concentrations. Moore et al. [27] reported that a four-week lithium administration to BD patients was associated with increased NAA concentrations in the frontal, temporal, parietal and occipital regions. Lithium-treated BD patients showed the higher NAA concentrations in the frontal cortex [28] as well as in the basal ganglia [26] than comparison subjects and brain lithium levels were also associated with the higher NAA concentrations [30]. However, another longitudinal study conducted by Friedman et al. [31] did not demonstrate the NAA level increase with lithium as well as valproate treatments. In a study of paediatric BD patients, there were no changes in the anterior cingulate NAA levels with lithium treatment [32]. In another study, paediatric BD patients showed the increased medial prefrontal NAA levels [33] with short-term (one week) and long-term (six weeks) lithium treatment. Characteristics of the developing brain including an ongoing developmental process of pruning should be considered in interpreting the lithium effects on the brain of children with BD. Taken together, NAA reduction in BD patients is one of the most frequently replicated findings and the potential normalization of the NAA reduction with the treatment, lithium in particular, has been reported by a number of studies (Table 1). These findings support possible neuronal and the mitochondrial involvement in the pathophysiology of BD.

Choline-containing compounds (Cho) (Table 2) The Cho resonance is detected at 3.23 ppm and one of the major components of Cho are soluble membrane phospholipid metabolites including phosphocholine (PC), and glycerophosphocholine (GPC) [49]. Free choline and acetylcholine contribute less than 5% of the signal [49]. PC is used in the synthesis of membrane phospholipids, while

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Fig. 3 Schematic presentation of the findings from longitudinal 1 H MRS studies that examine medication effects on brain metabolite levels in adult patients with bipolar disorder. See also Plate 3. Abbreviations: Cho, Choline; Cr, Creatine; Glx, Glutamate, Glutamine and g-amino butyric acid; HDRS, 17-item Hamilton Depression Rating Scale; MRS, Magnetic Resonance Spectroscopy; NAA, N-acetylaspartate. (a) Lithium effects on brain metabolite levels in patients with bipolar disorder. Regular triangles represent increase in brain metabolite levels or metabolite/Cr þ PCr ratios in patients with bipolar disorder after lithium treatment compared to those in their baseline. Inverted triangles represent decrease in brain metabolite levels or metabolite/Cr þ PCr ratios in patients with bipolar disorder after lithium treatment compared to those in their baseline. Rectangles represent no changes in metabolite levels or metabolite/Cr þ PCr ratios in patients with bipolar disorder after lithium treatment. (b) Cytidine effect on brain metabolite levels and depressive symptoms in depressed patients with bipolar disorder. Bars represent estimated glutamate/glutamine changes from baseline in cytidine and placebo add-on patients with bipolar depression. P values above the bars indicate significant difference between treatment groups in rates of decreasing glutamate/glutamine levels throughout the treatment period with mixed-effect regression model. Squares and trend lines represent the estimated HDRS score in cytidine and placebo add-on patients with bipolar depression. Asterisks represent p < 0.01 significant difference between treatment groups in rates of improvement in HDRS scores from Week 1 through Week 4 with mixed-effect regression model. (Reprinted from Yoon et al., in press. Decreased glutamate/glutamine levels may mediate cytidine’s efficacy in treating bipolar depression: A longitudinal proton magnetic resonance spectroscopy study. Neuropsychopharmacology, with permission from Nature Publishing Group).

GPC is the product of degradation of membrane phospholipids [50]. Cho is required for the synthesis of the neurotransmitter acetylcholine and phosphatidylcholine, the key component of the phospholipid membrane [1]. Since acetylcholine is produced only in cholinergic neurons and the synthesis of phosphatidylcholine occurs within all cells, altered Cho signal is likely to primarily reflect the changes in phospholipid membrane metabolism [51]. Elevated cerebral Cho concentrations have frequently been reported in the 1 H MRS studies of BD. Moore et al. [45] reported that BD patients exhibited the higher Cho/Cr þ PCr ratios in the cingulate cortex than comparison subjects. Altered Cho/Cr þ PCr ratios were correlated with more severe depressive symptoms. They also investigated medication effects on cerebral Cho levels. BD patients taking antidepressant medications, but not lithium or valproate, showed reductions of Cho/Cr þ PCr ratios to the level comparable to that observed in comparison subjects. Higher Cho concentrations or Cho/Cr þ PCr ratios in BD patients relative to comparison subjects were also

observed in the basal ganglia [16,46]. In contrast, reduced frontal Cho signals were also reported in medication-free BD patients [21]. Several 1 H MRS studies examining the dorsolateral prefrontal cortex and hippocampus did not find any altered Cho levels in BD patients relative to comparison subjects [4,5,7–9,11,20,22]. Until recently, only a few 1 H MRS studies have examined the effects of medication, especially lithium, on Cho signals in BD patients. Most of the studies suggest that lithium treatment may not alter cerebral Cho levels [30,31,46,48]. However, one study suggested that chronic lithium treatment was associated with a reduction in Cho levels [36], while another study reported that BD patients treated with lithium had a higher Cho/Cr þ PCr ratio relative to comparison subjects [26]. Stoll et al. [52] examined the efficacy of choline treatment and its effects on brain metabolite levels in six treatmentrefractory patients with rapid-cycling BD. Interestingly, choline, in the presence of lithium, exerted a successful treatment efficacy and increased Cho levels in the basal ganglia. In a double-blind trial of eight lithium-treated

Subjects

Gender (M/F)

Moore et al. [45]

Hamakawa et al. [16]

5/13

6/14

5/4

6/8

20 controls

9 patientsc

14 controls

5/14

18 patients

19 controls

36 (11)

38 (10)

44 (10)

46 (13)

40 (6)

42 (10)

Mean age (SD)

predominantly depressed all mediated not available

11 and 16 examined in depressive and euthymic states, respectively (some examined repeatedly) 4 cases medication-free not available 9 BD I

STEAM

CSI

1.5 T

STEAM

each voxel 2 cm3

bilateral ACC

27 cm3

single voxel

" Cho/Cr þ PCr ratio in right ACC

" Cho levels in basal ganglia in BD patients with depressive episode " Cho/Cr þ PCr and Cho/NAA ratios in basal ganglia in BD patients with depressive or euthymic episodes

no difference in Cho/Cr þ PCr ratio between lithium-treated and non-treated patients

27 cm3

left basal ganglia

STEAM

10 treated with lithium age of onset, 31.7 8 BD I, 10 BD II

" Cho/Cr þ PCr ratio in basal ganglia

Results Cho/Cr þ Pcr or Cho levelsb

left basal ganglia

Regions of examined/ Voxel size

1.5 T

single voxel

1.5 T

Imaging methods (field strength/ technique/ acquisition)

all euthymic

10 BD I, 9 BD II

Patients characteristics (subtype/current episode/medication/ illness durationa)

positive correlation between Cho/Cr þ PCr ratio and HDRS scores

not examined

no association between Cho/Cr þ PCr ratio and age

Clinical correlations

|

Studies on the adult patients with bipolar disorder Kato et al. [46] 19 patients 5/14

Study

Table 2 Published 1 H MRS research on Cho/Cr þ PCr and Cho levels in patients with bipolar disorder.

146 Chapter 14

Deicken et al. [25]

Winsberg et al. [5]

Hamakawa et al. [17]

Frey et al. [21]

Cecil et al. [6]

15/0

9/11

20 controls

15 patients

9/11

7/13

20 controls

20 patients

8/15

10/22

32 controls

23 patients

11/21

9/12

21 controls

32 patients

6/11

17 patients

41 (11)

34 (14)

38 (14)

37 (10)

45 (11)

34 (9)

34 (10)

22 (5)

22 (7)

all euthymic all medication-free for at least 2 wk 15.0 (12.8) 15 BD I

all euthymic, 8 subjects were also examined in depressive episode 4 cases medication-free not available 10 BD I/10 BD II

7 hypomanic, 17 depressed, 1 mixed, 7 euthymic all medication free at least for 2 wk 10.0 (9.6) 15 BD I, 8 BD II

9 manic, 8 mixed all medicated 5 (4) 20 BD I, 12 BD II

17 BD I

8 cm3

single voxel

-15.6 cm3 single voxel

bilateral thalamus

8 cm3 single voxel PRESS

1.5 T

bilateral DLPFC

1.5 T

STEAM

bilateral frontal cortical regions

-1.5 T

PRESS

left DLPFC

8 cm3

medial prefrontal GM/medial prefrontal WM

1.5 T

single voxel PRESS

1.5 T

no difference in Cho levels between groups

no difference in Cho/ Cr þ PCr ratios between groups

no difference in Cho levels between groups

# Cho levels in DLPFC

# Cho levels in medial prefrontal GM

no association between Cho levels and clinical characteristics (continued)

not examined

no association between metabolite levels and medication use

no association between Cho levels and clinical characteristics

positive correlation between WM Cho levels and YMRS scores

Functional Imaging Techniques

| 147

Michael et al. [18]

Deicken et al. [8]

6/2

6/2

8 controls

20/0

20 controls

8 patients

15/0

10/7

17 controls

15 patients

10/7

15/0

15 controls

17 patients

Gender (M/F)

Subjects

41 (15)

40 (14)

36 (11)

39 (10)

38 (10)

40 (13)

38 (11)

Mean age (SD)

all manic 2 medicated not available

left DLPFC

3.4 cm3 single voxel STEAM

PRESS

12 medicated 18.7 (9.5) not available

each voxel 1.1 cm3

hippocampus

hippocampus/ DLPFC/STG/ IFG/OC/ ACC/PCC/ prefrontal WM/ thalamus

each voxel 1.5 cm3

Regions of examined/ Voxel size

1.5 T

CSI

1.5 T

- spin echo sequence

CSI

all euthymic

4 manic or hypomanic, 7 depressed, 6 euthymic 6 medication-free for at least 2 wk not available 15 BD I

1.5 T

spin echo sequence

13 medicated 22.1 (9.7) 17 BD I

Multi-slice

Imaging methods (field strength/ technique/ acquisition)

all euthymic

Patients characteristics (subtype/current episode/medication/ illness durationa)

no difference in Cho levels between groups

no difference in hippocampal Cho levels between groups

no difference in hippocampal Cho/ Cr þ PCr ratios between groups

Results Cho/Cr þ Pcr or Cho levelsb

not examined

not examined

not examined

Clinical correlations

|

Bertolino et al. [7]

Study

Table 2 (Continued)

148 Chapter 14

Scherk et al. [11]

Atmaca et al. [9]

Brambilla et al. [20]

Dager et al. [19]

6/7

6/7

13 controls

6/6

12 controls

13 patients

6/6

16/16

32 controls

12 patients

2/8

10/14

24 controls

10 patients

13/16

29 patients

31 (6)

32 (6)

27 (8)

28 (7)

35 (10)

37 (14)

32 (8)

30 (11)

all euthymic

PRESS

not available not available 13 BD I

single voxel

1.5 T

CSI

1.5 T

single voxel STEAM

1.5 T

PEPSI

CSI

1.5 T

all manic

1 depressed, 9 euthymic 4 medication-free at least for 2 wk 15.9 (10.3) 12 BD I

all predominantly depressed all medication-free 13.5 (10.2) 8 BD I, 2 BD II

11 BD I, 17 BD II, 1 BD NOS

3.5 cm3 (hippocampus)/

left

each voxel 0.84 cm3

hippocampus

8 cm3

left DLFPC

frontal WM/ cingulate/ caudate/ putamen/ thalamus/ insula/ parietal WM (all bilateral)/ midline occipital each voxel 1 cm3

hippocampus/left thalamus/left putamen

no difference in hippocampal Cho/ Cr þ PCr ratios between groups

no difference in Cho levels between groups

no difference in Cho levels in GM and WM between groups

(continued)

no difference in hippocampal Cho/Cr þ PCr ratios between groups

not examined

negative correlation between Cho levels and number of prior affective episodes

no association between Cho levels and clinical symptoms

Functional Imaging Techniques

| 149

11/10

21 controls

34 (10)

36 (12)

55 (2)

Davanzo et al. [47]

non12 (4) gender matched

13 controls

10 (2)

13 (3)

8/2

6/5

10 patients

11 controls

Studies on the adolescents or children with bipolar disorder Chang et al. [12] 15 patients 13/2 13 (3)

7/8

15 patients

9/10

19 controls

54 (2)

Mean age (SD)

PRESS

5 medicated not available

medial frontal cortex/ occipital cortex 8 cm3

1.5 T

single voxel

-8 cm3 single voxel PRESS

bilateral DLPFC

8 cm3

single voxel PRESS

3T

ACC, parietooccipital cortex

12 cm3

bilateral hippocampus

3.4 cm3 (thalamus)/ 3.3 cm3 (putamen)

Regions of examined/ Voxel size

3T

single voxel PRESS

7 manic, 3 mixed

all euthymic 14 medicated not available 10 BD I

not available

all manic all medicated age of onset, 25.5 (9.5)

all euthymic all medicated not available 15 BD I

3T

spin echo sequence

all medicated

8.2 (6.5) 21 BD I

Imaging methods (field strength/ technique/ acquisition)

Patients characteristics (subtype/current episode/medication/ illness durationa)

no difference in Cho levels between groups

no difference in Cho/ Cr þ PCr ratio between groups

no difference in Cho levels between groups

no difference in Cho levels between groups

Results Cho/Cr þ Pcr or Cho levelsb

not examined

not examined

no association between metabolite levels and medication status

not examined

Clinical correlations

|

€ u € r et al. [4] Ong

10/11

21 patients

Colla et al. [22]

Gender (M/F)

Subjects

Study

Table 2 (Continued)

150 Chapter 14

Cecil et al. [15]

Castillo et al. [23]

Olvera et al. [14]

Gallelli et al. [24]

Sassi et al. [13]

5/4

6/4

10 controls

8/2

10 controls

9 patients

9/1

10 patients

19/15

36 controls

11 (2)

10 (1)

non-age matched

8

14 (3)

13 (3)

14 (3)

17/9

17/18

12 (3)

19/9

28 with prodromal symptoms 26 controls

35 patients

14 (3)

17 (4)

22/10

9/7

18 controls

16 (3)

32 patient

6/8

14 patients

1 medicated not available

PRESS

all medication free at least for 1 wk not available 3 BD I, 3 BD II, 1 BD NOS, 2 MDD - all euthymic

single voxel PRESS

1.5 T

single voxel

medial frontal cortex/right frontal WM/ cerebellar vermis 8 cm3

bilateral frontal lobes/ bilateral basal ganglia 8 or 27 cm3

8 cm3

single voxel PRESS 1.5 T

left DLPFC

8 cm3

bilateral DLPFC

8 cm3

left DLPFC

1.5 T

PRESS

single voxel

3T

STEAM

single voxel

1.5 T

not available

not available 24 medicated 4.3 (3.7) not available

28 BD patients medicated not available 23 BD I, 12 BD II

not available

1 depressed, 13 euthymic 13 medicated 3.8 (2.4) not available

10 BD I, 3 BD II, 1 BD NOS

no difference in Cho levels between groups

no difference in Cho/ Cr þ PCr ratio between groups

no difference in Cho levels between groups

-no difference in Cho/ Cr þ PCr ratio between groups

no difference in Cho levels between groups

(continued)

not examined

not examined

not examined

not examined

negative correlation between Cho levels and number of prior affective episodes

Functional Imaging Techniques

| 151

Subjects

Gender (M/F) Mean age (SD)

Wu et al. [36] d

Stoll et al. [48]

35 (3) (VPA) 31 (3)

(VPA) 8/10

(lithium)

5/6

- 11 VPA treated patients

18 controls

40 (3)

32 (6)

9/5 (lithium)

6/0

6 controls

34 (9)

31 (5)

- 14 lithium treated patients

7/0

6/3

7 patients

9 controls

Effects of medication on Cho/Cr þ PCr and Cho levels 3/6 37 (3) Sharma et al. [26] 9 patients (4 BD, 4 SPR, 1 MDD)

Study

all euthymic 14 treated with lithium 11 treated with VPA not available

7 BD I, 4 BD II (VPA)

all euthymic all treated with lithium not available 7 BD I, 7 BD II (lithium)

4 manic all BD patients treated with lithium not available not available

4 BD, 4 SPR, 1 MDD

Patients characteristics (subtype/current episode/medication/ illness durationa)

PRESS

single voxel

3T

single voxel STEAM

1.5 T

single voxel STEAM

1.5 T

Imaging methods (field strength/ technique/ acquisition)

12 cm3

left temporal cortex

27 cm3

parietal cortex

15.6 cm3

basal ganglia/ occipital cortex

Regions of examined/ Voxel size

# Cho/Cr þ PCr ration in lithium/VPAtreated patients relative to controls

no difference in Cho/ Cr þ PCr ratio between lithiumtreated patients and controls

" Cho/Cr þ PCr ratio in basal ganglia in lithium-treated BD patients relative to controls

Results Cho/Cr þ Pcr or Cho levelsb

not examined

not examined

not examined

Clinical correlations

|

Table 2 (Continued)

152 Chapter 14

Davanzo et al. [32]

Forester et al. [30] f

Frye et al. [29]

Friedman et al. [31] e

9/2

—

—

11 controls

6/3

9 patients

9/2

7/5

12 controls

11 paediatric patients

17/6

5/7

12 controls

23 patients

9/12

21 patients

agematched

11

—

66 (10)

33 (11)

36 (11)

31 (6)

30 (9)

9 manic, 2 hypomanic 9 medicated at baseline not available

not available all treated lithium not available 2 BD II, 9 BD mixed

single voxel PRESS

1.5 T

single voxel PRESS, ISIS

8 cm3

ACC

8 cm3

ACC

PRESS

5 medicated 17.4 (10.4) 9 BD I 4T

27 cm3

single voxel

all depressed

frontal WM/ cingulate/ caudate/ putamen/ thalamus/ insula/ parietal WM (all bilateral)/ midline occipital each voxel 1 cm3

medial frontal cortex

PEPSI

CSI

1.5 T

1.5 T

all predominantly depressed 12 assigned to lithium treatment/9 assigned to VPA treatment not available BD I or BD II

8 BD I, 13 BD II

no changes in ACC Cho/ Cr þ PCr ratio with 1-wk lithium treatment

no association between brain lithium levels and ACC Cho levels

no difference in Cho levels between groups at baseline no changes in Cho levels with 12-wk lamotrigine treatment

no changes in GM Cho levels with lithium nor VPA treatment

(continued)

no association between metabolite ratio and serum lithium level after lithium treatment

not examined

not examined

Functional Imaging Techniques

| 153

—

—

—

16 (2)

Mean age (SD)

all depressed all medication free at least for 1 wk (19 with past history of exposure to psychotropic medication) -age of onset, 11.4 (4.0)

28 BD I

Patients characteristics (subtype/current episode/medication/ illness durationa)

single voxel PRESS

1.5 T

Imaging methods (field strength/ technique/ acquisition) medial PFC, bilateral prefrontal WM 8 cm3

Regions of examined/ Voxel size

Clinical correlations

not examined

Results Cho/Cr þ Pcr or Cho levelsb

no changes in Cho levels with 6-wk lithium treatment

Abbreviations: ACC, Anterior Cingulate Cortex; BD, Bipolar Disorder; Cho, Choline-containing compounds; Cr, Creatine; CSI, Chemical Shift Imaging; DLPFC, Dorsolateral Prefrontal Cortex; GM, Grey Matter; HDRS, Hamilton Depression Ration Scale; IFG, Inferior Frontal Gyrus; ISIS, Image Selective In vivo Spectroscopy; MDD, Major Depressive Disorder; MRS, Magnetic Resonance Spectroscopy; NAA, N-acetylaspartate; NOS, Not Otherwise Specified; OC, Occipital Cortex; PCC, Posterior Cingulate Cortex; PCr, Phosphocreatine; PEPSI, Proton Echo-Planar Spectroscopic Imaging; PRESS, Point Resolved Spectroscopy; SPR, Schizophrenia; STEAM, Stimulated Echo Acquisition Mode; STG, Superior Temporal Gyrus; T, Tesla; VPA, Valproate; WM, White Matter; YMRS, Young Mania Rating Scale. a Years (SD). b All results presented in Table 2 are those of patients with bipolar disorder relative to comparison subjects except where indicated otherwise. c Serial MRSI assessments (27 occasions) were performed in 9 BD patients. d Same cohort as Silverstone et al. [35] and Silverstone et al. [28]. e Participants of this study was a subgroup of subjects studied at baseline in the medication-free state [19]. f Lithium MRS was also conducted to measure brain lithium levels.

6/23

28 paediatric patients

Patel et al. [37]

Gender (M/F)

Subjects

Study

|

Table 2 (Continued)

154 Chapter 14

Functional Imaging Techniques

patients with rapid-cycling BD, Lyoo et al. [53] did not confirm the superior efficacy of choline treatment to the placebo administration. However, purine levels in the basal ganglia, measured by 1 H MRS, decreased with 12-week oral choline administration. This potentially means that exogenous choline administration may exert a beneficial effect on the mitochondrial function in BD through increased phospholipid synthesis. In child and adolescent BD patients, many of 1 H MRS studies did not find alterations in Cho levels relative to comparison subjects [12–14,23,47]. A number of, if not all, studies have reported the altered Cho levels in BD patients, which may reflect the impaired phospholipid metabolism in BD patients. However, this finding, observed in adult patients remains to be tested in paediatric BD patients and the potential treatment effects on Cho levels should be confirmed in the future studies.

Myo-inositol (mI) (Table 3) The primary resonance of mI lies at 3.56 ppm. Since mI is largely presented in glial cells, it has been suggested as a glial cell marker [54]. In addition, mI exerts its role as an osmolite and a storage form for glucose [55]. Most importantly, mI functions as a precursor to the phosphatidylinositol, which is a component of phospholipid membranes, as well as a substrate for the phosphoinositide secondmessenger system [39,56]. This potentially indicates that altered mI levels may be associated with the abnormal phospholipid metabolism and intracellular signalling systems. Since lithium has been recognized to exert its actions on the phosphoinositide system as a potent, noncompetitive inhibitor of inositol-1-phosphotase [57,58], several 1 H MRS studies to date have focused on the effects of lithium treatment on cerebral mI levels. Also, a substantial amount of preclinical evidence has suggested that the depletion of inositol pool might be the underlying mechanisms through which lithium works in patients with BD [57,58]. Moore et al. [34] reported that short-term as well as longterm administration of lithium decreased the frontal mI levels by about 30% in BD patients in their longitudinal follow-up study. This lithium treatment effect on mI levels was also observed in children with BD. Davanzo et al. [47] found higher prefrontal mI levels in paediatric BD patients than patients with intermittent explosive disorder as well as comparison subjects. A later longitudinal study by the same research group [32] reported that only seven days of lithium administration was required to bring reductions of the frontal cerebral mI levels in 11 children and adolescents with BD. In a study using 1 H MRS and 31 P MRS, Silverstone et al. [35] found that there were no differences in mI as well as PME levels between lithium-treated BD patients and comparison subjects. They explained this negative finding

|

155

as a potential normalization of pathophysiological alteration of the phosphoinositide cycle in BD patients treated with lithium. However, some 1 H MRS studies [26,30] reported opposite results, where BD patients treated with lithium had a greater mI levels than in comparison subjects. Similarly, a longitudinal follow-up study using 1 H MRSI to evaluate medication-free BD patients also reported increased mI levels with lithium treatment for over three months [31]. More recently, a six-week 1 H MRS study of adolescent BD patients did not find any alterations in the prefrontal mI levels after short-term (seven days) as well as long-term (42 days) lithium treatments [37]. It is challenging to explain and interpret the findings of opposite directions in increased, decreased, even unchanged mI concentrations with lithium treatment measured by 1 H MRS in BD patients. Lithium inhibits inositol-1-phosphotase may result in the accumulation of inositol monophosphates and at the same time the depletion of the inositol pool. Other literature suggests that long-term lithium treatment may increase the inositol-1-phosphotase activity [59–61], which would result in increase of the inositol pool. It should also be considered that mI resonance in 1 H MRS is the sum of mI and inositol monophosphates. Separate measurement of mI and inositol monophosphates, using both 31 P MRS and 1 H MRS, respectively, would be necessary to further examine the lithium effects on the phospholipid metabolism and the intracellular signalling systems. Please also see the following section on the results of 31 P MRS studies in BD for relevant issues.

Glutamate/glutamine/gamma-aminobutyric acid (GABA)(Glutamix, Glx) (Table 4) A mixture of closely related amino acids, including glutamate, glutamine and GABA, resonates between 2.1 and 2.4 ppm [39]. At low field strength, this overlapped resonance of Glx is hard to resolve separately [39]. Since the glutamate and glutamine may predominantly contribute to the Glx signal, this resonance has often been assumed to reflect alterations in the glutamate/glutamine cycle [1]. Until recently, several 1 H MRS studies have reported elevated Glx level in BD patients relative to comparison subjects. Dager et al. [19] studied 32 medication-free patients with BD using 1 H MRSI. Medication-free BD patients, mainly depressed, demonstrated elevated Glx and lactate levels in the cerebral grey matter relative to comparison subjects. Patients with acute mania also showed higher Glx/Cr þ PCr ratio and Glx levels in the prefrontal and parieto-occipital cortices relative to comparison subjects [4,18] and this was less likely to be due to medication effects [4]. Similarly, occipital glutamate þ glutamine/ Cr þ PCr ratios were higher in unmedicated recovered BD patients than in comparison subjects [10]. Colla et al. [22]

Sharma et al. [26]

Silverstone et al. [35] c

Davanzo et al. [32]

43 (3)

(lithium) 37 (3) (VPA) 31 (3) 37 (3)

10/6

(lithium) 5/6 (VPA) 9/10 3/6

- 16 lithium treated patients

- 11 VPA treated patients

9 patients (4 BD, 4 SPR, 1 MDD)

19 controls

age-matched

9/2

11 controls

11

9/2

11 paediatric patients

3/6

27

Mean age (SD)

9 controls

Gender (M/F)

36

Subjects

all euthymic 16 treated with lithium 11 treated with VPA - not available 4 BD, 4 SPR, 1 MDD

7 BD I, 4 BD II (VPA)

9 manic, 2 hypomanic 9 medicated at baseline not available 8 BD I, 8 BD II (lithium)

all depressed all medication free at least for 2 wk not available 2 BD II, 9 BD mixed

11 BD I, 1 BD II

Patients characteristics (subtype/current episode/medication/ illness durationa)

1.5 T

- basal ganglia/ occipital cortex

12 cm3 single voxel PRESS

left temporal cortex

8 cm3

ACC

right frontal/left temporal/ central occipital/left parietal regions 8 cm3

Regions of examined/ Voxel size

3.0 T

single voxel PRESS

1.5 T

single voxel STEAM

1.5 T

Imaging methods (field strength/ technique/ acquisition)

" mI/Cr þ PCr ratio in basal ganglia in lithiumtreated BD patients relative to controls

no difference in mI/Cr þ PCr ratio between three groups

# mI/Cr þ PCr ratio in ACC with 1-wk lithium treatment

# mI level in frontal region with 4-wk lithium treatment

Resultsb

not examined

not examined

no association between metabolite ratio and serum lithium level after lithium treatment

not examined

Clinical correlations

|

Effects of medication on mI/Cr þ PCr and mI levels Moore et al. [34] 12 patients 5/7

Study

Table 3 Published 1 H MRS research on mI/Cr þ PCr and mI levels in patients with bipolar disorder.

156 Chapter 14

Patel et al. [37]

Forester et al. [30] e

Friedman et al. [31] d

28 paediatric patients

6/23

—

—

5/7

12 controls

6/3

9/12

21 patients

9 patients

6/3

9 controls

16 (2)

—

66 (10)

31 (6)

30 (9)

31 (5)

not available all treated lithium not available 28 BD I

all predominantly depressed 12 assigned to lithium treatment/9 assigned to VPA treatment not available 9 BD I

4 manic all BD patients treated with lithium not available 8 BD I, 13 BD II

1.5 T

single voxel PRESS, ISIS

4T

PEPSI

CSI

1.5 T

single voxel STEAM

medial PFC, bilateral prefrontal WM

8 cm3

ACC

frontal WM/ cingulate/ caudate/ putamen/ thalamus/ insula/ parietal WM (all bilateral)/ midline occipital each voxel 1 cm3

15.6 cm3

significant changes in mI levels of medial PFC and right prefrontal WM with 6-wk lithium treatment

positive correlation between brain lithium levels and ACC mI levels

" GM mI levels with lithium treatment relative to VPA treatment or measurement error (follow-up of controls)

(continued)

positive correlation between changes in medial PFC mI levels from 1–6wk and changes in CDRS-R scores during same period

not examined

Functional Imaging Techniques

| 157

Gender (M/F)

—

Subjects

—

—

Mean age (SD)

single voxel

PRESS

all medication free at least for 1 wk (19 with past history of exposure to psychotropic medication) age of onset, 11.4 (4.0)

Imaging methods (field strength/ technique/ acquisition)

all depressed

Patients characteristics (subtype/current episode/medication/ illness durationa) 8 cm3

Regions of examined/ Voxel size

" mI levels on 6-wk treatment relative to those on 1-wk treatment

Resultsb

no association between mI levels and serum lithium levels

Clinical correlations

Abbreviations: ACC, Anterior Cingulate Cortex; BD, Bipolar Disorder; CDRS-R, Children’s Depression Rating Scale-Revised; Cr, Creatine; CSI, Chemical Shift Imaging; Glx, Glutamate and Glutamine; GM, Grey Matter; ISIS, Image Selective In vivo Spectroscopy; MDD, Major Depressive Disorder; mI, myo-Inositol; MRS, Magnetic Resonance Spectroscopy; PCr, Phosphocreatine; PEPSI, Proton Echo-Planar Spectroscopic Imaging; PFC, Prefrontal Cortex; PRESS, Point Resolved Spectroscopy; SPR, Schizophrenia; STEAM, Stimulated Echo Acquisition Mode; T, Tesla; VPA, Valproate; WM, White Matter. a Years (SD). b All results presented in Table 3 are those of patients with bipolar disorder relative to comparison subjects except where indicated otherwise. c Same cohort as Silverstone et al. [28] and Wu et al. [36]. d Participants of this study was a subgroup of subjects studied at baseline in the medication-free state [19]. e Lithium MRS was also conducted to measure brain lithium levels.

Study

|

Table 3 (Continued)

158 Chapter 14

Bhagwagar et al. [10]

Dager et al. [19]

Michael et al. [18]

6/10

9/9

18 controls

10/14

24 controls

16 patients

13/16

6/2

8 controls

29 patients

6/2

8 patients

9/12

38 (14)

37 (14)

32 (8)

30 (11)

41 (15)

40 (14)

22 (5)

Mean age (SD)a

21 controls

Gender (M/F)

22 (7)

Subjects

Studies on the adults patients with bipolar disorder Cecil et al. [6] 17 patients 6/11

Study

all euthymic

all predominantly depressed all medication-free 13.5 (10.2) 16 BD I

all manic 2 medicated not available 11 BD I, 17 BD II, 1 BD NOS

9 manic, 8 mixed all medicated 5 (4) not available

17 BD I

Patients characteristics (subtype/current episode/medication/ illness durationa)

single voxel

3T

PEPSI

CSI

1.5 T

single voxel STEAM

1.5 T

single voxel PRESS

1.5 T

Imaging methods (field strength/ technique/ acquisition)

Table 4 Published 1 H MRS research on Glx/Cr þ PCr and Glx levels in patients with bipolar disorder.

" Glx/Cr þ PCr ratio in occipital cortex

# GABA/Cr þ PCr ratio in occipital cortex

18 cm3

" lactate levels in GM

" Glx levels in GM

" Glx levels in left DLPFC

" Composite amino acid signal in medial prefrontal WM

Results on Glx/ Cr þ PCr ratio or Glx levelsb

occipital-parietal region

frontal WM/ cingulate/ caudate/ putamen/ thalamus/insula/ parietal WM (all bilateral)/ midline occipital each voxel 1 cm3

3.4 cm3

left DLPFC

8 cm3

medial prefrontal GM/medial prefrontal WM

Regions of examined/Voxel size

(continued)

no association between Glx or GABA ratios and clinical characteristics

no association between Glx or lactate levels and clinical symptoms

not examined

negative correlation between orbitofrontal WM AA levels and valproate treatment duration

Clinical correlations

Functional Imaging Techniques

| 159

Frey et al. [21]

11/21

10/22

32 controls

9/10

19 controls

32 patients

10/11

21 patients

11/10

21 controls

34 (9)

34 (10)

55 (2)

54 (2)

34 (10)

36 (12)

Mean age (SD)a

7 hypomanic, 17 depressed, 1 mixed, 7 euthymic all medication free at least for 2 wk 10.0 (9.6)

PRESS

all medicated not available 20 BD I, 12 BD II

PRESS

single voxel

1.5 T

single voxel

3T

single voxel PRESS

all euthymic

all manic all medicated age of onset, 25.5 (9.5) 21 BD I

PRESS

all medication-free for at least 3 mo 2 (range 0.5 to 10.1) 15 BD I 3T

Imaging methods (field strength/ technique/ acquisition)

Patients characteristics (subtype/current episode/medication/ illness durationa)

8 cm3

left DLPFC

12 cm3

bilateral hippocampus

8 cm3

ACC, parietooccipital cortex

Regions of examined/Voxel size

no difference in Glx levels between groups

" glutamate levels in bilateral hippocampus

" Glutamine/ glutamate ratio in ACC and parietooccipital regions

Results on Glx/ Cr þ PCr ratio or Glx levelsb

no association between Glx levels and clinical characteristics

negative correlation between glutamate levels and diurnal saliva cortisol levels positive correlation between hippocampal NAA and glutamate levels

no association between metabolite levels and medication status

Clinical correlations

|

Colla et al. [22]

7/8

15 patients

€ u € r et al. [4] Ong

Gender (M/F)

Subjects

Study

Table 4 (Continued)

160 Chapter 14

Olvera et al. [14]

Moore et al. [62]

Davanzo et al. [47]

17/18

19/15

35 patients

36 controls

15 ADHD 7 controls

not available

non-gender matched

13 controls

8 ADHD þ BD

8/2

8/2

10 patients

10 controls

14 (3)

13 (3)

6 to 13 yr old

12 (4)

10 (2)

non-age matched

Studies on the adolescents or children with bipolar disorder Castillo et al. [23] 10 patients 9/1 8

PRESS

all medication free at least for 1 wk not available 10 BD I

not available 24 medicated 4.3 (3.7)

not available 3 ADHD medicated 2 ADHD þ BD medicated not available 23 BD I, 12 BD II

PRESS

5 medicated not available not available

single voxel PRESS

1.5 T

single voxel PRESS

1.5 T

single voxel

7 manic, 3 mixed

1.5 T

single voxel

1.5 T

not available

not available

8 cm3

left DLPFC

4.8 cm3

ACC

8 cm3

medial frontal cortex/occipital cortex

8 or 27 cm3

bilateral frontal lobes/bilateral basal ganglia

no difference in Glx levels between groups

# ACC Glx/ Cr þ PCr and Glx/mI ratios in BD patients relative to ADHD þ BD patients

no difference in Glx levels between groups

" Glx/Cr þ PCr ratio in bilateral frontal lobe and basal ganglia

(continued)

not examined

not examined

not examined

not examined

Functional Imaging Techniques

| 161

Frye et al. [29]

17/6

7/5

23 patients

12 controls

5/7

33 (11)

36 (11)

31 (6)

Mean age (SD)a

12 controls

Gender (M/F)

30 (9)

Subjects

all depressed

PEPSI

12 assigned to lithium treatment/9 assigned to VPA treatment not available BD I or BD II

single voxel

1.5 T

CSI

-1.5 T

Imaging methods (field strength/ technique/ acquisition)

all predominantly depressed

8 BD I, 13 BD II

Patients characteristics (subtype/current episode/medication/ illness durationa)

27 cm3

medial frontal cortex

frontal WM/ cingulate/ caudate/ putamen/ thalamus/insula/ parietal WM (all bilateral)/ midline occipital each voxel 1 cm3

Regions of examined/Voxel size

" Glx and glutamate levels at baseline " Glx and glutamate levels in nonmelancholic depressed patients relative to melancholic subjects

# GM Glx levels with lithium treatment relative to VPA treatment or measurement error (followup of controls) no changes in GM lactate levels with lithium nor VPA treatment

Results on Glx/ Cr þ PCr ratio or Glx levelsb

not examined

Clinical correlations

|

Effects of medication on Glx/Cr þ PCr and Glx levels 21 patients 9/12 Friedman et al. [31] c

Study

Table 4 (Continued)

162 Chapter 14

Moore et al. [64]

Moore et al. [63]

—

—

11 (3)

(unmedicated)

8 atypical antipsychotics treated (unmedicated) 10 unmedicated — not available

(antipsychotic 12 manic treated)

5/5

PRESS

CSI

each voxel 4.8cm3

ACC

PRESS

7 unmedicated, 15 medicated not available 18 BD I 1.5 T

8 cm3

single voxel

10 manic, 9 mixed, 1 depressed, 2 euthymic

(8 atypical antipsychotics treated/10 unmedicated)

12 (3)

ACC

4.0 T

17.4 (10.4) 22 BD I

11 (3) 7/1 (antipsychotic treated)

3/10

10 controls

13 (4)

18 paediatric patients

9/13

22 paediatric patients

PRESS

5 medicated

" Glx/Cr þ PCr ratios in patients treated with atypical antipsychotics relative to unmedicated patients

" glutamine levels in medicated patients relative to unmedicated patients no significance difference in glutamate levels between unmedicated and medicated patients

# glutamine levels in remitted patients with 12-wk lamotrigine treatment relative to nonremitted subjects

(continued)

negative correlations between ACC Glx/Cr þ PCr ratios and YMRS/ CGI-mania scores

Trend in negative correlations between ACC glutamate levels and CDRS scores

Functional Imaging Techniques

| 163

—

—

—

16 (2)

—

all depressed all medication free at least for 1 wk (19 with past history of exposure to psychotropic medication) age of onset, 11.4 (4.0)

all depressed 18 assigned to cytidine þ VPA treatment/17 assigned to placebo þ VPA treatment 13.6 (9.2) 28 BD I

22 BD I, 13 BD II

Patients characteristics (subtype/current episode/medication/ illness durationa)

single voxel PRESS

1.5 T

single voxel PRESS

3.0 T

Imaging methods (field strength/ technique/ acquisition)

8 cm3

medial PFC, bilateral prefrontal WM

3.4 cm3

ACC

Regions of examined/Voxel size

no changes in Glx levels with 6wk lithium treatment

# ACC Glx levels with cytidine add-on treatment relative to placebo addon treatment

Results on Glx/ Cr þ PCr ratio or Glx levelsb

not examined

positive correlations between ACC Glx levels changes and HDRS score changes in cytidine add-on group not in placebo add-on group

Clinical correlations

Abbreviations: AA, Amino Acid; ACC, Anterior Cingulate Cortex; ADHD, Attention-Deficit Hyperactivity Disorder; BD, Bipolar Disorder; CDRS, Children’s Depression Rating Scale; CGI-mania, mania subscale of the Clinical Global Impression Bipolar Disorder Scale; Cr, Creatine; CSI, Chemical Shift Imaging; DLPFC, Dorsolateral Prefrontal Cortex; GABA, g-Aminobutric Acid; Glx, Glutamate and Glutamine; GM, Grey Matter; HDRS, Hamilton Depression Ration Scale; MRS, Magnetic Resonance Spectroscopy; NAA, N-acetylaspartate; NOS, Not Otherwise Specified; PCr, Phosphocreatine; PEPSI, Proton Echo-Planar Spectroscopic Imaging; PFC, Prefrontal Cortex; PRESS, Point Resolved Spectroscopy; STEAM, Stimulated Echo Acquisition Mode; T, Tesla; VPA, Valproate; WM, White Matter; YMRS, Young Mania Rating Scale. a Years (SD). b All results presented in Table 4 are those of patients with bipolar disorder relative to comparison subjects except where indicated otherwise. c Participants of this study was a subgroup of subjects studied at baseline in the medication-free state [19].

6/23

28 paediatric patients

—

—

35 (9)

Mean age (SD)a

|

Patel et al. [37]

18/17

35 patients

Yoon et al. [65]

Gender (M/F)

Subjects

Study

Table 4 (Continued)

164 Chapter 14

Functional Imaging Techniques

determined the hippocampal glutamate levels out of overlapped resolution spectrum of Glx using 3 Tesla scanner. They found elevated glutamate levels in remitted BD patients relative to comparison subjects. Based on the consistent findings of elevated Glx levels in BD, a few studies in BD patients, examining the effects of medications targeting glutamatergic neurotransmission, have been conducted. Frye et al. [29] examined prefrontal Glx levels in patients with bipolar depression. Increased prefrontal Glx levels were observed in BD patients and increased glutamine levels appeared to be reduced with treatment of 12-week lamotrigine administration. A recent longitudinal 1 H MRS study reported that 12-week cytidine supplementation to valproate decreased prefrontal Glx levels in patients with bipolar depression relative to placebo supplementation [65]. Cytidine is a dietary agent, known to exert its actions on the neuronal-glial glutamate cycling and cytidine-induced reductions in cerebral Glx levels in patients with bipolar depression were correlated with resolution of depressive symptoms (Figure 3b). Lithium treatment, but not valproate, was also suggested to decrease GM Glx levels [31]. In their study, the authors suggested that lithium may potentially normalize the bioenergetic alterations of the redox state in BD, based on the results of the GM Glx elevation from the same cohort of medication-free patients [19]. There have been some inconsistencies in the alterations of Glx levels in paediatric BD patients. As compared with healthy children, Castillo et al. [23] found that children with BD showed similarly elevated levels of Glx in the frontal and the basal ganglia regions compared to those of adult patients. Alterations in glutamatergic neurotransmission were also suggested in BD children who were comorbid with attention deficit hyperactivity disorder [62]. In contrast, Olvera et al. [14] did not find alterations in cerebral Glx levels in 35 paediatric BD patients. In the study of child and adolescent BD patients using a 4T 1 H MRS, Moore et al. [63] reported that unmedicated patients showed lower prefrontal glutamine levels than medicated patients and comparison subjects, while there was no difference in the prefrontal glutamate levels between groups. In line with these findings, a recent study of paediatric BD patients with manic episode showed lower prefrontal Glx/Cr þ PCr ratio in patients with manic episode than in those stably treated with the atypical antipsychotics [64]. Glutamatergic neurotransmissional abnormalities in patients with BD may reflect disturbed neuronal-glial interactions, which are involved in the glutamate to glutamine conversion in glial cells and glutamine to glutamate conversion in neurons [4]. This hypothesis is supported by several post-mortem studies reporting the glial cell reductions in BD [66–69]. Alternatively, increased demands on neuronal energy metabolism induced by the elevated levels of excitatory neurotransmitter including glutamate may

|

165

disconcert the normal balance between the mitochondrial oxidative phosphorylation and the glycolysis in BD [1,19]. However, further studies will be needed to confirm the role of glutamate and glutamine in the pathophysiology of BD.

Creatine (Cr)/phosphocreatine (PCr)(Table 5) Cr peak lies on 3.02 ppm on the 1 H spectrum and reflects the sum of both Cr and PCr. PCr is the central energy marker and acts as a reservoir for the generation of ATP [70]. Maintenance of equilibrium between Cr and PCr is regulated by the cellular demand for high-energy phosphate. The resonance of Cr on the 1 H spectrum has been regarded as relatively “constant” in normal brain [71] and could be thus used as the internal reference value to each metabolite peak in several 1 H MRS studies. Evidence from the recent studies, however, indicates that cerebral Cr levels could be altered in several pathological conditions [72]. Cr also exerts a role in the cerebral osmoregulation [73]. BD patients demonstrated the reduced Cr þ PCr levels in the dorsolateral prefrontal cortex [21] as well as in the hippocampus [8] relative to comparison subjects. Hamakawa et al. [17] reported that reductions in Cr þ PCr levels were greater in depressed than in euthymic BD patients. This might indicate a state-dependent alteration of Cr þ PCr levels in BD. In their study, there was a gender specific difference in Cr þ PCr concentration in BD patients. Similarly, higher Cr þ PCr levels were reported in the thalamus of male BD patients [25] relative to comparison subjects. Frye et al. [29] reported higher Cr þ PCr levels in the prefrontal cortex in patients with bipolar depression than in comparison subjects. In contrast to the previous research, there have been several studies that did not find any alterations of Cr þ PCr levels in patients with BD [6,18–20].

Phosphorous (31p) MRS (Table 6) Membrane phospholipid: phosphomonoester (PME) and phosphodiester (PDE) PMEs are composed of various metabolites including PC and phosphoetanolamine, which are the major precursors of phospholipids [84]. Inositol-1-phosphate may contribute to this resonance, particularly in conditions where it accumulates due to the inhibition of inositol-1-phosphotase [85]. PDEs include more mobile phospholipids and are the major product of phospholipid breakdown including GPC and glycerophosphoethanolamine [84]. Both signals of PME and PDE may reflect the turnover of membrane phospholipid turnover. Changes in PME and PDE signals may also indicate the alteration of membrane integrity in both neuronal and non-neuronal tissues. Several 31 P MRS studies, thus far, have suggested that changes in the cerebral PME levels may show a

Subjects

Gender (M/F)

Mean age (SD)

Frye et al. [29]

17/6

7/5

12 controls

10/22

32 controls

23 patients

11/21

20/0

20 controls

32 patients

15/0

Deicken et al. [8] 15 patients

Frey et al. [21]

7/13

20 controls

33 (11)

36 (11)

34 (9)

34 (10)

36 (11)

39 (10)

37 (10)

1.5 T

Imaging methods (field strength/ technique/ acquisition)

single voxel

PRESS

5 medicated 17.4 (10.4)

1.5 T

27 cm3

medial frontal cortex

8 cm3

single voxel

each voxel 1.1 cm3

hippocampus

left DLPFC

PRESS

Results on Cr þ PCr levelsb

no association between Cr þ PCr levels and clinical characteristics

not examined

no association between metabolite levels and medication use

Clinical correlations

not examined " Cr þ PCr levels in medial frontal cortex at baseline no changes in Cr þ PCr levels with 12-wk lamotrigine treatment

# Cr þ PCr levels in DLPFC

# Cr þ PCr levels in bilateral hippocampus

- bilateral frontal cortical # Cr þ PCr levels in left regions frontal region in depressed patients relative to euthymic patients 15.6 cm3

Regions of examined/Voxel size

1.5 T

CSI PRESS

all depressed

7 hypomanic, 17 depressed, 1 mixed, 7 euthymic all medication free at least for 2 wk 10.0 (9.6) BD I or BD II

all euthymic 12 medicated 18.7 (9.5) 20 BD I, 12 BD II

single voxel all euthymic, 8 subjects were also examined in depressive episode 4 cases medication-free STEAM not available 1.5 T 15 BD I

15 BD I, 8 BD II

Patients characteristics (subtype/current episode/medication/ illness durationa)

|

Studies on the adults patients with bipolar disorder Hamakawa 23 patients 8/15 45 (11) et al. [17]

Study

Table 5 Published 1 H MRS research on Cr þ PCr levels in patients with bipolar disorder.

166 Chapter 14

Colla et al. [22]

Brambilla et al. [20]

Dager et al. [19]

Michael et al. [18]

Cecil et al. [6]

Deicken et al. [25]

10/11

9/10

19 controls

16/16

32 controls

21 patients

2/8

10/14

24 controls

10 patients

13/16

6/2

8 controls

29 patients

6/2

9/12

21 controls

8 patients

6/11

15/0

15 controls

17 patients

15/0

15 patients

55 (2)

54 (2)

35 (10)

37 (14)

32 (8)

30 (11)

41 (15)

40 (14)

22 (5)

22 (7)

38 (11)

41 (11)

all euthymic all medicated not available

1 depressed, 9 euthymic 4 medication-free at least for 2 wk 15.9 (10.3) 21 BD I

all predominantly depressed all medication-free 13.5 (10.2) 8 BD I, 2 BD II

all manic 2 medicated not available 11 BD I, 17 BD II, 1 BD NOS

9 manic, 8 mixed all medicated 5 (4) not available

22.1 (9.7) 17 BD I

all euthymic 13 medicated

15 BD I

single voxel PRESS

3T

single voxel STEAM

1.5 T

PEPSI

CSI

1.5 T

single voxel STEAM

1.5 T

single voxel PRESS

12 cm3

bilateral hippocampus

8 cm3

left DLFPC

frontal WM/cingulate/ caudate/putamen/ thalamus/insula/ parietal WM (all bilateral)/midline occipital each voxel 1 cm3

3.4 cm3

left DLPFC

medial prefrontal8 GM/ medial prefrontal8 WM 8 cm3

each voxel 1.5 cm3

Multi-slice spin echo sequence 1.5 T

bilateral thalamus

1.5 T

no difference in Cr þ PCr levels between groups

no difference in Cr þ PCr levels between groups

no difference in Cr þ PCr levels in GM and WM between groups

no difference in Cr þ PCr levels between groups

no difference in Cr þ PCr levels between groups

no difference in Cr þ PCr levels between groups

(continued)

not examined

no association between Cr þ PCr levels and clinical characteristics

negative correlation between WM Cr levels and HDRS scores

not examined

not examined

no association between Cr þ PCr levels and clinical characteristics

Functional Imaging Techniques

| 167

11/10

21 controls

34 (10)

36 (12)

Mean age (SD)

17/18

19/15

36 controls

non-

13 controls

35 patients

8/2

9/7

18 controls

10 patients

6/8

14 patients

6/4

14 (3)

13 (3)

gender

10 (2)

17 (4)

16 (3)

11 (2)

not available 24 medicated 4.3 (3.7)

PRESS

5 medicated not available 23 BD I, 12 BD II

single voxel PRESS

1.5 T

12 (4)

matched

1 depressed, 13 euthymic single voxel 13 medicated STEAM 3.8 (2.4) 1.5 T 10 BD I

single voxel 1 medicated not available PRESS 10 BD I, 3 BD II, 1 BD NOS 1.5 T

8 cm3

left DLPFC

7 manic, 3 mixed

medial frontal cortex/ occipital cortex

8 cm3

left DLPFC

no difference in Cr þ PCr levels between groups

no difference in Cr þ PCr levels between groups single voxel

trend in # Cr þ PCr levels in left DLPFC

trend in # Cr þ PCr levels in cerebellar vermis

no difference in Cr þ PCr levels between groups

Results on Cr þ PCr levelsb

not examined

8 cm3

not examined

no association between Cr þ PCr levels and clinical characteristics

not examined

no association between metabolite levels and medication status

Clinical correlations

Abbreviations: ACC, Anterior Cingulate Cortex; BD, Bipolar Disorder; Cr, Creatine; CSI, Chemical Shift Imaging; DLPFC, Dorsolateral Prefrontal Cortex; GM, Grey Matter; HDRS, Hamilton Depression Rating Scale; MDD, Major Depressive Disorder; MRS, Magnetic Resonance Spectroscopy; NOS, Not Otherwise Specified; PCr, Phosphocreatine; PRESS, Point Resolved Spectroscopy; STEAM, Stimulated Echo Acquisition Mode; T, Tesla; WM, White Matter. a Years (SD). b All results presented in Table 5 are those of patients with bipolar disorder relative to comparison subjects except where indicated otherwise.

Olvera et al. [14]

Davanzo et al. [47]

Sassi et al. [13]

10 controls

8 cm3

single voxel PRESS

medial frontal cortex/ right frontal WM/ cerebellar vermis 8 cm3

ACC, parieto-occipital cortex

Regions of examined/Voxel size

3T

Imaging methods (field strength/ technique/ acquisition)

3 BD I, 3 BD II, 1 BD NOS, 1.5 T 2 MDD - all euthymic

all manic all medicated age of onset, 25.5 (9.5)

15 BD I

Patients characteristics (subtype/current episode/medication/ illness durationa)

|

Studies on the adolescents or children with bipolar disorder Cecil et al. [15] 9 patients 5/4 10 (1)

7/8

15 patients

€ u € r et al. [4] Ong

Gender (M/F)

Subjects

Study

Table 5 (Continued)

168 Chapter 14

Kato et al. [77]

Kato et al. [76]

4/6

gender matched

9 controls

10 patients

7/4

12/2

14 controls

11 patients

10/2

12 patients

16/0

16 controls

Deicken et al. [75]

12/0

12 patients

Deicken et al. [74]

Gender (M/F)

Subjects

Study

42 (9)

40 (11)

41 (11)

40 (10)

40 (8)

40 (11)

40 (9)

Mean age (SD)

all manic, 7 repeatedly scanned at euthymic after lithium treatment not available not available not available

all euthymic all medication free at least for 1 wk not available not available

spin echo sequence

all medication free at least for 1 wk not available not available

1.5 T

frontal lobe

not available

single voxel

DRESS

frontal lobe

25 cm3

right and left temporal lobes

25 cm3

right and left frontal lobes

Regions of examined/Voxel size

1.5 T

MRSI spin echo sequence

2T

single voxel

2T

Imaging methods (field strength/ technique/ acquisition)

all euthymic

not available

Patients characteristics (subtype/current episode/medication/ illness durationa)

Table 6 Published 31 P MRS research in patients with bipolar disorder.

# PME and pHi levels in euthymic BD patients relative to controls

" PME/total phosphorous compounds ratios in manic patients relative to euthymic patients and controls

# PME level in bilateral temporal lobes in euthymic patients

# PME level in bilateral frontal lobes in euthymic patients " PDE level in bilateral frontal lobes in euthymic patients

Resultsb

(continued)

not examined

no association between PME/ total phosphorous compounds ratios and duration/ serum levels of lithium treatment

not examined

not examined

Clinical correlations

Functional Imaging Techniques

| 169

16/24

27/33 8/21

40 patients

60 controls 29 patients

Kato et al. [80]

gender matched

17 controls

Kato et al. [79]

8/9

gender matched

10 controls

17 patients

Gender (M/F)

Subjects

40 (14) 43 (12)

42 (12)

39 (10)

40 (11)

41 (9)

Mean age (SD)

14 BD I, 15 BD II

all euthymic all patients treated with lithium, 11 with antipsychotics, 6 with antidepressants

1.5 T

single voxel DRESS

frontal lobe

not available

frontal lobe

DRESS

all medicated not available 31 BD I, 9 BD II 1.5 T

not available

single voxel

all patients repeatedly scanned at euthymic and manic states

DRESS

3 medicated at baseline not available not available frontal lobe

not available

single voxel

all depressed, all patients repeatedly scanned at euthymic after treatment

1.5 T

Regions of examined/Voxel size

Imaging methods (field strength/ technique/ acquisition)

Patients characteristics (subtype/current episode/medication/ illness durationa)

# PCr levels in BD II (all states) patients relative to controls

# PME and pHi levels in frontal lobe

# PME and pHi levels in euthymic BD patients relative to controls " PME and pHi levels in manic states relative to euthymic states in BD patients

" PME and pHi levels in depressed states relative to euthymic states in BD patients

Resultsb

no association between PME/ PCr/pHi levels and HDRS scores

no association between PME levels and ventricular enlargement

no association between PME/pHi levels and brain lithium levels

Clinical correlations

|

Kato et al. [78]

Study

Table 6 (Continued)

170 Chapter 14

Murashita et al. [82]

Kato et al. [81]

3/16

12/13

25 controls

6/15

21 controls

19 patients

8/17

27/32

25 patients

59 controls

37 (14)

46 (10)

43 (10)

40 (9)

38 (13)

all euthymic all medicated (9 lithium responders/10 lithium nonresponders) age of onset, 32.8

13 BD I. 6 BD II

patients repeatedly scanned at euthymic (21), depressed (11), or manic (12) states

—

not available

patients repeatedly scanned at euthymic (21), depressed (25), or hypomanic (10) states 15 medicated

1.5 T

phase-encoding

CSI

1.5 T

DRESS

single voxel

occipital region

not available

frontal lobe

not available

" PME levels in hypomanic or depressed BD II patients relative to controls no difference in PME levels between euthymic BD II patients and controls # PME levels in euthymic BD I patients relative to controls # left frontal PCr levels in depressed patients relative to controls # right frontal PCr levels in euthymic and manic patients relative to controls " left frontal PME levels in depressed patients relative to controls # PCr levels in postphotic stimulations relative to prephotic stimulation in lithium-resistant bipolar patients, however, neither in controls nor lithium-responders

(continued)

not examined

negative correlation between left frontal PCr levels and HDRS scores

Functional Imaging Techniques

| 171

37 (3) (VPA) 31 (3)

5/6 (VPA) 9/10

6/4

10 controls

32 (14)

all euthymic all medicated not available

all euthymic 16 treated with lithium 11 treated with VPA not available not available

7 BD I, 4 BD II (VPA)

8 BD I, 8 BD II (lithium)

Patients characteristics (subtype/current episode/medication/ illness durationa)

- single voxel DRESS

1.5 T

PRESS, ISIS

single voxel

3T

Imaging methods (field strength/ technique/ acquisition)

52.5 cm3

basal ganglia

12 cm3

left temporal cortex

Regions of examined/Voxel size

# pHi levels in BD patients relative to controls

no difference in PME levels between medicated patient groups and controls

Resultsb

not examined

not examined

Clinical correlations

Abbreviations: BD, Bipolar Disorder; CSI, Chemical Shift Imaging; DRESS, Depth Resolved Surface-coil Spectroscopy; HDRS, Hamilton Depression Rating Scale; ISIS, Image Selective In vivo Spectroscopy; MRS, Magnetic Resonance Spectroscopy; MRSI, Magnetic Resonance Spectroscopic Imaging; PCr, Phosphocreatine; PDE, Phosphodiesters; PME, Phosphomonoesters; T, Tesla; VPA, Valproate. a Years (SD). b All results presented in Table 6 are those of patients with bipolar disorder relative to comparison subjects except where indicated otherwise. c Same cohort as Silverstone et al. [28] and Wu et al. [36].

7/6

13 patients

49 (12)

(lithium)

(lithium)

- 11 VPA treated patients

Hamakawa et al. [83]

43 (3)

10/6

- 16 lithium treated patients

Silverstone et al. [35] c

19 controls

Mean age (SD)

Gender (M/F)

Subjects

Study

|

Table 6 (Continued)

172 Chapter 14

Functional Imaging Techniques

state-dependent pattern in patients with BD. Studies on euthymic BD patients have consistently demonstrated that the frontal as well as temporal PME concentrations were lower in BD patients relative to comparison subjects [74,75,78,79]. In contrast, manic or hypomanic BD patients showed the higher PME levels than euthymic BD patients [76–78,80]. It remains controversial whether lithium treatment alters the PME resonance, which also includes contributions from inositol monophosphate. Yildiz et al. [86] reported that 1 and 2 weeks of lithium administration increased PME levels in healthy volunteers. In the amphetamine challenge test of Silverstone et al. [87], amphetamine challenge after 1 week of lithium treatment increased PME levels in healthy volunteers. Silverstone et al. [35] reported in a cross-sectional study that there were no differences in PME levels between lithium or valproate-treated BD patients and comparison subjects. Authors suggested that lithium or valproate treatment may normalize the altered phosphoinositide pathway in BD patients to the levels of healthy comparison subjects.

High-energy phosphates: phosphocreatine (PCr) PCr is a high-energy phosphate formed from ATP and creatine by creatine kinase and functions as a buffer of ATP [88]. Several 31 P MRS studies, if not all, suggested altered PCr levels in patients with BD. Long-term abnormalities in cerebral PCr levels may indicate alterations in cellular metabolism, including an insufficient ATP supply for normal cellular function. Abnormally lower PCr levels [80,81] and its correlation with depressive symptoms [81] have been reported in BD patients. Photic stimulation induces immediate cell activity, which might be related to short-term decreases in PCr concentrations [46]. Murashita et al. [82] conducted a photic stimulation experiment in BD patients with the poor treatment response to lithium. They found that lithiumresistant patients showed a slower recovery from reductions in PCr levels in response to photic stimulation than comparison subjects. Taken together, these alterations of PCr in BD suggest the cellular energy metabolic disturbances that are potentially related to the pathophysiological role of mitochondrial dysfunction in patients with BD. Intracellular pH (pHi) The findings of altered pHi in BD have mainly been reported by Kato and colleagues. Euthymic BD patients consistently showed reduced pHi levels in the frontal as well as in the basal ganglia regions relative to comparison subjects [77,78,80,83]. Since the levels of pHi was positively correlated with the duration of lithium treatment [79], lower pHi levels in euthymic BD patients does not appear to be related to the treatment [89]. In contrast, compared with

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euthymic BD patients or comparison subjects, manic or depressed BD patients had higher pHi levels [77,78].

Summary and clinical implications In BD patients, even though there are some inconsistencies, altered cerebral levels of various brain metabolites have been reported (Figure 2). NAA level reduction in BD patients is one of the most consistently replicated findings, which suggests decreased neuronal viability and dysfunction of the mitochondria. Another consistent finding would be the elevated glutamate levels in BD patients relative to comparison subjects. Increased extracellular glutamate levels could cause excitatory neuronal toxicity and in turn, may have resulted in decreased levels of NAA. Rapid neuronal firing in BD patients, possibly with increased glutamate levels, may have produced more lactate, causing lactate acidosis and ultimately lowering pHi levels observed in 1P MRS studies. Higher glutamate levels in BD patients relative to comparison subjects may have been caused by disturbed neuronal-glial interactions. Altered ratios of neuron numbers and glial cell numbers [66–69] could be responsible for the disturbed glutamate-glutamine cycle. Dysfunctional mitochondrial oxidative metabolism in BD patients, which is important in discharge and reuptake of glutamate, may in part explain increased levels of glutamate [90]. Drugs acting on the glutamatergic system, such as lamotrigine and cytidine, decreased the cerebral levels of glutamine or Glx in BD patients. Although results are not stable, possibly due to sample heterogeneity or different medications and mood states, alterations in cerebral Cho, mI, Cr, PCr, PME and PDE levels suggest that there are likely to be brain energy metabolism abnormalities, membrane dysfunction and the second messenger system disturbance in BD patients. Newer agents beyond neurotransmitter theory-based ones, which are intended to rebuild cell membranes or to provide pro-mitochondrial effects, could further be tested for potential effects in BD patients. There have been efforts to measure medication effects on brain metabolites and clinical relevance with MRS methodology, a tool for measuring the brain chemistry. Lithium effect was most widely studied, However, further studies are needed to confirm the effect of lithium on brain metabolites.

Diffusion tensor imaging in bipolar disorder Introduction There has been a substantial amount of evidence that white matter (WM) abnormalities play an important role in the pathophysiology of BD. White matter hyperintensities

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(WMH) on brain MRI, which have been suggested to represent dilated perivascular spaces, localized demyelination, astrocytic gliosis and atherosclerosis, are likely to interrupt WM fibres [91–93]. Previous studies have reported a greater prevalence of WMH in BD patients than in comparison subjects [94]. The increased prevalence of WMH in BD is one of the most robust and consistently replicated abnormalities reported in BD [94]. Several conventional structural brain imaging studies have suggested global [95] and regional [96] WM volume reductions in BD patients, although a recent meta-analysis did not confirm WM volume changes in BD [94]. DTI is a relatively new imaging technique and allows direct investigations of the microstructural WM integrity by measuring the microscopic diffusion of water [97–99]. Although there are several methodological issues and controversies on the DTI analysis, quantification of the directionality and the rate of microscopic water diffusion, which are reflected in fractional anisotropy (FA) and the apparent diffusivity coefficient (ADC), respectively, have most commonly been used for analysing DTIs. Reduced FA values in the WM fibres reflect a reduction in WM integrity, while increases in ADC are associated with the microstructural changes in WM consistent with a decrease in WM integrity. This modality has widely been used in the field of clinical research on traumatic brain injury, cerebral ischaemia and ageing [100]. Since Adler et al. [101] reported reduced FA in nine BD patients, the number of DTI studies involving BD patients has continuously increased. The most popular approach for the quantitative analyses of DTI is the ROI method, which is especially useful when there are a priori hypothesized brain regions. Another approach for diffusion data quantification is a voxel-based analysis (VBA), which might be appropriate when a whole brain-wise approach is more desirable. When an ROI approach is adopted, reliable voxel placement becomes an important methodological challenge. Accurate spatial normalization of DTI image sets would help reduce spurious findings in applying a voxel-based method of assessing DTI data. However, despite this limitation, analytic methods for brain DTI data are undergoing rapid evolution and DTI is likely to remain as an important tool for examination of the microstructural WM integrity. Table 7 shows the published DTI research in patients with BD.

DTI Studies of bipolar disorder using a region-of-interest approach Since abnormalities in the frontocortico-subcortical pathways have been suggested to be closely related to psychotic and mood symptoms, the frontal WM region has been considered as a critical region of interest (ROI) for DTI analysis in BD.

Reduced FA values in the anterior frontal WM, linking the prefrontal cortex with subcortical and other cortical regions, were first reported in a DTI study of BD patients [101]. In this study, FA and ADC measures were examined in eight a priori selected frontal ROIs in nine BD patients and nine comparison subjects. Haznedar et al. [103] performed structural volumetric analyses for GM/WM of the frontal cortex, in addition to a DTI analysis, using the ROI approach. In this relatively larger sample of 40 BD patients and 36 comparison subjects, BD patients had volume reductions in GM and WM of the frontal cortex. Amongst the frontal ROIs, higher relative anisotropy in the frontal intergyral association fibres was observed in BD patients relative to comparison subjects. In contrast, BD patients had lower relative FA values in the anterior fronto-occipital fasciculus connecting the orbitofrontal cortex with the temporal and occipital lobes. Amongst the ROIs of anterior and posterior limbs of the internal capsule, the connectivity in the posterior limb of the internal capsule, which primarily consists of thalamus connections, frontopontine tracts, parietopontine tracts and corticospinal tracts, was reduced in BD patients relative to comparison subjects. A study by Beyer et al. [102], however, did not find a difference in FA in any a priori selected frontal ROIs. FA values, as well as ADC of the orbitofrontal, superior frontal and middle frontal ROIs, were calculated in 14 BD patients and 21 comparison subjects. FA of all three ROIs did not differ between groups. However, higher ADC values were observed in bilateral orbitofrontal ROIs of BD patients than of comparison subjects. This result suggests microstructural abnormalities in the orbitofrontal WM of BD patients. A later study by Regenold et al. [104] was consistent with the findings of Beyer et al. [102]. DTIs from eight BD patients were examined for mean ADC values, not FA values, in eight ROIs across cerebral lobes bilaterally. When these ADC values were compared with those of nine patients with neurological disease, increases in ADC values of bilateral frontal lobe ROIs were noted (left, p ¼ 0.015 and right, p ¼ 0.012). The cingulum bundle, which participates in prefrontotemporal connections, has frequently been examined in patients with psychiatric disorders. Wang et al. [108] placed ROI of the anterior cingulum on five coronal slices anterior to the mid-anterior commissure-posterior commissure (AC-PC) slice and ROI of the posterior cingulum on five coronal slices posterior to the mid-AC-PC slice. BD patients demonstrated reduced FA in the anterior cingulum and not in the posterior cingulum relative to comparison subjects. Several studies in BD examined the WM connectivity of the corpus [105,108,109]. Wang et al. [109] used both a voxelbased approach called Statistical Parametric Mapping (SPM; Wellcome Department of Cognitive Neurology, London,

Subjects

Gender (M/F)

Mean age (SD)

Patients characteristics (subtype/current episode/ medication/illness durationa)

Regenold et al. [104]

8 patients

6/4

matched samples

40 patientsc

36 controlsc

4/17

21 controls

Haznedar et al. [103]

4/10

6/3

Beyer et al. [102] 14 patients

9 controls

58 (13)

41 (12)

42 (11)

45 (14)

44 (18)

31 (7)

EPI

not available 17 BD I medicated not available 8 BD I

1.5T

7 directions

1.5T

EPI

6 directions

16 cyclothymia

5 manic/hypomanic, 6 depressed, 3 euthymic not available 13.6 (12.1) 17 BD I, 7 BD II,

EPI

all medicated not available not available 1.5T

25 directions

3T

Imaging methods (field strength/ number of directions/ sequence)

not available

Using the conventional voxel-based and regions-of-interest approaches Adler et al. [101] 9 patients 4/5 32 (8) 9 BD I

Study

Table 7 Published DTI research in patients with bipolar disorder. Resultsb

" ADC in the bilateral OFC ROIs

not examined

not examined

Clinical correlations

bilateral frontal/ temporal/ parietal/occipital WM

" ADC in the bilateral frontal ROIs

no associations between the numbers of hospitalization, number of affective episodes and ADC in the ROIs (continued)

not examined bilateral frontal WM/ # RA in anterior fronto-occipital anterior and fasciculus and " RA posterior limbs of in the frontal the internal intergyral capsule association fibres amongst frontal ROIs RA # RA in the posterior limb of internal capsule ROI

bilateral OFC/SFG/ MFG WM FA/ADC

prefrontal WM at 15, # FA in the anterior, superior frontal 20, 25, and 30 ROIs mm superior to the AC FA/ADC no difference in elsewhere

Regions of examined (Tool of analysis)/ Measurements

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Versace et al. [107]

11/20

11/14

25 controls

matched

31 patients

28 controls

13/23

4/6

10 controls

Bruno et al. [106] 36 patients

6/5

30 (9)

36 (9)

matched

39

32 (9)

33 (11)

55 (13)

4/6

8 controls with neurological diagnosis

11 patients

Mean age (SD)

Gender (M/F)

Subjects

14 depressed, 17 euthymic

EPI

34 medicated 13.8 31 BDI

6 directions

3T

7 directions

1.5 T

6 directions EPI

1.5T

EPI

Imaging methods (field strength/ number of directions/ sequence)

not available

all euthymic all medicated 12.0 (9.8) 25 BD I/11 BD II

all medicated 20.1 (5.4) 11 BD I

4 manic, 3 mixed, 1 depressed

Patients characteristics (subtype/current episode/ medication/illness durationa)

Resultsb

FA/longitudinal and radial diffusivity

whole brain (TBSS)

FA/ADC

whole brain (SPM)

no associations between FA or ADC and the number of admission and the disease duration

positive correlation between the onset age and ADC in the splenium

Clinical correlations

# FA in the right negative correlation uncinate fasciculus between the medication load and FA in the left optic radiation #FA in the left optic " FA in the left radiation and the uncinate right anterior fasciculus, the left thalamic radiation in optic radiation, the subjects taking and the right mood stabilizers anterior thalamic relative to those not radiation taking

" ADC in the bilateral prefrontal and right posterior frontal regions

#FA in the inferior, middle temporal and middle occipital regions

" FA in the genu of genu, left anterior, corpus callosum right anterior, splenium ROIs of corpus callosum FA/ADC

ADC

Regions of examined (Tool of analysis)/ Measurements

|

Yurgelun-Todd et al. [105]

Study

Table 7 (Continued)

176 Chapter 14

Sussmann et al. [110]

42 patients

40 controls

22/20

15/27

9/24

15/27

42 controls

Wang et al. [109] 33 patients

13/29

Wang et al. [108] 42 patients

40 (10)

29 (9)

32 (10)

29 (9)

33 (10)

7 manic or hypomanic, 7 depressed, 19 euthymic not available not available 42 BD I

1.5 T

EPI

32 directions

3T

# FA in the anterior cingulum ROI

no associations between the diagnostic subtype, the mood state, medication state, and FA in the ROIs

#FA in the left optic radiation in the depressed BD patients relative to euthymic patients

whole brain (SPM2)/ # FA in the superior thalamic radiation bilateral anterior (Voxel-based) limb of the internal capsule and uncinate fasciculus ROIs

negative correlation between the depressive symptom severity and FA in the anterior thalamic radiation (continued)

whole brain (SPM5)/ # FA in the genu, the no associations between the clinical variables rostral body, and anterior, middle, and FA in the ROIs the anterior and posterior midbody of corpus corpus callosum callosum (VoxelROIs based) FA # FA in the anterior and the middle corpus callosum ROIs (ROI based)

32 directions

EPI

FA

3T

depressed patents, 12.3 (9.8); euthymic patents, 11.8 (6.3) 25 rapid cycling

11 manic or hypomanic, 9 depressed, 22 euthymic 35 medicated not available 19 rapid cycling

anterior and posterior cingulum ROIs

EPI

all medicated

Functional Imaging Techniques

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16 controls

9/7

8/8

22/16

38 controls

Using the tractography approach Houenou 16 patients et al. [112]

15/15

19/19

38 controls

30 patients

Gender (M/F)

Subjects

41(13)

42 (13)

32 (9)

33 (9)

37 (12)

Mean age (SD)

EPI

not available 18.3 (11.1) 25 BD I/2 BD II/3 BD NOS

41 directions

EPI

all euthymic

14 medicated not available

1.5 T

EPI

all medicated not available not available

25 directions

not available

1.5 T

51 directions

Imaging methods (field strength/ number of directions/ sequence)

all euthymic

Patients characteristics (subtype/current episode/ medication/illness durationa)

Clinical correlations

# FA in the left cerebellar WM

" FA in the bilateral frontal WM

no associations between the clinical variables (illness duration and symptom severity) and fibres’ characteristics

" FA in bilateral frontal WM and # FA in the left cerebellum in patients without substance use disorder

# FA in the left anterior no associations between the medication use limb of the internal and FA in the ROIs capsule and the bilateral uncinate fasciculus ROIs (ROI based)

Resultsb

" the number of seed masks for reconstructed tractography; between the left subgenual subgenual cingulate, cingulate and left amygdaloamygdalohippocampal hippocampal complex, pons complex and cerebellum FA/ADC/the number of reconstructed fibres

FA/axial and radial diffusivity

whole brain (ART, TBSS)

FA

Regions of examined (Tool of analysis)/ Measurements

|

Mahon et al. [111]

Study

Table 7 (Continued)

178 Chapter 14

21/19

28/21

40 patients

49 controls

35 (11)

40 (10)

Pavuluri et al. [116]

Frazier et al. [115]

10/3

5/3

8 controls

13 patients

4/6

7/10

10 patients

17 controls

15 (3)

9 (3)

9 (2)

Studies on the adolescents or children with bipolar disorder Adler et al. [114] 11 patients 5/6 14 (2)

McIntosh et al. [113]

6 directions

3T

all medicated not available 13 BD I

1.5 T

25 directions EPI

3T

51 directions EPI

1.5 T

not available

all manic all medication-naive first episode 10 BD I

11 BD I

not available not available 18.8 (11.1)

not available

not examined

no associations between the clinical variables (illness duration, symptom severity, and treatment) and fibres’ characteristics

# FA in the anterior anterior corona corona radiata radiata, anterior, and posterior limbs of internal capsule, superior region of internal capsule, superior and inferior longitudinal fasciculus, cingulum, and splenium

| (continued)

not examined

no associations between superior longitudinal # FA in the superior the clinical variables frontal tracts fasciculus and (illness duration, including the cingulatesymptom severity, bilateral superior paracingulate and treatment) and longitudinal WM ROIs FA in the ROIs fasciculus and the cingulateparacingulate ROIs FA # FA in the left orbitofrontal WM and the right anterior corpus callosum

prefrontal WM at 15, # FA in the left superior-frontal 20, 25, and 30 WM tracts mm superior to the AC FA/ADC

# FA in the uncinate seed masks for fasciculus and tractography; anterior thalamic anterior thalamic radiation radiation and uncinate fasciculus FA

Functional Imaging Techniques 179

12/14

14/12

26 controls

6/9

15 controls

26 patients

Gender (M/F)

Subjects

15 (2)

16 (2)

14 (3)

Mean age (SD)

Imaging methods (field strength/ number of directions/ sequence)

6 directions

EPI

16 manic or mixed

all medicated not available

all euthymic 27 directions all medication-free for EPI at least 7 d 7 (2.2) 26 BD I 1.5 T

Patients characteristics (subtype/current episode/ medication/illness durationa)

FA/ADC

whole brain

FA/ADC/r-FCI

Regions of examined (Tool of analysis)/ Measurements

Clinical correlations

no associations between # FA in the right the duration of orbitofrontal, the treatment and FA in bilateral temporal, the ROIs and the left occipital lobe " ADC in the bilateral subgenual regions, the postcentral gyrus, the precuneus, the temporal, and the occipital regions

# r-FCI in the splenium

Resultsb

Abbreviations: AC, Anterior commissure; ADC, Apparent Diffusion Coefficient; ART, Automatic Registration Toolbox; BD, Bipolar Disorder; DTI, Diffusion Tensor Imaging; EPI, Echo Planar Imaging; FA, Fractional Anisotropy; MFG, Middle Frontal Gyrus; NOS, Not Otherwise Specified; OFC, Orbitofrontal Cortex; r-FCI, Regional Fibre Coherence Index; RA, Relative Anisotropy; ROI, Region Of Interest; SFG, Superior Frontal Gyrus; SPM, Statistical Parametric Mapping; T, Tesla; TBSS, Tract-Based Spatial Statistics; WM, White Matter. a Years (SD). b All results presented in Table 7 are those of patients with bipolar disorder relative to comparison subjects except where indicated otherwise. c Among them, DTI scans were conducted only in 33 BD patients and 34 comparison subjects.

Kafantaris et al. [117]

Study

|

Table 7 (Continued)

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United Kingdom) for a spatial normalization of images and the ROI approach in order to investigate the connectivity of the corpus callosum. They found reduced FA values in the anterior and middle, but not posterior, corpus callosum in 33 BD patients relative to 40 comparison subjects both in ROIs (at p < 0.01, Bonferroni corrected for three subregions) and voxel-based (at p < 0.005, uncorrected) DTI analyses. On the other hand, Yurgelun-Todd et al. [105] reported that 11 BD patients had higher FA values in the midline of the genu relative to 10 matched comparison subjects. Mean diffusivity of all ROIs of the corpus callosum did not differ between groups. In addition to the studies using the ROI-based analyses, there have been two studies that adopted a technique of DTI tractography, which allows the virtual reconstruction of WM bundle fibres [98,118]. Houenou et al. [112] reconstructed the WM tract between the subgenual cingulate cortex and the amygdalo-hippocampal complex and calculated the mean FA values, the mean ADC values and the number of reconstructed fibres. The results from this tractography study demonstrated that the number of tract fibres between the left subgenual cingulate cortex and left amygdalo-hippocampal complex was greater in BD patients relative to comparison subjects. There was no difference in mean FA or ADC values for all reconstructed fibre tracts between groups. In another study by McIntosh et al. [113], bilateral uncinate fasciculus and anterior thalamic radiations were segmented using the tractography methodology. They found that FA values in the reconstructed tracts of both regions were reduced in BD patients.

DTI Studies of bipolar disorder using a voxel-based approach Only a few DTI studies using a voxel-based approach have been published. Mahon et al. [111] conducted a VBA of the FA data, using the registration module of the Automatic Registration Toolbox (ART; [119]). They reported higher FA values in the bilateral frontal WM and lower FA values in the left cerebellar WM in 30 BD patients relative to 38 comparison subjects (p < 0.001, cluster size
50). Mean FA values of the extracted WM bundles from those clusters, which encompassed the fibres of corticopotine, corticospinal, superior thalamic radiation fibres and pontine crossing tract, were also different between BD patients and comparison subjects. Versace et al. [107] examined 31 BD patients and 25 comparison subjects with a voxel-based approach, employing a nonlinear registration algorithm of the Tract-based Spatial Statistics (TBSS; [120,121]). BD patients showed reduced FA values in the right uncinate fasciculus and greater FA values in the left uncinate fasciculus, left optic radiation and right anterior thalamic radiation (corrected p < 0.05). These results suggest that there

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might be a right and left asymmetry in WM tracts, which connect the orbitomedial prefrontal cortex with subcortical limbic regions. Sussmann et al. [110] used small volume corrections for the hypothesized brain regions in the voxel-based approach when studying 42 familial BD patients and 38 comparison subjects. Spatial normalization of the images was conducted using SPM2. They found reduced FA values in the superior thalamic radiation regions in BD patients relative to comparison subjects (corrected p ¼ 0.018). This seems to contrast with the results of Versace et al. [107]. With the small volume correction for the uncinate fasciculus and the anterior limb of internal capsule, FA values in both regions was reduced in BD patients compared to comparison subjects. Another voxel-based DTI study using SPM2 suggested that there are WM abnormalities in the fronto-temporal regions in BD patients [106]. Reduced FA values in the inferior and middle temporal regions, which encompass the inferior longitudinal fasciculus, was observed in BD patients (corrected p ¼ 0.04), while ADC values were higher in the bilateral prefrontal and the right posterior frontal regions of the BD patients relative to comparison subjects (corrected p < 0.05). Areas of higher ADC values involved the part of the corpus callosum and the anterior frontooccipital fasciculus connecting the prefrontal cortex with the temporal and occipital regions.

DTI Studies of paediatric bipolar disorder There have been a few DTI studies of paediatric or adolescent BD patients. Adler et al. [114] examined 11 adolescents with BD and 17 matched healthy adolescents. The mean age of study participants was 14 years old (SD 2) and all adolescents with BD were in the first episode of mania and medication-naive at the time of scanning. The ROIs were selected in the same prefrontal regions as their previous study [101]. Adolescents with BD showed similar FA reductions in the superior frontal regions to those of adult BD patients [101]. A recently published study by Pavuluri et al. [116] also reported reduced FA values in the anterior corona radiata connecting the prefrontal regions with the brainstem in 13 adolescents with BD (mean age [SD] ¼ 14.8 years [2.5]) amongst a priori selected 6 ROIs. With a larger sample size (26 patients and 26 matched comparison subjects), Kafantaris et al. [117] reported reduced FA values in the right orbitofrontal, the bilateral temporal and the left occipital regions in BD patients (mean age [SD] ¼ 16.0 years [1.5]) relative to comparison subjects (mean age [SD] ¼ 15.3 years [1.5]) at the cluster size of
100 and the significance level of uncorrected p < 0.005. In addition, BD patients had higher ADC values in the bilateral subgenual, postcentral, precuneus, temporal and occipital regions at the same statistical significance level.

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Until recently, only one DTI study of children with BD has been published. Frazier et al. [115] compared FA values between 10 children with BD (mean age [SD] ¼ 9.2 years [3.0]) and eight age-matched children using both voxelbased and ROIs analyses. Children with BD had reduced FA values in the bilateral superior frontal tracts, which encompass the superior longitudinal fasciculus and the cingulate-paracingulate WM regions relative to referent children. FA values in the left orbitofrontal WM and the right anterior corpus callosum were also reduced in children with BD compared with healthy children.

Differences in clinical characteristics may also have contributed to the inconsistency of the findings from previous DTI studies on BD. All DTI studies, except for that of Adler et al. [114], included patients who were previously exposed to medications. Only a few studies have examined the relationships between medication use and WM integrity, even as a post-hoc analysis. A more homogeneous study group would be more efficient to detect the disease-specific WM pathologies. It would be also worthwhile to adopt the longitudinal study design and to examine how the moodstabilizers and/or the antipsychotics might affect the WM pathologies.

Summary and clinical implications Although several DTI studies of individuals with BD have suggested abnormalities of WM integrity particularly in the frontal cerebral regions (Figure 4), regional differences in directionality and/or the rate of diffusion between groups suggest these findings must be interpreted with caution. DTI methodology is a relatively new technique and there have been several methods, and also controversies, regarding the details of image acquisition and image analysis, especially concerns regarding possible misregistration issue. Considering that a relatively small number of studies on BD have been published to date following the first report in 2004, further studies with more sophisticated methodology that can address the aforementioned methodological problems, are warranted. This would provide a more definitive answer on the roles of the WM integrity abnormalities in the pathophysiology of BD.

Functional magnetic resonance imaging in bipolar disorder Introduction The technique of fMRI, which can measure signal intensity changes associated with increased neural activity, was introduced in the early 1990s. It has been a mainstay of neuroimaging methodology for evaluating the functional organization of the brain. Until recently, blood-oxygenlevel-dependent (BOLD) contrast has been the most popularly used fMRI technique [123]. With good spatial and high temporal resolution, this method permits the measurement of regional differences in oxygenated blood levels over time that are associated with changes in brain activity [124,125]. In addition to its use in exploring functional localization and cognitive neuroanatomy, the fMRI technique has

Fig. 4 Regions of increased and decreased FA in patients with bipolar disorder relative to comparison subjects. Abbreviations: Ant, Anterior; Post, Posterior; Sup, Superior. See also Plate 4. Red circles represent higher FA in patients with bipolar disorder relative to comparison subjects, blue circles represent lower FA in patients with bipolar disorder relative to comparison subjects. Parcellated white matter mask is adapted from stereotaxic white matter atlas [122].

Functional Imaging Techniques

widely been used for understanding and characterizing pathophysiological mechanisms of various psychiatric disorders [126]. Frontier areas of the fMRI include the characterization of endophenotypes and markers of disease-specific traits, which may potentially be predictive of treatment response or prognosis [126]. Central clinical features of BD are abnormal emotional regulations and impaired cognitive control [127]. In both domains of pathology, the prefrontal cortical-subcortical limbic functional connectivity might play an important role. Most fMRI studies on BD have, therefore, examined functional activation of brain regions associated with emotional and fronto-executive processing. Since the first fMRI report on BD by Yurgelun-Todd et al. [128] in 2000, over 45 fMRI studies have been published to date (Table 8). Amongst them, about half of the papers have been published in 2007 and 2008. Findings from the studies employing fMRI methods have enabled functional localization of some of the pathophysiological processes, which may be responsible for the development of BD.

Emotional processing Emotional processing involves the several steps including the perception, the induction and the regulation of emotions, all of which are associated with the key symptoms of BD, such as mood instability and affective lability [156]. The ventral-limbic regions including the amygdala, the striatum, the ventral cingulate, the ventromedial prefrontal cortex, the anterior hippocampus and the anterior insula might be activated during the performance of emotional processing [157]. Impaired cognitive controls of the dorsal frontal regions and the resultant cognitive-emotional interference have been consistently hypothesized as being related to the pathophysiology of BD. Both the hyperactive ventral-limbic network and the hypoactive dorsal-cognitive network have been implicated in the major functional alterations in BD. To examine the abnormal functional connectivity in emotional processing, several experimental paradigms have been adopted in the fMRI studies on BD. Recognition of the facial expression is the most frequently used task and other emotional challenges have been used as the stimuli to activate the relevant neural responses. Yurgelun-Todd et al. [128] examined the neural response of the dorsolateral prefrontal cortex and the amygdala during the fearful and happy facial affect recognitions in 14 BD patients and 10 comparison subjects using a ROI-based analysis. BD patients showed a reduced activation in the right dorsolateral prefrontal cortex and increases in the left amygdala activation to the fearful facial affect relative to comparison subjects. Signal changes in the dorsolateral prefrontal cortex and the amygdala in response to the happy facial expression did not differ between groups.

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This result suggested that BD patients had deficits in fearful affect recognition due to a disturbed prefronto-limbic circuitry. In addition to the prefronto-limbic abnormality, some reversal of the normal right-lateralized temporal lobe activation in response to emotional prosody was reported [132]. In an auditory affect study of 10 BD patients, a greater activation in the left superior temporal gyrus was observed compared to comparison subjects [132]. This result suggested that BD patients might have left-lateralized temporal lobe responses to emotional prosody in contrast to the right-lateralized in normal subjects. Blumberg et al. [139] suggested that patterns of neural disturbances might be different according to the mood states at the time of scanning and tried to characterize stateand trait-dependent functional abnormalities in BD patients. Since then, a substantial numbers of studies have tried to accurately characterize the mood state of BD patients at the time of scanning. In a study involving 17 euthymic BD patients, Wessa et al. [135] had participants perform the emotional and nonemotional Go-NoGo task during scanning to examine the cerebral underpinnings of the influence of emotional information on cognitive processes. Activation in the temporal cortical regions was increased in BD patients relative to comparison subjects when comparing the contrast between the emotional Go-NoGo and nonemotional Go-NoGo tasks. In addition, as compared with control subjects, overactivities to emotional versus neutral distracters were observed in the orbitofrontal cortex, the insula, the caudate and the dorsal cingulate cortex of BD patients. In another fMRI study where the emotional Go-NoGo task was used, manic patients showed a similar pattern of increased responses in ventral brain regions to the emotional stimuli [129]. In this study, manic patients showed a greater activation in the left ventrolateral prefrontal cortex to emotional stimuli and the activation in ventral and medial prefrontal regions was also increased in response to emotional distracters [129]. Those studies indicated that increased activity in the ventral frontal brain regions in euthymic as well as manic patients might reflect a greater demand for inhibition of emotional stimuli in BD patients relative to comparison subjects. Similarly, Lawrence et al. [130] reported that BD patients exhibited increased neural responses in subcortical (ventral striatal, thalamic, hippocampal) and ventral prefrontal cortical regions to both positive and negative facial expressions relative to comparison subjects. In contrast, Malhi et al. [131,133] reported attenuated ventral-limbic brain activity in response to the emotional stimuli in euthymic BD patients. In the study of euthymic female BD patients (n ¼ 12, [133]), diminished overall neural responses to emotional word stimuli were observed in cortical and subcortical structures, including the inferior frontal gyrus, the middle temporal gyrus, putamen,

Mitchell et al. [132]

Malhi et al. [131]

Lawrence et al. [130]

Elliott et al. [129]

0/10

10 controls 23/0

7/4 0/10

(9 MDD)b 11 controls 10 patients

11 patients

13/8

3/8

11 controls

12 patients

4/4

8 patients

5/3

10 controls

Gender (M/F)

9/5

Subjects (BD patients/ control subjects)

43 (2)

36 (13)

37 (12)

41 (11)

38 (10)

34

aged 19 to 54 yr

Mean age (SD)

all manic or hypomanic all medicated not available

9 depressed, 3 euthymic all medicated 4 rapid cycling

(7 manic, 1 hypomanic) 7 medicated 12 BD I, 9 MDD

all manic

6 manic,1 depressed, 7 euthymic all medicated 7 BD I

not available

Patients characteristics (subtype/current episode/medication)

Auditory emotional prosody

Affect-inducing captionedpictures recognition task

Facial affect recognition task

Emotional GoNoGo task

Facial affect recognition task

Experimental paradigm

" left STG during an auditory affect task suggesting left lateralization of the normal neural response to emotional prosody

brain activation of hypomanic patients involved the prefrontal and subcortical regions including the caudate and thalamus to normally activated regions during the emotional processingc

" ventral PFC and " subcortical (ventral striatum, thalamus, hippocampus) activation to both positive and negative facial affect

" left VLPFC activation to the emotional relative to neural stimuli " left medial PFC activation to emotional distracters

# right DLPFC and " left amygdala activation to the fearful facial affect

Resultsa

not examined

not examined

lithium/antidepressant medications were related to the normalization in the subcortical and dorsal PFC activity to emotional stimuli

not examined

negative correlation between CPZ equivalent antipsychotic medication dose and the amygdala activity for male patients

Clinical correlations

|

Emotional Processing Tasks Yurgelun-Todd 14 patients et al. [128]

Study

Table 8 Published fMRI research in patients with bipolar disorder.

184 Chapter 14

Altshuler et al. [136]

Wessa et al. [135]

Chen et al. [134]

Malhi et al. [133]

5/6

9/8

17 controls

11/6

17 controls

11 patients

10/7

2/6

8 controls

17 patients

13/3

0/12

12 controls

16 patients

13/0 0/12

(12 SPR)d 13 controls 12 patients

30 (7)

32 (7)

45 (11)

45 (13)

39 (13)

41 (13)

34 (6)

32 (4) 35 (9)

all depressed 9 medicated

15 medicated 11 BD I

17 euthymic

10 BD I, 7 BD II

all medicated

8 manic, 8 depressed

all euthymic 8 medicated 16 BD I

not available all medicated 12 BD I

Face matching task

Emotional GoNoGo task

Explicit/Implicit facial affect recognition task

Emotional Stoop task

# bilateral OFC (BA47) and right DLPFC (BA 9) and " left OFC (BA10) activation during emotional facial matching

" superior and ventral frontal gyral, precentral gyral, cingulate, putamen, and thalamic activation to the happy faces in BD depressed patients " precentral and postcentral gyral, MTG, parahippocampal gyral, striatum, thalamus, and brain stem activation to the fearful faces in all BD patients "bilateral OFC, right posterior cingulate gyrus, left insula, bilateral caudate nuclei during the inhibition of emotional distracters "right MTG, ITG, and STG activation during emotional Go-NoGo condition

" left fusiform gyral activation to the sad faces in BD manic patients

# IFG, STG, MTG, putamen, caudate, thalamus, and amygdala activations to emotional word stimuli

not examined

not examined

not examined

not examined

(continued)

Functional Imaging Techniques

| 185

Adler et al. [140]

Blumberg et al. [139]

15 controls

matched samples

10/10

20 controls

15 patients

5/0 18/18

(5 SPR)f 5 controls 36 patients

5/0

5/7

12 controls

30 (9)

29 (9)

32 (11)

32 (3) 39 (10)

33 (6)

42 (11)

42 (12)

Mean age (SD)

15 euthymic 10 medicated

23 medicated not available

11 manic, 10 depressed, 15 euthymic

not available all medicated 36 BD I

not available

all medication-free for at least 10 d

all euthymic

8 BD I

Patients characteristics (subtype/current episode/medication)

N-back working memory task

Stroop task

Verbal fluency task

Facial affect recognition task

Experimental paradigm

" fronto-polar PFC, temporal cortex, basal ganglia, thalamus, and posterior parietal cortex activation during the working memory task

# left rostral regions of the ventral PFC activation during the Stroop task within BD patients: " left caudal regions of the ventral PFC activation in depressed BD relative to euthymic BD patients/# right ventral PFC activation in manic BD relative to euthymic BD patients

" medial frontal cortex, left IFG, medial parietal cortex, cerebellum, right lingual gyral activation during the verbal fluency task

" left parahippocampal gyrus and # right VLPFC, left dorsal PFC, right cingulate, and right precentral gyral activation to the emotional stimuli in BD patients at baseline # left temporal gyrus and " bilateral prefrontal cortical activation to the emotional stimuli following lamotrigine monotherapy

Resultsa

not examined

no association between symptom severity and the degree of activation

not examined

no association between the depressive symptom changes and the lamotrigine-related regional activity changes

Clinical correlations

|

Fronto-executive Function Tasks Curtis et al. [138] 5 patients

3/5

8 patients

Jogia et al. [137] e

Gender (M/F)

Subjects (BD patients/ control subjects)

Study

Table 8 (Continued)

186 Chapter 14

Altshuler et al. [145]

Strakowski et al. [144]

Strakowski et al. [143]

Monks et al. [142]

Gruber et al. [141]

4/7

9/7

16 controls

11 patients

6/10

4/6

10 controls

16 patients

4/6

12/0

12 controls

10 patients

12/0

5/6

10 controls

12 patients

8/3

11 patients

36 (8)

30 (9)

28 (7)

25 (7)

8 medicated 11 BD I

16 euthymic

all euthymic -all medication-free for at least 1 mo 16 BD I

all medicated 10 BD I

46 (4)g

26 (8)

all euthymic

46 (3)g

11 BD I

all euthymic all medicated 12 BD I

25 (4)

37 (7)

Go-NoGo task

Stroop task

Continuous performance task

Two-back working memory task; Sternberg task

Stroop task

# right lateral OFC, left cingulate cortex, right hippocampal activation during the inhibitory task

# MFG, temporal cortex, putamen, and cerebellar vermis activation during the interference task

" VLPFC, parahippocampal, amygdala, insula, and visual association cortex and # medial prefrontal and fusiform gyral activation during the attention task

# bilateral frontal, temporal, and parietal and " left precentral, right medial frontal, and left supramarginal gyral activation during the working memory task no group difference during the Sternberg task

# right ACC and " right DLPFC activation during the interference condition

negative correlation between the duration of the manic episode and right frontal activity – no association between the symptom severity and the degree of activation (continued)

psychotropic medications were related to increased activity in DLPFC and ACC

positive correlation between task performance and MTG activity in BD patients

positive correlations between task performance and right inferior frontal and bilateral VLPFC activity in BD patients

not examined

positive correlation between CPZ equivalent antipsychotic medication dose and the left DLPFC activity

Functional Imaging Techniques

| 187

Mechelli et al. [149]

Drapier et al. [148]

McIntosh et al. [147]

35 (11)

16 medicated 29 BD I

22 medicated

21/24

42 (12) 38 (11)

not available

not available 42 medicated 20 BD I

45 controls

10/10 9/20

(20 unaffected first-degree relatives) 20 controls 29 patients

37 (12) 43 (10)

all medicated 42 BD I

all euthymic

all manic or hypomanic 7 medicated 10 BD I

Patients characteristics (subtype/current episode/medication)

not available

19/18 9/11

(27 SPR)f 37 controls 20 patients

39 (11)

36 (10)

41 (13)

31 (7)

Mean age (SD)

(41 SPR)i

21/21

7/4

11 controls

42 patients

6/4

5/8

13 controls

10 patients

Gender (M/F)

Subjects (BD patients/ control subjects)

Verbal fluency task

N-back working memory task

Hayling sentence completion test

Stroop task

Experimental paradigm

interaction effect between the diagnosis and the genotype of neuregulin 1 on the right OFC and the right inferior frontal regions post-hoc analysis showed " right OFC activation in BD patients with high-risk variant

" left ventral frontal pole cortical activation during the working memory task particularly in the unaffected relatives

" left DLPFC and # right insula activation during the sentence completion taskh

# left DLPFC, left VLPFC, left fusiform gyrus, and left precuneus activation and " left OFC and MFG activation during the interference task

Resultsa

no associations between the dose of medication, IQ, and depressive symptom, severity and the degree of activation

not examined

negative correlation between the reversal learning errors and the ventral striatum and the OFC activity

positive correlations between state anxiety scores and the left DLPFC and the left precuneus activity

negative correlation between the BDI scale scores and the left OFC activity

Clinical correlations

|

Kronhaus et al. [146]

Study

Table 8 (Continued)

188 Chapter 14

Pavuluri et al. [153]

Rich et al. [152]

Chang et al. [151]

6/4

5/5

10 controls

11/10

21 controls

10 patients

10/12

10/0

10 controls

22 patients

12/0

4/6

12 patients

10 controls

14 (2)

15 (2)

15 (3)

14 (3)

14 (3)

15 (3)

15 (3)

Studies on the adolescents or children with bipolar disorder Blumberg 10 patients 4/6 14 (3) et al. [150]

all euthymic all medication-free for at least 7 d

18 medicated 10 BD I

6 hypomanic, 4 depressed, 12 euthymic

20 BD I

12 medicated

not available

not available 7 medicated 12 BD I

10 BD I

Affective face processing task

Facial affect processing task

Two-back working memory task; International affective picture system task

Stroop task

# right VLPFC and " right pregenual anterior cingulate, amygdala, and paralimbic cortex activation to both angry and happy faces

" bilateral DLPFC, IFG, and right insula activation to the negatively valenced pictures " bilateral caudate, bilateral thalamus, left MFG/SFG, and left ACC activation to the positively valenced pictures " left amygdala, accumbens, putamen, and ventral PFC activation during the process of hostile face " left amygdala and bilateral accumbens activation during the process of fear face

" bilateral ACC, left putamen, left thalamus, left DLPFC, and right IFG and # cerebellar vermis activation during the working memory task

" left putamen and left thalamus activation during the Stroop task

not examined

(continued)

no association between the current mood, the use of medications, and the degree of activation

positive correlation between the hostile rating and the left amygdala activity

not examined

positive correlation between the depressive symptom severity and the ventral striatum activity

Functional Imaging Techniques

| 189

—

—

—

16 (1)

15 (2)

14 (3)

Mean age (SD)

not available

all depressed

13 medicated 3 BD I, 3 BD II, 2 BD NOS

5 hypomanic, 21 euthymic

24 BD I, 2 BD II

Patients characteristics (subtype/current episode/medication)

International affective picture system task

Motor inhibition task

Experimental paradigm

positive correlation between the depressive symptom severity and the left DLPFC activity at baseline positive correlation between the symptom improvement with 8-wk lamotrigine treatment and changes in the bilateral amygdala activity

# bilateral caudate, putamen, accumbens, and right ventral PFC activation when failing in the motor inhibition " right ventral PFC activation during the successful motor inhibition

Resultsa

not examined

Clinical correlations

Abbreviations: ACC, Anterior Cingulate Cortex; BA, Brodmann’s Area; BD, Bipolar Disorder; BDI, Beck Depression Inventory; CPZ, Chlorpromazine; DLPFC, Dorsolateral Prefrontal Cortex; fMRI, functional Magnetic Resonance Imaging; IFG, Inferior Frontal Gyrus; IQ, Intelligence Quotient; ITG, Inferior Temporal Gyrus; MDD, Major Depressive Disorder; MTG, Middle Temporal Gyrus; NOS, Not Otherwise Specified; OFC, Orbitofrontal Cortex; PFC, Prefrontal Cortex; SPR, Schizophrenia; STG, Superior Temporal Gyrus; VLPFC, Ventrolateral Prefrontal Cortex. a All results presented in Table 8 are those of patients with bipolar disorder relative to comparison subjects except where indicated otherwise. b This study was designed to directly compare the neural activity of BD and MDD during emotional processing. c The results were not from the between-group analyses. d Eleven patients with bipolar disorder were used as a psychiatric comparison group in this study. e This study examined the changes in neural activity of patients with bipolar disorder after a 12-week lamotrigine monotherapy. f This study was designed to directly compare the neural activity of BD and SPR during cognitive processing. g Standard error. h The results were of patients with bipolar disorder relative to patients with schizophrenia. i This study was of the patients with SPR and BD, which was designed to compare the subjects with high risk variant of neuregulin 1 gene and those without. j This study examined the changes in neural activity of adolescent patients with bipolar disorder after an 8-week lamotrigine monotherapy.

4/4

8 patients

9/8

17 controls

Chang et al. [155] j

12/14

26 patients

Leibenluft et al. [154]

Gender (M/F)

Subjects (BD patients/ control subjects)

|

Study

Table 8 (Continued)

190 Chapter 14

Functional Imaging Techniques

caudate, thalamus and amygdala, in patients relative to comparison subjects. Malhi et al. [131] examined the neural responses to the positive and negative captioned pictures in each group of 10 hypomanic females and 10 comparison subjects. Regions of brain activation in hypomanic patients involved subcortical regions, including caudate and thalamus as well as routinely activated prefrontal regions during the emotional processing [131]. This means that activation of caudate and thalamus to the emotional stimuli in BD patients might be dependent on mood state. Chen et al. [134] investigated the differential patterns of neural activation in response to the facial affect recognition between manic and depressed BD patients. Both BD groups showed increased neural responses in several brain regions to fearful facial expression relative to comparison group (n ¼ 8). Manic BD patients (n ¼ 8) exhibited increased activations in the left fusiform gyrus in response to sad faces. Implicit recognition of sad faces was associated with increased activity, while explicit recognition was associated with decreased activity in the limbic and frontal regions in manic BD patients. In contrast, when recognizing the happy faces, depressed BD patients (n ¼ 8) showed overactivation in the prefronto-striato-thalamic regions, including the

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191

superior and ventral frontal gyrus, the precentral gyrus, cingulate, putamen and thalamus relative to comparison subjects. These findings are consistent with the pre-existing theory of the abnormal ventral limbic network in BD [129,131,135,158]. On the other hand, Altshuler et al. [136] reported that BD patients had impaired dorsal and ventral prefrontal function during an emotional task, which may normally subserve the cognitive control of emotional processing. In their study, depressed BD patients showed reduced activations of the bilateral orbitofrontal and the right dorsolateral prefrontal cortex during the emotional facial expression task. In addition, increased activation of the left anterior prefrontal cortex (BA 10), which may be more specific to the depressed state, was also observed in BD patients relative to comparison subjects. Although the relatively small sample sizes and the variability of experimental paradigms of fMRI studies may make it difficult to draw a firm conclusion, currently available evidence collectively suggest increased activity in the ventral prefrontal cortex and the subcortical limbic structures during emotional processing in BD patients (Figure 5). Although less consistent amongst studies,

Fig. 5 Regions of increased and decreased activation under emotional processing tasks in patients with bipolar disorder. Abbreviations: Sup, Superior; Mid, Middle; Inf, Inferior. See also Plate 5. Regions of increased (triangle) and decreased (reverse triangle) activation under emotional processing tasks in patients with bipolar disorder from the Table 8. Regions were marked based on the Talairach coordinates, Brodmann areas or anatomical description in the reports. In patients with bipolar disorder, there were abnormal cortical and subcortical activations in the brain regions including prefrontal and temporal cortex, striatum, thalamus and amygdala when taking emotional processing tasks such as the facial affect recognition and emotional Go-NoGo tasks relative to comparison subjects.

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several prefrontal subregions may also be affected during the emotional processing in BD patients.

Fronto-executive control function Executive function, including working memory and the attention, has frequently been measured with the N-back working memory task, the Stroop test and the continuous performance test. These tasks normally activate the regions of the dorsolateral, the anterior cingulate and the ventral prefrontal cortex in healthy subjects [159,160]. Since the study of Curtis et al. [138] reporting an increased prefrontal cortical activation during the verbal fluency task in BD, several fMRI studies have reported altered activities in the prefronto-limbic network during the executive tasks in BD. Blumberg et al. [139] examined 36 BD patients (11 manic, 10 depressed and 15 euthymic mood state) and 20 comparison subjects using fMRI during the Stroop task. Signal changes in the left rostral region of the ventral prefrontal cortex during the task were attenuated in BD patients relative to comparison subjects and this finding appeared to be independent of mood state at the time of scanning. Within BD patients, there were, however, differential signal changes in the caudal regions of the ventral prefrontal cortex during the task between mood states. Activation in the left caudal region of the ventral prefrontal cortex was greater in depressed patients compared to euthymic patients, while the signal activation in the right ventral prefrontal cortex was attenuated in manic BD patients compared to euthymic BD patients. In the fMRI study of Strakowski et al. [144], 16 euthymic BD patients and 16 matched comparison subjects performed a counting Stroop interference task, which normally activates the regions of the anterior cingulate and the dorsolateral prefrontal cortex [161]. BD patients showed a lower task performance than comparison subjects. Although there was no difference in activation of brain regions commonly associated with the Stroop task, the anterior cingulate and the dorsolateral prefrontal cortices, BD patients demonstrated a lesser activation in the temporal cortex, the middle frontal gyrus, putamen and midline cerebellum relative to comparison subjects. This attenuated brain activation might be related to reduced task performances in BD patients by an inefficient modulation of impulse control including error detection and response inhibition. A study of remitted BD patients [146] also suggested that there are reduced activations in the dorsolateral and ventrolateral prefrontal cortex while performing the Stroop task in BD patients. Altshuler et al. [145] measured the neural response to the Go-NoGo task in 11 BD patients with manic episode and 13 comparison subjects. BD patients exhibited reduced activities in the right lateral orbitofrontal cortex, the right hippocampus and left cingulate cortex during the task relative

to comparison subjects. Decreased orbitofrontal activation in manic BD patients may reflect impaired roles of the orbitofrontal cortex in regulating or suppressing responses. Impaired function of the orbitofrontal cortex might be related to disinhibited behaviours commonly observed in BD patients with manic episode. Strakowski et al. [143] have studied 10 medication-free and euthymic BD patients and 10 matched comparison subjects. This study aimed to evaluate the state-independent abnormalities in brain functional activation of BD irrespective of medication effect. Medication-free and euthymic patients were enrolled since both medication ([128]; Blumberg et al., [162]; [130,141]) and mood state [134,139] have been reported to have effects on the functional signal changes in response to the cognitive or emotional stimulus. Brain regions of the limbic/paralimbic (parahippocampus, amygdala and insula), the ventrolateral prefrontal and visual association cortices exhibited a greater activation during the Continuous Performance Task in BD patients than in comparison subjects. In contrast, BD patients showed a decreased activation in the medial frontal cortex and the fusiform gyrus during the task relative to comparison subjects. Authors suggested that abnormal activation in the anterior limbic network might be an alternative strategy to process the attention information in order to compensate the inappropriate emotional network activation in BD patients. Similarly, another study of euthymic BD patients, examining the neural responses to the working memory task, reported that they have overactivations in the prefrontostriato-thalamic network [140]. During the performance of the N-back Working Memory Task, activities in the frontopolar prefrontal cortex, the temporal cortex, basal ganglia, thalamus and the posterior parietal cortex were increased in BD patients relative to comparison subjects. In interpreting currently available fMRI studies, several important points need to be taken into consideration. Small sample sizes could result in type 2 error and in studies with small sample sizes, inter-individual variability in the task performance could be an important confounding factor. Difference in the mood state at the time of scanning and a wide variability of cognitive tasks employed may make it difficult to directly compare findings of fMRI studies. For example, a task-specific brain dysfunction in BD was suggested by Monks et al. [142]. Reduced activations in the bilateral frontal, temporal and parietal cortex and increased activations in the left precentral, the right medial frontal and the left supramarginal gyri were observed in BD patients during the N-back task relative to comparison subjects. However, there was no between-group difference in the brain activation while performing the Sternberg task, which can also measure a working memory load. Despite these potential limitations, fMRI studies in BD have reported findings of functional abnormalities, both

Functional Imaging Techniques

increased and reduced activity, in the dorsal and ventral prefrontal cortices during the cognitive control tasks relative to comparison subjects.

Functional neuroimaging studies comparing bipolar disorder and other psychiatric disorders There have been a few fMRI studies examining differences in brain functional activities during the emotional or cognitive tasks in BD and other major psychiatric disorders including major depression and schizophrenia. In a study of 12 patients with BD, 9 patients with major depression and 11 comparison subjects [130], euthymic or depressed BD patients exhibited increased neural responses in subcortical and ventral prefrontal cortical regions to both positive and negative facial expressions relative to comparison subjects and patients with major depression. In contrast, patients with major depression demonstrated attenuated responses to all emotional expressions relative to comparison subjects. McIntosh et al. [147] reported a differential brain activation during the Hayling Sentence Completion Task between BD patients and schizophrenia who were clinically stable at the time of scanning. Increased activity in the left dorsal prefrontal cortex was observed in BD patients, whereas activity of the right insula was attenuated in patients with schizophrenia.

Medication effects in fMRI studies of bipolar disorder There have been debates on whether and how psychotropic medications affect the brain functional alterations in BD [156]. Given that most of the functional imaging studies of bipolar populations thus far were of patients who were previously exposed to the medications, the potential confounding effects of psychotropic medications on the findings should be taken into consideration in interpreting the results. Several fMRI studies did not find any potential medication effects on neural responses to cognitive control and emotional processing [135,139,145,146,150]. Some other studies, in contrast, suggested the psychotropic medications could ameliorate abnormal neural activity during the emotional or cognitive tasks. It was suggested that medication might partly normalize abnormally increased subcortical limbic activity to emotional stimuli ([128]; Blumberg et al., 2005; [130]) and attenuated prefrontal cortical activity to cognitive control stimuli [141]. For example, a significant negative correlation between antipsychotic medication dose and amygdala activity to the emotional expression was observed [128]. Patients who were taking psychotropic medications

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193

showed a smaller increase in subcortical limbic activity to emotional stimuli (Blumberg et al., 2005; [130]). Antipsychotic medications increased neural activity in the anterior cingulate and dorsolateral prefrontal cortices in response to a cognitive control task [141]. In a recent longitudinal study of euthymic BD patients, increased activities in the temporal cortical regions and diminished activities in the prefrontal regions during facial affect recognition task seem to be normalized with a 12-week lamotrigine monotherapy [137]. Similar findings were reported in adolescents with bipolar depression [155]. Adolescents with bipolar depression treated with lamotrigine for 8 weeks showed a reduction in the right amygdala activation to the negative stimuli, which was correlated with an improvement in depressive symptoms. In conclusion, there have been some inconsistencies regarding the potential effects of the psychotropic medications, which may be attributed to the heterogeneous patterns of medication use and a wide variability of study paradigms employed. Longitudinal studies with a controlled design of each class of psychotropic medications are needed to examine the potential effects of medications on the neural responses to emotional and cognitive stimuli in BD patients.

Potential applications of fMRI study for genetic characterization of bipolar disorder Drapier et al. [148] suggested that altered frontal activation in response to a working memory task might be associated with the genetic vulnerability for BD. They designed an fMRI study comparing 20 remitted BD patients, 20 of their unaffected first-degree relatives and 20 matched comparison subjects during the N-back task. Relative to comparison subjects, neural responses in the left frontal polar cortical regions to the working memory task were increased in unaffected relatives as well as in BD patients. Authors suggested that prefrontal functional abnormalities during working memory tasks might be a potential endophenotype for BD. Recently, imaging genetic studies, which examine how the specific gene might affect the brain function and whether the specific gene-related functional changes could increase the vulnerability to the disease, has been introduced in the research of BD. Mechelli et al. [149] examined the brain function while 29 BD patients and 45 comparison subjects underwent the verbal fluency task. They found the interaction effect between the diagnosis and the genotype of neuregulin 1 on the right posterior orbitofrontal gyrus. Increased activation in the right orbitofrontal gyrus was observed only in the BD patients with the high-risk variant of neuregulin 1. This study suggested the specific genetic pattern-associated changes in prefrontal cortical activation in BD.

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fMRI studies on paediatric bipolar disorder Based on the typical features of early-onset BD and a high genetic loading for the disorder, there has been interest in the functional brain pathophysiology of paediatric and adolescent BD patients. In the study of 10 adolescents with BD (aged 10–17 years) and 10 comparison subjects (aged 11–18 years) [150], adolescents with BD demonstrated increased signal activity of the left putamen and thalamus in response to the colournaming Stroop task relative to comparison subjects. Chang et al. [151] examined 12 male paediatric BD patients with familial burden (mean age [standard deviation, SD] ¼ 14.7 years [3.0]) and matched 10 comparison males (mean age [SD] ¼ 14.4 years [3.2]). All BD children were euthymic. The 2-back visuospatial working memory task and the International Affective Picture System were selected to measure the neural responses to cognitive and affective stimuli, respectively. Similar to the study of Blumberg et al. [139,150], BD children had greater activity in the bilateral anterior cingulate cortex, left putamen, left thalamus, left dorsolateral prefrontal cortex and the right inferior frontal gyrus in response to the visuospatial working memory task relative to comparison subjects. During the affective task, BD patients showed greater activity in the bilateral dorsolateral prefrontal cortex, the inferior frontal gyrus and the right insula in response to the negatively valenced pictures relative to comparison subjects. When viewing the positively valenced pictures, BD children had greater activity in the bilateral caudate and thalamus, the left middle and superior frontal gyrus and the left anterior cingulate cortex. Authors suggested that overall overactivity in prefronto-limbic regions might be associated with a hyperactive brain state and reflective of a developmental stage of BD. Pavuluri et al. [153] reported that euthymic, unmedicated paediatric BD patients (n ¼ 10, mean age [SD] ¼ 14.9 years [1.9]) showed a reduced activation in the right side of ventrolateral prefrontal cortex and an increased activation in the right pregenual anterior cingulate, amygdala and the paralimbic cortex in response to both angry and happy faces relative to comparison subjects (n ¼ 10, mean age [SD] ¼ 14.3 years [2.4]). In line with this result, which show exaggerated neural activity of the limbic area in response to emotional stimuli, Rich et al. [152] reported that paediatric BD patients had greater activity of the left amygdala, accumbens, putamen and ventral prefrontal cortex when exposed to hostility face and greater activity of the left amygdala and bilateral accumbens when exposed to fear face, relative to comparison subjects. Impaired motor inhibition may be associated with behavioural disturbance of paediatric BD patients, including impulsivity and irritability (McClure et al., [163]). To examine the underlying functional brain abnormalities for the

deficit in motor inhibition of paediatric BD patients, Leibenluft et al. [154] examined 26 adolescents with BD (mean age [SD] ¼ 13.6 years [2.6]) and matched 17 comparison subjects (mean age [SD] ¼ 14.6 years [1.8]). When failing in the motor inhibitory task, adolescents with BD showed attenuated neural responses in the bilateral striatal and right ventral prefrontal regions relative to comparison subjects.

Acknowledgements This work was supported in part by grants from the National Institute of Health (7K24DA015116, Dr Renshaw), from the National Alliance for Schizophrenia and Affective Disorders (NARSAD Independent Investigator Award, Drs Lyoo and Renshaw) and from the Korea Research Foundation (KRF-2008-220-E00021, Drs Lyoo and Renshaw).

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Functional Brain Imaging Studies in Bipolar Disorder: Focus on Cerebral Metabolism and Blood Flow John O. Brooks III1, Po W. Wang2 and Terence A. Ketter2 1 2

UCLA Semel Institute for Neuroscience and Human Behavior, Los Angeles, CA, USA Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA

Introduction Cerebral metabolic studies of bipolar disorder have provided significant contributions to our understanding of the disorder and its neural substrates. In this chapter we shall consider data obtained through several different scanning modalities. Our primary focus will be the gold standard of cerebral metabolism, positron emission tomography with flourodeoxyglucose-18 (18 FDG-PET). This neuroimaging test relies on the injection of 18 FDG and the subsequent detection of its uptake in the brain, often after a period of rest, but on occasion after the patient engages in a specified activity. Although not direct assessments of metabolism, we augment our discussion with consideration of cerebral blood flow data, derived from PET with oxygen-15 water (H215O), as well as single photon emission computed tomography (SPECT) with technetium-99m hexamethylpropyleneamine oxime (99m Tc-HMPAO) or technetium99m exametazime (99m Tc-EMZ).

Overall organization In this chapter, cerebral metabolism and blood flow findings are organized around the theme of corticolimbic dysregulation, which is the hypothesis that dysregulation of a corticolimbic network is a major contributor to the clinical phenomenology of bipolar disorder. Before reviewing neuroimaging research in this context, we first describe the hypothesis and its underlying neuroanatomy. The corticolimbicnetwork model [1–4] accounts for a range of clinical symptoms and neuroimaging findings in bipolar disorder. An adaptation of this model, provided in Figure 1, providesaschematicofnetworklinkagesacrossbrainregions that have been implicated in the pathophysiology of bipolar

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disorder. We integrate this network model to link previously proposed basal ganglia-thalamocortical circuits [5] and thus provide a theoretical explanation of the metabolic changes associated with bipolar disorder. Alexander and colleagues [5] described a series of basal ganglia-thalamocortical circuits, including limbic and lateral orbitofrontal circuits implicated in affective processes, and a dorsolateral prefrontal circuit that may contribute to integration of affective processes with higher cognitive functions. Dysfunction of these circuits may lead to impaired thalamic gating or modulation of sensory or affective information, which in turn could allow such input to disrupt cognitive and motor processes and thus contribute to the clinical profiles of mood disorders. Similarly, Mega and Cummings [7] suggested that frontal-subcortical circuit dysfunction could explain many of the clinical manifestations of bipolar disorder. We shall describe three frontalsubcortical circuits in more detail: dorsolateral prefrontal, lateral orbitofrontal and anterior cingulate.

Dorsolateral prefrontal and oribitofrontal circuits The origins of the dorsolateral prefrontal subcortical circuit [7] lie in Brodmann’s Areas (BA) 9 and 10, which are located in dorsal and anterior portions of the lateral convexities of the frontal lobes. From BA 9 and 10, neurons project to the caudate nucleus and then directly to the mediodorsal globus pallidus interna and indirectly to the dorsal globus pallidus externa. The dorsal global pallidus externa projects to the lateral subthalamic nucleus from which fibres terminate in the globus pallidus interna and substantia nigra pars reticulata. The output from both structures terminates in the ventral anterior and mediodorsal thalamus, which in turn projects back to BA 9 and 10 to complete the circuit. The dorsolateral prefrontal circuit receives afferent projections from BA 46 and 7a and has efferent projections to BA 46 and 8.

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pallidum as well as the rostrodorsal substantia nigra. The ventral pallidum provides projections to the magnocellular mediodorsal thalamus, which completes the circuit by projecting back to the anterior cingulate. The subgenual prefrontal cortex is the region of the anterior cingulate that is inferior and posterior to the genu of the corpus callosum and commonly described as BA 25. The subgenual prefrontal cortex has both efferent and afferent connections with the ACC, as illustrated in Figure 1.

Clinical expressions of circuits

Fig. 1 A model of corticolimbic dysregulation in bipolar disorder. Areas generally associated with increased activation in bipolar disorder are in red and those with decreased activation are in blue. Note that colour-coding of regions is intended to represent the consensus findings for the region, because all findings have not been uniform. Numbers for BAs are provided where appropriate. ACC ¼ anterior cingulate cortex; AMYG ¼ amygdala; ATC ¼ anterior temporal cortex; CV ¼ cerebellar vermis; DLPFC ¼ dorsolateral prefrontal cortex; HYPTH ¼ hypothalamus; MOFC ¼ medial orbital prefrontal cortex; PHG ¼ parahippocampal gyrus; SGPFC ¼ subgenual prefrontal cortex; THAL ¼ thalamus; VLPFC ¼ ventrolateral prefrontal cortex. From Brooks et al. [6]. See also Plate 6.

The orbitofrontal circuit [7] originates in the anterior and ventral portions of the lateral convexities of the frontal lobes in BA 10 and 11, sending projections to the ventromedial caudate, which in turn projects to the mediodorsal globus pallidus interna as well as the substantia nigra pars reticulata. The globus pallidus and the substantia nigra project to the ventral anterior thalamus and the magnocellular division of the mediodorsal thalamus. The circuit is completed through the projections of the thalamus to the lateral orbitofrontal cortex. The orbitofrontal circuit has afferent projections from the superior temporal lobe and the orbitofrontal area as well as amygdala, rostromedial thalamus, medial substantia nigra and dorsal raphe. Efferent connections from the orbitofrontal circuit extend to the orbital and medial frontal areas, the mediofrontal aspect of BA 9, portions of the anterior cingulate and the insula.

The prefrontal cortex in general, and the dorsolateral prefrontal circuit in particular, are implicated in many neurocognitive and affective modulatory functions that are relevant to bipolar disorder, such as attention, reasoning and decision making, temporal organization of behaviour, working memory, organization of information, relation of cognition and emotion and modulation of emotion. The orbitofrontal circuit mediates behaviour and impairments associated with irritability and affective liability. In healthy subjects, the anterior cingulate cortex has been associated with performance monitoring [8] and is thought to be an important mediator of motivated behaviour [7]. The dorsal and ventral aspects of the anterior cingulate appear to be related to cognitive and affective processing, respectively. The subgenual prefrontal cortex may contribute to modulation of human mood states [9]. More importantly, because of the connections between the subgenual prefrontal cortex, the anterior cingulate cortex and other limbic regions, the subgenual prefrontal cortex may play a significant role in the integration of cognitive and emotional information [4].

Summary and implications The corticolimbic network includes neuroanatomical circuits that give rise to many of the behaviours and cognitive abilities that are altered in bipolar disorder. Of course, correlative function does not itself establish causality, but a number of structural and functional studies support the hypothesis of corticolimbic dysregulation as an explanation of many features of bipolar disorder. For example, resting state functional magnetic resonance imaging studies of major depression [10] suggest that cerebral metabolic changes may reflect network dysregulation.

Anterior cingulate circuit Mega and Cummings [7] described the anterior cingulate circuit as originating in BA 24 of the anterior cingulate, which provides input to the ventral striatum (ventromedial caudate, ventral putamen, nucleus accumbens and olfactory tubercle). From the ventral striatum, there are projections to the rostromedial globus pallidus interna and ventral

Cerebral blood flow and metabolism across affective states To appreciate better the nature of corticolimbic metabolic dysregulation in bipolar disorder, we shall describe findings according to the affective state of the participants. We consider only depression, mania and euthymia because,

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Fig. 2 Metabolic changes associated with bipolar depression relative to healthy controls. Decreased absolute metabolism is in blue. From Brooks et al. [6]. See also Plate 7.

to our knowledge, there are no neuroimaging studies of exclusively mixed episodes and in general patients in mixed states have been analysed in toto with patients in other mood states (primarily mania). Many studies have been performed with medicated bipolar disorder patients, which can complicate interpretation. However, medications may not confound neuroimaging findings as much as some have contended [11].

Cerebral metabolism studies in bipolar depression Cerebral metabolic studies of bipolar depression are not as numerous as those of unipolar depression, although extant studies suggest a number of similarities between the two. Studies have commonly detected decreased dorsolateral prefrontal cortical metabolism using 18 FDG-PET [6,12–17] and cerebral blood flow using H2 15 O-PET [18] or 99m Tc-HMPAO-SPECT [19,20]. However, a few reports failed to detect differences between depressed bipolar patients and healthy controls [21–23]. In a group of 17 treatment-resistant, largely rapid-cycling, medication-free inpatients diagnosed with moderate to severe bipolar depression, Ketter et al. [16] performed resting 18 FDG-PET scans and found that, compared to healthy controls, the depressed bipolar disorder patients exhibited decreases in absolute metabolism (i.e. the actual metabolic rate computed based on arterial blood sampling and the cerebral PET scans) in the inferior, middle and superior frontal gyri (BA 8, 9, 10, 44, 45, 46). In addition, decreased absolute temporal (BA 22, 39, 40, 42) metabolic rates were observed relative to control subjects. Ketter et al. did not find evidence of regional absolute metabolic increases. When metabolic rates were normalized to whole brain metabolism, there was evidence of not only relative metabolic decreases with a similar distribution to the absolute decreases, but also relative metabolic increases in anterior

limbic and paralimbic structures including the right amygdala, putamen and caudate. Ketter et al.’s [16] pattern of results may have been specific to the clinical characteristics of their sample of treatmentresistant, and in many cases rapid cycling, patients and thus not representative of bipolar depression in general. To check this possibility, Brooks et al. [6] performed a resting 18 FDG-PET study with a group of 15 medication-free depressed bipolar outpatients who were not selected on the basis of treatment resistance or rapid-cycling, and thus probably more representative of the clinical population as a whole. As illustrated in Figure 2, when compared to healthy controls, patients with bipolar depression exhibited decreased absolute metabolic rates in dorsolateral prefrontal cortex (BA 10, 46), medial orbital prefrontal cortex (BA 10, 11), anterior cingulate (BA 24, 32) and subgenual prefrontal cortex (BA 25). Analysis of normalized cerebral metabolism yielded a similar pattern of findings. Brooks et al. did not find evidence of increased absolute or normalized limbic metabolism, which suggests that limbic hypermetabolism may be specific to treatment-resistant and/or rapid-cycling bipolar depression. Brooks et al.’s findings were replicated in a sample of mostly medicated patients with bipolar depression [24], where depressed patients exhibited decreased metabolism in bilateral prefrontal, insula and cingulate cortices. Brooks et al.’s [6] and Ketter et al.’s [16] studies included patients diagnosed with bipolar disorder type I as well as those diagnosed with type II. In a study restricted to 13 patients with type II, 18 FDG-PET scans were obtained from patients who were taking therapeutic doses of lithium or divalproex and healthy controls [25]. Interestingly, these depressed type II patients exhibited increased limbic and paralimbic metabolism (in the amygdala, orbitofrontal cortex, anterior cingulate and insula) in a fashion analogous to the study of Ketter et al. However, in a study of younger, depressed bipolar disorder patients, we did not

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find altered absolute cerebral metabolism relative to healthy controls in the dorsolateral prefrontal cortex or the subgenual prefrontal cortex [26], but did find evidence of differential relations between both regions and performance on an attention task that suggested that individual differences in subgenual prefrontal metabolism were related to attention and differences in dorsolateral prefrontal metabolism to inhibitory control. A recent study compared cerebral metabolism using 18 FDG-PET in heterogeneously medicated subjects diagnosed with bipolar (N ¼ 12) or unipolar (N ¼ 18) depression [24]. Although the sample size was limited, the authors found evidence of a greater decrease in prefrontal and anterior cingulate metabolism in depressed bipolar patients compared to healthy controls. For patients with unipolar depression, there was evidence of lower metabolism in the prefrontal cortex, posterior cingulate and insula compared to healthy controls. The authors did not find any evidence of hypermetabolic regions in their depressed patients (either bipolar or unipolar) compared to healthy controls. An older 18 FDG-PET study of 7 bipolar and 3 unipolar heterogeneously medicated patients who were depressed also reported prefrontal hypometabolism relative to healthy controls [17]. Another of the early studies of cerebral metabolism in bipolar depression revealed prefrontal hypometabolism [27]. This study compared medication-free patients diagnosed with bipolar (N ¼ 10) or unipolar (N ¼ 10) depression to patients with obsessive/compulsive disorder and depression (N ¼ 10) and controls. Although current neuroimaging analysis programs were not available, Baxter et al. [27] reported that patients with unipolar or bipolar depression exhibited similarly lower dorsolateral prefrontal metabolism compared to healthy controls. Interestingly, the authors did not find any differences between patients with unipolar depression and those with bipolar depression. Although this study suggests that there may be cerebral blood flow similarities in unipolar and bipolar depression, the analytic techniques and limited statistical power could account for the inability to detect cerebral metabolic differences between unipolar and bipolar depression in this study. In one report, in 16 mildly depressed unmedicated treatment-resistant, largely rapid-cycling, medication-free bipolar inpatients compared to healthy controls, relative metabolic activity was increased in the left prefrontal cortex, including ventrolateral structures such as the inferior frontal gyrus [16] a finding reported in some studies of unmedicated depressed unipolar patients imaged in the resting condition [21,28–30]. Some (but not all) studies have found evidence of normalized amygdala hypermetabolism. For example, Ketter et al. [16] reported amygdala hypermetabolism when their absolute 18 FDG-PET findings were normalized to whole brain metabolism. In addition, other work has reported

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amygdala hypermetabolism associated with bipolar depression in unmedicated patients [31]. The reasons for the somewhat variable findings of 18 FDG-PET studies are unclear. Studies that reported limbic hypermetabolism included medicated or unmedicated patients, as have studies that reported hypometabolism. An explanation based on the presence of cerebral metabolic subtypes is not readily supported, because the samples of the studies do not differ systematically. Moreover, there is no reason to expect such subtypes would exert such a strong influence in each study.

Cerebral blood flow studies in bipolar depression Several researchers have studied the neural substrates of bipolar depression using H2 15 O-PET-PET, which provides an index of cerebral blood flow, which is believed to vary with cerebral metabolism. In a H2 15 O-PET study involving transient induced sadness in 11 depressed and 9 euthymic bipolar disorder patients taking lithium or valproate, Kr€ uger et al. [32] found that for both depressed and euthymic patients, sadness was associated with increased blood flow in the insula and cerebellum as well as decreased blood flow in the dorsal prefrontal cortex, medial orbitofrontal cortex, posterior cingulate and temporal cortex. Euthymic patients diverged from their depressed counterparts in that only euthymic patients exhibited increased blood flow in the anterior cingulate, whereas depressed patients uniquely exhibited increased blood flow in the lateral prefrontal cortex. Prior to any mood induction, euthymic patients exhibited greater blood flow in the anterior cingulate and orbitofrontal cortex. Thus, the results from this blood flow study seem to be more consistent with 18 FDG-PET findings of prefrontal hypometabolism in bipolar depression. Cerebral blood flow does not always mirror cerebral metabolism. Indeed, in some situations blood flow and metabolism appear to be dissociated [33]. For example, there is preliminary evidence that cerebral blood flow and metabolism are positively correlated in 9 healthy controls and 9 unmedicated depressed bipolar disorder patients [33], but not in 8 unmedicated patients diagnosed with unipolar depression. Thus, there is probably a positive correlation between cerebral blood flow and metabolism in bipolar disorder.

Summary of cerebral blood flow and metabolism studies in bipolar depression Although there is some variability across studies, including a few null results, current research permits some generalizations. In terms of the corticolimbic dysregulation model, it appears that cerebral metabolism in bipolar de-

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pression is characterized by prefrontal hypometabolism, particularly in the dorsolateral and medial orbital regions. This hypometabolism is generally found in the temporal cortex as well, although deeper limbic structures have been found to exhibit hypermetabolism in certain subsets of depressed bipolar disorder subjects (e.g. rapid cycling and treatment resistant). There is also a reasonable case to be made for hypometabolism in both the anterior and posterior cingulate, to varying degrees, with probable hypometabolism in the subgenual prefrontal cortex. Blood flow studies are largely consistent with the metabolic studies in that patterns of perfusion typically overlap regions implicated in metabolic studies. In bipolar depression it appears that prefrontal circuits exhibit the most change in association with depression. Anterior cerebral blood flow and metabolism decreases often correlate with the severity of bipolar and unipolar depression [16,21,27,30,34–43]. However, some studies failed to detect such a relation [44–48]. This could result from lack of sensitivity of measures of cerebral metabolism or mood, or both. Importantly, there is notable concordance between metabolic dysregulation and structural alterations (described elsewhere in this volume).

Cerebral metabolism studies in mania The study of mania presents abundant challenges because of the volatile clinical status of manic patients. Consequently, studies of mania are few and typically characterized by small samples, even by neuroimaging standards, of patients with varying current medications. Indeed, in the past 20 years, there have only been four 18 FDG-PET studies of mania. One of the earliest 18 FDG-PET studies of mania included six unmedicated patients and, without the benefit of contemporary analytic techniques, reported increased lateral prefrontal metabolism compared to controls [27]. However, this finding was not replicated in later work.

A larger-scale study in primarily medicated patients that suggested dorsolateral prefrontal cortex dysregulation used resting 18 FDG-PET [49]. In this study, the authors performed a factor analysis on the 26 regions of interest (ROI) they defined and then argued for the existence of four categories representing: (1) an anterior/posterior gradient; (2) left amygdala/right temporal: (3) left frontal/right limbic: and (4) anterior cingulate. They computed factor scores for each patient based on the factors they defined to determine whether the groups could be distinguished based on their metabolic patterns. For both the anterior/posterior gradient factor and the left amygdala/right temporal factor, they found that 15 manic patients exhibited lower normalized metabolic rates than healthy controls. al-Mousawi et al. noted that the anterior/posterior factor largely reflected activity in the DLPFC. Thus, manic patients exhibited hypometabolism in the DLPFC relative to controls [49]. Drevets and colleagues [9] published a resting 18 FDG-PET study of paralimbic metabolic dysregulation, which reported increased resting subgenual prefrontal metabolism in four patients (only one of whom was medicated) with bipolar mania. Notably, the definition of the subgenual prefrontal cortex in Drevets’ study is slightly different than ones used subsequently. In particular, Drevets’ region of interest tends to encompass more of BA 24, which is more pregenual. The more common definition of the subgenual prefrontal cortex typically comprises BA 25, which includes the rectal gyrus. The actual significance of the differing definitions is unclear. We recently completed a resting 18 FDG-PET study in eight primarily briefly medicated patients with mania, which was remarkable for the degree to which the results were consistent with an amalgam of previous findings [50]. As shown in Figure 3, we found evidence of simultaneous decreased prefrontal metabolism as well as limbic/paralimbic hypermetabolism. Specifically, hypometabolism was found in the dorsolateral prefrontal cortex as well as a

Fig. 3 Metabolic changes associated with bipolar mania relative to healthy controls. Regions with decreased metabolism are in blue, and increased metabolism in red. From Brooks et al. (2010). See also Plate 8.

Functional Brain Imaging Studies in Bipolar Disorder

portion of the anterior cingulate cortex. We did not find evidence of altered amygdala metabolism, but metabolism was increased in the adjacent hippocampal complex and marginally so in the subgenual prefrontal cortex. Given the variability in findings of altered amygdala metabolism in mania, it may be that such perturbations are associated with specific tasks as opposed to a state feature of mania.

Cerebral blood flow studies in mania Early studies of cerebral blood flow alterations in mania tended to be somewhat nonspecific, ranging from finding no difference between 30 medicated manic patients and controls [51] to generally increased left hemisphere cerebral blood flow in a sample of 11 mostly unmedicated manic patients [52]. In a study that investigated the relation between neurocognitive function and cerebral blood flow, Benabarre et al. [53] performed resting 99m Tc-HMPAO-SPECT scans of 7 manic, 8 hypomanic, 12 depressed and 3 euthymic unmedicated bipolar patients. Unfortunately, the results were not reported according to mood state, but Benabarre et al. found a relation between memory and decreased frontal metabolism. Another resting N-isopropyl-p123 I-iodoamphetamine 123 IMP-SPECT study suggested evidence of decreased frontal blood flow in 11 patients with bipolar mania [41]. A resting 99m Tc-EMZ-SPECT study of 7 patients who developed mania after lithium was replaced with placebo revealed evidence of increased blood flow in the anterior cingulate cortex [54]. A third resting state 99m Tc-HMPAO-SPECT study of mania found that compared to healthy controls, 5 medication-free patients with mania exhibited decreased blood flow in the right dorsal and basal temporal cortices [55]. This finding is somewhat at odds with studies that have suggested increased metabolism in deeper temporal structures. Blumberg et al.’s [56] H2 15 O-PET study of five manic and six euthymic medicated bipolar patients with six healthy controls revealed a decreased activation of the prefrontal area during a word generation task. In particular, manic subjects exhibited decreased activation in BA 10 relative to control subjects. Blumberg et al. posited that decreased blood flow in the prefrontal cortex could be responsible for some of the cognitive and emotional symptoms of mania, especially impaired planning, judgement and insight. Indeed, Blumberg et al. [56] also suggested that decreased prefrontal metabolism may be associated with cognitive and emotional symptoms of mania and that impaired orbitofrontal modulation of the amygdala and hypothalamus could contribute to dysregulation of more primitive affective processes. In subsequent work, Blumberg et al. [57] studied five manic patients and six euthymic medicated patients with H2 15 O-PET and found increased left anterior cingulate activity and increased left caudate activity in manic

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compared to the euthymic patients. They hypothesized that increased anterior cingulate activity could explain the attention and cognitive dysfunction associated with mania. Rubinsztein et al. [58] compared the performance of 6 manic bipolar and 6 depressed unipolar primarily medicated patients to that of 10 controls on a decision-making task administered during H2 15 O-PET scans, which allowed assessment of regional cerebral blood flow. They found the expected performance differences amongst the groups, but also reported activation (increased blood flow) in the anterior cingulate gyrus of manic patients and reduced activation in the superior frontal gyrus. Rubinsztein et al.’s findings are consistent with those of Blumberg et al. [56], who found decreased right prefrontal blood flow in a group of six manic patients compared to five euthymic bipolar patients.

Summary of cerebral blood flow and metabolism studies in mania As with bipolar depression, cerebral metabolic findings have been somewhat variable for bipolar mania, but certain themes are consistent with the hypothesis of corticolimbic dysregulation. In general, the evidence appears fairly consistent regarding prefrontal (especially orbitofrontal and dorsolateral) cortex hypometabolism associated with mania. The finding of limbic and paralimbic hypermetabolism conjointly with prefrontal hypometabolism suggests that some clinical signs of mania could reflect inadequate regulation of a hyperactive limbic network. This inadequacy of regulation could give rise to increased metabolism in the subgenual prefrontal cortex, which presumably mediates aspects of the limbic/prefrontal interface. Cerebral blood flow studies that have included different cognitive tasks suggest that metabolic dysregulation in several regions manifest as hypoactivation (dorsolateral prefrontal cortex) or hyperactivation (anterior cingulate cortex) compared to control subjects on tasks of decisionmaking or word generation.

Cerebral metabolism studies in euthymic bipolar disorder patients Few cerebral metabolic studies have targeted the euthymic phase of bipolar disorder. Yet, there is increasing evidence that at least some of the pernicious changes associated with syndromal mood episodes in bipolar disorder persist into euthymia. Thus, it is important to not only clarify mood states of study participants, but to conduct studies in different mood states. An early 18 FDG-PET study of 16 bipolar and 4 unipolar medication-free patients used mild electrical shock during the uptake phase of the scan and found evidence of decreased prefrontal metabolism in the patient group relative to healthy controls [14]. The authors suggested that this

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difference could be responsible for some of the cognitive deficits associated with the disease. Ketter and associates found that in primarily treatment resistant rapid cycling bipolar disorder unmedicated patients during euthymia compared to healthy controls, resolution of the prefrontal absolute hypometabolism and anterior paralimbic normalized hypermetabolism seen in depression, but persistence of cerebellar normalized hypermetabolism [16]. We reported a recent study that provided more comprehensive evidence of cerebral metabolic dysfunction during euthymia in bipolar disorder. We performed the first study using a group of euthymic bipolar disorder patients over the age of 50 (average age 59 years) and administered resting 18 FDG-PETscans [6]. The patient sample comprised primarily medicated patients diagnosed with bipolar disorder type I or II. Our primary focus was to explore the degree of corticolimbic metabolic dysregulation during euthymia, so we performed ROI analyses using the regions specified in Figure 1. We generated a statistical parametric map, which is shown in Figure 4. Even though the bipolar disorder patients in this sample had at most minimal affective symptoms and were taking varying medications, there was evidence of corticolimbic dysregulation. Specifically, prefrontal structures, including the dorsolateral prefrontal cortex, and to a lesser extent the ventrolateral prefrontal cortex, exhibited decreased normalized resting metabolism compared to healthy controls. Conversely, limbic (parahippocampal gyrus, amygdala) and to a lesser extent paralimbic (subgenual prefrontal cortex, anterior temporal cortex) exhibited increased normalized resting metabolism. We hypothesized that the corticolimbic metabolic dysregulation that we observed could contribute to the residual neurocognitive and behavioural changes that have been observed in older adults with bipolar disorder.

Cerebral blood flow studies in euthymic bipolar disorder patients Most studies of cerebral blood flow in the euthymic phase of bipolar disorder are task-specific. Thus, the interpretation of the studies must be made in light of the task performed as opposed to traits that could be expressed in resting state studies. A recently published resting state cerebral blood flow study of younger bipolar disorder patients during a period of euthymia employed 99m Tc-HMPAO-SPECT [59]. Consistent with the results of our 18 FDG-PET study of older adults described previously [6], the authors found that when compared to healthy controls, 16 medicated euthymic bipolar disorder patients exhibited decreased blood flow in the medial frontal, cingulate and medial temporal regions. However, this SPECT study did not report evidence of alterations in perfusion in limbic regions that would correspond to the study by Brooks et al. [6] in older adults. Results of task-related studies have been variable, and could reflect task demands, but do provide important information regarding cerebral changes. For example, a blood flow study of six euthymic medicated bipolar disorder patients did not demonstrate superior temporal abnormalities in a verbal fluency task as assessed by H215O-PET [60]. However, H215O-PET study of brain responses to novel motor sequences in 13 primarily medicated euthymic bipolar disorder type II patients revealed that instead of activating a superior parietal and supplementary motor area circuit as in controls, the bipolar disorder patients exhibited rather widespread activation of medial prefrontal and limbic structures and insula [61]. Blumberg et al. [56] used H215O-PET and a word generation task and found evidence of decreased prefrontal blood flow (BA 11) in eight primarily unmedicated euthymic bipolar I disorder patients. Deckersbach et al. [62] used H215O-PET in conjunction with the study phase of a memory test and found that

Fig. 4 Resting state cerebral metabolic differences in older, euthymic patients with bipolar disorder compared to healthy controls. Regions with increased metabolism in bipolar disorder patients are in red and those with decreased metabolism are in blue. From Brooks et al. [6]. See also Plate 9.

Functional Brain Imaging Studies in Bipolar Disorder

eight primarily unmedicated euthymic bipolar I disorder patients exhibited decreased prefrontal (BA 9, 46) blood flow compared to healthy control subjects. We reported evidence of differential associations between resting cerebral metabolism and verbal recall deficits in 16 mostly medicated older adults with bipolar disorder and 11 healthy comparison subjects [63]. Specifically, we found evidence that verbal memory deficits were more strongly related to prefrontal hypometabolism and paralimbic hypermetabolism in bipolar disorder subjects than in healthy comparison subjects.

Summary of cerebral blood flow and metabolism studies in euthymic bipolar disorder patients Because of the paucity of studies of cerebral metabolism during euthymia, conclusions that may be drawn regarding trait abnormalities of cerebral metabolic dysregulation in bipolar disorder are limited. Based on studies of older adults with bipolar disorder, it appears that repeated episodes of dysregulation of prefrontal cortex and limbic, and to some extent paralimbic, structures during affective episodes could lead to more pernicious dysregulation that persists in euthymia. The persistence of abnormalities in euthymia in older patients could be related to the combination of ageing and illness progression. Blood flow studies that have incorporated cognitive tasks support the contention that trait abnormalities are present at least in the dorsolateral prefrontal cortex and certain limbic structures.

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dysregulation of the dorsolateral prefrontal circuit and, to a lesser extent, the anterior cingulate circuit. Manic episodes appear be associated with dorsolateral, and to some degree ventrolateral, prefrontal hypometabolism. There also seems to be consensus that hypermetabolism occurs in limbic (parahippocampal gyrus and amygdala) and paralimbic (subgenual prefrontal and anterior cingulate) regions. As with bipolar depression, decreased dorsolateral prefrontal metabolism may contribute to attention deficits. Limbic hypermetabolism may contribute to the affective instability that characterizes mania. Manic episodes thus appear associated with diffuse corticolimbic dysregulation through all major circuits. Curiously, studies have not provided evidence that supports cerebral metabolic differences in the thalamus however. This could be related in part to changes being more difficult to detect due to the thalamic subregions involved having a smaller volume compared to the dorsolateral prefrontal cortex. Continued episodes of corticolimbic dysregulation, at least from a metabolic perspective, may contribute to more persistent dysregulation during euthymia. Evidence thus far appears to support this contention, although there are few cerebral metabolic studies of the euthymic phase of bipolar disorder and only one study of older euthymic patients with bipolar disorder. Longitudinal studies of cerebral metabolism across mood states and across the life span are necessary for a more comprehensive understanding of the cerebral metabolic dysregulation in bipolar disorder.

References Conclusions Cerebral metabolism and blood flow studies to date support the general contention that bipolar disorder is manifest at least in part through corticolimbic dysregulation. In particular, in older patients with bipolar disorder, dorsolateral and medial orbital prefrontal hypometabolism may persist through euthymia. Limbic and paralimbic hypermetabolism may be phenomena that increase over the course of the illness as suggested by the presence in euthymic older patients. Collectively, metabolic studies of bipolar disorder suggest several areas of corticolimbic dysregulation. It appears that in both depression and mania, dorsolateral prefrontal cortex hypometabolism contributes to the attention deficits that characterize affective episodes. Other areas of hypometabolism include the subgenual prefrontal cortex and, to some extent, the orbitofrontal cortex. Although many studies have not found evidence of limbic and/or paralimbic hypermetabolism, a few researchers report such hypermetabolism in rapid-cycling or treatment-resistant bipolar depression. Thus, in terms of cerebral metabolic changes, bipolar depression may be more associated with

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Neurotransmitter Systems in Bipolar Disorder Marina Nakic1, John H. Krystal1 and Zubin Bhagwagar1,2 1 2

Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA Bristol Myers Squibb, USA

Bipolar disorder is a severe, chronic debilitating disorder which exerts a crippling burden on individuals and their families. According to the National Comorbidity Survey replication, the lifetime prevalence for bipolar I and II disorders is 1.0% and 1.1%, respectively [1]. The World Health Organization Global Burden of Disease study ranked bipolar disorder sixth amongst all medical disorders in years of life lost to death and disability [2]. The lifetime risk of suicide in patients with diagnosis of bipolar disorder ranges from 8% to 20% [3]. Despite these worrisome statistics, pathophysiology of bipolar disorder remains largely unknown. However there is an abundance of data implicating abnormalities of monoaminergic (dopaminergic, noradrenergic, serotonergic), cholinergic, glutamatergic, GABA-ergic, glucocorticoid and peptidergic systems in pathophysiology of bipolar disorder [4]. These findings have contributed to elucidating some aspects of the pathophysiology of the bipolar disorder and influenced development of pharmacological strategies over the past several decades. The major findings implicating the involvement of the above listed neurotransmitter systems in bipolar disorders will be reviewed in this chapter.

The role of monoamines and acetylcholine in the pathophysiology of bipolar disorder Monoaminergic hypotheses The formulation of catecholamine hypothesis of mood disorders dates back to the 1960s. The hypothesis, independently developed by Bunney and Davis [5] and Schildkraut [6], postulates that a deficiency of monoamine neurotransmitters norepinephrine, dopamine and serotonin in the brain constitutes a biological basis of depression. Mania was conceptualized as a state of excess of catecholmines [6,7]. Initial evidence for the role of monoamines in affect regulation came from the observation that the antihypertensive Bipolar Disorder: Clinical and Neurobiological Foundations Edited by Lakshmi N. Yatham and Mario Maj © 2010 John Wiley & Sons, Ltd. ISBN: 978-0-470-72198-8

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agent reserpine induced depression in a subset of hypertensive patients [8,9]. Subsequent studies demonstrated that reserpine interfered with vesicular storage of serotonin and norepinephrine, thereby depleting presynaptic pool of monoamines available for release from the synapses [9,10]. Further evidence came from yet another serendipitous clinical observation that iproniazid, an antimycobacterial agent, improved mood in tubercular patients with depression [11–13]. The effect was later attributed to the ability of iproniazid to inhibit monoamine oxidase (MAO), the mitochondrial enzyme that degrades monoamines in the presynaptic nerve terminal, thus preventing degradation of serotonin, norepinephrine and dopamine. Imipramine, initially developed for the treatment of agitation in psychotic patients, was also found to have antidepressant properties [14]. Subsequently, it was discovered that it acts by inhibiting reuptake of norepinephrine and serotonin, both centrally and peripherally [15]. Evidence for the role of monoamines in pathophysiology of mania has been derived from observation of behavioural effects of drugs such as L-dopa, bromocriptine and d-amphetamine, all of which precipitated mania by enhancing central catecholaminergic transmission [16–19]. In the late 1960s, Coppen [20], Lapin and Oxenkrug [21] formulated the indoleamine hypothesis of depression attributing vulnerability to major depression to low serotonergic activity. In 1974, Prange and colleagues extended this hypothesis from major depression to bipolar disorder, by proposing a permissive hypothesis of serotonin function that suggested that reduced serotonin level sets the stage for a mood disorder, depression or mania, depending on the underlying catecholamine level. According to this hypothesis, depression ensues in the context of low serotonin and low catecholamine level, whereas mania is the result of low serotonin and abnormally high catecholamine level [22].

Monoamine metabolism and neuroanatomy Catecholamines Monoaminergic systems are extensively distributed throughout the network of brain stem, limbic, striatal and

Neurotransmitter Systems

prefrontal cortical neuronal circuits thought to support the behavioural and visceral manifestations of mood disorders [23]. The catecholamines, dopamine and norepinephrine, are synthesized from amino acids phenylalanine and tyrosine. The first and rate-limiting step in synthesis of catecholamines is the conversion of tyrosine to 3,4-dihydroxyphenylalanine (L-DOPA) by the enzyme tyrosine hydroxylase [24]. This step can be inhibited reversibly by the administration of alpha-methyl-p-tyrosine (AMPT), which therefore inhibits the production of both, norepinephrine and dopamine. The second enzyme, DOPA decarboxylase, converts L-DOPA into dopamine. In noradrenergic neurons, the third enzyme, dopamine beta-hydroxylase converts dopamine into norepinephrine. Norepinephrine is stored in synaptic vesicles until release is triggered by a nerve impulse. Dopaminergic neurons lack the enzyme dopamine beta-hydroxylase, resulting in an inability to convert dopamine to norepinephrine. Although norepinephrine is synthesized from dopamine their tissue distribution differs markedly [25,26]. The action of catecholamines is terminated by two principal enzymes, MAO, located in the mitochondria of the presynaptic neurons, and catechol-O-methyl transferase (COMT), located mainly outside of the presynaptic nerve terminal [25]. Action of these enzymes results in production of catecholamine metabolites, of which 3-methoxy-4hydroxypheylglycol (MHPG) is the major norepinephrine metabolite, and homovanillic acid (HVA) is the major dopamine metabolite. In addition to enzymatic activity, norepinephrine is removed from the extracellular space by a presynaptically located norepinephrine transporter [26]. Dopaminergic neurons similarly possess a dopamine reuptake pump, which works analogously to the norepinephrine transporter [27]. Norepinephrine exerts its effects via alpha- and beta-adrenergic receptors, located postsynaptically, and alpha-2 autoreceptors, located presynaptically, that mediate negative feedback regulatory signalling [28]. Dopamine exerts action via a plethora of receptors and autoreceptors [29–31]. The main source of norepinephrine in the brain is locus coeruleus, located in the rostral pons. Noradrenergic neurons from locus coeruleus give rise to diffuse axonal projections and innervate virtually all areas of the brain and spinal cord. The mammalian brain also contains smaller collections of additional noradrenergic and adrenergic neurons that are located in discrete regions of pons and medulla [32,33]. Locus coeruleus output is involved in flightor-fight responses and regulate level of arousal, the responses of the sympathetic nervous system including pulse rate and blood pressure, and signalling of danger to organism. Locus coeruleus receives input from numerous neurotransmitter and peptidergic systems, including serotonergic, GABAergic, glutamatergic, cholinergic and

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opioid [34]. The main source of dopamine in the brain is ventral mesencephalon, from where dopaminergic projections distribute widely throughout the central nervous system [27].

Indoleamines Serotonin (5-HT) is synthesized from tryptophan in a series of reactions involving hydroxylation of L-tryptophan to 5-hydroxytriptophan (5-HTP) via the enzyme tryptophan hydroxylase, a rate-limiting step, and decarboxylation of 5-HTP into 5-hydroxytriptamine or serotonin (5-HT) via aromatic amino acid decarboxylase [35]. Upon release, serotonin interacts with a complex system of receptors. Based on pharmacological and molecular properties at least 14 types of 5-HT receptors have been identified in mammalian brain [36,37]. The serotonin transporter in brain is responsible for the active re-uptake of serotonin back into neurons, and is situated both in perisynaptic membranes of nerve terminals and in dendritic arbors in close proximity to serotonin-containing cell bodies in the midbrain and brain stem raphe nuclei [38]. Once inside the serotonergic neuron, serotonin is metabolized by the MAO into inactive metabolite, 5-hydroxyindoleacetic acid (5-HIAA). The main location of the cell bodies of 5-HT neurons is a beaded structure called the raphe nucleus; the two main midbrain raphe nuclei, the dorsal raphe and the median raphe, project virtually to all forebrain regions, including thalamus, hypothalamus, caudate-putamen, hippocampus and neocortex [39]. Melatonin is synthesized from the tryptophan by enzyme 5-hydroxyindole-O-methyltransferase [40]. Production of melatonin by the pineal gland is under the influence of the hypothalamus, and is regulated by environmental light/ dark cycles via the suprachiasmatic nucleus. The cyclic nature of bipolar illness, as well as disturbances in sleepwake cycle all suggest that dysfunction in melatonin metabolism might be involved in pathophysiology of bipolar disorder [41]. In addition to its timekeeping functions, melatonin is an effective antioxidant and regulator of several antioxidant enzymes [40]. Melatonin’s cytoprotective properties may have practical implications in the treatment of neuropsychiatric disorders.

Adrenergic-cholinergic balance in mood disorders Perturbations in cholinergic transmission have long been implicated in pathophysiology of mood disorders. Since the discovery by Willoughby in 1898 that pilocarpine, a muscarinic cholinergic agonist, alleviates mania, numerous studies have demonstrated the mood-altering effects of acetlycholine modulating agents [42]. In the early 1970s, based on the above studies and animal data [43], Janowsky and colleagues developed an adrenergic-cholinergic balance

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hypothesis of bipolar disorder. This hypothesis proposed that depression represents an overabundance of central acetylcholine, relative to central adrenergic neurochemicals, and mania represents the converse [44]. In a seminal experiment, Janowsky and colleagues [44] investigated the effects of administration of a centrally acting cholinesterase inhibitor, physostigmine, or the peripherally acting cholinesteraze inhibitor, neostigmine, to manic, depressive and schizophrenic patients, as well as healthy volunteers. The study showed that administration of physostigmine but not neostigmine resulted in decreased symptoms of mania and an increase in depressive symptoms [44]. Further support for the involvement of the cholinergic system in bipolar disorder was provided in the early 1980s by Sitaram and colleagues, after demonstrating that administration of cholinergic agonist arecoline resulted in faster induction of REM sleep, suggestive of cholinergic supersensitivity in 14 bipolar patients [45]. The effect was seen whether the patients were symptomatic or in full remission.

Cholinergic metabolism and neuroanatomy Acetylcholine is synthesized from acetyl coenzyme A and choline in a reaction catalysed by the enzyme acetyltransferase [46]. Upon release, the action of acetylcholine on post synaptic receptors is terminated by the enzymes acetylcholinesterase and butyrylcholinesterase, which turn acetylcholine into inactive products [47–49]. Acetylcholine exerts its action via numerous receptors of which the main subtypes are muscarinic and nicotinic. Nicotinic receptors are ligand-gated, rapid-onset, and excitatory ion channels [50] while muscarinic receptors are G-protein-linked, and can be excitatory or inhibitory [51].

Peripheral measures The monoamine hypotheses of mood disorders postulated that depression is caused by deficient monoamine production, whereas manic states result from an increase in monoamine production [5,6]. Much of the earlier studies on the pathophysiology of mood disorders, therefore, focused on measuring levels of monoamines and their metabolites in bodily fluids. Such measurements provided evidence of dysfunction in catecholaminergic and serotonergic systems as predicted. However as can be seen below while a dysfunction of these systems was reported there was inconsistency in the specific direction of dysfunction. Therefore early studies found that in patients diagnosed with bipolar disorder, plasma and urinary norepinephrine and its metabolite MHPG levels were decreased during the depressed phase compared to euthymic state, and elevated during the manic phase [52]. However, subsequent studies failed to replicate these findings [53,54], or found that

norepinephrine concentration was lower in bipolar patients than in either unipolar depressive or disease-free controls [55]. Swann and colleagues conducted an extensive set of studies of monoamine function in bipolar patients. In one of the studies, researchers compared CSF concentrations of MHPG, HVA and 5-HIAA between the manic patients and healthy comparison individuals. The manic patients had significantly higher levels of MHPG. Levels of HVA and 5-HIAA were elevated only in female manic patients [56]. The comparison of biogenic amine levels, between mixed manic and agitated depressed patients, revealed higher MHPG in CSF, as well as higher urinary norepinephrine excretion, in a mixed manic group [57]. Later studies by the same group investigated the relationship between the catecholamine functioning, as reflected in CSF and urinary concentration of catecholamine metabolites, and psychomotor performance. The study showed performance impairment in unipolar and bipolar depressed patients, but no differences in the performance between manic patients and controls [58]. Increase in the total excretion of catecholamines and their metabolites were associated with better test performance in healthy controls and males with unipolar depression. In bipolar depressed patients, however, increase in CSF MHPG was associated with worsening of performance [58]. CSF levels of the major dopamine metabolite, HVA, have been found to be decreased in bipolar depression [54]. HVA levels in mania were reported to be higher [59,60], or not different from the control groups [56,61–63]. Studies of the CSF 5-HIAA in bipolar patients have generally produced inconsistent results [64,65]. CSF 5HIAA levels in manic patients compared with controls have been reported to be decreased [66,67], or unchanged [60,68]. Another study compared mixed bipolar patients with pure manic and unipolar depressive patients [69]. Whereas both serotonin and 5-HIAA levels were higher in the patients with pure mania than in those with depression, the mixed group could be biochemically divided into two subgroups, those resembling pure manic and pure depressive groups [69]. This has to be considered against the background of emerging literature showing that there was an association between low CSF 5-HIAA level and suicidal behaviour [61]. In general, use of the studies measuring levels of monoamines in bodily fluids has provided us with evidence of a dysfunction in these systems which have been considered key to the pathophysiology of the illness. However the discrepancy in the results could well be due to methodological limitations in determining the relative contribution of the peripheral versus central plasma and urinary metabolites, the effects of medication and insufficient information regarding the phase of the illness. Both CSF and plasma sample collection in general, pose a variety of procedural and interpretational challenges, including the effect of the

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acute stress of the procedure, and sampling at a single time point [70].

Monoamine challenge studies The monoaminergic hypothesis of mood disorders has been tested extensively using monoamine depletion techniques [71]. Transient and reversible reduction of the central levels of a particular neurotransmitter allows for the investigation of the effects of such a manipulation on mood symptoms. Synthesis of serotonin is entirely dependent on the availability of its precursor amino acid tryptophan. Therefore, manipulation of tryptophan level in the central nervous system will affect serotonin transmission. Since the only source of tryptophan for humans is diet, elimination of tryptophan is achieved by administration of tryptophanfree amino acid drink [72,73]. The manipulation of central norepinephrine has been approached in a different manner. The synthesis of catecholamines critically depends on the action of tyrosine hydroxylase. This step can be reversibly inhibited by the administration of AMPT, which therefore inhibits the production of norepinephrine and dopamine. Monoamine depletion studies have yielded mixed results in bipolar patients. Acute typtophan depletion in remitted bipolar patients revealed either no effect [74–76], or transient worsening of manic symptoms [77]. Catecholamine depletion resulted in attenuation of symptoms of acute mania in patients treated with antipsychotics [78]. The same procedure in remitted bipolar patients treated with lithium resulted in no immediate effect, but was followed by a transient relapse of hypomanic symptoms after a 24–48 hrs delay [79].

Post-mortem brain tissue studies of monoaminergic function Examination of postmortem human brain tissue has been a mainstay of research strategies in the investigation of the pathophysiology of mood disorders for over a century. Earlier studies focused on comparing number of neurons and glial cells [80,81], cortical thickness [82,83] or cell architecture [84], between patients with mood disorders and healthy controls. Subsequent sophistication in methodology allowed comparison at the cellular and subcellular level. Newer techniques employing high throughput mRNA technologies including microarray platforms (cDNA arrays and oligonucleotide-based arrays) allow evaluation of changes in expression at the level of the entire genome [85,86].

Catecholamines An extensive study [87] demonstrated no difference in the levels of norepinephrine, dopamine and serotonin in the

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hippocampus, caudate nucleus, putamen, mediodorsal thalamus, frontal, parietal, occipital or temporal cortices between the brain samples from patients with antemortem diagnosis of bipolar disorder and those from disease nonafflicted, matched controls [87]. However, the same study reported significantly increased norepinephrine turnover (MHPG/norepinephrine ratio) in the thalamus, as well as frontal, temporal and occipital cortices of bipolar patients. This could be viewed as reflecting either an excess of production or accelerated metabolism of norepinephrine. Significant reductions were detected in major serotonin metabolite 5-HIAA and serotonin/5-HIAA ratio in frontal and parietal cortex, as well as in HVA, the major dopamine metabolite, in the parietal and occipital cortex of bipolar patients [87]. Using immunocytochemistry with computerassisted quantification of immunoreactivity for tyrosine hydroxylase and tryptophan hydroxylase, Wiste and colleagues [88] recently demonstrated less tyrosine hydroxylase and tryptophan hydroxylase immunoreactivity in locus coeruleus of bipolar suicides, compared to major depression suicides and matched controls, suggesting potentially lower noradrenergic and serotonergic levels in bipolar suicides. The results of both studies were interpreted as consistent with serotonin permissive hypothesis of bipolar disorder [22,87,88]. Receptor autoradiography studies, investigating density and functional integrity of beta-adrenergic receptors in frontal, occipital or temporal cortex [87], or 5HT2A and 5HT1A receptors in frontal cortex [89,90] or hippocampus [91], revealed no differences between brain tissue samples from bipolar patients relative to control samples. On the other hand, Pantazopoulos and colleagues [92] used in situ hybridization to measure expression differences in dopamine D1 receptor mRNA in hippocampus of bipolar and schizophrenic patients. Bipolar patients demonstrated significant and sector specific decrease in D1 mRNA expression in CA2 sector of hippocampus [92].

Serotonin A decrease in the affinity of [3H]citalopram binding to the serotonin transporter has been reported in the hippocampus, but not frontal cortex of the patients with bipolar disorder [91]. The same study reported no differences in the density of serotonin transporter, or 5HT2A, 5HT1A, 5HT1D and 5HT1F receptors between the bipolar and control hippocampal samples [91]. On the other hand, Sun and colleagues, using serial analysis of gene expression method, demonstrated increased serotonin transporter mRNA level in frontal cortex of bipolar patients relative to matched controls [93]. New evidence suggests abnormalities in the interaction between the neurotransmitter receptor and G-proteins in bipolar disorder [94]. Supportive of this hypothesis is the previous demonstration of decrease in

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serotonin, isoproterenol and carbachol stimulated guanosine 50 -O-(3-[35S] thiophosphate) binding in cortical tissue from subjects with bipolar disorder [95].

Acetylcholine Severance and Yolken [96] compared nicotinic acetylcholine receptor subunit mRNA expression in prefrontal cortex of patients with antemortem diagnosis of bipolar disorder or schizophrenia, and unaffected controls, and found modest up-regulation of alpha-4 message in bipolar patients with history of psychosis relative to controls. In summary, studies investigating the levels of monoamine transmitters, or quantity and functional integrity of monoamine receptors and transporters in postmortem brain tissue of patients with bipolar disorder have not suggested a consistent direction of change of functioning. The inconsistencies might be related to the regional differences, generally small sample sizes, lack of information on the phase of illness, effects of antemortem medication regimen, freezer storage time, brain ph and postmortem interval [97,98].

Neuroimaging studies Advance in neuroimaging have brought unprecedented possibilities for in vivo studies of the human brain [99,100]. In particular, positron emission tomography (PET), single photon emission computerized tomography (SPECT) and magnetic resonance spectroscopy (MRS) enable measurement of local cerebral glucose metabolism, blood flow, receptor and transporter number and functional integrity, as well as concentrations of biochemical metabolites in a given volume of brain tissue, elucidating the contribution of neurotransmitter systems dysfunction to mood disorders.

Catecholamines In a study conducted in patients with acute mania, Pearlson and colleagues [101] used the radiotracer N-[11 C]methylspiperone to compare D2 receptor density between neuroleptic-free psychotic bipolar patients, schizophrenic patients and normal controls. Increase in D2 binding potential was demonstrated in the striatum of bipolar and schizophenic patients compared to controls, leading authors to conclude that potentially higher number of D2 receptors is marker for psychosis rather than for the specific disorder. Using D2/D3 receptor tracer iodobenzamide before and after amphetamine challenge, Anand and colleagues [102] detected no differences in D2 striatal baseline levels between euthymic bipolar patients and matched controls, nor there were differences between the two groups in the amphetamineinduced decrease in striatal iodobenzamide binding. Since a decrease in iodobenzamide binding has been shown to be related to the amount of striatal dopamine release, the

findings were interpreted as consistent with enhanced postsynaptic dopamine responsivity in bipolar disorder [102]. In another study, conducted in acutely manic patients, Yatham and colleagues [103] examined presynaptic dopaminergic function in neuroleptic- and mood-stabilizer na€ıve nonpsychotic manic patients before and after treatment with divalproex sodium by measuring [18 F]6-fluoro-L-dopa uptake in the striatum. The study revealed no significant differences in baseline [18 F]6-fluoro-L-dopa uptake between the manic patients and healthy controls. Treatment with divalproex sodium resulted in reduced [18 F]6-fluoroL-dopa uptake in patient group, possibly through decrease in aromatic L-amino acid decarboxylase [103]. D1 dopamine receptor binding was studied using the PET radioligand [11C]-SCH23390 in frontal cortex and striatum of patients with bipolar disorder in various phases of disease (euthymic, depressed and one manic) and normal controls. The binding potential was significantly lower in the frontal cortex in the patient group compared to the control group. No significant differences were detected in striatum [104].

Serotonin Studies have examined the quantitative and qualitative properties of serotonin receptors in bipolar disorder. PET imaging, using the 5HT1A receptor ligand [11 C]WAY100635, demonstrated reduction in 5HT1A binding potential in the raphe nucleus, mesiotemporal cortex, occipital cortex and postcentral gyri in a mixed group of recurrent depressed and bipolar patients [105]. More recent development of high affinity and selectivity radioligands for serotonin transporter enabled further assessment of its function in bipolar disorder [106]. One study, employing PET radioligand [11 C]( þ )McN5652, found an increase in thalamic serotonin transporter binding, and no difference in midbrain binding in a small group consisting of non-medicated, depressed or euthymic bipolar patients relative to controls [11 C]DASB [107]. However, another PET-[11 C]( þ )McN5652 study found a reduction in serotonin transporter binding in the midbrain, thalamus, putamen, amygdala, hippocampus and anterior cingulate cortex in bipolar depressed patients [106]. Cannon and colleagues [108] used a newly developed PET radioliand [11C]-3-amino-4-(2-dimethylaminomethylphenylsulfanyl)-benzonitrile ([11 C]DASB) that binds to the serotonin transporter with high affinity and selectivity, to compare serotonin transporter binding between bipolar depressed patients and healthy controls. Serotonin transporter binding was significantly increased in the insula, medial prefrontal cortex, dorsal cingulate cortex, caudate and thalamus, areas known to receive extensive innervations by serotonergic neurons. Decreased serotonin transporter binding was detected in the brainstem at the level of pontine raphe nucleus in bipolar subjects compared to controls. This data is compatible both with Ichymia study

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as well as with the report of Sun and colleagues reporting increase in serotonin transporter RNA transcript in postmortem samples of frontal cortex of individuals with bipolar disorder [93,107].

Acetylcholine Spectroscopic imaging suggests abnormalities in metabolism of choline-containing compounds in symptomatically ill bipolar patients, although the true direction of the change is unclear. Choline is a precursor and metabolite of membrane phospholipids, second-messenger compounds, and the neurotransmitter acetylcholine. The choline resonance, visible by 1 H MRS represents combined signals from several choline-containing compounds, including phosphocholine and glycerophosphocholine. Several studies so far demonstrated increase in choline concentration in the basal ganglia [109–111] and anterior cingulate cortex [112] of bipolar patients. However, other studies have demonstrated reduction of choline and NAA concentrations in orbital frontal grey matter [113], or hippocampus [114], or no difference in choline concentration in anterior cingulate [115,116], or dorsolateral prefrontal cortex [117,118] between bipolar patients and matched controls

Genetic studies Twin and other family studies indicate that genetic factors contribute substantially to the liability for developing bipolar disorder [119,120]. However, the causative genes or genetic risk factors have not been well established [121]. Recent meta-analysis of functional polymorphisms suggests that three genes coding for products involved in monoaminergic neurotransmission may be significantly associated with bipolar disorder: monoamine oxidase A [122], COMT [123] and 5-HTTLPR [119]. The most consistent finding is an association between the excess of allele 5 or 6 of the MAOA-CA repeat and bipolar disorder in female bipolar patients [122,124].

Amino acids and the pathophysiology of bipolar disorder Amino acidergic hypotheses The amino acids glutamate (Glu), gamma-aminobutyric acid (GABA) and glycine (Gly) serve as neurotransmitters at most of the mammalian central nervous system synapses [125,126]. Abnormal functioning of the glutamatergic system has been implicated in pathophysiology of numerous neuropsychiatric disorders, amongst others amiotrophic laterals sclerosis [127], Huntington’s chorea [128], Alzheimer’s disease [129], schizophrenia [130], epilepsy, cocaine addiction and alcohol abuse [131]. Over the past

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several years, increasing evidence suggests that dysregulation of glutamate neurotransmission contributes to the pathology of mood disorders as well [125,132,133]. The hypothesis of GABAergic dysfunction in mood disorders was initially formulated by Emrich and colleagues in 1980, following observation of the efficacy of an anticonvulsant and GABA agonist, valproate, in treatment of mania [134]. Since then, considerable preclinical and clinical data have been accumulated suggesting that GABA plays a role in affective disorders [135–137]. Through its action as the major inhibitory neurotransmitter in the brain, GABA modulates as array of behavioural and physiological mechanisms related to mood pathology, including sleep, feeding behaviour, aggression, sexual behaviour, pain responsiveness, cardiovascular regulation, thermoregulation and locomotor activity [138].

Glutamate metabolism and neuroanatomy Glutamate is the most abundant excitatory neurotransmitter in the brain, with estimated presence at 60% of the synapses [125,126]. Glutamate in the brain originates from two sources: (1) synthesized de novo from glucose via the Krebs cycle and transamination of alpha-ketoglutarate; and (2) from glutamine that is synthesized in glial cells from glutamate via action of glutamine synthetase, transported into nerve terminals, and locally converted into glutamate by glutaminase. Glutamate is released from the nerve terminal by a calcium-dependent exocytosis following cell depolarization [26]. Glutamate is essential to neurotransmission, but cytotoxic when present in excess. Rapid removal from the synaptic cleft is crucial to ensure maintenance of extracellular levels of glutamate below those that cause excitatory damage [139–141]. Clearance is accomplished through action of five, so far identified, high-affinity, sodium-dependent excitatory amino acid transporters (EAAT 1-5) located on the presynaptic terminals and neighbouring glial cells [142]. Mechanisms involved in excitotoxic action of glutamate involve damage to mitochondria from excessively high intracellular calcium level, and activation of calcium dependent kinases and proteases, with subsequent cytoskeletal damage, protein misfolding and overproduction of oxygen radicals eventually resulting in cell death [143]. Excitotoxicity from excessive glutamate stimulation has been implicated in variety of neuropsychiatric disorders [127–129], and accumulating evidence implicates excitotoxic damage in mood disorders as well and in schizophrenia [144,145]. Glutamate exerts its action through activation of ionotropic and metabotropic receptors. Ionotropic receptor subtypes bear the names of their selective agonists: Nmethyl-D-aspartate (NMDA), amino-3-hydroxy-5-methylisoxazole-4-propionic acid (AMPA) and kainate [146–148].

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Metabotropic glutamate receptors, located on neurons, pre-, post- and extra-synaptically, as well as on glia, and are classified as group I, II and III based on their interactions with regulatory G-proteins [146]. AMPA and kainate receptors mediate fast excitatory synaptic transmission and are associated primarily with voltage-independent channels that gate a depolarizing current through influx of sodium ions. AMPA receptors are heteromeric assemblies of GluR1-4 subunits [149]. Kainate receptors are composed of tetrameric combinations of three subunits, GluR5-7, KA1 and KA2 [148]. The NMDA receptor complex is endowed with a number of distinct recognition sites for endogenous and exogenous ligands, including magnesium, glycine and zinc binding sites, in addition to the transmitter binding site, and a polyamine-regulatory site. In contradistinction to other ionotropic glutamate receptors, activation of NMDA depends on simultaneous presence of glutamate and depolarization of the postsynaptic membrane. This characteristic contributes to unique property of NMDA receptors to code simultaneously occurring events, characteristic central to many forms of synaptic plasticity, including learning and memory [150]. NMDA receptors are heteromeric assemblies of an obligatory NR1 subunit with a NR2A-D and NR3A-B subunits, assembled in the endoplasmic reticulum to form functional channels with differing physiological and pharmacological properties and distinct patterns of expression and regional distribution [131]. NMDA receptors are anchored in the postsynaptic density and linked to a large complex of intracellular proteins, including PSD95, PSD93, NF-L and SAP102 [151–153].

GABA metabolism and neuroanatomy GABA is the most abundant inhibitory neurotransmitter in the mammalian brain. It is estimated that approximately 40% of neurons use GABA as a neurotransmitter [154]. In addition to acting as an inhibitory neurotransmitter, GABA participates as an intermediate in energy metabolism [155]. Most GABA neurons are local circuit interneurons, but GABA is also found on certain long projection neurons [156]. GABAergic interneurons are abundant in mood-related structures of the forebrain, including anterior cingulate cortex, hippocampus and amygdala [157]. The GABAergic system extensively interacts with the dopaminergic [158,159], glutamatergic [160] and serotonin systems [161], as well as hypothalamo-pituitary-adrenal axis [162]. GABA in GABAergic terminals is formed from glutamate in an enzymatic reaction mediated by the glutamic acid decarboxylase (GAD), using pyridoxal phosphate as a cofactor. GAD is present in at least two molecularly distinct isoforms, termed GAD65 and GAD67 [163]. GAD65 is primarily localized to axon terminals, whereas GAD67 is more abundant in neuronal cell body [164]. Upon release,

GABA is rapidly removed from synaptic cleft by a highaffinity sodium-dependent reuptake process. Four subtypes of GABA transporters (GATs) named GAT-1, GAT-2, GAT-3 and BGT-1, have been cloned. The transporters are present on both, neurons and glial cells [165]. GATs are regulated by several factors including GABA itself, brainderived neurotrophic factr (BDNF), and hormones [166]. GABA aminotransaminase is a mitochondrial enzyme primarily responsible for the degradation of GABA. Inhibitors of GABA aminotransaminase rapidly raise GABA levels in human brain [167], and possess anticonvulsant and anxiolytic properties [168]. The synaptic effects of GABA in the central nervous system are mediated through two major receptor subtypes termed GABA-A and GABA-B. GABA-A subtype is an ionotropic receptor that allows increased chlorine conductance following the binding of GABA, and is predominantly involved in fast inhibitory synaptic transmission. GABA-B receptor is a G-protein coupled receptor [137].

Peripheral measures of GABA and glutamate Changes in glutamate levels have been reported in plasma [169] and cerebrospinal fluid [170,171] of individuals afflicted with bipolar disorder, with inconsistent findings. While Frye and colleagues reported decrease in glutamate and glycine [170], Levine and colleagues reported increased glutamate in CSF in bipolar and unipolar depressed patients compared to controls [171]. Altamura and colleagues [172] reported higher glutamate plasma levels in patients with mood disorder, including bipolar disorder, compared to neurological patients with tension headache, healthy volunteers or patients with schizophrenia, anxiety or organic mental disorder. On the other hand, a study led by Palomino reported decreased levels of plasma glutamate during first psychotic episode that was part of either bipolar disorder or schizophrenia [169]. Plasma measures conducted during manic phase, demonstrated significant increase of both glutamate and glycine that persisted in remission [173]. Studies assessing CSF GABA levels reported either lower levels [174] or no differences in comparisons between bipolar patients and matched controls [59,175,176]. Studies assessing plasma GABA levels demonstrate decrease in patients with bipolar disorder irrespective of the phase of disease, in accord with Emrich hypothesis [175,177,178].

Postmortem studies A number of postmortem brain tissue studies investigated glutamate [179,180] or GABA levels, receptor density and binding properties, as well as receptor subunit and PSD components expression patterns in patients with bipolar disorder [181,182]. Although most of the studies reported

Neurotransmitter Systems

differences in those parameters, no consistency in findings emerged so far.

Glutamate Postmortem autoradiography studies use radiolabelled receptor agonists and antagonists to assess receptor density and functionality. Radioligands that interact with binding sites on NMDA receptor complex include [3 H]MK-801 that binds to an intra-channel site; [3 H]ifenprodil, that binds to a polyamine site; [3 H]CPG39653, that binds to a glutamate site; and [3 H]MDL105,519, that binds to a glycine (D-serine) co-agonist site. Radioligands [3 H]AMPA and [3 H]kainate are used as markers for the respective receptors. Using autoradiography method, Scarr and colleagues [183] compared density of hippocampal ionotropic glutamate receptors between the patients with bipolar disorder and matched controls. Whereas no changes were found in densities of AMPA and kainate receptors, decrease in [3 H]MK-801 binding was observed. However, non-significant decrease in binding of [3 H]CGP39653 led to the conclusion that the observed change reflected decrease in the number of open channels with no apparent difference in NMDA receptor density in hippocampal samples from bipolar subjects [183]. Similar decrease in [3 H]MK-801 binding was reported more recently by Beneyto and colleagues [179]. However, no changes in the expression in the NMDA receptor subunits and an increase in [3 H]MDL105,519 hippocampal binding, indicating an increase in the number of NMDAreceptor glycine binding sites, were simultaneously observed. No changes in receptor binding were detected in dorsolateral prefrontal cortex using the same radioligand methodology [180]. Decrease in NMDA NR1 subunit transcript was detected in several studies in hippocampus [91,184], dorsolateral prefrontal [180] and perirhinal cortex [179]. However, other studies have either not replicated these findings [179,185], or detected the same change in brain tissue of the patients afflicted with schizophrenia or major depressive disorder, questioning specificity of the finding to the bipolar disorder [180]. The findings are similarly inconclusive with regard to the expression of NR2A NMDA receptor subunit. NR2A mRNA expression level was found to be either decreased in hippocampus [184] and anterior cingulate cortex [182], or unchanged in the hippocampus [179] and DLPFC [180], between the patients with bipolar disorder and patients with antemortem diagnosis of MDD, schizophrenia and matched controls. Amongst the components of the NMDA-receptor associated proteins within the PSD, decrease in SAP102 mRNA expression was most consistently reported finding in brain samples from bipolar patients. Such decrease was observed in the hippocampus [184], DLPFC [180], striatum [186] and

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thalamus [187]. Reductions in PSD95 mRNA were additionally observed in striatum [186] and thalamus [187], but not DLPFC [180] of bipolar patients compared to matched controls. No changes were detected in expression of NF-L mRNA levels in DLPFC of bipolar patients [180]. Decrease in AMPA GluR3 and GluR6 receptor subunit mRNA was detected in entorhinal cortex [179]. Decrease in expression of kainate receptor KA2 was detected in the prefrontal cortex [188]. No differences were detected in the hippocampus GluR5, 6 and 7 immunoreactivity between the patients with bipolar disorder and matched controls [189]. Along similar lines, using in situ radioligand binding, no differences were detected in AMPA or kainite receptor density between hippocampal samples from patients with bipolar disorder and matched controls [183].

GABA Abnormalities in the GABAergic system have been identified in the GABA level, neuron and transporter density, as well as GABAergic receptor functioning in postmortem brain tissue of bipolar patients. GABAergic interneurons are anatomically and functionally heterogenous [80]. GABAergic interneurons can be classified by their immunoreactivity for the calciumbinding proteins parvalbumin, calbindin and calretinin [190]. Using these markers, majority of immunohistochemical studies in postmortem brains of bipolar patients found reduced number of calbindin and parvalbuminpositive cells in regions that participate in mood regulation, namely the anterior cingulate cortex [80,191], hippocampus [80,97], entorhinal [92] and dorsolateral prefrontal cortex, all suggesting that bipolar disorder might be associated with decreased levels of GABA [192]. Another interesting marker for the GABAergic interneurons is reelin, an extracellular glycoprotein involved in neuronal migration, synaptogenesis and dendritic plasticity [97,193]. Reelin expression, both at the mRNA and protein level, was significantly decreased in the prefrontal cortex [194] and the hippocampal formation of bipolar patients [181] compared to control tissue samples. Studies investigating expression of key enzymes involved in the synthesis of GABA, reported altered levels of expression of both 67 and 65 kDa isoforms. A predominant finding is a decrease in GAD67 mRNA and protein levels in multiple brain regions, including prefrontal cortex [194], anterior cingulate cortex [182], caudate nucleus and cerebellum [181]. While in some studies changes in mRNA GAD67 expression are paralleled by similar decrease in expression of GAD65 mRNA [181,195,196], other studies fail to replicate such findings [194]. In summary, a variety of differences between the brain samples from bipolar patients and matched controls were

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detected in amino acidergic systems, but the functional significance of these findings is at present unclear. Inconsistencies might be related to the regional differences, generally small sample sizes, effects of antemortem medication regimen, freezer storage time, postmortem interval and brain ph [97,98]. Assessment of receptors functionality in general can be affected by post-translational modifications, binding with other components of the receptor complex, or rate of protein degradation, none of which can be assessed by the mRNA expression studies [197]. Moreover, recent research provide evidence that synaptic NMDAR number and subunit composition are not static, but change dynamically in a cell specific and synapse-specific manner in response to neuronal activity or sensory experience [198].

Neuroimaging studies Proton MRS is providing increasingly valuable insight into the role of glutamatergic and GABAergic transmission in mood disorders [199]. Earlier MRS studies reported levels of a composite ‘Glx’ peak, which contains overlapping resonances of glutamine, glutamate and GABA. Most studies conducted in patients with bipolar disorder revealed elevated Glx levels in the cortical grey matter of anterior cingulated [200], frontal cortex [201] and basal ganglia [202] in unspecified phase of the illness relative to controls, as well as in the DLPFC of acutely manic patients relative to controls [203]. Newer methodology using higher strength magnetic fields allows resolution of the Glx peak into its constituents, providing a unique insight into glutamtergic and GABAergic system function in bipolar disorder [204,205]. One such study reported elevation in hippocampal glutamate that correlated with NAA level in remitted bipolar patients on lithium maintenance [205]. Bhagwagar and colleagues reported reduction in occipital cortex GABA concentration in medication-free, recovered unipolar depressed and bipolar patients [204]. However, a recent study led by Kaufman reported no significant difference in the levels of glutamate or GABA between bipolar patients and controls [206]. Increased glutamate levels could be neurotoxic, and possibly result in anatomical abnormalities reported in brain imaging and postmortem studies. Therefore, measurement of two other chemicals, N-acetyl-aspartate (NAA) [207] and lactate [208] may provide indirect information on the neuronal functional integrity as well as assessment of brain’s bioenergetic status. NAA is located only to neurons, and not found in mature glial or blood cells. Decrease in NAA levels detected in dorsolateral prefrontal cortex of bipolar patients [115] may reflect neuronal loss, decreased neuronal viability or impaired neuronal functioning. Lactate is a product of anaerobic glycolysis. Increase in brain lactate is associated with seizure activity, ischaemic pathology or rigorous cognitive activation tasks [208]. Significant

reduction in both manic and depressive symptoms correlated with decrease in lactate levels [209]. In summary, most studies conducted in patients with bipolar disorder revealed elevated Glx levels, suggesting hyperglutamatergic state in several key regions involved in mood regulation. However, given the overall inconsistencies in findings, observed biochemical abnormalities likely present markers of a trait vulnerability to mood disorders, rather than neurochemical correlates of an abnormal mood state [204,210].

Genetic studies Several genetic studies have found associations between genetic polymorphisms and dysregulation of glutamatergic neurotransmission in bipolar disorder [211]. Polymorphisms in G72/G30 gene locus on chromosome 13 (13q32-33) confer susceptibility to bipolar disorder in several independent datasets [212]. Products of both genes are involved in glutamatergic signalling cascade [213].

Neuroendocrine systems and neuropeptides One of the most consistent findings in biological psychiatry is derangement of endocrine functioning in patients with mood disorders [70]. Central to regulating bodily homoeostasis and neuroendocrine response to external and internal stressors is the hypothalamus. Through action of neuropeptides, which it synthesizes and secretes, the hypothalamus controls an immense number of bodily functions, which include stress response, control of body temperature, ingestive behaviours, emotions, sexual activity, circadian cycles, blood pressure, as well as electrolyte balance [214].

Hypothalamic-pituitary-adrenal axis (HPA axis) Disturbance in homoeostatic balance, conveyed to the hypothalamus through the action of numerous neurotransmitters, including acetylcholine, noradrenaline, serotonin and GABA [215], causes activation of the HPA axis resulting in a release of a corticotropin-releasing factor (CRF) into the portal circulation, CRH-mediated release of adrenocorticotropic hormone (ACTH) from the anterior pituitary, and ACTH-mediated release of the cortisol from the adrenal gland [216–218]. CRF, a 41-amino acid peptide, exerts its action through two types of receptors, CRF1 and CRF2, and it appears that these two receptors mediate opposing effects, with CRFR1 activating and CRFR2 inhibiting, the CRF-mediated stress response. CRFR1 is the predominate subtype in limbic regions and in pituitary regulation of HPA axis activity [219]. Cortisol exerts its action through activation of two types of

Neurotransmitter Systems

receptors; type I or mineralocorticoid receptor (MR) with high affinity for endogenous corticosteroids, and type II or glucocorticoid (GR) receptors, with low affinity for cortisol [220]. Acute consequence of the HPA axis activation is mobilization of energy reserves to facilitate coping with stress. Chronic activation of the stress axis, or exogenous administration of corticosteroids for the treatment purposes, however, result in a host of neuropsychiatric disorders, of which mood disorders, including major depression, mania and delirium, are the most prominent [221,222]. Peripheral measures of hormones in bodily fluids may not provide a reliable insight into the brain functioning, as a number of associated variables, including hypothalamo/ pituitary blood flow, degree of stress, diet, sleep or level of activity, are difficult to control. Nevertheless, the evidence of HPA abnormalities have been repeatedly demonstrated in all phases of bipolar illness, and include elevated baseline serum cortisol levels, nonsupression of cortisol on the dexamethasone suppression test (DST) [223], and elevated cortisol release during the DST/CRF test [224]. Measurements of salivary cortisol yielded inconsistent results with some studies reporting increased [29], and in some no changes, in salivary cortisols level in bipolar patients compared to controls [225]. Postmortem studies investigating quantity of glucocorticoid and mineralocorticoid receptors demonstrated decreased glucocorticoid mRNA in the inferior temporal cortex, subiculum and entorhinal cortex in brain samples from patients carrying antemortem diagnosis of bipolar disorder, compared to patients with schizophrenia, unipolar depression or matched controls [226]. Another postmortem brain study found significantly lower mineralocorticoid receptor mRNA level in the dorsolateral prefrontal cortex of bipolar brain samples compared to controls [227]. Significant decrease in CRF-binding protein mRNA was detected in the amygdaloid nuclei of bipolar female and schizophrenic patients [228]. An increased number of CRF expressing neurons was found in hypothalamic paraventricular nucleus in the combined unipolar and bipolar depressed patient group [229]. This study potentially demonstrates the hyperactivity of CRH neurons, which could be related to activation of the HPA axis in patients with mood disorders. Recent interest has focused on a glucocorticoid receptor (GR) chaperone protein BCL-2 (B-cell CLL/lymphoma 2)associated athanogene (BAG1). BAG-1 attenuates glucocorticoid receptor (GR) nuclear translocation, activates ERK (extracellular signal-regulated kinase) MAP (mitogenactivated protein) kinases, and potentiates anti-apoptotic functions of BCL-2 [230]. The same study also demonstrated that that lithium/valproate induced BAG1 up-regulation attenuates GR nuclear translocation and also attenuates the activity of a reporter gene driven by GRs. BAG1 overexpression resulted in higher hippocampal levels of

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Hsp70 and lower levels of FKBP51 without changing overall GR levels or levels of Bcl-2, ERK, or pERK [231].

Hypothalamic-pituitary-thyroid axis (HPT axis) Thyroid hormones are involved in regulation of nearly every organ system in the human body. The regulation of thyroid hormone secretion is initiated by the release of hypothalamic tripeptide, thyrotropin-releasing hormone (TRH). After reaching the pituitary gland via portal circulation, TRH mediates release of the thyroid-stimulating hormone (TSH). Following release into general circulation, TSH mediates release of thyroid hormones (T3 and T4) from the thyroid gland. T3 and T4 have widespread metabolic effects and can alter many aspects of the peripheral and central nervous system functioning [232]. HPT axis dysfunction can induce a wide array of psychiatric symptoms. As early as 1864, Graves noted marked mood depression in patients with endemic goitre. Subsequent clinical observations linked hypothyroidism with depression and hyperthyroidism with euphoric states, including manic states. In particular, female patients with rapid cycling form of bipolar disorder seem to be particularly susceptible to disbalance in thyroid functioning [64].

Neuropeptide Y Neuropeptide Y (NPY) is a 36 amino acid long polypeptide, member of the pancreatic polypeptide family, and is present in extensive neuronal systems in the brain, especially in the hypothalamus and the amygdala [233]. NPY effects are mediated through at least five G-protein coupled receptor subtypes [234]. Of these, Y1 and Y2 are the most abundant in the brain. NPY coexist in neuronal cell bodies with catecholamines, GABA and somatostatin [235]. Its actions involve stimulation of food intake, modulation of circadian rhythms and regulation of release of several hypothalamic hormones, including the CRF. Numerous studies implicate NPY in regulation of mood [236]. Very few studies so far investigated involvement of NPY in pathophysiology of bipolar disorder and the results are, at present, inconclusive. Peripheral measures revealed no difference in plasma level NPY in bipolar patients stabilized on lithium and matched controls [237]. Postmortem studies revealed reduced NPY, Y1 and Y2 receptor mRNA in dorsolateral prefrontal cortex in patients with bipolar disorder and schizophrenia [238].

Substance P Substance P is an undecapeptide, with a key role in nociception. Substance P acts as an excitatory neurotransmitter in the primary afferent (dorsal root) nerve terminal in the

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mammalian spinal cord and regulates sympathetic noradrenergic function. Within the CNS, substance P is found in discrete areas of the CNS, including the amygdala, hypothalamus, substantia nigra, caudate-putamen and cortex, where it is thought to act as an excitatory neurotransmitter. Substance P is usually co-localized with one of the classic neurotransmitters, frequently serotonin. P mediates its effect via neurokinin-1 (NK-1) receptors [239]. A study of NK-1 receptor densities in the anterior cingulate cortex, measured using quantitative receptor autoradiography, in bipolar, unipolar depressed and schizophrenic patients detected no significant differences in total receptor densities amongst the groups [240]. No group differences were detected in CSF substance P immunoreactivity between bipolar manic or depressed, unipolar depressed and matched control samples [241].

Somatostatin Somatostatin has 2 active forms, 14 and 28 amino acids long, produced by alternative cleavage of a single preprotein. Somatostatin is released from the hypothalamus into portal circulation, and carried to the anterior pituitary, where it inhibits secretion of growth hormone from somatotrope cells. It exerts action through G protein-coupled receptor. Significant reduction in CSF somatostatin was observed in unipolar and bipolar depressed patients [242]. In contrast, manic patients had significantly higher CSF somatostatin compared to matched controls, in a study by Sharma and colleagues [243].

Conclusions A large number of studies have implicated abnormalities in monoaminergic (dopaminergic, noradrenergic, serotonergic), cholinergic, glutamatergic, GABA-ergic, glucocorticoid and peptidergic systems in pathophysiology of bipolar disorder [4]. Despite significant contributions of those studies, the precise pathophysiology of the bipolar disorder remains to be explored. One major obstacle in this process is the obvious heterogeneity of the mood states in bipolar disorder. The neurochemical profiles of the five different clinical manifestations of the bipolar disorder – manic, hypomanic, depressed, mixed and variable length euthymic periods are at present insufficiently characterized. The complexity and multidirectional interactions within numerous neurotransmitter systems add to difficulty interpreting observed changes as reflective of the cause of the disease, its consequence, or an organism’s attempt to overcome or compensate for the effects of disease [158–161]. Inconsistencies in the data obtained may also stem from the variety of technological challenges inherent to postmortem and neuroimaging studies, as well as peripheral measures. On the other hand, development of neuroimaging technologies

that permit in vivo characterization of the anatomical, physiological and neurochemical correlates of mood disorders, enables continuous advancement towards illuminating the pathophysiology of these conditions. In recent years, it has become increasingly clear that the view that particular transmitter abnormality causes mood disorder is over-simplistic [23]. At present, it is unclear why a number of patients do not respond to bipolar disorder treatment, nor do we understand the neurobiology of the lag between the administration and biological effect of the mood stabilizers and antidepressants. This discrepancy indicates that many biochemical steps are probably involved between the primary targets and biological effects. Recent exciting developments, outside the purview of this chapter, include the cloning and characterization of the circadian genes that have shed new light on the association between the circadian rhythms and bipolar disorder [244]. A growing body of evidence in recent years is implicating signal transduction pathways and mechanisms of cellular plasticity [4,94]. It may well be that these strategies will drive future efforts to understand the pathophysiology of bipolar disorder.

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Molecular Biology of Bipolar Disorder Ana Andreazza, Jun Feng Wang and Trevor Young Department of Psychiatry, University of British Columbia, Vancouver, Canada

Introduction Bipolar disorder (BD) is a common, chronic, recurrent mental illness with an estimated prevalence of about 1–3% of the worldwide population [1–3]. A growing number of studies have found impaired cognitive functions in BD patients that are present even after remission of symptoms [4–6], suggesting that BD may be associated with persistent cognitive dysfunction. Furthermore, BD is a systemic disease that is frequently associated with a wide range of physiological perturbations and medical problems, including cardiovascular disease, diabetes mellitus, obesity and thyroid disease [1,7], which is directly associated with increased morbidity and mortality observed in this disorder. Despite decades of extensive genetic and pharmacological studies, the aetiology and pathophysiology of this disorder remain unclear. Neurobiological studies of mood disorders over the past 40 years have focused on neuroanatomical and neurotransmitter abnormalities [8,9]. Neuroimaging and postmortem brain studies have detected that critical neural circuit modulating emotional behaviours are disturbed in BD. These include a significantly decrease in number or density of neurons in several brain areas, such as prefrontal cortex [10,11], anterior cingulate cortex [12], hippocampal corpus ammonius (CA2) [13], hypothalamic paraventricular nucleus [14] and amygdala [15]. In addition, several studies have also reported low glial cell number in the prefrontal cortex from subjects with BD [10,16]. Thus, postmortem studies have suggested that BD might be associated with neuronal and glial cell loss in specific brain areas, supporting the current hypothesis of altered neuroplasticity and neurotransmitter regulation in BD. This evidence has resulted in a recent burgeoning field of research investigating mechanisms of receptor coupled signal transduction. Intracellular signal transduction pathways are uniquely responsible for coordinating the cellular response to

Bipolar Disorder: Clinical and Neurobiological Foundations Edited by Lakshmi N. Yatham and Mario Maj © 2010 John Wiley & Sons, Ltd. ISBN: 978-0-470-72198-8

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information impinging on the cell from multiple sources and timeframes. It follows that abnormalities in these pathways may lead to functional imbalance in multiple neurotransmitter pathways, which could account for the diverse clinical features found in BD, such as a recurrent course, mood fluctuations, psychotic features, neurovegetative symptoms and cognitive impairment. In fact, the higherorder brain functions, such as behaviour, mood and cognition, are critically dependent on signal transduction processes for their proper functioning [17]. The time lag between the pharmacologic and clinical effects of mood stabilizers also suggests that long-term cellular and molecular events are important in the drugs’ mechanism of action. Over the past 10 years, studies using animal models, postmortem brain tissue and lymphocytes samples have examined the intracellular signal transduction pathways linked to neurotransmitters to investigate the biological basis of BD. In this chapter, we will review the evidences for abnormalities in signal transduction pathways in BD. We will also discuss how these pathways may be relevant in the treatment of this illness with mood stabilizing medication.

Signal transduction pathways Signal transduction pathways are uniquely responsible for coordinating the cellular response to information impinging on the cell from multiple sources and time frames [17]. These pathways follow a broadly similar course that can be viewed as a molecular circuit, which can detect, amplify and integrate diverse external signals to generate cellular response such as enzyme activity, stimulation of proliferation or cell death and lastly induced gene expression [17]. Abnormalities in these pathways may lead to a functional imbalance in multiple neurotransmitter pathways, which could account for the diverse clinical features found in BD [18]. Most neurotransmitter receptors are coupled to guanine-nucleotide binding proteins (G-protein). These proteins link receptors to specific enzymes that activate second messengers, or alternatively, they link to specific ion channels. Now, the extracellular signals are integrated,

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amplified and transmitted to specific intracellular enzymes, called effectors, which catalyse the production of an extensive array of cascading second messengers. In turn, these messenger molecules act on various protein kinases [17]. The activation of these kinases is instrumental in regulating diverse intracellular processes, including gene expression, and in relating these to lasting neurobiological changes [17]. The number of findings for abnormalities in signal transduction systems in samples obtained directly from patients is growing. Indeed, animal and cell culture studies have demonstrated pharmacological effects of mood stabilizers, especially lithium, suggesting its role in neuroprotection, which range from reducing excitotoxicity through increased glutamate uptake, to regulation of a number of second messenger systems, such as adenylate cyclase (cyclic adenosine monophosphate, cAMP), phosphoinositide (PI), protein kinase C (PKC), protein kinase A (PKA), protein kinase B (AKT) and glycogen synthase kinase-3 (GSK-3) [19]. The next sections of this chapter will characterize, define and describe the alterations in signalling transduction pathways in BD. We begin by examining the membrane receptor and how they are activated by external factors. Then, we will review the second messengers that relay information from the receptor-ligand complex. Lastly, we will discuss how the second messengers transduce this information to gene expression.

Membrane receptors and their coupling to signal transduction pathways Most signal transduction involves binding of extracellular signalling molecules (or ligands) to membrane receptors to transfer the information from the environment to the cell’s interior. One of the most common types of signal transduction pathways involves modulating adenylyl cyclase via GTP-binding proteins, more commonly known as G proteins [17]. G-protein coupled receptors play a critical role in BD, since the monoaminergic receptors are coupled to G protein. The tyrosine kinase receptors (TRK) also have an important role in BD, owing to bind growth factors that actives a neurotrophic cascade.

G-Proteins coupled receptors in BD G-proteins are an integral part of the intracellular signalling pathway, in that they link receptors in the membrane to diverse intracellular effectors molecules and responses (Figure 1). G proteins consist of three subunits: an a subunit that binds and hydrolyzes guanosine triphosphate (GTP), and b and g subunits that are tightly bound to one another [20]. This heterogeneous protein structure allows for the coupling of a wide variety of receptors to the same or different signal transduction systems, leading to nearly infi-

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nite combinations. Even modest changes in the levels of the G proteins have the potential to markedly alter the orderly progression of events from the membrane receptors to their intracellular targets. Stimulation of GPCR causes dissociation of G-protein subunits following the binding of GTP to Ga; this can subsequently result in the activation of distinct Gaand Gbg-sensitive isoforms of adenylate cyclase, phospholipase C (PLC) and other second messengers (see Figure 1). The interaction between GPCRs and the large number of different G-protein subunits can potentially be quite diverse, as one GPCR is capable of interacting with more than one G protein to result in multifunctional signalling [21,22]. The interest in studying G proteins in BD was largely prompted by animal studies. These studies found that lithium attenuates the function of several G proteins, including the stimulatory subtype (Gas) (for review see [23]). Gas levels (but not Gai, Gaq or Gb) have been described as increased in frontal, temporal and occipital cortex from patients with BD [24–26]. Furthermore, in the same samples, [25] showed increased activity of adenylate cyclase (AC), which correlate with the increased Gas levels, denoting a functional relevance. Using [[35]S]GTPgS binding, a specific binding assay for G proteins, Friedman and Wang [26] showed that brain membrane from patients with BD has enhanced 5-HT receptor-G-protein coupling. Dowlatshahi et al. [27] demonstrated decreased occipital cortex Gas levels in subjects with BD treated with lithium (Table 1). Studies in peripheral cells have showed the same results as postmortem tissue in patients with BD. Increased Gas levels have been found in mononuclear leucocytes (MNLs) from unmedicated patients with BD [30,31]. Supporting the hypothesis that G-protein coupling may be linked to mood state, several studies have demonstrated increased coupling levels during mania [32,33]. Avissar et al. [33] showed elevations to Gas and Gai levels in MNLs of patients with BD during mania and decreased levels during depression. In addition, Schreiber et al. [32] reported enhanced binding of [[3]H]Gpp(NH)p in MNLs of patients with mania, implicating increased G-protein levels and enhanced receptormediated G-protein activation in this patient group. More recently, Hahn et al. [34] demonstrated elevated [35S]GTPgS binding to platelet membrane Gas, Gai and Gaq/11 subunits in patients with BD during the manic phase. Increased levels of Gas 45- and Gas 52-kDa were reported in platelets of patients with BD in euthymia [35]. On the other hand, Alda et al. [36] measured Gas levels in transformed lymphoblasts from lithium-responsive patients with BD but did not find differences, compared with control subjects. This suggests that mood state may be an important factor in determining changes to Gas levels in blood cells from patients with BD (Table 1). Linkage studies in BD to the gene coding for Gas have yielded negative results [37–40] and, similarly, the

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Fig. 1 Signalling transduction pathways in Bipolar Disorder. Activation of stimulatory G-protein alpha subunits (Gas) leads to binding and activation of adenyl cyclase (AC), which in turn catalyzes the conversion of ATP into cAMP). The major target for cAMP is the protein kinase A (PKA). Once PKA is activated, it phosphorylates a number of other proteins including transcription factors, which regulate gene expression. G-protein isoforms Gq/G11 promotes activation of the phosphatidylinositol-specific phospholipase-b (PLC-b) enzyme PLC in turn catalyses the hydrolysis of the inositol-containing phospholipid phosphatidylinositol 4,5-bisphosphate (PIP2) into two second messengers: inositol 1,4,5-trisphosphate (IP3) and 1,2-diacylglycerol (DAG). IP3 binds to an IP3-specific receptor on the endoplasmic reticulum surface and stimulates the release of intracellularstored Ca2 þ . The transcription factors CREB suffer phophorylation by Ca2 þ which promotes transcriptional activation of gene expression. DAG, on the other hand, activates >PKC. PKC is involved in phosphorylating other proteins in the cell, such as GSK-3b. The Wnt protein bind to the frizzled receptors, and result in inhibits GSK-3b through dishevelled protein. GSK-3b inhibition promotes activation of b-catenin transcription factors. The last pathway showed in this figure is the tyrosine kinase recptors (TRK). Trk receptor activation promote RAS pathway activation which ultimate regulate gene expression by interaction with transcription factors, that is, CREB and b-catenin.

gene-expression levels of Gas do not appear to be altered in BD postmortem brain [28]. However, there is evidence suggesting abnormalities in the coupling of neurotransmitter receptors to the G-protein signal pathways [41]. Overactivation of G-protein-coupled serotonergic (reviewed by Catapano and Manji [42]) and dopaminergic receptors [43,44] have been described in patients with BD. Indeed, studies have identified an association between the serotonergic 5HT2A receptor polymorphisms and BD and have demonstrated that the most common polymorphism associated with BD is the C516T, C135T and A-1438G [45–47].

Interestingly, abnormalities in the 5HT1A receptor binding in BD patients are normalized with chronic lithium administration [8]. The G-protein coupled dopaminergic receptors, D1 and D2, may also be associated with BD, supported by the association between the illness and the D1 receptor’s A48G polymorphism [48]. Massat et al. [49] found a significant association between D2 receptor and BD. Another receptor that has been received attention in BD is the G-protein receptor kinase 3 (GRK3). A recent study demonstrated significantly decreased protein and mRNA levels

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Table 1 G protein signalling in bipolar disorder. Samples

Findings

Reference

Postmortem brain Cerebral cortex

" Gas, $ Gai, Gaq, Gb $ Gas mRNA levels " coupling of 5-HT receptors to membrane of G-proteins # Gas in lithium-treated subjects # Gb, Gg and GRK3 " 3[H]Gpp(NH)p binding in patients during mania " Gas levels in unmedicated depressed patients " Gas and Gai levels in patients during mania # Gas and Gai levels in patients during depression " Gas mRNA levels in unmedicated patients " Gas 45- and Gas 52-kDa in patient in euthymia " [35S]GTPgS binding to Gas, Gai and Gaq/11 $ Gas levels in lithium-responsive patients

[24,25] [28] [26] [27] [29] [32] [31] [33]

Leukocytes

Platelets Transformed lymphoblast a

[30] [35] [34] [36]

" – increased levels, # – decreased levels and $ no alteration in relation to healthy control group.

of G-protein b3, G-protein g and GRK3 in postmortem prefrontal cortex of BD compared to control subjects [29]. The same study did not find significant group differences in the protein or mRNA levels of GRK2. GRK3 protein levels were also investigated in lymphoblatoid cell lines derived from patients with BD, these patients showed decreased GRK3 levels and these decreases correlated with disease severity [50]. Taken together, there is considerable evidence, both conceptually and experimentally, that supports altered Ga levels and function, or both. This could occur through increased receptor G-protein coupling and could play an important role in the biological basis of BD.

Tyrosine kinase receptor TRKs are transmembrane proteins with an intracellular kinase domain and an extracellular domain that binds ligand. There are many TRK proteins -at are classified into subfamilies, depending on their structural properties and ligand specificity [51–53]. These include many growth factor receptors, such as nerve insuline-like growth factor (IGF) and brain-derived neurotrophic factor (BDNF) receptors. To conduct their biochemical signals, TRK need to be activated by binding of specific ligands such as growth factor. Interaction between the receptor and the ligand stimulate autophosphorylation of tyrosines within the cytoplasmic tyrosine kinase domains of the TRKs, causing their conformational changes. The kinase domain of the receptors is subsequently activated, initiating signalling cascades of phosphorylation of downstream cytoplasmic molecules. These signals are essential to various cellular processes, such as control of cell growth, differentiation, metabolism, and migration [51,52]. The function of growth factors is mediated through the activation of TRK [53] as they interact with different sub-

types of TRK. Specifically, nerve growth factor (NGF) binds to TrkA; BDNF and neurotrophin-4 (NT4) bind to TrkB; and neurotrophin-3 (NT3) activates TrkC [53]. The activation of TRK and p75NTR receptors by neurotrophins induces regulation of several signalling pathways. The p75NTR receptor regulates three major signalling pathways: (1) NF-kB activation results in transcription of multiple genes, including several that promote neuronal survival; (2) Activation of the Jun kinase pathway similarly controls activation of several genes, some of which promote neuronal apoptosis; (3) Regulates the activity of Rho, which controls growth cone motility. Trk receptor also controls three major signalling pathways: (1) Activation of Ras results in activation of the MAP kinase-signalling cascade, which promotes neuronal differentiation including neurite outgrowth; (2) Activation of PI3 kinase through Ras or Gab1 promoting survival and growth of neurons and other cells; (3) Activation of phospholipase C g1 (PLC-g1) results in activation of Ca2 þ - and PKC regulating pathways that promote synaptic plasticity. These signalling pathways ultimately regulate gene expression by interaction with transcription factors, that is, CREB and b-catenin [51,53]. Growth factors, especially BDNF, have been extensively studied in BD (for review see [54]). BDNF exerts a role in regulating neuronal survival, structure, function and it is essential to long-term memory [55]. Decreased serum BDNF levels have been reported in BD patients in manic state [56,57] as well as in individuals with depressive symptoms [56]. During euthymia, studies have shown decreased levels [58] and unaltered BDNF levels [56] when compared to control groups. Interestingly, drug-free and medicated patients with BD showed decreased serum levels of BDNF, and these results may suggest that the association of lower serum BDNF and BD is maintained throughout pharmacotherapy, which strengthens the notion that BDNF serum levels may

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be considered a biomarker of mood episodes in BD [59]. Supporting the role of BDNF in BD, Dunham et al. [60] reported decreased expression of (pro)BDNF in hippocampus from subjects with BD or major depression. Another important factor that contributes to decreases in the expression of BDNF is ageing [61], which can contribute to age-related cognitive impairments [62]. Recent findings from our group showed accelerated age-related decreases in BDNF levels in patients with BD, in comparison to matched healthy subjects [63]. In addition, Kauer-Sant’Anna et al. [64] compared BDNF serum levels between early (1–3 years) and late (10–20 years) stage of the disorder, the results showing decreased BDNF levels only in late stage patients, suggesting that BDNF could be associated with illness progression. Furthermore, an accelerated ageing process has been suggested to occur in BD, as indicated by the alterations in diverse oxidative stress parameters [65–71].

Second messengers After the binding of signal proteins in the receptor, a second messenger is activated. This is responsible to amplify the stimulus and initiates a cell’s response cascade [17]. Second messengers include cAMP, PKA, PI, Ca2 þ , PKC and GSK-3, which typically modulate the phosphorylation state of intracellular proteins, which in turn regulate neuronal function [20]. Several studies have showed alterations in activity or levels of second messengers in BD, described below. We also have summarize this pathway in Figure 1 and the findings in BD in Tables 2–4.

The cAMP and PKA pathway One well characterized signal transduction pathway is the activation of stimulatory G-protein alpha subunits (Gas) that leads to the binding and activation of adenyl cyclase

(AC), which in turn catalyses the conversion of ATP into cAMP [20,99]. The major target for cAMP is another enzyme, cAMP-dependent protein kinase, also known as PKA (see Figure 1). Once PKA is activated, it phosphorylates a number of other proteins, including transcription factors, which regulate gene expression. This pathway is a critical step in linking short-term changes in neurotransmitter signalling to lasting neurobiological changes [100]. Several studies have reported that basal and receptoractivated AC activities are increased in patients with BD; these findings are summarized in Table 2. Postmortem brain studies of patients with BD identified increased levels of postreceptor stimulated AC activity [72] and increased levels of forskolin-stimulated cAMP production [24,25]. Studies in peripheral mononuclear cells from patients with BD suggest that there are changes in receptor and/or postreceptor sensitivity in the cAMP system without alterations to cell receptor number (reviewed by [101]). In platelet samples from treated euthymic bipolar patients, cAMPstimulated phosphorylation of Rap-1, a cAMP substrate was increased when compared to healthy subjects [76]. Interestingly, Zanardi et al. [102] showed increased basal and cAMP-stimulated protein phosphorylation after lithium treatment. Studies evaluating patients with BD in various mood states before and after treatment also have evidenced increased levels and activity of PKA, a major target for cAMP [77,78,103]. PKA activity was found increased in the temporal cortex of patients with BD [73]. Subsequent analysis of the specific PKA subunits suggests that elevated PKA activity in BD results from a state-related imbalance in the specific PKA subunits [75]. Platelets from both unmedicated euthymic and depressed patients with BD have been shown to have higher cAMP-stimulated PKA activity in comparison to healthy controls [77]. Increased levels of the PKA

Table 2 cAMP and PKA signalling in bipolar disorder. Samples

Findings

Reference

Postmortem brain Cerebral cortex

" AC activity

[72]

" fosfokolin-stimulated cAMP production " PKA levels in temporal cortex # [3 H]cAMP binding to PKA " Maximal and basal cAMP-dependent PKA activity and # PKA EC50 " PKA catalytic subunit in mania and depression, but not in euthymia. " Rap1 in mania, depression and euthymia " cAMP-stimulated PKA activity in unmedicated euthymic and depressed bipolar patients have significantly higher " PKA catalytic subunit and # [3 H]cAMP binding " basal PKA activity " PKA catalytic subunit levels

[24,25] [73] [74] [75] [76]

Platelets

Transformed lymphoblast a

[77] [89] [78]

" – increased levels, # – decreased levels and $ no alteration in relation to healthy control group.

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Table 3 PI pathway in bipolar disorder. Samples

Findings

Reference

Postmortem brain Cerebral cortex

" levels of Gaq/11 and PLC levels

[79]

" PKC levels # inositol levels in the prefrontal cortex but not in the occiptal or cerebellum # PI-coupled G-protein activation

[80] [81] [82]

Calcium Biopsy-derived Platelets

Calcium Platelets

Serum Calcium Transformed lymphoblast a

# " " # " "

Ca2 þ levels in response to odorant stimulation in olfactory neurons receptor PIP2 levels in patients during depression PKC activity in patients during mania PIP2 levels in lithium-treated patients during euthymia PKC-b1 and -b2 activity and mRNA levels in medication-free paediatric BD Intracellular Ca2 þ

[34] [83] [84] [85–88] [89] [90]

" " " " " #

Intracellular Ca2 þ in patients during mania and depression Thapsigargin-induced cytosolic Ca2 þ total and ionised Ca2 þ levels Basal Ca2 þ levels in patients with BD-1 Ca2 þ mobilisation by LPA stimulation Ca2 þ levels after LPA or Thapsigargin in lithium treated patients

[91] [92–94] [95] [96] [97] [98]

" – increased levels, # – decreased levels and $ no alteration in relation to healthy control group.

catalytic subunit in platelets were found in BD patients in the depressed or manic state compared with euthymic patients or healthy controls [76]. Interestingly, the same study showed that regardless of phase, patients with BD presented increased levels of Rap1, which is a protein substrate of PKA that has a role in regulating cell adhesion [76]. Karege et al. [78] reported that lymphoblast cells from patients with BD present increased PKA activity and reduced [3 H]cAMP binding to PKA regulatory subunits, in comparison with healthy controls. In addition, they reported that measurement of cAMP signalling system activity during PKA activation or inhibition in euthymic BD Table 4 Neurotrophic factors in bipolar disorder. Samples

Findings

Reference

Postmortem brain Hippocampus Serum

# (pro)BDNF and p75 expression

[60]

# BDNF levels in depression and mania $ BDNF levels in euthymia # BDNF unmedicated patients # BDNF levels euthymia # BDNF levels in drug-free and medicated patients # BDNF levels in late stage of the disorder but not in early stage

[56]

a

[57] [58] [59] [64]

" – increased levels, # – decreased levels and $ no alteration in relation to healthy control group.

patients revealed increased basal PKA activity, PKA catalytic subunit levels and enhanced pCREB expression in comparison with controls [104]. These findings support the involvement of cAMP and concomitant PKA activation in BD. Indeed, PKA activation has a relevant role in BD since it phosphorylates a number of other proteins, including transcription factors, which ultimately regulate gene expression and these findings are described below.

The phosphoinositide (PI) pathway Another important signalling pathway that is coupled to neurotransmitter involves the G-protein isoforms Gq/G11, which promotes the activation of phosphatidylinositolspecific phospholipase-b (PLC-b) enzyme [105]. PLC-b in turn catalyses the hydrolysis of the inositol-containing phospholipid phosphatidylinositol 4,5-bisphosphate (PIP2) into two second messengers: inositol 1,4,5-trisphosphate (IP3) and 1,2-diacylglycerol (DAG) (Figure 1) [103]. DAG remains bound to the membrane and IP3 is released as a soluble structure into the cytosol. IP3 then diffuses through the cytosol to bind to IP3-specific receptor on the endoplasmic reticulum (ER) surface and stimulates the release of intracellular-stored Ca2 þ from the smooth ER into the cytosol [106]. Many of Ca2 þ ’s effects are mediated by the Ca2 þ -binding protein, calmodulin, which then binds to a variety of target proteins, including protein kinases; that is, CaM kinase family (CaMK). CaMK I and IV isoforms are suggested to be involved in mediating transcriptional activation of gene expression, by phosphorylation of transcription factors, such as CREB (revised in [101]). Therefore,

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increment of intracellular Ca2 þ in neurons is directly connected with neurotransmitters release [19]. DAG, on the other hand, activates PKC, which comprises another family of kinases [107]. DAG causes PKC to move from the cytosol to the plasma membrane, where it also binds Ca2 þ and phosphatidylserine, a membrane phospholipid. These events relieve autoinhibition and cause PKC to phosphorylate various protein substrates. PKC also diffuses to sites other than the plasma membrane, such as the cytoskeleton, perinuclear sites and the nucleus [107]. Several studies have demonstrated alterations in the PI pathways in BD (reviewed in [108] and summarized in Table 3). Shimon et al. [81] have shown decreased levels of inositol in the prefrontal cortex but not in the occipital cortex or cerebellum of patients with BD. Increased levels of Gaq/ 11 and PLC [79] and diminished PI-coupled G-protein activation [82] were observed in occipital cortex from patients with BD, suggesting an adaptive increase in Gaq/11 expression as a result of deficient PI-signalling activity in BD [101]. Lymphoblastoid cell and lymphocytes from patients with BD have also demonstrated decreased levels of inositol [109], reduced inositol monophosphatase 2 (IMPA2) mRNA ([110,111] and reduced activity of IMPase [112]. Studies examining the relative content of membrane PIs have focused on the major PLC-b substrate, PIP2. Brown et al. [83] showed increased levels of PIP2 in platelets of patients with BD during depressed phase. Moreover, reduced levels of PIP2 in platelets in lithium-treated patients during euthymia have been shown [85–88]. DAG kinase is a member of the family of diacylglycerol kinases (DGKs) that play a major role in regulating the PI-signalling pathway. The major target of phosphorilation, for DGKs, is PKC [113]. This reaction is tightly regulated [114], thus even modest impairments in the function of DGKs can result in a dysregulation of PKC signalling. Recently, two completely independent genome-wide association studies have identified DGKH as a risk gene for BD. In the NIMH study, over 550 000 single nucleotide polymorphisms (SNPs) were genotyped in two independent case–control samples [115]. The 37 most significant SNPs were individually genotyped, and of these, the strongest association signal (p ¼ 1.5
108) was at a polymorphism in the DGKH gene. A second genome-wide association study, by the Wellcome Trust Case Control Consortium [37], investigated a different array of SNPs and found several in DGKH that were associated with BD at the 103 level. PKC activity has demonstrated to be increased in the manic state of patients with BD [84]. PKC levels were measured in postmortem brain tissue from subjects with BD and found increased in the frontal cortex, compared with control subjects [80]. Interestingly, lithium and valproate have been shown to have a potential role in

decreasing the levels of PKC in animal models, cell culture and platelets of lithium-treated patients (revised in [116]). On other hand, a recent study using platelets obtained from medication-free paediatric BD showed that PKC activity and the protein expression of PKC subunits beta I and beta II, but not PKC alpha or PKC delta, were significantly decreased in both membrane as well as cytosol fractions; after 8 weeks of mood stabilizer pharmacotherapy, PKC activity was significantly increased but there were no changes to any of the PKC isozymes in patients with BD [89]. These results indicate that PKC expression and activity may be associated with the molecular biology of BD and that pharmacotherapy with mood stabilizing drugs results in an increase and normalization of PKC activity in conjunction with improved clinical symptoms. Table 3 summarizes these findings. IP3 activation induces Ca2 þ release from the ER to the cytosol [106]. Although the importance of Ca2 þ in synaptic transmission and neurotransmitter release is well established, it has become increasingly apparent that Ca2 þ has a critical role in mediating diverse intracellular events; that is, synaptic plasticity, cell survival and excitotoxic cell death (reviewed in [117]). Dubovsky et al. [90] were the first to report that intracellular Ca2 þ concentration is elevated in platelets from patients with BD. Subsequently, the same group found increased free intracellular Ca2 þ in both depression and mania [79]. Increased total serum and ionized Ca2 þ has also been reported in euthymic lithium-treated patients compared with healthy controls [95]. More recently, intracellular Ca2 þ levels were examined in biopsy-derived olfactory receptor neurons from patients with BD in euthymia. Patients showed reduced Ca2 þ levels in response to odorant stimulation, whereas controls showed elevated levels [34]. In addition, elevated basal Ca2 þ concentrations have been detected in transformed B lymphoblasts in bipolar I disorder, compared with those in bipolar II disorder, major depression or healthy controls associated with abnormalities in receptor-coupled and G-protein-coupled adenylyl cyclase activity [96]. Thus, Ca2 þ homoeostasis appears altered across all mood states in BD (for summary of these results see Table 3). Agonist-induced Ca2 þ influx by thrombin, serotonin and platelet activating factor is reportedly enhanced in the cells derived from patients with BD, regardless of the agonist used [108,117]. Thapsigargin-induced cytosolic Ca2 þ response was found increased in peripheral blood cells from patients with BD [92–94]. Perova et al. [97] have shown increased Ca2 þ mobilization by lysophosphatidic acid (LPA) stimulation in B lymphoblast cell lines from patients with BD-I, as LPA has been shown to provoke Ca2 þ entry through a DAG-dependent TRPC3-like channel, and these findings suggest that the disturbance in Ca2 þ homoeostasis is probably due to disturbances in DAG-gated TRPC3 channels. Interesting, lithium attenuates LPA-stimulated

Molecular Biology

and store depletion (thapsigargin)-induced intracellular Ca2 þ mobilization in B lymphoblast cell lines from patients with BD-I [98]. Other factors such as N-methyl-D-aspartate receptor, calcium-permeable AMPA/kainate receptor or voltage-dependent calcium channel might also cause abnormal calcium signalling in neurons. Indeed, much evidence suggests that the genes of these receptors and channels are altered in the postmortem brains of patients with BD [118], and one of the strongest pieces of evidence of GWAS was CACNA1C encoding the L-type voltagedependent Ca2 þ channel [37]. The PI pathway has shown important and consistent alteration in BD, regardless of the mood state. These alterations are characterized by decreased inositol level, increased PIP2 levels, increased intracellular Caþ 2 and increased PKC in the frontal cortex. The PI pathway is also a target for mood stabilizers, emphasizing the relevance of this pathway for the pathophysiology of BD.

Regulation of the second messenger GSK-3 by protein kinase B (AKT) and Wnt system GSK-3 has been identified as an important second messenger in BD. This is a serine/threonine protein kinase existing as two distinct gene products a and b, both recognized as a ubiquitous multifunctional enzyme involved in the modulation of many aspects of neuronal function, that is, proliferation, differentiation, axogenesis and synaptogenesis [119]. As the majority of the studies in BD have focus in the GSK-3b, this chapter will focus on this isoform. As the list of substrates phosphorylated by GSK-3b include more than 40 proteins and also include dysregulation of metabolic, signalling and structural proteins as well as inhibition of transcription factors, regulating GSK-3b activity has great impact [120]. For example, GSK-3b is highly expressed in the adult brain and is known to phosphorylate a number of important cytoskeletal proteins, such as Tau, MAP-1B and MAP-2 [121]. GSK-3b-mediated MAP-1B phosphorylation is associated with the loss and/or unbundling of stable axonal microtubules [122]. Furthermore, GSK-3b promotes the intrinsic apoptotic-signalling pathway by regulating transcription factors that control the expression of pro- and anti-apoptotic proteins, by promoting microtubule disruption and cell structural changes that occur during apoptosis, and by promoting disruption of mitochondria [123]. In this context, numerous signalling pathways are involved in controlling the inactivation of GSK-3b, including the phosphoinositide 3-kinase (PI-3K) pathway and the Wnt pathway [116]. The activation of tyrosine kinases receptors, by growth factors, causes dimerization and undergoes autophosphorylation at tyrosine residues, which allows the activation of PI-3K, then in turn promotes the phosphorylation of the membrane phospholipid PIP2 to form PIP3, which activates the protein-serine/threonine kinase Akt [99]. Akt

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then phosphorylates a number of proteins that regulate cell survival. Substrates for Akt are GSK-3a and GSK-3b that is inactivated through the phosphorylation of the single serine residues serine 21 (GSK-3a) and serine 9 (GSK-3b), which is located in the regulatory N-terminal domain [99]. Another system involved in controlling the GSK-3 status is the Wnt pathway. The Wnt protein family is composed of at least 15 secreted glycoproteins [124]. These proteins bind to the ‘frizzled’ family of extracellular receptors, and result in a signal that is transduced via an intracellular protein, becoming dishevelled. Signalling through activated dishevelling inhibits GSK-3b [125]. GSK-3b inhibition promotes activation of several transcription factors, including bcatenin, HSF-1, AP-1 and CREB. These targets are believed to have a strong neuroprotective effects by allowing the transcription of specifics genes. GSK-3b has received great attention in BD, due to evidence that lithium and valproate inhibit GSK-3b through its phosphorylation (reviewed in [126]). The mechanism by which lithium increases phosphorylation levels is not yet fully delineated. One prominent pathway is the PI3K/Akt pathway. Several studies have shown that lithium increases BDNF levels in cell culture [127] and in an animal model [128] which, via the Trk B receptor, then stimulates the PI3K/Akt and MEK/ERK pathways [129,130]. Notably, the neuroprotective effects of lithium against excitotoxicity are mimicked by treatments with other GSK-3 inhibitors or by transfection with GSK-3 isoform-specific siRNA and dominant-negative mutants [131], suggesting that at least this aspect of lithium’s action is mediated through GSK-3 inhibition. Valproate also increases GSK-3b’s phosphorylation levels that promote GSK-3 inhibition. Lithium and valproate can activate the Wnt pathway and increase bcatenin mRNA and protein levels [132,133]. Several studies have examined the association of GSK-3 single nucleotide polymorphisms (SNPs) with BD [134–136]. In a Korean population, the 1727 A/T and 50 C/T SNPs of GSK-3 showed no difference between BD patients and controls [134], with similar results found in Caucasian populations [137]. In an Italian population, the 50 C/T SNP also showed no difference between BD and controls, but did influence the age of onset [135]. A fourth research study has found a general trend towards an association between the C allele, T/C polymorphism and BD. A closer examination of the data found a strong link between the T-50C polymorphism and females with bipolar II [136]. These four studies indicate that GSK-3 mutations are not linked to the presence of BD, with the exception of females with bipolar II disorder. Postmortem studies did not find differences in the levels of GSK-3b, b-catenin or Dvl-2 between BD, schizophrenia, major depressive disorder and controls [138]. It is conceivable that GSK-3 mutations may predict treatment efficacy. The first study that examined this issue found

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that the 50 C/T SNP mutation improved the recurrence index (frequency of episodes pre- and post-lithium treatment) following lithium administration [139]. However, subsequent studies found that neither genotype nor allele frequencies could predict a lithium response in bipolar I patients [140], nor was the T-50C polymorphism related to lithium prophylaxis [136]. Moreover, genetic and post mortem studies have not identified alteration on gene or protein expression of GSK-3 in patients with BD. However, the strong evidence that lithium regulates the phosphorulation levels of GSK-3 suggests the need for continued interest in this pathway to further understand the neurobiology of BD.

Transcription factors The activation of a transcription factor by a second messenger is the last step in the signal transduction. The consequence of transcription factor activation is a modulation of gene expression. Thus, a transcription factor is a protein that binds to specific DNA sequences and thereby controls the transfer (or transcription) of genetic information from DNA to messenger ribonucleic acid (mRNA) [141]. Transcription factors perform this function alone or with other proteins in a complex, by promoting (as an activator) or blocking (as a repressor) the recruitment of RNA polymerase to specific genes. Rather than the complete list of important transcription factors, this chapter describes the b-catenin, HSF-1, AP-1 and CREB due to the potential role in the patophysiology BD [141]. b-catenin is a proto-oncogene product and part of the canonical Wnt-1 pathway. The mechanism of regulation of b-catenin involves its phosphorylation by casein kinase 1 (CK1) at Ser-45 site and by GSK3 at Thr-41, Ser-37 and Ser-33 sites. This phosphorylation targets b-catenin to ubiquitination and degradation by the proteasome system [142]. Wnt proteins bind to a family of extracellular receptors known as ‘frizzled’. Frizzled receptors activate the intracellular protein dishevelled 1, which in turn inhibits GSK-3b. Inhibition of GSK-3 activity results in a decrease in the phosphorylation of its substrate b-catenin and hence stabilization of this transcription factor [143]. b-catenin then accumulates in the cytoplasm and translocates to the nucleus with the transcription factor Lef/Tcf to activate transcription [144]. Inhibition of GSK-3b leads to increased b-catenin levels by nonphophorylation. As b-catenin accumulates, it interacts with the transcription factor Tcf/Lef (T-cell factor/lymphoid enhancer factor), which is translocated to the nucleus. The Tcf/Lef- b-catenin complex activates the transcription of diverse genes that include several involved in the inhibition of apoptosis [144,145]. Interestingly, [146] when investigating the effects of lithium and/or VPA on b-catenin and Lef/Tcf-dependent transcription in a cerebellar granule cell line, they found that treatment with either

lithium or VPA alone resulted in a 5- to 7-fold increase in Lef activity, and that b-catenin levels were enhanced by lithium and valproate. HSF-1 is a transcription factor activated by many stress conditions; once activated, HSF-1 triggers the expression of chaperone proteins, including heat shock protein 70 (Hsp70). Hsp70 has been reported to have neuroprotective functions [147], such as blocking apoptosis by binding apoptosis protease activating factor-1 (Apaf-1), thereby preventing constitution of the apoptosome, the Apaf-1/ cytochrome c/caspase-9 activation complex [148,149] and suppressing JNK activation [150]. HSF-1 activity is suppressed by serial phosphorylation. ERK phosphorylates HSF-1 at Ser307, which then allows GSK-3b to phosphorylate HSF-1 at Ser303 [151]. GSK-3b negatively regulates HSF-1, as both DNA binding by HSF-1 and HSF-1-dependent transcription are negatively correlated with GSK-3b activity [152,153]. As already noted, lithium is a potent GSk3b inhibitor, which in turn may affect the HSF-1 pathway. Ren et al. [154] showed that lithium-induced HSP70 upregulation in a rat ischaemia/reperfusion model, which was preceded by an increase in the DNA binding activity of HSF-1. Activator protein-1 (AP-1) is a collection of homodimeric and heterodimeric complexes that contains members of the Jun, Fos, CREB and ATF families. These products bind to a common DNA site (known as the TPA response element) in the regulatory domain of the gene, and activate gene transcription in response to a variety of stimuli, including cytokines, growth factors and stress. Typically, these signals activate the MAP kinases, primarily JNK and p38, which results in AP-1 binding to a variety of genes [120]. A secondary regulator of AP-1 is GSK-3b, which phosphorylates c-Jun so as to reduce AP-1 binding activity [155]. AP-1 in turn controls a number of cellular processes including differentiation, proliferation and apoptosis. Its activation can be either neuroprotective or neurodegenerative, depending upon the particular molecules that form the AP-1 complex and their target genes [156]. Several studies have demonstrated the lithium is able to increase the activity levels of AP-1 in culture cell [157]. Valproate also increased the DNA binding activity of the AP-1 family in rat C6 glioma cells [158]. Chen et al. [159] reported that valproate also increased the mediated AP-1 gene expression. More recently, Spiliotaki et al. [160] evaluated the nuclear protein level of c-fos and JNK and the AP-1-DNA-binding in patients with BD during euthymic or depressed states. They showed that patients in a depressed state presented lower levels of c-fos and JNK and AP-1-DNA-binding than controls, whereas euthymic patients only showed decreased levels of JNK, addressing to the literature a possible state related of this pathway. CREB resides in the nucleus and spends most of its time in an inactive form. Its activation occurs after phosphorylation

Molecular Biology

at a particular amino acid (Ser-133) by a number of protein kinases, including those that are downstream targets of the signalling pathways discussed earlier in this article (PKA, MAPKs such as RSK1–3, and CaMKs) [161]. Once phosphorylated, the pCREB protein binds to a specific site in the promoter region of target genes, known as the cAMPresponse element (CRE). This leads to the production of mRNA, which is the blueprint for the synthesis of new proteins [162]. This is a critical step: in many ways it is the final link coupling the rapid fluctuations in neurotransmitter levels and receptor binding to the production of new proteins that can permanently alter the function or structure of specific brain regions. CREB also plays crucial roles in maintaining normal synaptic transmission and plasticity, such as hippocampal long-term potentiation and memory [163]. CREB is sensitive to several stimuli, including growth factors and stress, resulting in its regulation by several of the previously discussed pathways, including BDNF, MEK/ERK and GSK-3b (reviewed by [120]). CREB increases the expression of anti-apoptotic proteins, that is, members of the Bcl-2 family [164] and BDNF [165] that confer neuroprotective properties to CREB. As BDNF induces CREB activation and CREB upregulates BDNF expression, this creates a feedback loop throughout the cell survival-signalling pathway. Chronic lithium treatment alters CREB activity in excitotoxic situations by preventing glutamate-induced loss of phosphorylated CREB and CRE-driven gene expression [166]. Another line of evidence is the effect of pharmacotherapy on transcription factor activity. For example, Nibuya et al. [167] demonstrated that chronic antidepressant treatment increased rat hippocampal CREB protein and mRNA levels, as well as the binding of CREB to the CRE. Dowlatshahi et al. [168] showed higher temporal cortex CREB levels in patients with major depressive disorder treated with antidepressants in comparison with untreated patients. Zubenko et al. [169] found an association with the CREB1 polymorphism and major depressive disorder. Chen et al. [159] demonstrated that chronic lithium treatment decreased CREB phosphorylation in rat cerebral cortex and hippocampus. Recently, using a transgenic mice model, Boer et al. [170] showed decreased CRE/CREB-direct gene expression by chronic lithium treatment in hippocampus, cortex, hypothalamus and striatum and likewise reduced CREB phosphorylation. Levels of pCREB are also reported to be substantially down-regulated following depletion of adrenergic input. The effect of lithium on CREB phosphorylation is consistent with previous findings that this drug decreases cAMP signalling [171]. Chronic treatment with lithium has been shown to blunt agonist-stimulated cAMP production, and to regulate expression of specific AC isoforms and cAMP-dependent protein kinase activity in rat brain and platelets of lithium-treated BD subjects [172,173]. Recently, the CREB-c-activator, transducer of regulated

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CREB (TORC) has been identified as a novel target of lithium and shown to confer an enhancement of cAMP-induced CREB-direct gene transcription by lithium [170,174]. These results are in accordance with previous findings in temporal cortex from patients with BD [168]. The CREB family belongs to the leucine zipper family of DNA-binding proteins able to recognize the CRE. CREB1 is located on chromosome 2q32.3-q34 and exists in one of two isoforms (CREB347/CREB327), differing by a 14bp deletion [175]. CREB2 or ATF4 is located on chromosome 22q13.1 and is a repressor of CRE-dependent transcription [176]. Lastly, there is the CREB3 gene, also referred to as LUMAN, located on chromosome 9pter-p22.1. Its function has not been completely elucidated; however, it appears that CREB3 behaves as a transcriptional activator similar to CREB1. Mamdani et al. [177] studied the genetic variants associated with lithium responders and suggested that the CREB1-1H SNP and CREB1-7H SNP may be associated with BD and/or lithium response. Taken together, these findings support the involvement of transcription factor in the reponse to mood stabilizers and the neurobiology of BD. In summary, lithium increase the expression of B-catenin, HSP-1 and CREB and valproate increase the AP-1- DNA-binding and expression of B-catenin. Modulation of transcription factors by mood stabilizers are likely critical in connecting the regulation of gene expression, which can present the cell impairment by increasing expression of genes related to neuroplasticity and cell resilience.

Implications for the pathophysiology of BD and treatment Given the complexity of intracellular communication, several intracellular pathways have been implicated in the action of mood-stabilizers [178]. For example, lithium inhibits the inositol monophosphatase [179] and valproate and lithium lead to a reduction in PKC activity [180]. One of the substrates of PKC is myristoylated alanine rich C (MARCKS), which has decreased expression by lithium and valproate in neuronal culture [180]. Furthermore, studies suggests that lithium and valproate can increased levels of neurotrophic factors, such as BDNF in hippocampus of rats pre-treated with psychostimulant d-amphetamine [181]. More recent studies have suggested that mood stabilizer, especially lithium, can directly inhibits GSK-3b by competing with Mg þ 2, which may account for the antiapoptotic effects of the ion [182]. As described above lithium and valproate also activate the transcription factors CREB, B-catenin and HSP-1. Although remarkable progress has been made in our understanding of the signal transduction abnormalities associated with BD, it is important to point out that this work represents only the beginning. Findings supporting

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cAMP-signalling abnormalities in BD are extensive, and suggest increased levels of stimulatory G-protein, Gas, at least in the manic state. Studies of PI pathway, a set of findings including increased PIP2 levels and PKC activity has generally implicated alterations in this signalling pathway. Increased Ca2 þ responses in both peripheral blood cells and postmortem brain tissue of subjects with BD have been observed by several independent laboratories, broadly supporting the findings in PI signalling. Modulation of signalling pathways are central to understanding the neuroplasticity mechanism involved in BD and the mechanisms of action of the mood stabilizers. Future studies including large samples will be crucial to improve the understanding of intracellular signalling control in mood disorder, and will be a key to development of new drugs for the treatment of BD.

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Mitochondrial Dysfunction and Oxidative Stress Tadafumi Kato1, Flavio Kapczinski2 and Michael Berk3 1

Laboratory for Molecular Dynamics of Mental Disorders, RIKEN Brain Science Institute, Saitama, Japan ISBD Hospital de Clinicas, UFRGS Brazil Porto Alegre, RS, Brazil 3 Barwon Health and the Geelong Clinic, University of Melbourne, Victoria, Australia 2

Introduction In this book, many biological aspects of bipolar disorder have been reviewed, such as genetics, brain imaging, neurotransmitters, neuroendocrinology, circadian rhythms and pharmacology. Although the biological evidence reported in bipolar disorder is yet to be integrated, mitochondrial dysfunction hypothesis has a potential to build up an integrated understanding of the biology of bipolar disorder. In this chapter, the authors try to put together these fragmental findings into a cohesive unifying hypothesis. Details of findings suggestive of mitochondrial dysfunction introduced in this chapter are also shown in other chapters. Three broad areas will be covered, pre-clinical, clinical and treatment implications.

In addition, magnetic resonance spectroscopic studies showed decreased levels of N-acetylaspartate, a marker of neuronal viability (see Chapter 14 on imaging techniques in bipolar disorder), and structural brain imaging studies showed decreased volume of several brain areas (see Chapter 13, Structural Brain Imaging in Bipolar Disorder) in patients with bipolar disorder. Lithium and valproate, two major mood stabilizers that are effective in bipolar disorder, reportedly have neuroprotective effects [5], at least partly by acting on mitochondria [6]. These findings altogether suggest that patients with bipolar disorder have vulnerability at the metabolic and cellular level, and mood stabilizers may exert their efficacy by improving such cellular vulnerability.

Cellular vulnerability in bipolar disorder Several lines of evidence show that vulnerability at the cellular level is involved in the pathophysiology of bipolar disorder. An increased incidence of subcortical hyperintensity (SCH) lesions was found in 7 out of 10 studies [1]. Because there is no specific location of the lesion causing bipolar disorder, increased incidence of SCH suggests that patients with bipolar disorder might have vulnerability at the cellular level to cellular stress. Amongst the studies of peripheral blood cells, increased levels of calcium in platelets or cultured lymphoblastoid cells are most replicated findings, supported by 11 out of 15 studies [2,3]. Because calcium is an important mediator of apoptosis, this may also be relevant to cellular vulnerability in the cells of patients with bipolar disorder. Indeed, enhanced apoptosis was reported in cultured neuroepitherium derived from patients with bipolar disorder [4].

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Phosphorous magnetic resonance spectroscopy in bipolar disorder The pathophysiological mechanism of how such vulnerability is caused in bipolar disorder is not known. The mitochondrial dysfunction hypothesis may account for such a mechanism. This hypothesis was first proposed based on the findings in phosphorus-31 magnetic resonance spectroscopy (31 P-MRS). The principle of MRS is summarized in Chapter 14, on imaging techniques in bipolar disorder. In the early 1990s, Kato and colleagues studied brain phosphorus metabolism, using 31 P-MRS in patients with bipolar disorder, and reported that phosphocreatine (PCr), a high energy phosphate found in the brain and muscles, was decreased in the frontal lobes in patients with severe depression [7]. Subsequent studies suggested that such findings in the left frontal region were seen in patients with bipolar depression, especially bipolar II disorder [8], and correlated with scores on the Hamilton rating scale [9]. Photic stimulation-induced reduction of PCr in the occipital cortex was exaggerated in patient with lithium-resistant bipolar disorder [10].

Mitochondrial Dysfunction and Oxidative Stress

The other finding, suggestive of mitochondrial dysfunction, was reduced intracellular pH observed in euthymic patients with bipolar disorder [11]. This finding was also seen in drug-free euthymic patients with bipolar disorder, and decreased pH was associated with the presence of white matter hyperintensity lesions detected by T2-weighted magnetic resonance imaging (MRI) [12]. Reduced pH was also observed in the basal ganglia and in the whole head 31 P-MR spectra [13]. Uridine, a drug used for mitochondrial diseases, is reported to alter intracellular pH in patients with bipolar disorder [14]. Amongst these findings, reduced PCr [15] and exaggerated PCr response to photic stimulation [16] were also reported in patients with mitochondrial diseases, especially chronic external ophthalmoplegia (CPEO).

Role of mitochondrial DNA deletion in bipolar disorder Mitochondrial diseases are caused by mutations of mitochondrial DNA (mtDNA). MtDNA is a 16 kb circular DNA, existing in mitochondria. There are multiple copies of mtDNA in a mitochondrion. It is speculated that mtDNA originated from ancient symbiotic life. MtDNA encodes subunits of mitochondrial proteins responsible for oxidative phosphorylation, and also tRNAs and rRNAs. Genes for enzymes required for the replication and maintenance of mtDNA are encoded in the nuclear genome. There are two types of mitochondrial diseases. One of these diseases is caused by maternally inherited heteroplasmic point mutations of mtDNA. A representative disease of this kind is Mitochondrial myopathy, Encephalopathy, Lactic Acidosis, and Stroke-like episodes (MELAS), mostly caused by mtDNA 3243A > G. mutation. The other type of disease is associated with accumulation of multiple deletions of mtDNA that is caused by autosomally inherited mutations in genes regulating mtDNA maintenance. Autosomally inherited Chronic Progressive External Opthalmoplegia (CPEO) (adCPEO) is a representative disease of this kind. Suomalainen and colleagues reported a case with adCPEO with severe retarded depression [17]. At the autopsy, the patient was found to have mtDNA deletions in the brain. Importantly, the amount of mtDNA deletions was much higher in the frontal cortex and basal ganglia, compared with muscles. This report from Finland first suggested that accumulation of mtDNA deletions in the brain might cause mood disorders. Stimulated by this finding, Stine and colleagues searched for the mtDNA deletions in the postmortem brains of patients with bipolar disorder, but they could not detect any deletions using Southern blotting [18]. Using the same samples, however, Kato and colleagues found that the mtDNA 4977 bp common deletion was slightly but significantly increased in

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bipolar disorder [19]. No such increase of 4977 bp deletion was found in bipolar disorder in the Stanley Brain Bank samples [20,21]. The next impressive work in this field was reported from Italy [22]. Siciliano and colleagues reported a family with adCPEO linked with a missense mutation of adenine nucleotide translocator 1 (ANT1) (L98P). They diagnosed the members of this family using DSM-IV criteria, and reported that all four living adult patients with CPEO in this family also had bipolar disorder. The proband, who had onset of CPEO at age 40, had bipolar disorder since her teens. Her sister having CPEO since her twenties also had bipolar disorder since her teens. The other sister, who had muscle symptoms at age 42, had onset of bipolar disorder in her 20’s. Their mother had onset of bipolar disorder and CPEO at age 45. In this family, it seems as if bipolar disorder was the most prominent phenotype of the mutation. More recently, Fattal and colleagues applied the Mini International Neuropsychiatric Interview to 36 patients with mitochondrial diseases [23] and found that 6 (17%) of them had bipolar disorder and 19 (54%) had lifetime major depression. The average onset of mental disorder was 7.5 years before the diagnosis of mitochondrial diseases. There are several other studies and case reports supporting the possible relationship between mitochondrial diseases and bipolar disorder [23,24]. CPEO is a multi-system disease characterized not only by muscle symptoms such as ophthalmoplegia but also by many other symptoms. Mutations of several genes cause CPEO; POLG (polymerase g) [25], ANT1 (adenine nucleotide translocator 1) [26], Twinkle [27], POLG2 (accessory subunit of polymerase g) [28], and so on. These reports suggested that bipolar disorder and depression may be one type of manifestation of symptoms of adCPEO.

Gene expression analysis Evidence related to mitochondrial dysfunction of bipolar disorder was also reported from comprehensive gene expression analysis. Konradi and colleagues performed comprehensive gene expression analysis in the postmortem hippocampus, and found that mitochondria related genes were globally downregulated in patients with bipolar disorder [29]. Although sample pH and agonal factors, terminal condition before death, are known to profoundly affect expression levels of mitochondria related genes [30,31], there was no significant difference in sample pH amongst groups in their samples [29]. They interpreted this finding as suggestive of mitochondrial dysfunction in bipolar disorder. The same finding of global down-regulation of mitochondria related genes was replicated by other investigators [32–34]. However, the interpretation of this finding is

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still controversial. In two of these studies, mitochondriarelated gene were up-regulated rather than down-regulated when agonal/pH factors were controlled [32,33]. In the other study, it was speculated that reduced pH observed in patients with bipolar disorder may account for the downregulation of mitochondrial genes [34]. Interaction between agonal factors or medication and the disease for this finding is possible. Munakata and colleagues analysed the expression levels of mitochondria related genes, and found that LARS2 showed most prominent up-regulation [35]. LARS2 encodes an enzyme catalysing aminoacylation of leucine transfer RNA. LARS2 was up-regulated in transmitochondrial cybrids carrying the mtDNA 3243G mutation within tRNALeu(UUR). When the 3243 mutation was screened using a sensitive method with protein nucleic acid (PNA), accumulation of the 3243G in the brain was found in 2 of 15 patients with bipolar disorder and 1 of 15 patients with schizophrenia, but not in the 15 controls.

Genetics Excess transmission of bipolar disorder from a mother compared with from a father, has been noted in early genetic studies of bipolar disorder [36]. McMahon and colleagues suggested that such phenomenon might be caused by maternal transmission of mtDNA [37]. However, no mutations causative for bipolar disorder were identified by sequencing of whole mtDNA in the probands in maternally inherited pedigrees [38,39]. Munakata and colleagues also sequenced mtDNA in six patients with bipolar disorder, who developed mitochondrial disease-like somatic symptoms after the diagnosis of bipolar disorder. Amongst the sequence variations found in these subjects, 3644C, a missense mutation in a complex I subunit (ND1), was suggested to have pathological significance because this mutation caused impaired complex I activity in transmitochondrial cybrids, and this variation was significantly associated with bipolar disorder in Japanese case control analysis. While 9 out of 630 (1.4%) patients with bipolar disorder had this mutation, only 1 out of 734 controls (0.14%) had this mutation. Although mtDNA 10398 polymorphism [40] and NDUFV2 [41] encoding a complex I subunit were also reported to be associated with bipolar disorder, such findings should be treated with caution, because association finding of common variations in this size of patient population is difficult to reproduce [42].

the promoter of calmodulin kinase IIa [43]. The mice had mtDNA deletions in various brain regions, such as frontal cortex and hippocampus. Four other lines of mutant mice carrying POLG mutations have been reported so far; cardiac muscle specific D181A mice [44], mutant POLG knock-in mouse (D257A) [45,46] and cardiac muscle specific mutant POLG (Y955C) transgenic mouse [47]. While cardiac muscle specific transgenic mice showed cardiomyopathy, knock-in mice showed various ageing-associated phenotypes, such as kyphosis and alopecia. Neurobehavioral phenotypes of the two knock-in mice strains have not been reported yet. Although multiple deletions were first noticed in patients with CPEO, point mutations were also increased in the tissues of these mice. There is an ongoing debate as to whether deletions or point mutations are more important, for the phenotypes of POLG mutant mice [48]. The neuron specific mutant POLG (mPOLG) transgenic (Tg) mice did not show marked abnormality in sensorimotor functions and learning and memory. On the other hand, they showed altered intra-day wheel running activity rhythm, with high activity at the beginning of, as well as at the end of, the light phase [43]. This altered intra-day activity rhythm was improved by electroconvulsive stimulation [49]. The wheel running activity was decreased in the mice, and after the treatment with amitriptyline, a tricyclic antidepressant that can cause a manic switch in patients with bipolar disorder, the Tg mice showed manic switch-like enhancement of activity. Female mice showed robust periodic change of wheel running activity associated with oestrous cycle. This periodic activity change, as well as altered intra-day rhythm, was improved after the lithium treatment [43]. These findings supported the three validity criteria as an animal model; construct validity, supported by comorbidity of bipolar disorder with CPEO, face validity, periodic activity change and altered intra-day rhythm, and predictive validity, that is, effect of lithium treatment.

Consequence of mitochondrial dysfunction There are several possible explanations for the cause of these characteristic behavioural phenotypes. One is a calcium signalling abnormality, resulting in altered neuroplasticity. The second is progressive cell loss in particular brain region(s). The third possibility is increased generation of reactive oxygen species due to mitochondrial dysfunction.

Animal models

Calcium signalling

To study the possible role of mtDNA mutations in the brain in pathophysiology of bipolar disorder, we generated a transgenic mouse carrying mutant POLG (D181A) under

As discussed above, calcium signalling abnormalities have been reported in blood cells obtained from patients with bipolar disorder [3,50]. Basal calcium levels and calcium

Mitochondrial Dysfunction and Oxidative Stress

response to phosphoinositide-linked receptor stimulation were reported to be elevated in patients with bipolar disorder. Calcium release from endoplasmic reticulum (ER) is followed by calcium uptake by mitochondria at microdomain between these two organella. Mitochondrial calcium uptake has been reported to be involved in neuronal functions, such as exocytosis and neuroplastic changes [51]. Thus, mitochondrial dysfunction may cause altered neural functions associated with impairment of mitochondrial calcium signalling. Because the driving force behind calcium uptake by mitochondria is the proton gradient generated by mitochondrial respiratory chain, mitochondrial dysfunction may decrease membrane potential and cause impaired calcium uptake. When calcium retention capacity (CRC) was measured in isolated mitochondria obtained from the mutant POLG Tg mice, but there was no difference of CRC [52]. Contrary to their expectation, mitochondria isolated from the brains of Tg mice showed enhanced calcium uptake rate. Gene expression analysis of the brains of the Tg mice showed down-regulation of cyclophilin D (CypD) [52]. CypD is a component of permeability transition pore. A CypD inhibitor, cyclosporin A, mimicked the enhanced uptake rate in the mitochondria of Tg mice. Thus, they concluded that decrease of CypD is related to the enhanced calcium uptake rate in the mitochondria derived from Tg mice. CypD might become a potential target of drug development.

Progressive cell loss POLG mutations are not specific risk factors for bipolar disorder. Homozygotes or compound heterozygotes of POLG mutations show Alpers syndrome, CPEO or ataxia [53]. POLG mutations are also related to complex diseases, such as Parkinson’s disease and diabetes mellitus [54]. Thus, POLG mutation is not a specific risk factor for bipolar disorder, but may be related to cellular vulnerability in general. In the case of Parkinson’s disease, the substantia nigra has specific susceptibility to accumulate mtDNA deletions, and this may cause specific loss of dopaminergic neurons in susceptible individuals [55]. Bipolar disorder is associated with characteristic clinical course of shortening of episode interval after repeated relapses. This phenomenon has been interpreted as reflecting behavioural sensitization or kindling [56]. However, the findings noted above imply the other possibility; there are mood-stabilizing neurons in the brain, and these are gradually impaired in patients with bipolar disorder [2]. Neuropathological studies showed equivocal findings in various brain regions related to emotion, such as anterior cingulate cortex and hippocampus [2]. Reduction of neuron numbers in these regions is reported mainly in GABAergic interneurons rather than pyramidal neurons [57]. Thus,

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GABAergic interneurons may be related to the pathology of bipolar disorder. Altered intra-day activity rhythms, similar to the mutant POLG Tg mouse, have been reported in several mutant mice, and these genes are related to retino-hypothalamic pathway [58]. The retino-hypothalamic pathway is important for the regulation of circadian rhythm by light. Patients with bipolar disorder are reported to have various abnormalities of circadian rhythm regulation, such as altered melatonin response to light [59]. Thus, the retino-hypothalamic pathway may be relevant to the pathology of bipolar disorder.

Oxidative stress and mitochondrial dysfunction: a vicious cycle propelled by dopaminergic hyperactivity? Under physiological conditions, mitochondria are the major sources of reactive oxygen species (ROS), which are quenched by the anti-oxidant enzymes. In situations of imbalance between pro-oxidant/antioxidant states, oxidative damage may take place. The central nervous system is extremely vulnerable to peroxidative damage, since it is rich in oxidizable substrate, has a high oxygen tension (metabolizes 20% of total body oxygen) and a relatively low antioxidant capacity [60,61]. Excessive formation of ROS may present a threat to mitochondrial integrity and in turn, mitochondrial dysfunction can further increase the production of ROS [62]. As noted above, a number of postmortem studies have demonstrated that genes that regulate mitochondrial function are down-regulated in the hippocampus and prefrontal cortex of individuals with BD [29,32,34,63]. Another source of increased oxidative stress in BD episodes may be the increased dopaminergic system function during manic episodes [64]. First, dopamine (DA) is metabolized via monoamine oxidase (MAO) to produce hydrogen peroxide (H2O2) and dihydroxyphenylacetic acid [65,66]. H2O2, if not reduced by cellular antioxidant mechanisms such as GSH and GSH peroxidase, can react with transition metals such as iron to form hydroxyl radicals [67]. These molecules can immediately react with lipids, DNA and susceptible amino acids, thereby causing cellular damage [67]. Second, DA can suffer nonenzymatic hydroxylation in presence of Fe2 þ and H2O2 and form 6-hydroxydopamine (6-OHDA), a highly reactive quinone. This quinone is toxic to the nervous systems, and the mechanisms involved in this toxicity include endoplasmic reticulum-stress (ER-stress), activated GSK-3b by phosphorylation at tyrosine 216 and inhibition of Akt (phosphorilation at Ser473) [68]. Glutathione-S-transferase activity (GSH) provides a defence system against this toxic quinone [69,70]. MRS studies showed increased levels of Glu/Gln/GABA in adult bipolar patients (see Chapter 14, on imaging techniques in bipolar disorder). NMDA receptors are

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ionotrophic glutamate receptors that, when stimulated, allow the passage of calcium and sodium into the cell, thereby promoting the activation of p38, JNK and p53 that are generally proapoptotic [71]. In addition, JNK is related to induction of oxidative stress [72]. NMDA receptor activation triggers the activation of CAMKIV, present in mitochondrial external membrane, which may activate nitric oxide synthases (NOS1 and NOS3), thereby leading to increased nitric oxide production [73]. Activation of NMDA receptors also increases intracellular Ca2 þ levels, which when associated with oxidative stress, may trigger endoplasmic reticulum stress [74]; mitochondrial Ca2 þ uptake in combination with NO production may trigger the collapse of mitochondrial membrane potential, culminating in delayed cell death and release of free radicals [73].

Oxidative stress markers in bipolar disorder Previous studies have replicated that BD patients have higher lipid peroxidation and alterations in antioxidant enzymes in peripheral blood [75–77]. More recently, Andreazza et al. [78] studied the oxidative stress status in manic, depressive and euthymic subjects and found that individuals with BD have increased serum thiobarbituric acid reactive substance TBARS – a measure of lipid peroxidation – across all mood states. This is in line with a gene expression profile study showing that several antioxidation genes are down-regulated in BD [79]. It is well-known that oxidative stress is associated with DNA damage, endothelial dysfunction and telomere shortening. Notably, it has been recently demonstrated that BD patients have a marked increase of DNA damage in white blood cells, as assessed by single cell gel electrophoresis, and such DNA damage was correlated with the severity of symptoms [80]. Similarly, it has been found that some parameters of oxidative stress can be normalized by mood stabilizing treatment [81,82]. This is in accordance with preclinical studies showing that lithium and valproate exert antioxidant effects in vitro and in vivo [83,84]. A recent trial, assessing the potential application of the anti-oxidant N-acetyl-cysteine, has shown promising results in BD [85]. In addition, it has been reported that individuals with bipolar and unipolar disorder have accelerated telomere shortening, a measure of accelerated ageing [86]. The most important factor in accelerated telomere shortening is oxidative damage [87]. Telomere shortening is a marker of senescence and has been observed in several general medical conditions as cardiovascular disease [88] and may correlate to the excess of physical comorbidity presented by BD patients [89]. In a recent paper, Kapczinski et al. [90] have shown that within acute manic episodes, the increase in serum levels of TBARS occurs in tandem with a lowering in serum brain derived neurotrophic factor (BDNF). As mentioned above, this

can be construed as a consequence of endoplasmic reticulum stress due to pro-oxidant stated and consequent impairment in storage, folding and intracellular trafficking of BDNF. In this manner, acute mood episodes, particularly of mania, seem to be related to increased cellular damage via oxidative stress and a less active neurotrophic defence system. The net result of such episode-related changes may be cell endangerment and activation of pro-apoptotic cascades [91,92].

Treatment studies The evidence of oxidative stress as a component of the pathophysiology of major psychiatric disorders has resulted in prior therapeutic attempts to modulate oxidation biology. Many of these studies have targeted compounds that are not a core part of endogenous defences. Trials of conventional antioxidants, such as vitamins E and C, have showed inconsistent results in the treatment of schizophrenia and for tardive dyskinesia, and as a result have not been adopted by clinicians [93,94]. Some impact on symptomatology has been reported [95–98]. Methodological issues, including sample size, and the use of non-placebo controlled and non-randomized designs, make interpretation difficult. A further group of studies have examined the impact of known and widely used agents, and attempted to elucidate if they have any impact on oxidative pathways.

Effects of known treatment on oxidative systems Supporting a role of oxidative biology in the pathophysiology of major psychiatric disorders is a consistent thread of evidence that known treatments of diverse classes are able to modulate oxidative processes. It has been shown that oxidative systems are modulated by atypical antipsychotics. In some studies, state dependant changes are seen, such that oxidative dysregulation changes with symptom resolution. In two published studies in schizophrenia, Zhang described that baseline serum SOD, which differed from control values, shifted towards control levels with treatment [99,100]. Similarly, Dhakale showed that MDA and ascorbic acid tended to normalize with treatment [96]. Atypical and typical antipsychotics appear to differ in their oxidative profile. In animal models, haloperidol but not atypical agents were shown to increase oxidative stress [101]. The atypical agents clozapine, olanzapine and risperidone, reversed the haloperidol induced oxidative stress [102]. The glutathione precursor, N-acetylcysteine (NAC) is reported to reduce haloperidol induced oxidative stress [103]. The atypicals, olanzapine and quetiapine, have been shown to protect PC12 cells against oxidative stress [104,105].

Mitochondrial Dysfunction and Oxidative Stress

A handful of studies have shown normalization of oxidative disturbances following antidepressant treatment, supporting a modulatory role for these agents on oxidative systems [106–108], although there are negative studies [109]. In preclinical studies, varying antidepressants have been reported to correct GSH depletion following the inescapable shock behavioural model of depression [110]. Venlafaxine, moclobemide and phenelzine have all been shown to have effects on oxidative systems [111–113]. Similarly, mood stabilizers have documented antioxidant properties. In the amphetamine model of mania, both lithium and valproate prevented amphetamine-induced hyperactivity and prevented lipid peroxidation [84]. Valproate inhibits lipid peroxidation and protein oxidation in neuronal tissue culture models [114]. Both lithium and valproate block glutamate-induced intracellular calcium release, lipid peroxidation, protein oxidation, DNA fragmentation and cell death [83], and they additionally increase expression of the endoplasmic reticulum stress proteins calreticulin, GRP78 and GRP94 [115], levels of the anti-apoptotic factor bcl-2 [116], glutamate-cysteine ligase and glutathione [117], and they diminish cytochrome c release and caspase-2 activation [118]. They therefore share multiple actions across oxidative targets. Carbamazepine and lamotrigine share the ability to increase glutathione levels and glutamate-cysteine ligase gene expression, and this suggests common mechanisms of action amongst treatments used [117]. Indeed, these actions on oxidative biology, in addition to the shared effects on neurotrophins, unite these classes of agents with otherwise superficially diverse receptor profiles. An additional line of evidence supporting the role of oxidative stress in bipolar disorder derives from treatment studies demonstrating normalization of peripheral oxidative markers with treatment [76,81,119,120]. In a case report of twins, both presenting with mania, increased baseline levels of TBARS, SOD and DNA damage, and decreased CAT were described. The twin who responded to treatment showed normalization of TBARS and SOD; in contrast, oxidative markers did not change in the twin who refused treatment and remained manic [81]. Lithium treatment of mania has been shown to reduce lipid peroxidation, as measured by TBARS and SOD, returning them to control levels [82]. Similarly, treatment with lithium or the combination of lithium and olanzapine in individuals with mania has been shown to normalize some oxidative parameters, including TBARS, catalase, glutathione peroxidase and SOD [121]. Treatment of bipolar depression has also been shown to modify SOD [122].

Glutathione precursors Antioxidants have widely different pharmacokinetic and pharmacodynamic profiles; while vitamin E buffers lipid radicals, uric acid and bilirubin are free radical scavengers

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and coenzyme Q10 decreases mitochondrial ROS generation. Because of the centrality of the GSH system, GSH is probably the most generic antioxidant. GSH itself is not bioavailable and NAC, which is a precursor of cysteine, the rate-limiting step in GSH synthesis, is a viable precursor of GSH. NAC has been shown to replenish GSH in animal models of GSH depletion [123]. It also has the advantage of known tolerability and safety, in addition to widespread availability. NAC is used widely available for paracetamol overdose, as a renal protectant and as a mucolytic. Early trials of NAC have suggested efficacy in cocaine use [124–127] and refractory obsessive compulsive disorder [128], as well as OCD spectrum disorders [129]. Beneficial effects of NAC on mood have been documented in a double-blind, placebo-controlled study of NAC in patients with mild chronic bronchitis [130]. In schizophrenia, a randomized, multicentre, double-blind, placebo-controlled study of 140 patients showed moderate effect sizes on the PANSS negative, general and total scales, and the CGI improvement and severity scales. NAC treatment also reduced akathisia [131]. In a six-month randomized, double-blind, multicentre, placebo-controlled study of NAC, dosed at 2 g daily (N ¼ 75), improvements in the moderate to high effect sizes on measures of depression, quality of life and functionality in bipolar disorder were seen. As with the trial in schizophrenia, effects were lost after treatment discontinuation. In this trial, adverse effects did not differentiate from placebo, again akin to the results of the schizophrenia trial [85]. These data suggest that glutathione depletion may be a remediable component of the

Treatment

Pathophysiology

Atypical Antipsychotics

Dopaminergic Dysfunction

N-Acetylcysteine

Oxidative stress nDNA mutations

Vicious cycle

mtDNA mutations Lithium Valproate

ER stress dysfunction Mitochondrial Ca2+ dysregulation

Uridine Coenzyme Q10

Cellular vulnerability

Altered Neuroplasticity

Impairment of mood stabilizing neurons Fig. 1 Role of mitochondrial dysfunction and oxidative stress in bipolar disorder.

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etiopathogenesis of bipolar disorder, and plays a role in the genesis of depressive symptoms in particular. 10.

Conclusion In conclusion, mounting evidence suggests the role of mitochondrial function as aetiological factor for bipolar disorder. Mitochondrial dysfunction is suggested to cause oxidative stress. Multiple lines of evidence support the role of oxidative stress in the pathophysiology of bipolar disorder. Mood stabilizing agents have antioxidant properties and treatment to ameliorate oxidative stress such as Naetylcysteine is effective for bipolar disorder. Based on these lines of evidence, we here propose that vicious cycle of dopaminergic hyperactivity associated with mania and oxidative stress would cause bipolar disorder in individuals with mitochondrial dysfunction, and established and proposed treatments for bipolar disorder are effective for some point of this vicious cycle (Figure 1). This integrative hypothesis of bipolar disorder would explain many of characteristic features of bipolar disorder, and provide insight into new therapeutic targets for this difficult disorder.

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Neuroendocrinology of Bipolar Illness Timothy Dinan1 and Michael Bauer2 1 2

Department of Psychiatry, Cork University Hospital, Wilton, Cork, Ireland Department of Psychiatry and Psychotherapy, University Hospital Carl Gustav Carus, Technische Universit€at Dresden, Fetscherstraße 74, D-01307 Dresden, Germany

Despite advances in pharmacology, bipolar disorder remains enigmatic from a pathophysiological perspective. Over the past 30 years, numerous studies have been conducted examining endocrine aspects of major depression. Far fewer studies have been conducted on patients with bipolar illness than in patients with unipolar depression. There are several reasons for this, including the fact that unipolar depression is more common, it is difficult to maintain bipolar patients drug-free for any appreciable length of time and the simplistic but commonly held perception until relatively recently that mania was the biological inverse of depression hampered activity in the field. Over the past decade several important studies have been published examining neuroendocrine aspects of bipolar illness and while some of these studies are limited by the fact that medicated patients were recruited, some investigators have conducted studies in patients who were drug-free for an adequate period. We thus have a body of knowledge regarding hypothalamic-pituitary-adrenal axis (HPA) and hypothalamic-pituitary-thyroid axis (HPT) function in bipolar illness and these axes will be the primary focus of this chapter. Earlier studies tended to focus on monoaminergic regulation of anterior pituitary hormone release, in an effort to determine the sensitivity of monoaminergic receptors.

include 5-hydroxytryptamine (5-HT), noradrenaline, acetylcholine and the opioids. Under basal conditions corticotropin releasing hormone (CRH) produced by the parvicellular neurones is the dominant regulator of the axis [2]. In situations of chronic stress, many parvicellar neurones co-express vasopressin (AVP), which plays an important role in sustaining HPA activation [3]. CRH and AVP act synergistically on the anterior pituitary corticotropes to bring about the release of ACTH [4]. This in turn stimulates release of cortisol from the adrenal cortex, which feeds back to suppress the axis. Negative feedback is defined in terms of speed of response into immediate, intermediate and delayed. Much of the research in psychiatry has focused on delayed feedback. While high cortisol provides a break on HPA activity, it simultaneously has potent immuno-suppressive actions. Major depression has long been recognized as a disorder, frequently driven by psychosocial stress and associated with changes in HPA activity. Numerous studies have explored HPA activity in unipolar major depression but fewer studies have examined HPA activity in bipolar patients.

Basal HPA activity in bipolar disorder HPA regulation There is overwhelming evidence to indicate that adaptation to chronic stress involves response from the neuroendocrine system. While acute stress activates the sympathoadrenal medullary system (SAM), resulting in the components of the ‘fight or flight’ response with a release of catecholamines, chronic stress results in alterations of the HPA with changes in the release of cortisol [1]. A wide variety of neurotransmitters influence the hypothalamic paraventricular nucleus regulation of the HPA. These transmitters

Bipolar Disorder: Clinical and Neurobiological Foundations Edited by Lakshmi N. Yatham and Mario Maj © 2010 John Wiley & Sons, Ltd. ISBN: 978-0-470-72198-8

Various measurements of cortisol output have been reported in bipolar illness. These include measurements of cortisol in plasma, saliva and urine. Few studies have focused on CSF measurements. However, Swann et al. [5] found elevated CSF cortisol in mania, similar to that reported for depression. In a comprehensive study of salivary cortisol secretion, Deshauer et al. [6] obtained six salivary samples per day for three days in bipolar patients in remission and 28 offspring of bipolar patients. The advantages of measuring salivary cortisol include ease of collection and the fact that salivary cortisol is not protein bound and therefore a reflection of biologically active cortisol. No differences in salivary cortisol levels were observed at any time point. The data indicate that when bipolar patients are in remission, salivary cortisol levels are 255

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normal. Furthermore, subjects with a family history of bipolar illness do not show elevated salivary cortisol levels. These findings are in contrast to those of Wedekind et al. [7], who examined nocturnal urinary cortisol secretion in bipolar patients who were currently depressed at the beginning and end of inpatient treatment. They found elevations in cortisol, which were especially pronounced in bipolar psychotic patients. They conclude that the HPA over-activity is a trait rather than a state marker. The most sensitive time point for detecting differences between patient groups and healthy volunteers in terms of salivary cortisol is the level immediately taken upon wakening. Eighteen clinically stable lithium responsive patients were compared with healthy controls in terms of waking cortisol levels [8]. Even when clinically well, the bipolar patients had elevated morning cortisol. In a similar preliminary study, Ellenbogen et al. [9] examined morning and afternoon salivary cortisol levels in 10 normal adolescent offspring of bipolar patients and 10 matched offspring of parents without a history of mental illness. Salivary cortisol levels were higher in the offspring of bipolar patients than the matched controls. Again, the data suggest that the HPA in the first-degree relatives of bipolar patients show abnormalities at an early age. While overall the data are inconsistent, they do point to increased cortisol levels in bipolar patients.

Dexamethasone suppression test (DST) The low dose (1 mg) DST is the most extensively investigated test in the history of biological psychiatry but its usefulness in a clinical setting is limited due to low sensitivity and specificity. It is fundamentally a test of delayed feedback in the HPA. While the DST has been examined primarily in depression, studies in manic patients have been undertaken. Rates of non-suppression in mania are in the 40–50% range, similar to those reported for depression. However, as in the case of depression, the abnormality usually normalizes with effective treatment.

Dexamethasone/CRH test This test assesses both forward drive and feedback activity in the HPA and is carried out by administering dexamethasone (DEX) the evening prior to CRH challenge. Subjects usually receive an oral dose of DEX 1.5 mg at 23:00 h followed by CRH 1 mg/kg. Blood samples are collected at 15:00, 15:15, 15:30, 15:45, 16:00 and 16:15 h. It is well established that patients with major depression have an enhanced ACTH release, relative to healthy controls, when CRH is administered after DEX. The reason for this enhancement is not fully understood, though it has been postulated that enhanced vasopressin activity in depression may be involved.

Rybakowski and Twardowska [10] examined 40 patients with depression, 16 bipolars and 24 unipolars, both during an acute episode of depression and in remission. They found that during depressive episodes bipolar patients had a greater cortisol response to DEX/CRH than unipolar patients and there was a significant correlation between the endocrine response and the severity of depression. Furthermore, this anomaly persisted in the bipolars, even in remission. Schmider et al. [11] tested acute and remitted manic patients, those in acute depression and healthy controls. ACTH and cortisol release were significantly increased in both manic and depressed patients in comparison to healthy subjects. In remission manic patients had a decreased response but nonetheless a response significantly higher than seen in controls. The data indicate that in either an acute manic episode or in remission, bipolar patients have abnormalities in HPA function. A more comprehensive study of the DEX/CRH test in bipolar patients in remission was carried out by the Newcastle group [12]. They examined 53 bipolar patients, of whom 27 were in remission and 28 healthy controls. The bipolar patients had an enhanced cortisol response to the DEX/CRH relative to the controls. They conclude that the DEX/CRH test is abnormal in both remitted and nonremitted bipolar patients. Patients with a rapid cycling form of bipolar I disorder were investigated by Watson et al. [13]. Five patients were sequentially tested with DEX/CRH. The results were stable over time, suggesting that the test yields results that are independent of the mood state in such patients.

DEX/vasopressin test The release of ACTH from the anterior pituitary is under the joint control of CRH acting through CRH1 receptors and vasopressin acting on V3 (sometimes called V1b) receptors. The latter become more important during chronic stress. Dinan et al. [14] demonstrated increased responsiveness in these receptors in patients with major depression. They used desmopressin to stimulate ACTH release and found that patients with major depression released more ACTH than did healthy subjects. Watson et al. [15] examined DEX/ negative feedback on AVP release in 64 patients with mood disorder and 21 controls. 41 patients were bipolar and the remainder had chronic depressive disorder. 21 of the bipolars were in remission, 10 were depressed and 10 were rapidcycling. All subjects were administered DEX 1.5 mg at 23.00 h. On the following afternoon at 15.00 h, blood was collected for AVP measurement. Post-DEX levels were significantly higher in patients with bipolar illness and chronic depressive than matched healthy controls. It is not clear from the study whether or not AVP levels were elevated at baseline or whether the AVP emanates from the paraventricular nucleus or the magnocellular nucleus of the hypo-

Neuroendocrinology of Bipolar Illness

thalamus. However, it is tempting to speculate that the HPA over-activity seen in patients with bipolar illness may be driven by excess AVP.

CRH receptor studies Two CRH receptors are known, CRHR1 and CRHR2. Wasserman et al. [16] analysed single nucleotide polymorphisms (SNPs) in the CRH1 gene, in family trios with suicide attempter offspring (n ¼ 542), by using the transmission disequilibrium test both in a two-staged screening/replication sample design and in detailed re-analysis in the entire sample. Stratification based on the levels of lifetime stress showed reproducible association and linkage of a SNP in the CRHR1 gene (rs4 792 887) to suicide attempters exposed to low levels of stress (P ¼ 0.002), amongst whom most males were depressed (P ¼ 0.001). The identified allele may represent a part of the genetic susceptibility for suicidality by increasing HPA axis activity upon exposure to low levels of stress. Stratakis et al. [17] investigated genetic linkage between the CRH gene and bipolar disorder in 22 pedigrees. A short tandem repeat (STR) polymorphism adjacent to the CRH gene on human chromosomal region 8q13 was used to examine linkage. Affected sibling pair (ASP) and the likelihood-based disequilibrium tests revealed non-significant values. The authors conclude that the CRH gene is not linked to bipolar disorder and that if genes involved in the regulation of stress response are indeed linked to bipolar disorder, the search should be directed towards those that regulate CRH secretion or its effects on target tissues. De Luca et al. [18] conducted such a study. They exclusively studied bipolar patients and searched for markers conferring genetic susceptibility to suicide, by typing three polymorphisms of the CRHR2 gene, CRHR2(CA), CRHR2(GT) and CRHR2(GAT) in 312 families, where at least one subject had DSM-IV bipolar disorder. Family based association analyses in the suicide attempters using FBAT yielded no difference in the distribution of the alleles for all three markers. HBAT analysis for quantitative measures on suicide-related traits showed association between haplotype 5-2-3 and higher severity. The current results show that haplotype variation at the CRHR2 locus is associated with suicidal behaviour.

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The functioning of GR in lymphocytes of bipolar patients was explored by Spillotaki et al. [19]. Fifteen bipolar depressed patients, 15 bipolar euthymics taking lithium monotherapy and 25 matched controls were studied. Whole cell and nuclear extracts from lymphocytes were immunoblotted for GR, c-fos, c-jun N-terminal kinase (JNK) and nuclear factor-kappa B (NF-kappaB. Nuclear aliquots were submitted to electrophoretic mobility shift assay for GR, activator protein-1 (AP-1) and nuclear factor-kappa B. Intracellular signalling of GR, AP-1 and JNK was observed to be altered in bipolar patients. In a postmortem brain study [20], MR mRNA expression was assessed using in situ hybridization in the prefrontal cortex of patients with bipolar illness, major depression, schizophrenia and nonpsychiatric controls. In the dorsolateral prefrontal cortex Brodmann’s area 9 (BA 9), MR mRNA was significantly lower (p < 0.05) in all laminae (I–VI) in bipolar patients, and in laminae I, III, IV and VI in schizophrenics than in the controls. MR mRNA in BA 9 was negatively correlated with the duration of psychiatric illnesses. These results provide the first evidence of deficient prefrontal MR mRNA expression in bipolar disorder. Whether these findings may be linked to HPA alterations in bipolar illness is not clear.

Thyroid hormones Certain clinical facts about thyroid hormones and the brain have been known for over a century. Thyroid hormone metabolism plays a critical role in human brain development, and in the mature brain significant disturbances of the thyroid economy may profoundly alter mental function, including perception, cognition and emotion. Both excess production (hyperthyroidism) and inadequate thyroid hormone production (hypothyroidism) are associated with changes in mood and intellectual performance, and severe hypothyroidism can mimic melancholic depression and dementia in adults [21,22]. However, these facts have been tantalizing. If disturbed mood and behaviour is present in patients who suffer primary thyroid disorders, then is it possible that changes in the HPT axis play a role in the aetiology of mood and other psychiatric disorder? And if so, then might the thyroid hormones have value in the treatment of psychiatric illness, particularly affective illness?

Corticoid receptors

Thyroid status in patients with affective disorders

Cortisol binds to both glucocortioid receptors (GR) and mineralocorticoid receptors (MR). The former are found throughout the brain and show increasing occupancy with stress induced elevations in cortisol. MR receptors have the highest concentration in the septo-hippocampal projection and occupancy varies with the diurnal fluctuation in cortisol.

Based upon the clinical evidence that hypothyroidism can mimic depressive symptoms, the implicit hypothesis driving many of the clinical treatment studies is that individuals who respond to adjunctive thyroid treatment have a failing thyroid economy, or suffer subclinical thyroid disease. Several lines of evidence suggest that there may be abnormalities in thyroid hormone metabolism in patients with

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affective disorders, and that these may not be readily apparent with the standard tests to screen for thyroid disease. In fact, the vast majority of patients with primary affective disorders (>90%) have thyroid hormone blood levels within the euthyroid range [23]. However, within that normal range the thyroid hormone economy appears to be predictive of therapeutic response, with growing evidence that thyroid hormone levels in the low-normal range or below the normal range (i.e. thyroid hypofunction) can result in a sub-optimal treatment outcome. The most consistent finding in patients during the depressive phase of illness, compared to controls and healthy subjects, is an elevation of serum concentrations of total and free T4 (with normal T3 levels), which fall upon recovery and correlate with the speed at which that recovery occurs. Similarly, Frye et al. [24] have reported that within the ‘normal’ range a low level of free thyroxin (fT4) in patients with bipolar disorder is associated with more affective episodes and greater severity of depression during prophylactic lithium treatment. In another study, lower free thyroxin index (FTI) values and higher TSH values within the normal range were significantly associated with poorer treatment response in bipolar patients during the depressed phase [25]. Taken together these observations suggest that higher serum levels of thyroxin are adaptive in depression – much as an increase in thyroid metabolism is an adaptive response to cold stress – and that a robust thyroid economy confers an advantage that promotes rapid recovery following antidepressants treatment. Thus, a working hypothesis in seeking to explain these clinical observations is that thyroid hormones modulate the severity and course of depression rather than playing a specific pathogenic role. The hypothesis that thyroid hormones act as modulators in affective illness is further strengthened by studies of the relationship between thyroid function and the clinical course of bipolar disorder, especially that of the rapid cycling variant.

Rapid cycling bipolar disorder When examining thyroid function in bipolar illness, it is useful to distinguish between rapid cycling and non-rapid cycling bipolar disorder. By DSM IV definition, patients with a rapid cycling course of disease suffer four or more episodes of illness per year. Approximately 10–15% of bipolar patients experience rapid cycling; while similar to other bipolar patients nosologically and demographically, they tend to have a longer duration of illness and a more refractory course. Furthermore, women are disproportionately represented, making up 80–95% of rapid cycling patients, compared to about 50% of non-rapid cycling patients [22]. A variety of factors may predispose bipolar illness to a rapid cycling course, including treatment with tricyclic antidepressants (TCA), monoamine oxidase inhibitors (MAOI) and lithium.

There is also a longstanding debate as to whether thyroid axis abnormalities contribute to the development of rapid cycling in patients with bipolar disorder [26]. Several studies have found an association amongst indices of low thyroid function or clinical hypothyroidism and rapid cycling, while other studies refute this association. For example, one larger study reported that 23% of 30 patients with rapid cycling bipolar disorder had grade I hypothyroidism, while 27% had grade II and 10% had grade III abnormalities [27]. The results from various studies are inconsistent, and the conclusions to be drawn are often limited by their retrospective design and lack of a healthy control comparison group. Most importantly, many studies included patients who were receiving prophylactic long-term lithium treatment. The adverse effects of lithium on thyroid function do certainly have an impact on thyroid indices. On the other hand, cross-sectional studies of unmedicated patients with rapid cycling bipolar disorder have found no abnormalities in basal thyroid-stimulating hormone (TSH) and thyroxine levels. It was postulated that patients with rapid cycling may manifest no thyroid abnormalities until physiologically challenged by ‘antithyroid’ stressors. Such stressors may include spontaneously occurring thyroid disease or goiterogenic drugs such as lithium. In a recent controlled study, when previously unmedicated patients with rapid cycling were challenged with therapeutic doses of lithium, a significantly higher delta TSH after thyrotropin-releasing hormone stimulation was found than in age- and gendermatched healthy controls who also received lithium [28]. This result suggests that some patients with bipolar disorder have a dysfunction in the HPT axis that remains latent until the axis is challenged by the thyroprivic effect of lithium, and that changes in the thyroid economy may play a modulating role in the development of the rapid cycling pattern.

Thyroid autoimmunity Lithium therapy for patients with affective disorders has long been acknowledged to induce thyroid dysfunction. Although it was noted early on that lithium-induced thyroid failure could occur without the presence of thyroid autoimmunity, the role of thyroid autoimmunity in the development of lithium-induced thyroid disorders remains unclear. Some studies have reported a high prevalence for antithyroid antibodies in patients with affective disorders receiving lithium therapy, suggesting that thyroid autoimmunity may mediate the antithyroid effects of lithium. Other studies have not found an increased prevalence of antithyroid antibodies in patients with affective disorders receiving lithium when compared to the general population, normal controls or controls with psychiatric disorders [29]. Furthermore, patients who have thyroid

Neuroendocrinology of Bipolar Illness

autoimmunity prior to lithium exposure may show a rise in antibody titres, and have an increased risk of developing hypothyroidism while receiving lithium therapy. Specifically, thyroid peroxidase (TPO) antibodies were reported to be elevated in bipolar disorder with a prevalence of 28%, while results from other studies were inconsistent with reported rates ranging from 0–43%. In community studies, the rates of prevalence of TPO antibodies generally range from about 12–18%. The estimate of TPO antibody prevalence will vary with the sensitivity and specificity of the testing methodology, is increased in females, in old age, when TSH levels are abnormally high or low, and when individuals with known thyroid disease are included in the population. The impact of increasing age and female gender on the detection of TPO antibodies has also been noted in patients with affective disorders. Elevated thyroid antibodies were also reported in some studies of patients with unipolar depression, but not in others. It was also hypothesized that autoimmune thyroiditis, with TPO antibody as marker, may be a potential endophenotype for bipolar disorder, and is related to the genetic vulnerability to develop bipolar disorder rather than to the disease process itself. While offspring of parents with bipolar disorder were found to have increased vulnerability to develop thyroid autoimmunity as compared to high-school-aged controls, this was independent of any psychiatric disorder or symptoms. Thyroid antibody status was also associated with an increased risk for lithium-induced hypothyroidism, but not with current or former lithium treatment [30].

Thyroid hormones in the treatment of mood disorders Efforts to employ thyroid extract and thyroxine alone as therapeutic agents were rarely successful but since Prange’s classic triiodothyronine (T3) acceleration studies in the late 1960s, a series of open and controlled clinical trials have confirmed the adjunctive therapeutic value of thyroid hormones in unipolar and bipolar mood disorders. As early as the 1930s, Norwegian physicians used desiccated sheep thyroid gland to treat patients with cyclic mood disorders. While thyroid hormone monotherapy is not an adequate treatment for patients with primary mood disorders, since the late 1960s, a series of open and controlled clinical trials have confirmed the therapeutic value of adjunctive treatment with thyroid hormones in mood disorders. Specifically, there is some evidence that T3 can accelerate the therapeutic response to tricyclic antidepressants, and in treatment-resistant depression, T3 may augment the response to tricyclic antidepressants although the results have been inconsistent. T3 has also been shown to augment the response to sertraline but not to paroxetine. In a series of open-label studies, adjunctive treatment with supraphysiological doses of Levothyroxine (L-T4) was

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found to be effective in the maintenance treatment of patients with severe rapid cycling or resistant bipolar disorder who did not respond to standard measures [31–34]. Supraphysiological L-T4 may also have immediate therapeutic value in antidepressant-resistant bipolar and unipolar depressed patients during a phase of refractory depression [35,36]. In these patients with malignant affective disorder, doses of 250–600 mg/d L-T4 are required to achieve therapeutic effect, much higher than those used in the treatment of primary thyroid disorders. Although treatment with supraphysiological T4 requires close monitoring, the hyperthyroxinemia is tolerated surprisingly well. No serious effects, including loss of bone mineral density, were observed even in patients treated for extended periods [37,38]. The low incidence of adverse effects and high tolerability reported by patients with affective disorders who are receiving high dose thyroid hormone therapy contrasts with that typically seen in patients with primary thyroid disease. For example, patients with thyroid carcinoma treated with high doses of L-T4 to achieve suppression of TSH commonly complain of the symptoms of thyrotoxicosis. In summary, thyroid hormone supplementation is now widely accepted as an effective treatment enhancement, especially for patients with refractory bipolar disorders. The question remains, however, as to why this should be so.

Potential mechanisms of action What evidence is there to support this conjecture of a central disturbance of brain-thyroid metabolism in some patients who suffer refractory affective illness? Despite the clinical evidence of a close relationship between thyroid status and behavioural disturbance, metabolic effects of thyroid hormones in the adult mammalian brain have rarely been investigated in vivo. In part, this lack of curiosity may be traced to reports in the 1950s and 1960s that suggested that oxygen consumption in the mature human brain did not change with thyroid status. But the absence of a technology capable of direct in vivo measurement of brain thyroid metabolism is also responsible. That still does not exist, but the evaluation of cerebral blood flow and metabolism by functional brain imaging techniques is a starting point and recent studies have provided promising insights into the thyroid-brain relationship [39,40]. Following the lead of earlier clinical treatment studies, the effects of adjunctive supraphysiological doses of L-T4 on relative brain activity as a surrogate index of cerebral glucose metabolism were studied in euthyroid women with bipolar depression using PET technology with [18F-] fluorodeoxyglucose as the radiotracer [41]. At baseline, pretreatment, bipolar depressed women had functional abnormalities in prefrontal and limbic brain areas compared to healthy controls. Over seven weeks, the treatment with L-T4

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significantly improved mood and was accompanied by significant changes in relative brain activity. In particular, L-T4 treatment was associated with a widespread relative deactivation of limbic and subcortical structures, including the amygdala, hippocampus, caudate nucleus, ventral striatum, thalamus and cerebellar vermis. The findings suggest that in these treatment-resistant patients L-T4 produces mood improvement by actions on the specific limbic and subcortical circuits that have been implicated in the pathophysiology of mood disorders. Thyroid hormone receptors are widely distributed in the brain. Many of the limbic system structures where thyroid hormone receptors are prevalent have been implicated in the pathogenesis of mood disorders. However, the cellular and molecular mechanisms underlying these metabolic effects, and the specific neuropharmacological basis and functional pathways for the modulatory effects of thyroid hormones on mood, are yet to be understood. Interactions of the thyroid and neurotransmitter systems, primarily norepinephrine and serotonin, which are generally believed to play a major role in the regulation of mood and behaviour, may contribute to the mechanism of action in the developing and mature brain [42,43]. There is robust evidence, particularly from animal studies, that the modulatory effects on the serotonin system may be due to an increase in serotonergic neurotransmission [40]. Thyroid hormones also interact with other neurotransmitter systems involved in mood regulation, including dopamine postreceptor and signal transducing processes, as well as gene regulatory mechanisms. Furthermore, within the CNS, the regulatory cascade through which the thyroid hormones, particularly T3, exert their effects is not well understood: deiodinase activity, nuclear binding to genetic loci and ultimately protein synthesis may all be involved [39]. Other proposed mechanisms for thyroid involvement in the aetiology of mood disorders include disturbances or reactive hyperactivity in the HPT axis, as manifested in the blunted TSH response to TRH found in some patients with depression. In summary, thyroid hormones have a multitude of effects on the central nervous system, and it is now widely recognized that disturbances of mood and cognition often emerge in association with putative disturbance of thyroid metabolism in the brain. As knowledge in basic science and appropriate technology evolve, understanding of the role of thyroid hormone function in the adult brain will continue to be refined. Studies of the biology of thyroid hormone action shows that these hormones play an important role in normal brain function and that current laboratory tests on thyroid status may not provide a sufficiently accurate measure of thyroid hormone function within the CNS. In patients with primary thyroid disorders, both excess and inadequate thyroid hormones can induce behavioural abnormalities that mimic depression, mania

and dementia. These neuropsychiatric impairments are generally reversible following return to euthyroid status, although some defects may persist in a subset of patients. In patients with bipolar disorders, thyroid hormones appear to be capable of modulating the phenotypic expression of their illness. Even though most patients with primary mood disorders do not have overt thyroid disease, relative abnormalities in thyroid function are associated with a worse outcome. Furthermore, the adjunctive use of supraphysiological doses of L-T4 in malignant bipolar disorders frequently provides remission without adverse physiological effects where all other treatments have failed. As clinicians gain more profound knowledge about the interactions of thyroid hormones, behaviour and mood, they advance their understanding of the pathophysiology and treatment options for bipolar disorder and depression. Additional research with rigorous scientific designs is still needed to confirm the efficacy, safety and feasibility of thyroid hormone therapy in severely ill patients with mood disorders.

Monoamines and pituitary hormones It was first demonstrated more than 25 years ago that stimulation of noradrenergic alpha-2 receptors brought about the release of growth hormone (GH) and that such a response is blunted in major depression. This was interpreted as indicative of a subsensitivity of the alpha-2 receptor in depression. Anseau et al. [44] found blunted GH release following clonidine (alpha-2 agonist) challenge in seven manic patients. Similar responses were reported by Dinan et al. [45] in patients challenged with the noradrenergic re-uptake inhibitor desipramine. It is interesting to note that cholinergic inputs also regulate GH release and that manic patients challenged with the acetylcholinesterase inhibitor pyridostigmine show exaggerated release of GH. The data indicate an imbalance between noradrenergic and cholinergic regulation. The fact that 5HT receptors stimulate prolactin release has been used to study the sensitivity of such receptors. Studies using a variety of probe drugs demonstrate a 5HT receptor subsensitivity in unipolar major depression. Far fewer studies have been conducted in bipolar patients. When healthy subjects are administered d-fenfluramine, the 5HT releasing agent and re-uptake inhibitor, a significant increase in prolactin levels is observed. Unipolar depressives show a blunted response to this challenge. In a study of manic patients, Thakore et al. [46] found blunted responses similar to those found in depression.

Conclusions and future directions Bipolar illness is a challenging disorder to manage and improved therapies will only arise from an increased

Neuroendocrinology of Bipolar Illness

understanding of pathophysiology. Part of that increased understanding will involve neuroendocrine investigations. While studies in drug-free and drug-na€ıve patients are required, the major necessity is for large-scale longitudinal studies of newly diagnosed patients. Only by studying patients prospectively in different phases of their illness can we achieve real understanding of the evolving biology. This may be even more important in female patients where the hormonal milieu alters not only across the menstrual cycle but from the pre- to post-menopausal stages. The plethora of cross-sectional studies currently available have significant limitations. Prospective studies may not only help increase understanding of the disorder but possibly detect new targets for pharmacological intervention.

References 1. Rubin, R., Dinan, T.G. and Scott, L.V. (2001) The neuroendocrinology of affective disorders, in Hormones, Brain and Behaviour (eds D. Pfaff, A.P. Arnold, A.M. Etgen et al.), Academic Press, New York. 2. Vale, W., Spiess, J., Rivier, C. and Rivier, J. (1981) Characterisation of a 41 residue ovine hypothalamic peptide that stimulates secretion of the corticotropin and beta-endorphin. Science, 213, 1394–1399. 3. Dinan, T.G. and Scott, L.V. (2005) Anatomy of melancholia: focus on the hypothalamic-pituitary-adrenal axis overactivation and the role of vasopressin. J. Anat., 207, 259–264. 4. Aguilera, G. (1994) Regulation of pituitary ACTH secretion during chronic stress. Front. Neuroendocrinol., 15, 321–350. 5. Swann, A.C., Stokes, P.E., Casper, R. et al. (1992) Hypothalamic-pituitary-adrenocortical function in mixed and pure mania. Acta Psychiat. Scand., 85, 270–274. 6. Deshauser, D., Duffy, A., Alda, M. et al. (2003) The cortisol awakening response in bipolar illness: a pilot study. Can. J. Psychiat., 48, 462–466. 7. Wedekind, D., Preiss, B., Cohrs, S. et al. (2007) Relationship between nocturnal urinary corrtisol excretion and symptom severity in subgroups of patients with depressive disorders. Neuropsychobiology, 56, 119–122. 8. Deshauer, D., Duffy, A., Alda, M. et al. (2003) The cortisol awakening response in bipolar illness: a pilot study. Can. J. Psychiat., 48 (7), 462–466. 9. Ellenbogen, M.A., Hodgins, S. and Walker, C.D. (2004) High levels of cortisol among adolescent offspring of parents with bipolar disorder: a pilot study. Psychoneuroendocrinol., 29, 99–106. 10. Rybakowski, J.K. and Twardowska, K. (1999) The dexamethasone/corticotrophin-releasing hormone test in depression in bipolar and unipolar affective illness. J. Psychiat. Res., 33, 363–370. 11. Schmider, J., Lammers, C.H., Gotthardt, U. et al. (1995) Combined dexamethasone/corticotropin-releasing hormone test in acute and remitted manic patients, in acute depression, and in normal controls: I. Biol. Psychiatry, 38 (12), 797–802.

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12. Watson, S., Gallagher, P., Ritchie, J.C. et al. (2004) Hypothalamic-pituitary-adrenal axis function in patients with bipolar disorder. Brit. J. Psychiat., 184, 496–502. 13. Watson, S., Thompson, J.M., Malik, N. et al. (2005) Temporal stability of the dex/CRH test in patients with rapid-cycling bipolar I disorder: a pilot study. Aust. NZ J. Psychiat., 39, 244–248. 14. Dinan, T.G., Lavelle, E., Scott, L.V. et al. (1999) Desmopressin normalises the blunted adrenocorticotropin response to corticotropin-releasing hormone in melancholic depression: evidence of enhanced vasopressinergic responsivity. J. Clin. Endocrinol. Metab., 84, 2238–2240. 15. Watson, S., Gallagher, P., Ferrier, N. and Young, A.H. (2006) Post-dexamethasone arginine vasopressin levels in patients with severe mood disorders. J. Psychiat. Res., 40, 353–359. 16. Wasserman, D., Sokolowski, M., Rozanov, V. and Wasserman, J. (2008) The CRHR1 gene: a marker for suicidality in depressed males exposed to low stress. Genes Brain Behav., 7 (1), 14–19. 17. Stratakis, C.A., Sarlis, N.J., Berrettini, W.H. et al. (1997) Lack of linkage between the corticotrophin-releasing hormone (CRH) gene and bipolar affective disorder. Mol. Psychiat., 2, 483–485. 18. De Luca, V., Tharmalingam, S. and Kennedy, J.L. (2007) Association study between the corticotrophin-releasing hormone receptor 2 gene and suicidality in bipolar disorder. Eur. Psychiat., 22, 282–287. 19. Spillotaki, M., Salpeas, V., Malitas, P. et al. (2006) Altered glucocorticoid receptor signalling cascade in lymphocytes of bipolar disorder patients. Psychoneuroendocrinol., 31, 748–760. 20. Xing, G.Q., Russell, S., Webster, M.J. and Post, R.M. (2004) Decreased expression of mineralscorticoid receptor mRNA in the prefrontal cortex in n achizophrenia and bipolar disorder. Int. J. Neuropsychopharmaol., 7, 143–153. 21. Whybrow, P.C., Prange, A.J. Jr and Treadway, C.R. (1969) Mental changes accompanying thyroid gland dysfunction. Arch. Gen. Psychiatry, 20, 48–63. 22. Bauer, M., Beaulieu, S., Dunner, D.L. et al. (2008) Rapid cycling bipolar disorder – diagnostic concepts. Bipolar Disord., 10, 153–162. 23. O’Connor, D., Gwirtsman, H. and Loosen, P.T. (2003) Thyroid function in psychiatric disorders, in Psychoneuroendocrinology: The Scientific Basis of Clinical Practice (eds O.M. Wolkowitz and T.J. Rothschild), American Psychiatric Press, Inc., Washington DC. 24. Frye, M.A., Denicoff, K.D., Bryan, A.L. et al. (1999) Association between lower serum free T4 and greater mood instability and depression in lithium-maintained bipolar patients. Am. J. Psychiatr., 156, 1909–1914. 25. Cole, D.P., Thase, M.E., Mallinger, A.G. et al. (2002) Slower treatment response in bipolar depression predicted by lower pretreatment thyroid function. Am. J. Psychiatr., 159, 116–121. 26. Cowdry, R.W., Wehr, T.A., Zis, A.P. and Goodwin, F.K. (1983) Thyroid abnormalities associated with rapid-cycling bipolar illness. Arch. Gen. Psychiatr., 40, 414–420. 27. Bauer, M.S. and Whybrow, P.C. (1990) Rapid cycling bipolar affective disorders. II. Treatment of refractory rapid cycling

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with high-dose levothyroxine: a preliminary study. Arch. Gen. Psychiatr., 47, 435–440. Gyulai, L., Bauer, M., Bauer, M.S. et al. (2003) Thyroid hypofunction in patients with rapid cycling bipolar disorder after lithium challenge. Biol. Psychiatry, 53, 899–905. Baethge, C., Blumentritt, H., Bergh€ ofer, A. et al. (2005) Longterm lithium treatment and thyroid antibodies: a controlled study. J. Psychiatry Neurosci., 30 (6), 423–427. Kupka, R.W., Nolen, W.A., Post, R.M. et al. (2002) High rate of autoimmune thyroiditis in bipolar disorder: lack of association with lithium exposure. Biol. Psychiatry, 51, 305–311. Stancer, H.C. and Persad, E. (1982) Treatment of intractable rapid-cycling manic-depressive disorder with levothyroxine. Arch. Gen. Psychiatr., 39, 311–312. Bauer, M.S. and Whybrow, P.C. (1990) Rapid cycling bipolar affective disorders. II. Treatment of refractory rapid cycling with high-dose levothyroxine: a preliminary study. Arch. Gen. Psychiatr., 47, 435–440. Baumgartner, A., Bauer, M. and Hellweg, R. (1994) Treatment of intractable non-rapid cycling bipolar affective disorder with high-dose thyroxine: an open clinical trial. Neuropsychopharmacol., 10, 183–189. Bauer, M., Bergh€ ofer, A., Bschor, T. et al. (2002) Supraphysiological doses of L-thyroxine in the maintenance treatment of prophylaxis-resistant affective disorders. Neuropsychopharmacol., 27, 620–628. Bauer, M., Hellweg, R., Gr€ af, K.J. and Baumgartner, A. (1998) Treatment of refractory depression with high-dose thyroxine. Neuropsychopharmacol., 18, 444–455. Bauer, M., Szuba, M.P. and Whybrow, P.C. (2003) Psychiatric and behavioral manifestations of hyper- and hypothyroidism, in Psychoneuroendocrinology: The Scientific Basis of Clinical Practice (eds O.M. Wolkowitz and T.J. Rothschild), American Psychiatric Press, Inc., Washington DC, pp. 419–444.

37. Gyulai, L., Bauer, M., Espana-Garcia, F. et al. (2001) Bone mineral density in pre- and post-menopausal women with affective disorder treated with long-term L-thyroxine augmentation. J. Affect. Disord., 66, 185–191. 38. Bauer, M., Heinz, A. and Whybrow, P.C. (2002) Thyroid hormones, serotonin and mood: of synergy and significance in the adult brain. Mol. Psychiatr., 7, 140–156. 39. Bauer, M., Goetz, T., Glenn, T. and Whybrow, P.C. (2008) The thyroid-brain interaction in thyroid disorders and mood disorders. J. Neuroendocrinol., 20, 1101– 1114. 40. Bauer, M., Silverman, D.H.S., Schlagenhauf, F. et al. (2009) Brain glucose metabolism in hypothyroidism: a positron emission tomography study before and after thyroid hormone replacement therapy. J. Clin. Endocrinol. Metab., 94 (8), 2992–2999. 41. Bauer, M., London, E.D., Rasgon, N. et al. (2005) Supraphysiological doses of levothyroxine alter regional cerebral metabolism and improve mood in bipolar depression. Mol. Psychiatry., 10 (5), 456–469. 42. Henley, W.N. and Koehnle, T.J. (1997) Thyroid hormones and the treatment of depression: An examination of basic hormonal actions in the mature mammalian brain. Synapse, 27, 36–44. 43. Whybrow, P.C. and Prange, A.J. Jr (1981) A hypothesis of thyroid-catecholamine-receptor interaction. Arch. Gen. Psychiatr., 38, 106–113. 44. Ansseau, m., von Frenckell, R., Cerfontaine, J.L. et al. (1987) Neuroendocrine evaluation of catecholaminergic neurotransmission in mania. Psychiat. Res., 22, 193–206. 45. Dinan, T.G., Yatham, L.N., O’Keane, V. and Barry, S. (1991) Blunting of noradrenergic stimulated growth hormone release in mania. Am. J. Psychiat., 148, 936–938. 46. Thakore, J.H., O’Keane, V. and Dinan, T.G. (1996) dfenfluramine-induced prolactin responses in mania: evidence for serotonergic subsensitivity. Am. J. Psychiatry, 153 (11), 1460–1463.

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Circadian Rhythms and Sleep in Bipolar Disorder Greg Murray1 and Allison Harvey2 1 2

Swinburne University of Technology, Hawthorn, Australia Sleep and Psychological Disorders Lab, University of California, Berkeley, CA, USA

Introduction and overview Circadian rhythm hypotheses have been prominent in the explanation of bipolar disorder (BD) for more than 20 years [1,2], and changes in sleep are part of diagnostic criteria [3]. Biological rhythmicity is also a priority for patients, who report significant concern about their sleep [4], and readily appreciate the importance of rhythm stability [5]. In short, there is consensus that biological rhythms play a critical role in the emotion dysregulation at the heart of BD.1 Biological rhythm approaches to BD complement the explanatory approaches discussed elsewhere in this volume, and this chapter includes numerous examples of overlap between circadian/sleep pathways and other targets of investigation. The aim of this review chapter is to encourage further research into these important pathways, by tracing the limits of scientific knowledge about biological rhythms in BD. We first outline the basics of circadian rhythms and sleep, highlighting the challenge of empirically separating these two factors. Subsequently, literature on circadian- and sleep-moderation of emotion is reviewed, largely focusing on non-clinical populations. Evidence for an association between biological rhythms and BD is detailed next, and causal inferences considered. The following section considers potential mechanisms of biological rhythm action in BD, particularly the impact of clock genes. Finally, we introduce clinical implications of the fact that biological rhythmicity is modified by behaviour (Section 20.6).

Circadian rhythms and sleep Circadian system

ment with the earth’s cyclic environment by predicting critical environmental change [6]. In mammals, the circadian pacemaker responsible for the temporal internal organization and generation of endogenous rhythms of approximately 24 h is located in the hypothalamic suprachiasmatic nucleus (SCN, [7]).2 At the molecular level, intrinsically rhythmic cells of the SCN generate self-sustained rhythmicity via an autoregulatory transcription-translation feedback loop regulating expression of the Period (Per1, Per2, Per3), cryptochrome (Cry1, Cry2), TIM, DEC1 and DEC2 genes [8].3 The endogenous period generated in the SCN is close to, but generally not equal to 24-hour. The process by which the pacemaker is both set to a 24-hour period and kept in appropriate phase with seasonally shifting astronomical day length is called entrainment. An important property of the circadian system, therefore, is its fundamentally open nature, and this open nature includes feedback to the pacemaker from clock-controlled activity of the organism [10]. Entrainment occurs via zeitgebers (environmental events that can affect phase and period of the clock), the most prominent of which is the daily alteration of light and dark due to the planet’s rotation [11]. To a lesser degree, the SCN is also responsive to non-photic cues, including arousal/locomotor activity, social cues, feeding, sleep deprivation and temperature [12].

Sleep Phylogenetically, sleep is a more recent and less ubiquitous adaptation than circadian rhythmicity [13]. The specific adaptive function of sleep is unknown, but the fact that sleep is strongly conserved in mammals [14], and evidence

The endogenous circadian time-keeping system, strongly conserved across species, is adapted to optimize engage2

1

The term biological rhythms is used to encompass both circadian and sleep-wake processes. Bipolar Disorder: Clinical and Neurobiological Foundations Edited by Lakshmi N. Yatham and Mario Maj © 2010 John Wiley & Sons, Ltd. ISBN: 978-0-470-72198-8

Endogenous circadian oscillators are in fact located in cells throughout the body. The circadian system is organized hierarchically, with the SCN clock as overarching pacemaker of cellular circadian oscillators in most peripheral body cells. 3 Molecular genetic investigations into the circadian system have been so successful that they have been forwarded as a model for exploring other domains of interest [9].

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for marked physical and cognitive consequences of sleep deprivation in humans (e.g. [15]), suggest that sleep serves an important function. Evidence is also accumulating for sleep’s role in particular types of cognition [16], memory consolidation and brain plasticity [17–19,21]. Based on characteristic physiological patterns, normal sleep can be divided into two distinct states: rapid eye movement (REM) and non-rapid eye movement (NREM). During REM (or paradoxical) sleep, the brain is highly activated, the muscles of the body are paralysed and dreaming occurs. In NREM, growth hormone is preferentially secreted and protein synthesis is increased, leading to the view that NREM may be critical for energy conservation and restoration. Characteristic EEG patterns support NREM sleep being further categorized into substages: (1) drowsiness, transition to sleep, lowest arousal thresholds; (2) light sleep; (3) and (4) deep sleep, highest arousal thresholds. Together, (3) and (4) are often called delta or slow wave sleep (SWS) [22]. On a typical night, sleep of a young adult begins in Stage (1) NREM and progresses through deeper NREM stages. The first episode of REM sleep occurs approximately 80–100 minutes after sleep onset. Thereafter, NREM sleep and REM sleep cycle with a period of approximately 90 minutes. NREM stages (3) and (4) concentrate in the early cycles and REM sleep episodes lengthen across the night. Therefore, in a normal night of sleep, SWS predominates in the early part of the sleep phase, while REM is more prevalent later in the night. Indeed, we are most likely to wake through the gate of REM sleep.

The relationship between circadian and sleep processes The sleep-wake cycle is regulated by two processes, one of which is the clock-like circadian system described above (typically called Process C). The second factor is sleep’s (hourglass-like) homoeostatic self-modulation (or Process S [23]). Process S is accumulated during wakefulness, dissipates during sleep and regulates duration and structure of sleep on the basis of the history of sleep and wakefulness. The bidirectional interaction between processes C and S predicts the propensity, timing and internal structure of sleep [24].4 A family of models, prominently Borbely’s twoprocess model [27] and the ‘opponent process’ model [28]

4

The interaction of these two processes regulates not only the sleepwake cycle: nervous system activity, neurobehavioural performance and hormonal levels are demonstrably moderated by this interaction [25]. The two also determine the macro-architecture of sleep, with the SCN primarily driving the timing of REM, and Process S determining the timing of SWS [26].

share the assumption of two interacting processes in sleep regulation, and differ in the nature of the proposed interaction.5 The neurobiology of the C
S interaction in sleep regulation is not fully understood. Research by Saper and others [31–33] supports a model of sleep in which arousal is mediated by discrete neuronal populations of the ascending reticular activating system, which project to the thalamus and basal forebrain. The mechanism by which this arousal system is curtailed to produce sleep involves the ventrolateral preoptic nucleus (VLPO). Mutual inhibition between arousal circuits and the VLPO ensure stability in either end state (asleep or awake) and rapid switching between the two. This so-called flip/flop switch [31] is modulated by a circadian alerting signal (operating through multiple relays in the hypothalamus), and, on the other side of the switch, the homoeostatic sleep drive.6 The neural mechanisms of the sleep homoeostat are unknown, but there is growing evidence that the wake-linked accumulation of the purine nucleoside adenosine may be involved through its inhibition of arousal circuits [34,35], potentially via astrocytes [36]. Under normal conditions Process C and Process S operate in synchrony [26], and in the field we can only observe the sleep-wake cycle, which is a complex endpoint of volition, circadian afferents and the sleep homoeostat. Most of what we know about separate circadian and sleep processes therefore comes from laboratory studies. In the forced desynchrony (FD) protocol, a non-24 h sleep wake schedule (typically 28 h) is enforced. Under these conditions, the circadian oscillator continues to cycle at approximately 24 h and desynchronizes from the sleep/wake cycle, which adopts the enforced 28-h period, thereby enabling separate estimate of circadian and sleephomoeostatic components [37]. The sleep disruption and isolation of the multi-day FD protocol make it unsuitable for individuals vulnerable to emotion dysregulation. Indeed, most FD studies screen participants to ensure they are exceptionally phlegmatic (S. Lockley, personal communication, March 2007), and no FD studies in BD have been reported.

5 Additional factors, including sleep inertia [29] and ultradian cycling between NREM and REM phases within sleep [30] are added in some models.

The same pathways are involved in a second flip/flop switch regulating the alternation between REM and NREM sleep. The sleep active neurons in the VLPO send a major output to the REM-off side of the REM switch. The orexin neurons in the lateral hypothalamus reinforce the wake side of the wake-sleep switch, and send an excitatory projection to the same REM-off target, thus preventing switching from wake into REM. 6

Circadian Rhythms and Sleep in Bipolar Disorder

Sleep, circadian function and affect As in the study of other psychiatric disorders, it is not uncommon to conceptualize BD as the extreme clinical manifestation of a neurobehavioral trait that is distributed throughout the population. Specifically, BD can be characterized as a pathologically elevated propensity to emotional dysregulation [38–40]. Before reviewing the known associations between biological rhythms and BD, it is therefore useful to review findings linking biological rhythms and emotion regulation in normal populations.

Sleep disturbance and emotion Behavioural data support the lay assumption that sleep disturbance strongly increases negative mood [41–46]. Sleep loss has been shown to not only increase negative emotional response to goal-thwarting events, but also decrease positive emotional responses to goal-enhancing events [47].7 High levels of emotional arousal can also disturb sleep, raising the possibility of vicious cycles between sleep disturbance and emotion dysregulation [49]. At the neural systems level, sleep deprivation has been linked to decreased medial-prefrontal cortical activity and increased amygdala activation, a distribution of activation consistent with impaired top-down regulation of emotional responses [50]. Conversely, emotion circuits affect homoeostatic and circadian drives for sleep [51,52].

Circadian interactions with emotion The circadian system modulates current mood state, specifically states of positive affect [53–56] and challenges to the circadian system, such as shift work and jet lag have negative consequences for mood [57,58]. Under naturalistic conditions, emotional state also moderates circadian function via its influence on social rhythms, light exposure, arousal and sleep [12,59]. Bidirectional influence can also be traced at the neurobiologic level: afferents from the SCN project via the paraventricular thalamic nucleus to the mesolimbic dopaminergic reward system [60], while emotion circuits impact circadian (and homoeostatic) aspects of sleep regulation [51].

Particular importance of REM sleep in emotion regulation The sleep state most strongly regulated by the SCN, REM sleep, may be particularly important in emotional processing and emotional regulation. Key findings include correlations between pre-sleep mood and REM parameters, 7

In contrast, the manic ascent of BD may involve a positive feedback loop between decreased sleep and increased response to goal-enhancing events [48].

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prospective associations between dream content and psychological outcomes, and REM-facilitated recall of emotional information [61,62]. There is also converging evidence concerning the neurobiology of REM-supported emotional processing (see, [63–67]). Stickgold has proposed a neurocognitive model of dream construction and function in which dreaming is the conscious awareness of critical ‘offline’ cortical generation functions occurring during sleep – the particular features of dreaming are consistent with activation of neural networks supporting weak cortical associations in the absence of dorsolateral prefrontal cortex or hippocampal feedback, but in the presence of active error detection circuits in the anterior cingulate cortex [19,20].

Neurotransmitters and the sleep
circadian
emotion interaction At least two neurotransmitter circuits are involved in the link between biological rhythms and emotion. First, dopaminergic pathways, especially cells of the ventral tegmental area (VTA) and zona compacta of the substantia nigra (SNc) are strongly implicated in reward motivation and positive affects [68–70]. Dopamine has been called a key substance in the regulation of sleep-wake [71], and dopaminergic neurons of the VTA and SNc are again implicated [72], particularly in REM sleep [73]. Dopaminergic pathways also have multiple interactions with the SCN [60,74,75]. Second, serotonergic pathways have pronounced (albeit complex) relationships with anxiety and stress responses [76]. Serotonergic pathways are critical in circadian function ([77]; and vice versa, [78]), sleep per se [33,79] and the interaction between stress and sleep [46,80–83].

From normal populations to patients with BD The above review presents strong behavioural evidence for the notion that emotion and emotion regulation are associated with sleep (particularly REM sleep) and with circadian function. Neuroanatomical pathways subserving these associations have been outlined, and the putative role of two critical neurotransmitters (dopamine and serotonin) has been described. It seems reasonable to propose that the same relationships hold in patients with BD, and indeed to hypothesize that the symptoms of mood episodes in BD may be attributable, at least in part, to the pathways described here. It is particularly noteworthy that an independent literature argues for dopaminergic and serotonergic circuits as critical pathways in BD [84,85].

Sleep, circadian function and mood symptoms in BD A number of specific links have been demonstrated between BD and circadian and/or sleep function. Our aim here is to

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critically consider the nature and implications of these known associations, and it is useful to group findings as shown in Box 1.

length and mood change in BD has been found in a number of studies [110,112–115]. .

Experimental and treatment effects -Deliberate sleep deprivation is a same-day powerful treatment

Box 1 Associations between BD and biological rhythm function .

Neurobiology shared between BD and biological rhythms -Circadian and sleep function are subserved by the same brain regions [86] and neurotransmitters [84,85] putatively involved in mood disorder. -Polymorphisms in circadian genes have been associated with symptoms of BD in pre-clinical and human studies [87–90].

.

Biological rhythms as diatheses to BD -Sleep disturbance and instability of 24 h rhythms continues when BD patients are not acutely ill [4,91–94]. -Dysregulation of 24 h activity rhythms has been reported in a familial high risk sample [95]. -Neuroticism, the primary (albeit non-specific) temperamental predisposition to BD, may be associated with circadian instability [96]. -Biological sensitivity to light, as measured in night-time suppression of the pineal hormone melatonin, has been proposed as a trait marker of vulnerability to BD [97]

for bipolar (and unipolar) depression [112,116]. Maintenance of the therapeutic effect beyond the next sleep phase is a target of current research [117]. -In a recent study, combined sleep deprivation, sleep phase advance and timed light was an effective adjunctive intervention for bipolar depression [118]. -Bright light can induce symptoms of mania [117], and has significant effects on bipolar depression [119]. -Experimentally induced sleep deprivation induces hypomania or mania in a proportion of patients [111,112] -Bright light can induce symptoms of mania, and ‘dark therapy’ has been found to stabilize patients with rapid cycling BD [117,120]. -Effective treatments for BD (lithium, antidepressants, anxioloytics, electroconvulsive therapy) affect circadian function [121–123]. Lithium and selective serotonin re-uptake inhibitors impact genes involved in circadian function [77,124–126]. -Improved social rhythmicity decreases relapse in BD [127].

-Delayed circadian phase of melatonin secretion has been reported in euthymic BD patients [98], and BD patients self-report as more evening type [99]. .

Cross-sectional associations -Some clinical features of BD are timed phenomena: diurnal variation in mood and early morning wakening in depression, as well as seasonal and other cyclic variation in symptoms, are suggestive of circadian involvement [100]. -Circadian rhythms (including activity, body temperature, melatonin, cortisol and thyrotropin) are altered in episodes of BD (see, for a review [101,102]). -Mania is strongly associated with decreased need for sleep, and insomnia and hypersomnia are both reliably found in bipolar depression (see, for a review, [103]). -Episodes of BD have been associated with sleep polysomnographic changes ([104–106]). The most consistent finding is abnormalities of REM sleep in both mania and bipolar depression (typically shorter latency and increased density, see [103]).

.

Predictive relationships -Episodes of BD can be precipitated by zeitgeber challenges, including seasonal change and time zone travel (see, for a review [107]). -Sleep disturbance is the most common prodrome of mania, and a significant prodromal symptom of bipolar depression [108].8 Altered sleep often precedes deterioration in clinical state and worsens further during an episode [108,110,111].

8

Sleep reduction has been called the final common pathway in the genesis of mania [109].

The findings summarized in Box 1 indicate that most phases of BD (depressed, manic, episode prodrome and inter-episode periods) are cross-sectionally associated with prominent sleep and/or circadian rhythm abnormalities. What is the significance of this conclusion? Disturbed sleep has significant impacts on quality of life in BD [128,129]. Also, as described above, sleep disturbance has detrimental impacts on emotion regulation in normal populations, an effect which may be greater in patients with BD. The primary consequence of this conclusion, then, is that outcomes in BD can be improved by addressing associated sleep difficulties. Moreover, due to the interdependency between sleep and circadian processes, it is reasonable to expect that interventions targeting sleep disturbance in BD may ameliorate circadian abnormalities and vice versa [130,131]. Such interventions are briefly introduced below. A range of evidence also suggests that sleep disturbance plays a causal role in BD. Not only is there prospective data linking sleep to mood in BD, but sleep changes reliably precede episodes (especially mania) and correlate with symptom load. Most strikingly, manipulation of sleep (sleep deprivation) improves bipolar depression and can induce hypomania/mania in some patients. This conclusion also aligns with current clinical practice, in which sleep monitoring is a central relapse prevention strategy [132]. The literature cited in Box 1 also provides support for circadian function as a causal pathway to BD. First, relapse can be precipitated by zeitgeber challenge (particularly light

Circadian Rhythms and Sleep in Bipolar Disorder

manipulations) and effective treatments for acute episodes moderate circadian parameters. Second, a range of data suggests that ‘circadian instability’ may act as a trait-like vulnerability or diathesis to BD. For example, activity and sleep disruptions are found outside episodes and in children of BD patients. Further evidence for a circadian diathesis comes from a possible link between circadian function and the general vulnerability trait neuroticism, and from preclinical and human studies suggesting an association between specific clock genes and BD. This conclusion is also consistent with existing approaches which emphasize circadian instability as an element of pathogenesis and a target for relapse prevention efforts ([101,130,133–135]).

Mechanisms underpinning biological rhythm involvement in BD The mechanisms by which biological rhythms affect the development, course and treatment of BD are not known. Early hypotheses emphasized gross abnormalities in circadian function, including short intrinsic period of the oscillator [136], phase advance [137], phase delay [138] and attenuated circadian amplitude [96,139,140]. The relation between Process C and S has also been implicated [141], and Process S itself has been hypothesized to underpin the therapeutic effect of sleep deprivation [143]. Coupling to external zeitgebers is critical in some models [127,140,143,144]. Physiological investigations of these molar hypotheses have been scarceover the pastdecade[2],and themethodological issues raised above are a barrier to progress. As research into molar circadian hypotheses has waned, the study of the genetics of circadian function in BD has expanded, and the remainder of this section is devoted to this burgeoning literature. As noted above, the molecular basis of the circadian clock is well understood, permitting the investigation of specific circadian genes that potentially influence BD. Traditional candidate gene studies have found trends for an association between BD and the CLOCK gene [145,146], but findings are inconsistent [147]. A single nucleotide polymorphism in the 30 flanking region of CLOCK has also been associated with clinical features of BD, namely patterns of more activity in the evening, delayed sleep onset and less sleep [148], higher rates of initial, middle and early insomnia [149], recurrence of illness episodes [149] and changes in neural response [87]. Several studies show that the mood stabilizer lithium affects circadian rhythms through the glycogen synthase kinase 3 beta gene (GSK-3b, [126,150,151]). Valproic acid may act via the same intracellular signalling pathway [152,153]. Investigations of associations between BD, its clinical features and GSK-3b, have not been consistent [154–156]. Findings for an association with the NR1D1

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gene, regulation of which by GSK-3b is important for clock function, are also mixed [157,158]. Other circadian genes for which some support exists include PER3 [159,160], ARNTL [100,160] and TIMELESS [100]. In addition, Shi et al. [146] reported an interaction between CLOCK and two other genes of interest for their potential circadian function (BHLHB2, CSNK1E). In one genome-wide association study [161], the gene VGCNL1 (the mouse homologue of which regulates circadian function) had a significant association with caseness. Larger genome-wide studies have not identified circadian gene associations [162,163]. Pre-clinical studies observing the effect of gene mutations have been a fruitful source of hypotheses. Mice with a mutation in the CLOCK gene show robust sensitization to cocaine and increases in the preference for and reward value of cocaine [90,164]. These mice also have increased dopaminergic activity in the ventral tegmental area (VTA) which may be responsible for the increase in the reward value of cocaine [164]. Notably, CLOCK mutant mice also show mania-like behaviour, which is reversed by lithium treatment [165] and this reversal is mediated by altered regulation of dopamine release in the VTA [164]. Evidence for a BD-relevant pathway linking circadian genes to the dopaminergic reward system is consistent with the strong comorbidity between BD and substance abuse [166], the association between manic states and psychostimulant use [167], and the action of atypical antipsychotic medications for mania [152]. A dopaminergic reward
clock gene circuit has been reliably demonstrated in non-human species (e.g. [168,169]) and is strongly implicated in human mood regulation [55,86,170–173].9 It is important to situate these clock gene findings within the broader genetics of BD (see Chapter 12, on Genetics of Bipolar Disorder). Like other psychiatric disorders, BD is probably inherited polygenetically, with numerous genes adding small effects to overall risk [161]. Evidence from human studies suggests that these genetic effects are probabilistic, non-specific, contingent on gene
gene
environment interactions, and causally remote from the phenotype [176].10 Given small genetic effects on risk, it is not surprising that failure to replicate associations is common, and that researchers have sought to refine the phenotype under investigation. In particular, endophenotypes (quantitative phenotypes

9

Clock genes in the mesolimbic system (i.e. beyond the SCN) play a significant role in the reward
clock gene interaction (e.g. [175,176]). 10

Indeed, genes identified as elevating risk for BD are not accurately characterised as ‘pathogenic’. The gene DGKH, for example, has support from genome-wide association studies as one of the stronger predictors of BD diagnosis. The majority of patients have this gene (89.9% in a Europeanorigin sample, [162]), but so do the majority of healthy controls (84.7%, op. cit.).

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intermediate between the genotype and the disorder [177]), are a major focus of contemporary study. Disturbance of circadian function is commonly forwarded as a candidate endophenotype for BD [89,100,178–181].

Psychosocial interventions targeting biological rhythms in BD Interactions between biology and psychosocial factors cannot be ignored in a biological rhythm approach to BD [182]. The circadian system is adapted to be open to external cues, and environmental manipulations (particularly light exposure) have predictable effects on amplitude and phase of the endogenous oscillator [183,184]. Under naturalistic conditions, human exposure to zeitgebers is gated by behaviour, prominently the sleep-wake cycle (above). The sleep-wake cycle is in turn moderated by volitional and social factors, and mediated partly through cognitive mechanisms (above). Biological rhythms therefore function as an open loop crossing multiple levels of the person and their environment. Psychosocial factors are integral to a biological rhythm explanation of BD, a conclusion which underpins the recent development of novel adjunctive psychosocial interventions for BD. The social zeitgeber hypothesis proposes that fundamental circadian instability in BD can be moderated by increased stabilization of daily rhythms and zeitgeber exposure [133]. This hypothesis takes clinical form in Social Rhythm Therapy ([185], see Chapter 33, on Interpersonal and Social Rhythm Therapy), which is a largely behavioural psychotherapy aimed at helping patients maintain stability in their social rhythms and so reduce the risk of relapse. In the treatment of BD, Social Rhythm Therapy is typically integrated with principles from interpersonal psychotherapy in a treatment known as Interpersonal and Social Rhythm Therapy (IPSRT, [185]). IPSRT has proven effective in two large studies [127,186]. Interest in biological rhythm management is expanding alongside growing research into adjunctive psychosocial treatments for BD [117,133,187,188]. Rhythm stabilization is a core component in most adjunctive psychosocial treatments for BD [134], including Cognitive Behavioural Therapy (see Chapter 32, Cognitive-Behavioural Therapy). Improving sleep quality is an important component of rhythm stabilization, and has functional benefits in its own right [189]. Interestingly, management of the sleep-wake cycle is a commonly reported well-being strategy amongst people with BD [190]. Our qualitative investigations suggest that this strategy is appealing not only because it is judged effective: it is empowering for patients to understand that a core element of BD biology is partly under their control (unpublished data). Chronotherapeutic interventions are an important target for further study. Future research into these interventions

should seek to identify moderators (e.g. light sensitivity, severity and diagnosis, temperament, gender) and mediators (e.g. sleep quality, sleep architecture, circadian rhythmicity, daytime arousal) of treatment outcome. Our knowledge of possible interactions between behavioural and pharmacological treatments is also limited. The recent discovery that light’s neurobiological effects are blueshifted [191,192] encourages a more sophisticated definition of dosage in light treatment for BD.

Summary and conclusions Four main themes can be drawn from the present review. First, standard laboratory protocols for separating sleep and circadian function may not be feasible in vulnerable populations, so the biologically important distinction between these processes is difficult to investigate. Fundamental questions can instead be addressed by extrapolation from well populations, perhaps quantified by their degree of risk for BD. Second, biological rhythm pathways are interwoven with other pathways implicated in BD (e.g. monoamines, GSK3b) and future research should actively address this complexity. Third, the wide variety of evidence demonstrating biological rhythm involvement in BD is a rich source of hypotheses for future work in this burgeoning area. Research in humans is yet to discover mechanisms of large effect, but preclinical studies suggest the reward
circadian interaction may be particularly fruitful. Finally, interventions built on chronobiological principles should be energetically investigated. These interventions are theoretically plausible, benign, economical and attractive to patients. In conclusion, research into sleep and circadian dysfunction in BP is an exciting, challenging and rewarding avenue for the future. It has potential to significantly broaden our understanding of one of the most serious of the mental illnesses and to improve the quality of life and functioning of patients.

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Treatment Adherence in Bipolar Disorder Jan Scott1 and Mary Jane Tacchi2 1 2

Department of Psychiatry, Newcastle University; Institute of Psychiatry, Institute of Neuroscience, Newcastle-upon-Tyne, UK Institute of Psychiatry, Institute of Neuroscience, Newcastle University, Newcastle-upon-Tyne, UK

Introduction The safe and successful delivery of efficacious treatments for bipolar disorders relies upon the patient’s (and often their caregiver’s) ability and willingness to accept and engage with the services provided, and to adhere with an agreed regime of medication and/or other interventions that make up the individual’s treatment plan. Understanding the complexity and maximizing the effectiveness of the interaction between the clinician and patient lies at the heart of achieving meaningful engagement with any treatment proposals. Collaboration between the clinician and patient is a critical first step if patient outcomes are to reflect the goals of both parties. The potential gain from a positive collaboration and a healthy clinician-patient working alliance is that patients report greater satisfaction with the services, largely as a consequence of increased trust in their clinicians and being offered the opportunity for more active participation in treatment decision making. The latter ensures that patients are more likely to view treatment options as acceptable, which in turn may increase adherence with currently prescribed or recommended treatments; it increases the likelihood of active help-seeking (especially in the prodromal phase of new episodes); and improves the probability of longer-term engagement with services, which is vital given the natural history of the disorder. The converse of all these benefits is largely true of unsatisfactory collaborations; many individuals who are treatment nonadherent, report at least one past experience of a negative therapeutic alliance. The chapter begins with a brief overview of research on medication non-adherence in bipolar disorders and then focuses on findings regarding individuals at risk of nonadherence that may be more informative when trying to address the problem in clinical settings. It then briefly highlights the general principles of engagement, as strategies

Bipolar Disorder: Clinical and Neurobiological Foundations Edited by Lakshmi N. Yatham and Mario Maj © 2010 John Wiley & Sons, Ltd. ISBN: 978-0-470-72198-8

that enhance adherence are unlikely to be effective unless practised within the context of an appropriate therapeutic relationship. This is followed by an overview of a health beliefs model that may help clinicians in their attempts to enhance treatment adherence and some simple strategies that can be employed in day-to-day clinical practice to reduce the risk of non-adherence.

Adherence It is widely acknowledged that the impressive benefits of medication observed under controlled research conditions are rarely replicated in clinical practice. In the past this efficacy-effectiveness gap was frequently attributed to drug pharmacokinetics and pharmacodynamics. It was some time before non-adherence with prescribed treatment regimens was recognized as the factor accounting for most of the variance in outcomes. Early attempts to understand non-adherences focused on socio-demographic and illness characteristics that might somehow explain adherence behaviour, and the general assumption was that individuals with severe mental disorders were at higher risk of nonadherence than those with physical disorders, and that they often failed to adhere because of lack of insight or lack of tolerance of treatment side-effects. Sadly, the view that a new medication, with fewer or different side effects, would resolve the problem is at odds with the evidence – namely, it is clear that the proportion of patients demonstrating significant levels of non-adherence (missing
30% of their medication per month) has not changed since the 1950s to the present day, a period during which there has been an exponential increase in the number of available medications with very different side-effect profiles from their predecessors. Furthermore, the prevalence of non-adherence in patients with bipolar disorders parallels the rates in physical disorders such as diabetes, epilepsy and hypertension. The ‘chronic disease management’ approaches that have been successful in improving the treatment of these lifespan medical disorders drew heavily on the literature on health belief models, which in turn emphasize the role of patient 275

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attitudes and beliefs about a disorder and its treatment and how these may influence adherence behaviours. These models have now begun to permeate into mental health and research on non-adherence increasingly focuses on how patient and caregiver beliefs about the disorder and its treatment, and the interactions between key individuals, can dramatically influence the degree of adherence. Some key issues in the development of our understanding of adherence behaviour will be briefly reviewed below. Early reviews of socio-demographic and general clinical factors associated with non-adherence in bipolar disorders ([1]) cited factors such as younger age, male gender, history of grandiosity, and complaints of ‘missing highs’. However, the hypothesis that basic socio-demographic variables directly predict adherence is undermined by contradictory findings and is not strongly supported by recent more sophisticated research [2]. For example, out of 12 studies, 5 identified a possible association between younger age and non-adherence; one found a trend in the same direction but reported no association and six did not find any association [3]. Also, any relationship between age, gender and non-adherence might be better explained by a third variable, such as the high prevalence of comorbid drug and/or alcohol misuse in young males with bipolar disorder. Similarly, a detailed review of the association between insight and adherence tends to suggest that while this may be relevant in some cases at certain times, for example when presenting with episode acute mania or psychotic depression, the more subtle concept of illness awareness (which captures aspects of denial of illness in clear conscience) is a better explanatory variable. Also, there is a growing literature suggesting that cognitive impairments (rather than insight alone) may adversely affect adherence [4]. Side effects were considered to have a detrimental effect on adherence in early studies, but again the research is undermined by the fact that many of the studies reporting this association failed to measure any other possible influences on adherence. Recent studies indicates that while sideeffects may reduce adherence in some individuals (while others will tolerate exactly the same side effect at an equal or worse level of severity), there is a difference between subjective and objective measures of side effects. If side effects are differentiated in this way, it is notable that fear of rather than the actual experience of side effects may be a better predictor of non-adherence [5]. Early research identifying ‘at risk populations’ is of only minimal utility in day-to-day clinical settings where a clinician wishes to assess individual factors that determine likely behaviour patterns. The exploration of individual beliefs is proving increasing fruitful. For example, Pope and Scott (2003 [6]) confirmed Jamison’s findings on subjective reasons for non-adherence, with both studies highlighting that two of the most frequently reported beliefs associated with non-adherence were that patients disliked

the idea that their moods were controlled by medication and disliked taking medication as it reminded them that they had a chronic illness. It was also found that many patients reported that when they felt well they thought there was no need to take medication. This factor is often overlooked, but is also critically important in clinical practice – as it identifies that adherence is not a static behaviour; patients’ adherence levels may fluctuate – so they cannot be classified permanently as adherent or non-adherent. Other individuals and interactions may also influence adherence behaviour. For example, a factor analysis of dimensions of adherence behaviour demonstrated that acceptance of medication (affinity) was the most important predictor of adherence, while negative interactions with clinicians (negative alliance) was endorsed four times more frequently by non-adherent as compared with adherent patients [2]. It was also noted that individuals with bipolar disorders who were non-adherent were more likely to be living with family members who were significantly less knowledgeable about bipolar disorder and its treatment and were more critical of the patient than the families of adherent subjects [5]. These findings confirm earlier research by Miklowitz, Perlicke and others that individuals with bipolar disorder living in high expressed emotion environments, particularly if this was also accompanied by a negative affective style of interaction or high caregiver burden, were at high risk of non-adherence and relapse. Figure 1 identifies those factors for which there is consistent evidence of an association with non-adherence or where the balance of research findings favour an association.

Therapeutic relationships The therapeutic relationship refers to a series of interactions between the clinician and patient. It is the vehicle through which engagement proceeds and time spent enhancing this interaction will increase the likelihood of satisfaction for all parties. All clinicians will be aware that some of their own therapeutic relationships develop more easily than others: knowledge about the process can help to improve interactions and overcome obstacles in clinician-patient encounters that the clinician finds more challenging personally. Individuals with bipolar disorders may present in markedly different ways at appointments and sometimes, for example, when a patient has symptoms of irritability and mania, the individual may show an amazing ability to ‘hit a nerve’ and/or challenge the clinician, despite the latter’s most skilled attempts to avoid any confrontation. Taking the time to reflect on one’s own actions and reactions in such circumstances, and reflecting on any recurring patterns in interactions deemed ‘difficult’ is invaluable in clarifying ways to modify one’s own behaviours to try to maintain a functional working alliance, especially when circumstances

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Basic Demographics, Illness or Treatment Factors Comorbid Substance Misuse Past History of Non-Adherence with Medical or Psychiatric Treatments Cognitive Impairments Lack of Insight Subjective Experience of Side Effects Fear of Side Effects

Individual, Family or Patient-Professional Relationship Factors Negative Expectations of or Attitudes toward Treatment eg ‘Taking medication everyday reminds me I have a chronic illness’; ‘I feel I am controlled by drugs’ Lack of Illness Awareness or Denial of Severity Poor Therapeutic Alliance Significant Others: Beliefs or Lack of Knowledge about Bipolar Disorder High Levels of Critical Comments EE Family) Fig. 1 Factors associated with increased risk of nonadherence in bipolar disorders.

dictate that the patient may not be able to modify their own ‘modus operandi’ at that moment. It goes without saying that many clinicians intuitively develop healthy alliances with patients, but others may need to more consciously practise the effective and skilful handling of a consultation with manic patients, or even with an individual who is struggling to come to terms with the diagnosis and the likely need for treatment. Furthermore, it often falls to the senior clinicians to try to impart knowledge to less experienced colleagues about how to maintain collaboration with individuals with bipolar disorder, given some of the potentially challenging presentations that occur. The following sections briefly offer an ‘aide memoir’ of some of the key research findings on these topics. DiMatteo [7] described the factors that are important in promoting a positive doctor-patient interaction. Most clinicians are aware of the essentials, such as the presence of warmth, positive regard, a lack of tension and non-verbal expressiveness. However, it is worth highlighting that, for example, the clinicians’ communication style often dictates the success of the therapeutic relationship. McCabe and Priebe [8] concluded that the extent to which patients feel listened to and the extent to which their specific concerns are addressed significantly affect the patients’ and caregivers’ views of the consultation. Di Matteo also noted that physicians who could accurately read body language developed more effective interpersonal relationships, emphasizing that communication occurs on many different levels.

Various models have been proposed to characterize the doctor-patient relationship and many promote the idea that this relationship should be an equal partnership rather than the clinician being in a position of authority and dictating the outcome of the process. In reality it is not always possible or ethical to endorse all choices expressed by patients, and/ or the responsibilities of clinical management mean it is sometimes necessary to take decisions on behalf of a patient without their agreement (such as involuntary admission). However, the general principle of seeking collaboration between both parties increases the prospect of effective two-way communication so that each person is aware of the other’s point of view and by increasing the possibility of early intervention in crises may actually reduce the likelihood of involuntary admission (see Figure 1). Ideally, the key elements for effective collaboration in the care and treatment of an individual with bipolar disorder will include the development of a shared understanding of the problem(s) to be addressed followed by open discussion and negotiation regarding the nature of any interventions to be tried and the interventions will target the jointly agreed goals of treatment.

Developing a shared understanding and agreeing treatment goals Most patients will attend a clinician at a time when they believe this person can help alleviate their distress and/or

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help them function at their desired level. Very few individuals with bipolar disorder will achieve enduring improvements in their quality of life without taking medication. However, many individuals desperately want to achieve their desired level of functioning through their own efforts, without taking long-term medication. Clinicians cannot ignore this dilemma and so they need to develop ways of working with patients who hold such views that maximize the chances of treatment adherence. The first principle to consider is that adherence with any treatment is more likely to occur if the clinician and patient agree on the problems they are tackling, the goals of treatment and the interventions that will be used to produce the required changes. In this approach, the use of medication is identified as one of several components of a multi-dimensional treatment package, and benefits of medication (especially what it can and cannot do) can be clarified and its specific role agreed.

Beliefs about illness Patients attending consultations have already begun to develop their own model of their difficulties and how these can be overcome. As such the clinician needs to explore this in order to decide if the patient is likely to accept medication. The use of a health belief model called the ‘cognitive representation of illness’ [2,9] is a useful framework that allows clinicians to begin to explore a patient’s understanding of their problems, their attitudes and expectations about treatment, and to gauge their coping style. Spending time exploring the five key themes of this model: identity, cause, time line, consequences, can it be cured or controlled (see Figure 2). It is notable that while individuals vary enormously in their beliefs about their problems and how to overcome them, the ideas expressed by anyone can virtually always be organized within these five key themes, no matter

•

what their background, culture or ethnicity. The core element in the process of beginning the treatment process is that in the first instance the clinician understands the patient’s model of what is happening to them, not vice versa. The rationale is that the patient’s misunderstandings, negative views or beliefs are more likely to produce barriers to implementing effective treatment and thus the primary goal is not simply to ascertain if the patient meets all the diagnostic criteria for a disorder, but fundamentally must identify the immediate road blocks to successful collaboration and clinical management. With established patients and/or those who are not acutely unwell, it is useful to examine the patient’s understanding of their perception of the ‘threat’ posed to them by any illness recurrence, most importantly whether they regard themselves as susceptible to future episodes and if so, whether they view any consequences of relapse as potentially serious (e.g. would a severe episode requiring hospitalization have a detrimental effect on their life). The essential element in this discussion is that the focus in on the risk to that individual as the evidence is that patients do not relate to general information (about risk of relapse) to their own situation without clear and specific ‘personalization’. This will give some indication of the prospects for adherence with continuation and maintenance treatments.

Goals of treatment Research on patients’ views of their reasons for seeking treatment for bipolar disorder is illuminating. Very few patients, even when acutely unwell, would state that their primary goal is to ‘get medication’. A depressed patient may desires ranging from ‘to be able to sleep’, or ‘to return to work as quickly as possible’. A clinician may recognize that prescribing medication may immediately begin to help with

Engagement is a multi-dimensional phenomenon comprising at least six key components: appointment keeping, client-therapist interaction, communication, openness, collaboration with treatment and medication adherence.

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Clinical management approaches are more likely to succeed if they include: engagement, negotiation of the structure of the intervention, agreed approaches to communication, agreement on the role and involvement of carers, discussion of shared and individual responsibilities, safety and containment issues.

Fig. 2 Key points in engagement and clinical management.

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Identity of problem. What does the individual think it is? Do they view it as a mental disorder?

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Cause. What ideas do they entertain about what has caused their problem(s)?

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Timeline. How long do they think it will last? Do they think it is transient, may persist or may be recurrent?

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Consequences. How do they think it will affect them? Do they think there may be any serious consequences of not having treatment?

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Cure. Does the individual think the problem can be cured or controlled? How has the individual attempted to cope with the symptoms and how do they appraise the effectiveness of their coping strategies?

the former, may then help improve the patient’s mental state and be a vehicle to achieving the return to work. However, it is important to recognize the subtle difference between the patient and clinician agreeing on the goals of their collaboration and agreeing the means of achieving the goals. This cannot be ignored as it is especially likely to need to be addressed when identifying how medication plays a part in long-term goals. For example, if the patient expresses a wish to get back to work, the clinician can introduce the idea that they need to identify the key steps involved in moving towards that goal; by asking questions, the clinician and patient can identify what the patient would need to be able to do in order to do their job. This guided process usually helps the patient catalogue several key milestones, such as being able to sleep and wake refreshed; to be able to concentrate for extended periods of time, being able to organize basic living routines and manage on a day-to-day basis, and so on. The clinician and patient can then discuss how to achieve each of these steps and the use of medication to improve sleep, concentration and reduce certain symptoms (or stabilize mental state) is now seen as a logical part of the process; planning daily activities and keeping a diary of what the patient did compared with what they planned can also be agreed as an essential part of working towards the goal. This shared decision making is a constructive way of educating patients about the process of change and where medication can be beneficial, while retaining their sense of autonomy and/or control over treatment decisions that affect their well-being. It also emphasizes that treatment is not medication alone [2].

Three questions to aid effective prescribing A simple process that can be used by a clinician is that before writing a prescription they ask themselves does this

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Fig. 3 Key themes to explore to establish patients’ illness model (adapted from Scott and Tacchi, 2002).

individual patient find the proposed medication regime – Acceptable? Understandable? Manageable? If the answer to any of these questions is no – concordance has not been achieved and adherence is unlikely. Indeed, do not waste time writing a prescription; it may not even be presented at a pharmacy! Continue the dialogue until an option is found that meets these criteria.

Is the treatment acceptable? Obviously agreement on the nature of the problem is a critical first step, as it will allow the patient make informed choices about the treatments available. If there are gaps in the patient’s understanding or areas of uncertainty that mean the clinician and patient do not yet have a shared view, there may still need to be further work before prescribing medication is likely to be followed by adherence. It is important to consider not only what information is needed by the patient, but how additional information might be provided and what approach is most likely to be acceptable to the individual (e.g. the clinician offering information leaflets to the patient vs. encouraging self discovery by the patient contacting advocacy groups or directly accessing information from appropriate Internet Web sites). The views of the patient’s significant others (e.g. relatives, partner) are also important, as these may influence the patient’s beliefs about their problems and/or attitudes towards proposed treatments. Taking all these aspects into account, the clinician can gauge whether or not the patient requires further help or information to aid their understanding of the particular problems. If the clinician understands the patient’s perspective, and has found common ground, it is relatively straightforward to determine what treatment options make sense to that patient at that moment and which may be more acceptable than others. Understanding and recording which proposed

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interventions are likely to be rejected by the individual is also necessary. Relatively few clinicians assess this in detail, yet a few moments spent establishing whether a patient has heard of, for example drug X, and then whether they have any reaction (positive or negative) to the suggestion of trying it, could prevent treatments being prescribed that are never likely to be accepted by the individual [2]. There are also practicalities with regard to acceptability of intervention, (which partly overlap with whether the treatment is manageable), for example the form the medication takes, that is injectable or oral, tablets or syrup, and frequency of dosing. Lingham and Scott [3] noted that if a patient chooses the form of medication and dosing regimen they are much more likely to adhere to this than if this is selected for them. Much has been written about how side effects of prescribed medication may affect adherence. However, when asked directly, patients rank this as only the seventh most important reason why they fail to adhere [10]. The presence of side effects per se does not predict non-adherence as accurately as either the patient’s fear of experiencing side effects or a lack of knowledge about how to manage common side effects should they occur [5,11]. An open discussion about these concerns from the outset may help to allay anxieties and also provide practical solutions should common side effects occur; for example, chewing sugar free gum to overcome a dry mouth, and so on. Being proactive in offering advice on common problems is likely to reduce the risk of non-adherence if the side effect does occur, and offers the opportunity to differentiate between side effects that are a nuisance and/or unpleasant but not dangerous versus adverse effects that will need the patient to seek urgent attention, without causing alarm.

Is the treatment understandable? Once the patient’s own ‘model’ or representation of the disorder is understood, it becomes clear where there are gaps in their knowledge that may hinder their understanding of the treatment rationale. If the patient and clinician have very divergent ideas on aetiology, time is needed to identify or establish some shared ground and agreed targets for any treatment interventions, for example if the patient reports disturbed sleep, the need to alleviate this may lead to agreement being reached about medication being prescribed for this symptom, even if the patient is less convinced by the clinician’s view of the diagnosis of the syndrome and the need for longer-term medication. If medication is successful in ameliorating a problem the patient considers important, it hopefully offers the clinician an opportunity to then revisit the possible role of medication in the overall treatment plan. This approach is preferable to trying to rush the patient into complying with the clinician’s preferred approach and/or trying to use evidence of undesirable clinical and personal consequences to push or even ‘frighten’ the patient into

a treatment ‘agreement’ they are not really engaged with (and will more than likely not adhere to once they have left the clinic). Many clinicians try to help patients by giving a ‘mini’ educational lecture on the disorder and its treatment and emphasizing the dire consequences of not adhering with treatment, hoping that the information and the fact that their presentation clearly fits with established knowledge will somehow mean the patient will now accept the diagnosis proffered and treatment suggested. This may sometimes be true, but evidence on ‘psycho-education’ clearly shows that didactic approaches and information alone do not change the patient’s attitudes or beliefs, and therefore neither improve adherence or outcomes. The worst case scenario is that this actually increases the chances of nonattendance as the patient fears disapproval from the expert whose advice they have failed to follow. As such, it is important to avoid lecturing the patient as, rather than helping the patient gain an understanding of the need for treatment, patients frequently report feeling ‘talked at’ and the effect can be the opposite of what is desired as it may undermine engagement with services or adherence. Guiding the patient to discover information for themselves and then discussing what they have found out will often help reinforce that the relationship is collaborative and that the clinician wants to hear and understand the patient’s perspective. This approach hopefully will increase the future prospects of gaining acceptance of an appropriate medication regime from what Gary Sach’s describes as a ‘menu of reasonable options’. Clinicians can sometimes take for granted that patients understand why they are taking medication if they are symptom-free. It is vital to check that the patient understands the difference between medications taken as an acute treatment, for example aspirin for a headache, and that which is taken long term to avoid a problem occurring, for example anti-hypertensives to prevent increases in blood pressure and thus avoid any negative health consequences of this. This is especially important as bipolar disorders often requires combinations of medications – some which ‘get you well’ (acute treatments with antidepressants or anti-manic agents) and those that ‘keep you well’ (moodstabilizers). Adherence with the latter is especially likely to be problematic to an individual who is symptom free; unless they are clear these medications are primarily targeted at preventing symptoms developing and have made their own decisions regarding their personal likelihood (susceptibility) of experiencing a further relapse and whether the consequences are tolerable (severity of symptoms, disruption to lifestyle, problems associated with possible admissions).

Is the treatment manageable? There are a number of practical considerations when prescribing medication, which again may be overlooked in

Treatment Adherence in Bipolar Disorder

a busy clinical practice. Checking simple things, however, often makes a significant difference – again the emphasis is initially on ‘asking not telling’ and ensuring knowledge about the practicalities have not been assumed for example Does the patient know the name of the medication that is being prescribed, the doses, how often this needs to be taken and what to do if they forget to take a dose? Does the patient know who will provide further prescriptions and what will happen if a change of dose is recommended (e.g. how will they get a new perscription, how long will it take to make the changeover)? These are not issues that are always covered, but research with patients identifies that lack of information and/or misunderstandings of certain statements in the literature provided with prescription medications can cause confusion and reduce adherence, for example when questioned, patients who read a statement ‘should not be taken with alcohol’ frequently reported that they excluded medication doses on days they attended a social event, as they did not know whether the consequences would be minor (feeling drowsy) or dangerous (life threatening interactions). It takes only a few moments to ensure such issues have been clarified for a patient, and it may make the difference between a medication regime being regarded as effective and ineffective. Finally, the clinician needs to check if there is any other additional help that would increase the likelihood that adherence will be maintained by this particular patient, for example, as noted in the section on acceptability, providing practical advice on how to manage any common side effects can prevent non-adherence. Patients prescribed medication can also be encouraged to use simple behavioural techniques to increase their likelihood of adherence such as keeping a written record, using prompts such as mobile phone alarm bleeps, or ‘pairing’ taking medication with another regular activity such as brushing their teeth. The use of once daily dosing is often hailed as an important technique for improving adherence, but again the actual evidence suggests choice of regime is the significant component, that is if the patient prefers to take the medication once a day and/or they know this will improve their chances of successful adherence, the prescription of a medication that has a ‘slow release’ or ‘long acting’ preparation is useful, but clinicians must establish, not assume, that the patient has a preference for taking the medication once a day rather than more frequently. A practical approach to some of the above issues is to provide a wallet sized treatment card for the patient to carry with them, outlining the information on medication and including a contact number if the patient experiences any difficulties. A shared written treatment plan also offers an opportunity to improve awareness of adherence issues rather than simply documenting the interventions, personnel involved, and so on. This can be helpful as it allows the clinician and patient to openly discuss and identify in

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advance any potential adherence problems and the possible solutions that the patient can instigate for themselves. For example, adding a specific section to the plan about the benefits to the individual of the particular treatment regime and sections highlighting potential problems, with ways to overcome difficulties with adherence (usually a list of bullet points on possible barriers to adherence followed by a further list on how these might be overcome). The patient may chose to involve carers in the process. However, even if those individuals are not engaged in any specific support strategies, it is useful and often important (with the patient’s permission) to ensure that, for example family members or social care coordinators share an understanding of the nature of the disorder, and the key issues relating to treatment to ensure concordance exists across all the key individuals involved in the patient’s life.

Monitoring and enhancing adherence Adherence is a dynamic process, it is not a static ‘all or nothing’ phenomena and indeed those individuals who take all or none of their prescribed medications are very rare. There is both inter-individual and intra-individual variation and even someone who has benefited from medication may show differences in their adherence pattern over time. The level of non-adherence that may adversely affect clinical outcome is not easy to determine, but a crude ‘rule of thumb’ is that if someone omits >¼30% prescribed medication over a month, the risk of relapse increases by about 10% every month. As such, it is necessary to regularly monitor where an individual is in their own ‘cycle of adherence’. It is important to create an atmosphere where the patient feels able to discuss the issue and any questions need to be constructed to ensure they are non-judgemental. Simple examples are: many individuals find it hard to stick with a course of tablets: Do you ever have any trouble taking all of your medication as prescribed? Are there times when it is more difficult to remember to take your medications? Does your medication regime fit in with your lifestyle? Do you ever try and cope on your own without your medication? The last question is particularly useful for establishing non-adherence in those who have negative attitudes or beliefs about medication (the other questions hint more at forgetting). Questions that allude to coping without medication or resolving problems independently are especially important, as this reflects the underlying rationale of many individuals with bipolar disorders, that is they are not wilfully disregarding advice from a clinician who they may well trust, but rather are desperately trying to avoid a sense of being controlled by or dependant on medication.

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It is good clinical practice to establish patterns of adherence and have some agreed means of recording this from the outset (e.g. a simple diary note through to a more detailed mood diary record), as this will prevent an accusatory feel if this were introduced some time after commencing with a newly prescribed medication. The possible drivers of medication non-adherence need to be explored in order to determine the most useful techniques to overcome this problem. Scott (1999 [12]) distinguishes between non-intentional and intentional adherence, which require different approaches. Unintentional non-adherence usually occurs when patients forget medications or find it difficult to establish regular patterns of adherence. A review of records of taking medication may however expose a different type of problem, namely that certain situations increase the individuals risk for non-adherence or that the primary problem relates to negative attitudes towards medication rather than difficulty in establishing a pattern of behaviour. Intentional non-adherence is usually an indication of cognitive barriers to engaging with medication such as beliefs that trying harder would allow the individual to deal with the symptoms without recourse to medication. Unintentional non-adherence is more likely to respond to a behavioural approach, but in practice both forms of nonadherence are usually tackled with these interventions initially. As noted in the previous section, negotiating the medication schedule and including patient preferences should be incorporated whenever possible. Use of a medi-pack or dosette that allows the daily medication regime to be organized in advance and self-monitoring of adherence is also helpful. Intentional non-adherence is not always easy to address in general day-to-day practice. However, some simple approaches to exploring attitudes and beliefs can be used. First, it is important to discover if there is a specific pattern to non-adherence, for example, are there specific days, times or situations where there is a high risk of omitting prescribed medication. Again the emphasis is then on guiding the patient to examine his or her own cognitions and behaviours, for example, a business man who omitted lithium prior to important contract meetings because he thought it would make him ‘dopey’. Simple ‘experiments’ can then be devised to test out these ideas, for example, carefully monitoring how he felt if he did take lithium before one contract meeting and then comparing this with a meeting when he did not take it. The information can then be used to discuss what ‘solutions’ might be reasonable – was there actual evidence that the lithium was adversely affecting his performance? Could there be any other explanation, for example, was he tired because he had not slept well the night before? Did anyone else notice he was ‘dopey’ or is this only a subjective phenomenon, might it relate to anxiety

about undertaking public presentations? After exploring these aspects, the clinician might be able to allay concerns that taking lithium had more ‘benefits than costs’, but by approaching the problem in this way, the patient may then be able to discuss whether he had any other issues with lithium, whether his adherence was affected in other circumstances not so far discussed and whether his real preference was actually to have a discussion about a change to a different mood stabilizer. While many clinicians would be unhappy or concerned about implementing such a change, there would be little point in avoiding or dismissing such a discussion. Failure to act in the face of these warning signs might mean the patient simply ‘votes with their feet’ and does not come back to see the clinician or stops the lithium in an unsupervised and hurried manner – all of which increase the risk of relapse. In some instances, clinicians may have to reluctantly accept the patient is not going to take medication for a period of time. However, the first thing to establish is whether this is a ‘no medication’ or a ‘no treatment’ option. If the client chooses to stop medication (and assuming compulsory treatment is not being considered nor justified at that moment) then it is vital that both parties plan the medication withdrawal programme and appointment frequency increases to ensure the patient receives additional support and help regarding non-medication coping strategies. Rather than withdrawing, the clinician needs to enter a dialogue about the need for gradual withdrawal to try to reduce immediate risks of relapse, and the need for the client to feel able to inform the clinician if they stop the medication more quickly than they plan, and so on. Also, clinicians should remember that often – when trying to get patients to try a new treatment – they negotiate an ‘experiment’ – often asking the patient to try the medication for six weeks with the clinician and patient evaluating the costs and benefits of this regimen. It is therefore sensible to try to use the same approach regarding stopping medication, that is, will the patient agree the length of time this medication-free experiment will last and the frequency of future clinical reviews. Most importantly, the clinician and patient need to agree clear criteria in advance about how they will identify the end point of an unsuccessful experiment – under what circumstances would the patient accept medication again. A record should then be kept of symptoms and agreed outcomes to make an accurate assessment of progress and the patient should ideally also identify someone outside the clinical setting whom they trust who will also help monitor their progress and can advocate on their behalf, particularly if they experience symptoms of a recurrence. At such a time, the clinician will hopefully have a further opportunity to negotiate a trial of medication [13]. By viewing bipolar disorder and its treatment from a longterm perspective, the clinician can hopefully maintain

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High Concerns

Sceptical

Ambivalent

Low Necessity

High Necessity Indifferent

Accepting

Low Concerns

a therapeutic alliance with the patient and work through these difficult periods.

Future directions – using a necessities-concerns framework Non-adherence with medication in bipolar disorder is prevalently costly and associated with poor clinical outcome. In common with other chronic conditions, however, approaches employed in routine practice have met with limited success. This is partly because the interventions have too often focused on assumed reasons for non-adherence, such as lack of insight, troublesome side-effects and unsatisfactory dosing regimens, rather than addressing the key patient beliefs that act as barriers to adherence [14] (See Figure 3). One model, which is now showing promise, is the Necessity-Concerns Framework [15]. This simply suggests that patient’s motivation to begin and continue treatment is influenced by their personal beliefs about treatment and how they judge their personal need for treatment relative to their personal concerns about potential adverse effects. Clatworthy et al. [16] have recently published a study that estimated how more than 250 individuals with bipolar disorders balance perceived needs against concerns and how these beliefs influenced adherence. The study found that scores on ratings scales of beliefs about treatment were the only significant predictors of reported adherence to medication; low adherence was associated with higher concerns about treatment and lower perceived personal need for treatment, such that for every one unit increase in the persons score on the ‘concerns’ rating scale employed, the odds of low adherence more than doubled. In contrast, for every one unit increase in perceived need, the odds of reporting low adherence halved. The relationship between necessity beliefs, concerns and adherence offer a target for interventions to help patients resolve treatment dilemmas and develop optimal adherence to appropriately prescribed medication by addressing

Fig. 4 The necessity-concerns framework.

treatment perceptions (necessity beliefs and concerns). For example, individuals can be classified according their expressions of Necessity and Concerns. As shown in Figure 4, this identifies four sub-groups of individuals according to their views of medication-Accepting (high necessity, low concerns), Ambivalent (high necessity, high concerns), Sceptical (low necessity, high concerns), or Indifferent (low necessity, low concern). Using this type of approach, the clinicians’ initial goal would be to ensure that the patient’s adherence behaviour was informed by a realistic evaluation of the likely benefit and risks of treatment, rather than by potentially misplaced beliefs and concerns. However, knowing where an individual is located within this framework then gives the clinician an opportunity to target their interventions and shape their comments to take into account the underlying but subtly different issues that influence adherence behaviour in those who are ambivalent (tackle concerns) or sceptical (tackle concerns and enhance necessity). It is hoped that this might prove a useful conceptual map that enables clinicians to elicit and respond to patients’ personal beliefs about bipolar disorders and devise simple strategies to optimize engagement and adherence with prescribed medication.

References 1. Goodwin, F. and Jamison, K. (1990) Manic Depressive Illness, 1st edn, OUP, Oxford. 2. Tacchi, M.J. and Scott, J. (2005) Improving Adherence in Schizophrenia and Bipolar Disorders, John Wiley & Sons Ltd, England. 3. Lingham, R. and Scott, J. (2002) Treatment non-adherence in affective disorders. Acta Psychiatr. Scand, 105, 164–172. 4. Martinez-Aran, A., Scott, J. et al. (2009) Treatment nonadherence and neurocognitive impairment in bipolar disorder. J. Clin. Psych. 70 (7), 1017–1023. 5. Scott, J. and Pope, M. (2002) Nonadherence with mood stabilizers: prevalence and predictors. J. Clin. Psychiatry, 63 (5), 384–390.

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6. Pope, M. and Scott, J. (2003) Do clinicians understand why patients stop taking mood-stabilizers? J. Affect. Disorders, 74, 298–291. 7. DiMatteo, M. (1979) A social-psychological analysis of physician patient rapport: Toward a science of the art of medicine. J. Soc. Issues, 35, 12–33. 8. McCabe, R. and Priebe, S. (2004) The therapeutic relationship in the treatment of severe mental illness. Int. J. Soc. Psychiatr., 50 (2), 115–128. 9. Levanthal, H., Diefenbach, M. and Levanthal, E. (1992) Illness cognition: using common sense to understand treatment adherence and affect cognition interactions. Cognitive Ther. Res., 6, 143–163. 10. Morselli, P. and Elgie, R. (2003) GAMIAN-Europe/BEAM survey I: Global analysis of a patient questioknnaire circulated to 3450 members of 12 European advocacy groups operating in the field of mood disorders. Bipolar Disord., 5, 265–278.

11. Kikkert, M. et al. (2006) Medication adherence in schizophrenia: exploring patients’, carers’ and professionals’ views. Schizophr. Bull., 32 (4), 786–794. 12. Scott, J. (1999) Cognitive approaches to improving adherence with Medication. Adv. Psych. Treatment, 5, 338–347. 13. Scott, J. (2002) Overcoming Mood Swings, Constable Robinson, England. 14. Scott, J. and Tacchi, M.J. (2002) A pilot study of concordance therapy for individuals with bipolar disorder who are nonadherent with lithium prophylaxis. Bipolar Disord., 4, 286–293. 15. Horne, R. (2003) Treatment perceptions and self regulation, in The Self-Regulation of Health and Illness Behaviour (eds L. Cameronand H. Leventhal), Routledge, London, pp. 138–153. 16. Clatworthy, J., Bowskill, R., Parham, R. et al. (2008) Understanding medication non-adherence in bipolar disorders using a Necessity-Concerns Framework. J. Affect. Disord., 116, 51–55.

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Acute Mania Paul E. Keck, Jr1, Susan L. McElroy2 and John M. Hawkins3 1

Lindner Center of HOPE; Craig & Frances Lindner; Department of Psychiatry, University of Cincinnati College of Medicine, Mason, OH, USA 2, 3 Lindner Center of HOPE; Department of Psychiatry, University of Cincinnati College of Medicine, Mason, OH, USA

Introduction Manic and mixed episodes occurring during the course of bipolar disorder are amongst the most serious acute psychiatric syndromes, often constituting a medical emergency and the need for hospitalization to ensure safety and allow aggressive treatment. The primary goal of treatment of manic and mixed episodes is rapid symptom improvement, with subsequent goals of full remission of symptoms and recovery of vocational and psychosocial function [1]. Treatment recommendation and monitoring of treatment response require consideration of the type and severity of presenting symptoms, including the presence of psychosis, depressive symptoms (degree of mixed syndrome), agitation and risk of violence; and consideration of illness characteristics such as episode frequency, co-occurring psychiatric and medical illnesses, and personal and family history of treatment response. Pharmacotherapy has been the cornerstone of treatment for bipolar manic and mixed episodes since the 1950s, but the therapeutic armamentarium has expanded greatly since then, especially over the past 15 years. Medicines with demonstrated efficacy in the treatment of manic and mixed episodes are summarized in Table 1. These medicines include agents from a broad range of pharmacologic classes, including first- and second-generation antipsychotics, lithium and several antiepileptics. In three to four week clinical trials administered as monotherapy, these medicines usually produce response rates of approximately 50% (defined as a reduction of symptoms of at least 50%) [2]. Since relatively few patients (<25%) achieve remission over a three to four week interval, combination treatment is a common strategy in clinical practice to improve short-term response and remission rates [3]. Below we review the

Bipolar Disorder: Clinical and Neurobiological Foundations Edited by Lakshmi N. Yatham and Mario Maj © 2010 John Wiley & Sons, Ltd. ISBN: 978-0-470-72198-8

clinical trials supporting the efficacy of various agents in the treatment of acute manic and mixed episodes in adults. We also discuss the use of electroconvulsive therapy in the treatment of acute mania and conclude with agents with promise in the treatment of acute mania as well as agents that were once thought to possibly possess antimanic activity, but where such efficacy has not been demonstrated.

Lithium Efficacy studies Lithium has been effectively used to treat acute bipolar manic and mixed episodes for over 50 years [4]. In randomized, double-blind, clinical trials, lithium was superior in efficacy compared with placebo [5–8], and comparable in efficacy with divalproex [9], carbamazepine [10,11], risperidone [12], olanzapine [13], quetiapine [14], aripiprazole [15], and first generation antipsychotics [16–22].

Clinical features associated with response Patients with and without psychosis responded equally well to lithium in the studies summarized above. In other analyses of lithium response, patients with predominantly euphoric or classic manic symptoms [23] and few lifetime mood episodes [24] displayed better lithium response rates than patients with predominantly mixed symptoms, numerous prior episodes and rapid cycling [25].

Dosing and therapeutic response Lithium doses titrated to the achieve plasma concentrations at the upper end of the therapeutic range (1.0–1.4 mmol/L) may be more efficacious at ameliorating manic symptoms than lower therapeutic plasma concentrations [26]. The rate of lithium titration may also affect rate of response. In one study, rapid rates of lithium dose escalation were associated with rate of reduction in manic symptoms [27]. With more 285

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Table 1 Agents with demonstrated efficacy in the treatment of acute bipolar mania. Lithium Antiepileptics Valproic acid Carbamazepine First Generation Antipsychotics Chlorpromazine Haloperidol Second Generation Antipsychotics Risperidone Olanzapine Quetiapine Ziprasidone Aripiprazole Paloperidone Asenapine

gradual titration, for example starting doses of 900 mg/d with incremental increases based on plasma concentrations, response to lithium occurred within 7–14 days in the randomized, controlled trials that employed this strategy [28].

Tolerability Higher therapeutic range plasma concentrations appear to be better tolerated during acute mania than when manic symptoms have subsided. Moreover, lithium doses required for effective maintenance treatment may be lower than those required to produce rapid acute antimanic effects [29]. Side effects commonly reported with lithium during acute mania trials include tremor, nausea, polydipsia, polyuria, weight gain and cognitive slowing. Serum creatinine levels and thyroid function tests require monitoring at the initiation of treatment and during follow-up maintenance therapy.

Valproic acid Efficacy studies The efficacy of formulations of valproic acid in the treatment of acute bipolar manic and mixed episodes was demonstrated in clinical trials of superiority versus placebo [9,30–33], and comparability in mean reduction of manic symptoms and response rates versus haloperidol [34] and olanzapine [35]. In a second head-to-head comparison trial with olanzapine, olanzapine-treated patients displayed a greater mean reduction in manic symptoms and a greater proportion achieved remission compared with divalproextreated patients [36]. Valproic acid has been studied as an adjunctive treatment in patients with manic episodes receiving first-generation antipsychotics [37]. In this trial, patients receiving the combination of valproic acid and an

antipsychotic displayed significantly greater response rates and required lower mean doses of antipsychotic compared with patients receiving antipsychotic and placebo.

Clinical features associated with response The presence of psychotic symptoms [34], depressive symptoms [23] and recent history of frequent mood episodes [38] did not appear to negatively impact response to valproic acid in clinical trials in which these features were assessed. This suggests that predictors of response to valproic acid in acute manic and mixed episodes may be broader than those associated with lithium [23].

Dosing and therapeutic response In contrast to lithium administration, one advantage of valproic acid administration is the strategy of initiating treatment with a starting dose that produces therapeutic plasma concentrations within 24 hours. Five studies examined the efficacy and tolerability of oral loading doses (20–30 mg/kg/day) of the divalproex or divalproex extended release formulations of valproic acid [30,34,35,39,40]. This dosing strategy was generally well tolerated with some evidence of more rapid response than with gradual titration starting at 750 mg/d. As with lithium, antimanic response to valproic acid appears to increase with titration to the upper end of the therapeutic range [35,41]. Again, similar to lithium, side effects, not surprisingly, also increase in frequency at higher plasma concentrations.

Tolerability Divalproex is the most commonly studied formulation of valproic acid in clinical trials in patients with acute bipolar mania. This formulation appears to be better tolerated than valproic acid [40]. Side effects commonly reported in clinical trials of divalproex in bipolar mania include nausea, vomiting, tremor, weight gain, somnolence and cognitive slowing. Rare adverse events associated with valproic acid formulations include pancreatitis, thrombocytopenia, significant hepatic transaminase elevation, hepatic failure and hyperammonemic encephalopathy in patients with urea cycle disorders. Therapeutic monitoring for patients receiving valproic acid includes plasma concentration, hepatic transaminase concentrations and platelet count.

Carbamazepine Efficacy studies The extended release beaded formulation of carbamazepine is the most well studied formulation of carbamazepine in clinical trials in acute bipolar manic and mixed

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episodes [42,43]. In these two placebo-controlled trials, carbamazepine was superior to placebo, findings which replicated the results of an earlier placebo-controlled crossover study [44]. In other clinical trials in patients with acute bipolar mania, carbamazepine was comparable in efficacy to lithium [10,11] and chlorpromazine [45,46]. However, in one small pilot comparison trial, patients receiving valproic acid displayed a better response compared with patients receiving carbamazepine [47]. These findings need to be replicated in a larger, adequately powered comparison trial. Oxcarbazepine has been an intriguing alternative to carbamazepine because, unlike carbamazepine, oxcarbazepine does not induce its own metabolism, has a lower rate of side effects and is generally better tolerated. However, data supporting the efficacy of oxcarbazepine in the treatment of acute bipolar manic and mixed episodes to date are not compelling. Initial interest was piqued when oxcarbazepine was found to exert comparable improvement in manic symptoms in small controlled trials versus haloperidol [48] and lithium [49], respectively. These initial results were not borne out in a recent large, multicentre placebo-controlled trial in adolescents [50]. In this latter, seven-week study, oxcarbazepine was not superior to placebo in reduction of manic symptoms.

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No clear plasma concentration-response relationship has been identified for carbamazepine in the treatment of acute mania. Concentrations between 4 and 12 microgram/mL are usually associated with response in mania and epilepsy, and neurological side effects often become pronounced at concentrations >12 microgram/mL [54].

Tolerability Side effects may limit treatment with carbamazepine more than with most other antimanic agents [54]. Common side effects reported in clinical trials in acute mania include sedation, ataxia, diplopia, nystagmus, transient leucopenia and rash. Rare but serious side effects include StevensJohnson syndrome, agranulocytosis, aplastic anaemia and hepatitis. Since carbamazepine can affect cardiac conduction, it should be used with caution in patients with heart block and other cardiac conduction problems [54]. Carbamazepine is also associated with hyponatremia in some patients, and can be especially troublesome in older patients [54]. Routine work-up and therapeutic monitoring for patients receiving carbamazepine includes an electrocardiogram, complete blood count and hepatic transaminase concentrations. Patient education about the signs and symptoms of Stevens-Johnson syndrome and blood dyscrasias may be more important than blood monitoring [54].

Clinical features associated with response Predictors of carbamazepine response have not been replicated in more than one study to date. Findings from individual studies suggest that carbamazepine may be less efficacious in patients who do not respond to or adequately tolerate lithium [46,51], but more efficacious than lithium in patients with atypical presentations of mania [52], and in patients with a stable or decreasing episode frequency [53]. Patients with mixed episodes did not respond as well as patients with manic episodes in one study [42], but patients with each type of episode responded equally well in another [43]. Severity of manic episode or the presence of psychosis has not been a predictor of response [42,43].

Dosing and therapeutic response Since data regarding the efficacy of oxcarbazepine in the treatment of acute mania are lacking at present, dosing and therapeutic response for carbamazepine only will be discussed. Loading strategies for carbamazepine treatment of acute mania do not appear to be viable due to the potential for adverse and treatment-limiting neurological side effects with this approach [54]. Starting doses in most carbamazepine clinical trials in acute mania have typically been 400–800 mg/d, with gradual titration by 200 mg/d every two to four days as tolerated and to clinical response [54].

First-generation (typical) antipsychotics Efficacy studies Chlorpromazine and haloperidol are the only two firstgeneration antipsychotics examined in placebo-controlled trials in acute bipolar mania [55,56]; both agents were superior to placebo. In addition, these and other first generation agents have been found to exert similar antimanic efficacy when compared with lithium [16–22], valproic acid [34], carbamazepine [46,47], and second-generation antipsychotics [56–59].

Clinical features associated with response First-generation agents have the advantages of rapid acute efficacy, and efficacy in treating psychotic as well as manic symptoms. However, they have the disadvantages of extrapyramidal side effects, prolactin elevation and risk of worsening depressive symptoms [57,60].

Dosing and therapeutic response Dosage ranges of first-generation antipsychotics used in the treatment of acute exacerbations of schizophrenia are usually used and effective in the treatment of acute bipolar mania.

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Tolerability

Clinical features associated with response

As described above, first-generation antipsychotic agents have side effects overall that are shared by this group of medications, and largely mediated by their strong binding affinities to the postsynaptic dopamine D2 receptor. These include, commonly, extrapyramidal side effects, akathisia, prolactin elevation and cognitive dulling. These agents are also associated with rare but serious side effects such as tardive dyskinesia and neuroleptic malignant syndrome.

In most of the trials reviewed above, response to secondgeneration antipsychotics was similar in patients with or without psychosis and in manic and mixed episodes. The exception to this generalization was in trials of quetiapine, which excluded patients with mixed episodes. Thus, data from placebo-controlled trials regarding the efficacy of quetiapine in mixed episodes are lacking.

Second-generation (atypical) antipsychotics Efficacy studies With the exception of clozapine, all atypical antipsychotics widely available to date, including olanzapine [61,62], risperidone [63,64], quetiapine [14,56], ziprasidone [65,66] and aripiprazole [15,67,68], have been shown to be superior to placebo as monotherapy in the treatment of acute mania in at least two placebo-controlled trials. As summarized above, when compared with haloperidol [56–59], lithium [12–15,69], divalproex [35,70] and each other [71], second-generation agents exerted similar antimanic efficacy. The only exception was one study in which olanzapine-treated patients had significantly greater mean improvement in manic symptoms compared with divalproex-treated patients [36]. Differences in study design, statistical power and initial dosing of olanzapine and divalproex likely explain the different results between the two comparison trials [35,36]. A number of studies have examined the efficacy of secondgeneration antipsychotics compared with placebo in combination with lithium, divalproex [72–78] or carbamazepine [79]. In the majority of these trials, the addition of a second-generation antipsychotic was superior to placebo in reduction of manic symptoms and time to initial improvement [72–77]. In an adjunctive study of ziprasidone versus placebo in combination with lithium, the ziprasidone group displayed a greater and more rapid improvement initially, but this difference was not sustained at two weeks of treatment, possibly because patients in lithium titration finally reached a therapeutic effect by this time point. In one [79] of two [73,79] adjunctive risperidone trials, the risperidone group was not superior to the placebo group overall, but this may have been due to the inclusion of patients receiving carbamazepine and subsequent induction of hepatic metabolism of risperidone leading to subtherapeutic levels. The prototypical second-generation antipsychotic, clozapine, has not been studied in placebo-controlled trials in acute bipolar mania. However, reports of its efficacy in large case series of patients with treatment refractory bipolar disorder provide supportive data for its use when other agents are inadequately effective [80,81].

Dosing and therapeutic response For olanzapine, in the two placebo-controlled trials, the rate of improvement was faster with an initial starting dose of 15 mg/d [62], compared with 10 mg/d [61]. One study specifically compared rapid dose escalation (20–40 mg/d) with gradual titration (starting at 10 mg/d) and found significant reductions in agitation within the first day of administration of the rapid escalation strategy compared with usual titration [82]. For risperidone, doses of 4 mg/d appear to be rapidly efficacious (within three days) [63], with a lower risk of extrapyramidal side effects compared with higher doses [64]. In the quetiapine monotherapy clinical trials, the mean modal dose associated with antimanic efficacy was approximately 600 mg/d [83]. Ziprasidone appeared to have increasing antimanic efficacy within the range of doses studied in monotherapy clinical trials of 80–160 mg/d. Aripiprazole was initiated at doses of 15 or 30 mg/d in monotherapy clinical trials.

Tolerability The second-generation antipsychotics, not unexpectedly given their different pharmacological profiles, differ somewhat in common side effects reported in monotherapy trials. In short-term acute mania trials, the most common side effects associated with olanzapine were somnolence, constipation, dry mouth, increased appetite, weight gain and orthostatic hypotension. For risperidone, common side effects reported in acute mania trials included prolactin elevation, akathisia, somnolence, dyspepsia and nausea. Headache, dry mouth, constipation, weight gain, somnolence and dizziness were the most common reported side effects in acute mania trials of quetiapine monotherapy. Common ziprasidone side effects reported monotherapy mania trials were headache, somnolence, extrapyramidal side effects, akathisia and dizziness. Lastly, for aripiprazole, common side effects reported included headache, nausea, vomiting, constipation, insomnia and akathisia. Although the risks of tardive dyskinesia and neuroleptic malignant syndrome appear to be substantially less than with first -generation antipsychotics, second-generation agents are not entirely devoid of these risks.

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Electroconvulsive therapy Efficacy studies Electroconvulsive therapy remains an important nonpharmacological treatment option for patients who do not respond well to or tolerate pharmacotherapy, or who have severe, psychotic or catatonic symptoms. Four small controlled trials have examined the efficacy of electroconvulsive therapy in the treatment of acute bipolar mania [84–87]. In these studies, electroconvulsive therapy was superior to lithium [84], and the combination of lithium and haloperidol [85] in reduction of manic symptoms. When used in combination with chlorpromazine, electroconvulsive therapy was superior to sham therapy [86]. Recently, bifrontal electoconvulsive therapy was reported to produce more rapid improvement in manic symptoms compared with bitemporal electroconvulsive therapy [87].

Clinical features associated with response As there are few controlled trials of electroconvulsive therapy in mania, there are limited data on clinical features associated with response. Importantly, the presence of severe manic symptoms, psychosis and catatonia do not predict poor response. In one trial, the presence of depressive symptoms at baseline was associated with response to electroconvulsive therapy [84].

New potential antimanic agents Two new second-generation antipsychotic agents, paloperidone and asenapine, were superior to placebo and comparable in efficacy to quetiapine and olanzapine, respectively in a large multicentre trial in patients with acute bipolar mania [88–90]. To our knowledge, no other new second-generation antipsychotics, including bifeprunox, have yet been studied in controlled trials in bipolar mania. Perhaps the most intriguing new agent to be found promising in preliminary controlled trials in acute bipolar mania is tamoxifen [91,92]. Based on findings that suggest that protein kinase C (PKC) activity may be altered in mania, these trials sought to determine whether a PKC inhibitor, tamoxifen, would exert significant improvement in manic symptoms. In each study, patients receiving tamoxifen displayed significantly greater improvement compared with patients receiving placebo, and tamoxifen was well tolerated. These promising initial positive results require replication in a larger study.

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not been shown to possess such efficacy when studied in randomized, controlled clinical trials. These include verapamil [93,94], topiramate [95], lamotrigine [96,97] and gabapentin [98].

Clinical recommendations Acute manic and mixed episodes, with or without psychosis, often constitute a medical emergency, and frequently require hospital admission to ensure the safety of patients and others, as well as to provide a therapeutic environment for rapid recovery. Antimanic agents are the cornerstone of treatment of bipolar manic and mixed episodes. As reviewed above, the therapeutic armamentarium has expanded dramatically in the last 15 years. Monotherapy or combination therapy (most commonly a second-generation antipsychotic agent and lithium, valproate or carbamazepine) represent standard treatment approaches. Doses of antimanic agents often need to be titrated to the higher end of therapeutic ranges to achieve rapid improvement, balanced against the risk of side effects [99]. Since manic or mixed episodes form just one phase of the overall challenge of assisting patients in the management of bipolar disorder, two different, and at times competing treatment needs, warrant consideration: the need to rapidly ameliorate symptoms to ensure safety, reduce morbidity and hasten recovery versus the need to recommend an antimanic agent that may need to be used not just in acute treatment, but sustained into maintenance therapy. Thus, agents that have side effects, for example sedation, that may be beneficially acutely, may not be as advantageous in longterm treatment. Similarly, the choice of combination therapy over monotherapy may have short-term benefits in hastening recovery, but pose the dilemma in longer-term treatment of obscuring which agent is the most effective and complicating treatment by the burden of additive side effects. The studies reviewed above provide a compendium of the evidence-based treatment of acute bipolar manic and mixed episodes. Selection or recommendation of specific agents or combinations of agents requires the consideration of prior treatment response, the presence of potential predictors of response, patient preference, severity of the acute episode, the presence of co-occurring psychiatric and other medical conditions, history of side effects and tolerability, and other considerations such as the likelihood of treatment adherence, and cost and availability of one regimen over another [99].

Summary Agents without demonstrated antimanic efficacy Over the past decade, a number of medications, which showed early promise as potential antimanic agents, have

Less than 15 years ago, only lithium and the first-generation antipsychotics, along with electroconvulsive therapy, were effective treatments for patients with acute bipolar manic or mixed episodes. The number of available agents has

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expanded dramatically since then, offering patients with bipolar disorder therapeutic options where none previously existed. Since mania is often a medical emergency, expanding treatments for this phase of bipolar disorder has no doubt substantially reduced human suffering and the potential risks of harm to self and others posed by acute manic states.

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61. Tohen, M., Sanger, T.M., McElroy, S.L. et al. (1999) Olanzapine versus placebo in the treatment of acute mania. Am. J. Psychiatry, 156, 702–709. 62. Tohen, M., Jacobs, T.G., Grundy, S.L. et al. (2000) Efficacy of olanzapine in acute bipolar mania: a double-blind, placebocontrolled study. Arch. Gen. Psychiatry, 57, 841–849. 63. Hirschfeld, R.M.A., Keck, P.E. Jr, Kramer, M. et al. (2004) Rapid antimanic effect of risperidone monotherapy: a 3-week multicenter, double-blind, placebo-controlled trial. Am. J. Psychiatry, 161, 1057–1061. 64. Khanna, S., Vieta, E., Lyons, B. et al. (2009) Risperidone in the treatment of acute mania: double-blind, placebo-controlled study. Brit. J. Psychiat., 187, 229–234. 65. Keck, P.E. Jr, Versiani, M., Potkin, S. et al. (2003) Ziprasidone in the treatment of acute bipolar mania: a three-week, placebo-controlled, double-blind, randomized trial. Am. J. Psychiatry, 160, 741–748. 66. Potkin, S., Keck, P.E. Jr, Segal, S. et al. (2005) Ziprasidone in acute bipolar mania: a 21-day randomized, double-blind, placebo-controlled replication trial. J. Clin. Psychopharmacol., 25, 301–310. 67. Keck, P.E. Jr, Marcus, R., Tourkodimitris, S. et al. (2003) A placebo-controlled, double-blind study of the efficacy and safety of aripiprazole in patients with acute bipolar mania. Am. J. Psychiatry, 160, 1651–1658. 68. Sachs, G.S., Sanchez, R., Marcus, R. et al. (2006) Aripiprazole in the treatment of acute manic or mixed episodes in patients with bipolar I disorder: a 3-week placebo controlled study. J. Clin. Psychopharmacol., 20, 536–546. 69. Li, H., Ma, C., Wang, G. et al. (2008) Response and remission rates in Chinese patients with bipolar mania treated for 4 weeks with either quetiapine or lithium: a randomized and double-blind study. Curr. Med. Res. Opin., 24, 1–10. 70. DelBello, M.P., Kowatch, R.A., Adler, C.M. et al. (2006) A double-blind randomized pilot study comparing quetiapine and divalproex for adolescent mania. J. Am. Acad. Child Psy., 45, 305–313. 71. Perlis, R.H., Baker, R.W., Zarate, C.A. Jr et al. (2006) Olanzapine versus risperidone in the treatment of manic or mixed states in bipolar I disorder: a randomized, double-blind trial. J. Clin. Psychiat., 67, 1747–1753. 72. Tohen, M., Chengappa, K.R.N., Suppes, T. et al. (2002) Efficacy of olanzapine in combination with valproate or lithium in the treatment of mania in patients partially nonresponsive to valproate or lithium. Arch. Gen. Psychiatry, 59, 62–69. 73. Sachs, G.S., Grossman, F., Ghaemi, S.N. et al. (2002) Combination mood stabilizer with risperidone or haloperidol for treatment of acute mania: a double-blind, placebo-controlled comparison for efficacy and safety. Am. J. Psychiatry, 159, 1146–1154. 74. Sachs, G.S., Chengappa, K.N.R., Suppes, T. et al. (2004) Quetiapine with lithium or divalproex for the treatment of bipolar mania: a randomized, double-blind, placebo-controlled study. Bipolar Disord., 6, 213–223. 75. Yatham, L.N., Paulsson, B., Mullen, J. et al. (2004) Quetiapine versus placebo in combination with lithium or divalproex for the treatment of bipolar mania. J. Clin. Psychopharmacol., 24, 599–606.

76. Vieta, E., T’joen, C., McQuade, R.D. et al. (2008) Efficacy of adjunctive aripiprazole to either valproate or lithium in bipolar mania patients partially nonresponsive to valproate/lithium monotherapy: a placebo-controlled study. Am. J. Psychiatry, 165, 1316–1325. 77. DelBello, M.P., Schweirs, M.L., Rosenberg, H.L. et al. (2002) A double-blind, randomized, placebo-controlled study of quetiapine as adjunctive treatment for adolescent mania. J. Am. Acad. Child Psy., 41, 1216–1223. 78. Weisler, R.H., Dunn, J. and English, P. (2004) Ziprasidone adjunctive treatment of acute bipolar mania: a randomized, placebo-controlled trial. Abstracts of the 16th Annual Meeting of the European College of Neuropsychopharmacology, Prague, Czech Republic. 79. Yatham, L.N., Grossman, F., Augustyns, I. et al. (2003) Mood stabilizers plus risperidone or placebo in the treatment of acute mania. International, double-blind, randomized controlled trial. Brit. J. Psychiat., 182, 141–147. 80. Green, A.I., Tohen, M., Patel, J.K. et al. (2000) Clozapine in the treatment of refractory psychotic mania. Am. J. Psychiatry, 157, 982–986. 81. Calabrese, J.R., Kimmel, S.E., Woyshville, M.J. et al. (1996) Clozapine for treatment-refractory mania. Am. J. Psychiatry, 153, 759–764. 82. Baker, R.W., Kinon, B.J., Maguire, G.A. et al. (2003) Effectiveness of rapid initial dose escalation of up to forty milligrams per day of oral olanzapine in acute agitation. J. Clin. Psychopharmacol., 23, 342–348. 83. Vieta, E., Mullen, J., Brecher, M. et al. (2005) Quetiapine monotherapy for mania associated with bipolar disorder: combined analysis of two international, double-blind, randomized, placebo-controlled studies. Curr. Med. Res. Opin., 21, 923–934. 84. Small, J.G., Klapper, M.H., Kellams, J.J. et al. (1988) Electroconvulsive treatment compared with lithium in the management of manic states. Arch. Gen. Psychiatry, 45, 727–732. 85. Mukerjee, S., Sackheim, H.A. and Schnur, D.B. (1994) Electroconvulsive therapy of acute manic episodes: a review of 50 years’ experience. Am. J. Psychiatry, 151, 169–176. 86. Sikdar, S., Kulhara, P. and Avasthi, A. (1994) Combined chlorpromazine and electroconvulsive therapy in mania. Brit. J. Psychiat., 164, 806–810. 87. Hiremani, R.M., Thirthalli, J., Tharayil, B.S. et al. (2008) Double-blind randomized controlled study comparing short-term efficacy of bifrontal and bitemporal electroconvulsive therapy in acute mania. Bipolar Disord., 10, 701–707. 88. Hirschfeld, R.M.A., Panagides, J., Alphs, L. et al. (2007) Asenapine in acute mania: a randomized, double-blind, placebo- and olanzapine-controlled trial. Abstracts of the 160th Annual Meeting of the American Psychiatric Association. American Psychiatric Publishing, Inc., Washington, DC, p. 333. 89. Vieta, E., Berwaerts, J., Nuamah, I. et al. (2008) Randomized, placebo, active-controlled study of paloperidone extendedrelease (ER) for acute manic and mixed episodes in bipolar I disorder. Eur. Neuropsychopharmacol., 18 (Suppl 4), S369. 90. Cutler, A. (2008) A randomized, double-blind, placebocontrolled, parallel-group, dose-response, multicenter study

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four double-blind placebo-controlled trials. Bipolar Disord., 8, 15–27. Anand, A., Oren, D.A. and Berman, R.M. (1999) Lamotrigine treatment of lithium failure in outpatient mania: a doubleblind, placebo-controlled trial. Abstracts of the 3rd International Conference on Bipolar Disorder. University of Pittsburgh, Pittsburgh, PA. Frye, M.A., Ketter, T.A., Kimbrell, T.A. et al. (2000) A placebocontrolled study of lamotrigine and gabapentin monotherapy for refractory mood disorders. J. Clin. Psychopharmacol., 20, 607–614. Pande, A.C., Crockatt, J.G., Janney, C.A. et al. (2000) Gabapentin in bipolar disorder: a placebo-controlled trial of adjunctive therapy. Bipolar Disord., 2, 249–255. Keck, P.E. Jr and McElroy, S.L. (2007) Pharmacological treatments for bipolar disorder, in A Guide to Treatments That Work, 3rd edn (eds P.E. Nathan and J.M. Gorman), Oxford University Press, New York, NY, pp. 323–350.

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Pharmacological Treatment of Bipolar Depression Allan H. Young1 and Charles B. Nemeroff2 1 2

Department of Psychiatry, Institute of Mental Health, University of British Columbia, Vancouver, BC, Canada Department of Psychiatry and Behavioral Sciences, University of Miami Miller School of Medicine, Miami, FL, USA

Introduction Bipolar disorders are characterized by episodes of mania/ hypomania and depression and are estimated in the population to have a lifetime prevalence of approximately 2% [1,2]. The impact of bipolar disorders has recently been estimated to amount to 2% of all disability-adjusted life years associated with non-communicable disease worldwide [3]. The degree of disability associated with episodes of bipolar depression may be greater than that associated with episodes of bipolar mania [4] and patients with bipolar depression frequently have pronounced psychosocial impairment [5,6]. This is of particular importance given that patients with bipolar disorder are likely to experience depressive symptoms far more frequently than symptoms of mania [7,8]. Furthermore, bipolar depression is a major risk factor for suicide and long-term follow-up studies suggest that predominantly depressed bipolar patients suffer the highest mortality rates from this cause [9]. Effective treatment of depression in bipolar disorders represents a key therapeutic challenge. All treatment should be based on accurate diagnosis but several factors may confound the diagnosis (and thus treatment) of bipolar disorder, including a considerable symptomatic overlap with other psychiatric illnesses; a potentially incomplete medical history of the patient and lack of patient insight or acceptance of diagnosis. Treatment is further complicated by the high prevalence of comorbidities, such as anxiety disorders and substance use disorders. These comorbidities frequently have a detrimental effect on the disease course, including an increase in the number of suicide attempts [10–13]. A combination of these factors can lead to bipolar disorder being under-diagnosed and high rates of misdiagnosis (commonly as unipolar major depressive disorder, anxiety disorder or schizophrenia) have been reported [14]. Inaccurate diagnosis often results in inappropriate treatment being implemented, which may compromise long-term outcomes.

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Diagnostic accuracy may be improved by intensive scrutiny for the presence of manic/hypomanic, psychotic or reverse vegetative symptoms in every patient presenting with depressive symptoms, in establishing whether there is a family history of bipolar disorder, and whether the patient had a prepubertal onset of depression. This chapter focuses on the pharmacological treatment of bipolar depression, although other treatment modalities, both psychological and somatic, exist. For a more extensive discussion and specific treatment recommendations the reader is referred to recent international guidelines [15,16]. Treatments for bipolar 1 and bipolar II depression will be discussed separately.

Treatments for the management of bipolar I depression Lithium In a review of short-term, placebo-controlled, double-blind, cross-over trials that compared the efficacy of lithium with placebo, seven out of eight studies found that lithium was significantly more effective than placebo [17]. Furthermore, approximately half of the patients experienced a relapse of depressive symptoms when lithium was substituted by placebo [17]. However, a more recent double-blind, randomized, placebo-controlled study of quetiapine and lithium as acute monotherapy treatment for bipolar depression found no statistically significant difference between lithium and placebo [18]. The mean serum lithium levels in this study were 0.61 mEq/L and it is unknown if response rates would be greater with higher serum lithium levels. The duration of acute treatment was also 8 weeks, leaving the possibility open of an undetected slower beneficial effect of lithium on bipolar depression. Two early studies examined the efficacy of lithium in the long-term treatment of bipolar disorder. In the first study, 205 patients with bipolar disorder, most recent episode manic, were randomized to lithium or placebo for a period of two years [19]. The number of manic episodes, but not depressive episodes, was significantly lower with lithium

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compared with placebo. In the second smaller study, 44 patients with bipolar disorder, most recent episode depressed, were randomized to lithium, imipramine or placebo for two years [19,20]. In this study, the number of depressive episodes, but not manic episodes, experienced was significantly lower in the lithium group compared with the placebo group. Meta-analyses of trials of lithium in patients with bipolar disorder include further data concerning the use of lithium; importantly they summarize recent studies, which have included lithium as an active comparison to new medications [21,22]. Lithium was shown in these analyses to be more effective than placebo in preventing any new mood episodes. However, although lithium was superior to placebo in preventing manic episodes, this was not clearly shown for depressive episodes [21,22]. Baldessarini and Tondo [23] carried out a pooled analysis of data from 24 studies that investigated the clinical effects of long-term lithium in 360 patients with bipolar disorder who received lithium maintenance treatment since 1970. In the period 1970–1981, the number of recurrences of mania or depression per month was 2.7% compared with 0.5% per month in the period 1982–1996, suggesting that loss of effectiveness has not occurred with lithium as maintenance treatment over time.

Lamotrigine Monotherapy Lamotrigine monotherapy was initially examined in a double-blind, placebo-controlled study for the acute treatment of bipolar I depression [24]. More recently, this study was included in a review of five double-blind, placebocontrolled trials, all of which assessed the efficacy of lamotrigine in the acute treatment of bipolar depression [25]. These five randomized, placebo-controlled trials have also been reviewed by others [26,27]. Although there is a widespread belief that lamotrigine has a beneficial effect on depressive symptoms in the depressed phase of bipolar disorder, the overall pooled effect was modest at best. It is, however, important to note that the advantage of lamotrigine over placebo was greater in the more severely depressed participants. Two longer-term studies compared the effectiveness of lithium and lamotrigine monotherapy over a period of 18 months in 638 patients with bipolar I disorder and recent episodes of mania or depression [28,29]. Bowden et al. demonstrated that lamotrigine was significantly more effective than placebo at prolonging the time to intervention for a depressive episode [28]. This finding is supported by the study by Calabrese et al. that again found that lamotrigine significantly prolonged time to a depressive episode [29]. A pooled analysis of data from these trials showed that lamotrigine, but not lithium, was superior to

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placebo at delaying the time to intervention for a depressive episode [30].

Adjunctive lamotrigine The use of adjunctive lamotrigine as a treatment for bipolar I depression was investigated in the Systematic Treatment Enhancement Programme for Bipolar Disorder (STEP-BD) study. This study was designed to evaluate the rate of recovery (defined as no more than two symptoms meeting Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) threshold criteria for a mood episode and no significant symptoms present for 8 weeks) with open-label lamotrigine, inositol or risperidone as adjuncts to a mood stabilizer for up to 16 weeks in patients (n ¼ 66) with treatment-resistant bipolar I or bipolar II depression. Recovery rates were 23.8% (95% CI ¼ 5.8 to 41.8) with lamotrigine compared with 17.4% (95% CI ¼ 2.4 to 32.4) with inositol and 4.6% (95% CI ¼ 0 to 14.6) for risperidone (no significant between group differences were reported) [31]. In addition, the use of adjunctive lamotrigine was recently evaluated in an eight-week, double-blind, randomized, placebo-controlled trial; the results suggested that lamotrigine in combination with lithium was superior to lithium monotherapy [32]. A comparison of the adjunctive use of lamotrigine and lithium in the long-term treatment of bipolar disorder has been carried out in an open, randomized trial [33]. Patients were randomized to receive lithium (dosed to attain serum levels of 0.5–0.8 mmol/L, n ¼ 78) or lamotrigine (up to 400 mg/day, n ¼ 77) for up to six years, with concomitant pharmacologic therapy allowed for the first six months of the study period. The primary outcome measure was the cumulative probability of the patients only requiring monotherapy at month 6 and continuing on monotherapy after this assessment. No differences were noted between lamotrigine and lithium when used as adjunctive therapy with respect to the primary outcome measure [33].

Divalproex Relatively little evidence exists supporting the use of divalproex in bipolar 1 depression. A small eight-week, doubleblind, placebo-controlled, randomized study that evaluated the clinical efficacy of Divalproex (up to 2500 mg/day) in 25 outpatients with bipolar I depression found that the active treatment was significantly more effective than placebo in improving symptoms of depression [34]. Some further evidence is provided by a very small double-blind, randomized study in which patients with bipolar I depression (n ¼ 9) received divalproex or placebo for six weeks [35]. Divalproex was associated with a significantly greater reduction in MADRS total score, the

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primary efficacy measure, from baseline to Week 6 compared with placebo (p < 0.001; standardized effect size [Cohen d] ¼ 0.81).

Carbamazepine A double-blind study evaluated the acute effects of carbamazepine monotherapy in 35 patients with depression, including 16 patients with bipolar I depression and 8 with bipolar II depression, over a median treatment duration of 45 days. The investigators found that 62% of patients receiving carbamazepine monotherapy (mean dose of 971 mg/day; achieving mean
SD blood levels of 9.3
1.9 micrograms/ml; range, 3–12.5 micrograms/ml) experienced a response (mean improvement of 1 point on the Bunney-Hamburg scale) [36].

Quetiapine Monotherapy Evidence for the acute efficacy of quetiapine monotherapy in patients with bipolar I or bipolar II depression is provided by the results of two large, 8-week, randomized, doubleblind, placebo-controlled studies that evaluated quetiapine monotherapy (300 and 600 mg/day) [37,38]. In the first study, effect sizes (based on change in MADRS total score from baseline to Week 8) in patients with bipolar I depression were 0.91 and 1.09 for quetiapine, 300 and 600 mg/day, respectively. In the second study, effect sizes at Week 8 for the bipolar I subgroup were 0.67 and 0.51 for quetiapine, 300 and 600 mg/day, respectively. Importantly, treatment-emergent mania rates did not differ from placebo [37,38]. The efficacy of quetiapine or lithium as acute monotherapy was further evaluated in a double-blind, placebocontrolled study in patients with bipolar I and bipolar II depression. The study consisted of an initial acute phase lasting eight weeks, during which patients were randomized to receive quetiapine 300 mg/day, 600 mg/day, lithium or placebo. This was followed by a continuation phase lasting between 26 and 52 weeks. The primary endpoint of the acute phase of the study was the change from baseline to Week 8 in MADRS total score. In the bipolar I subgroup of patients (n ¼ 487) the mean change in MADRS total score at Week 8 was 14.8 with quetiapine 300 mg/day (p < 0.05 vs. placebo) and 16.5 with quetiapine 600 mg/day (p < 0.05 vs. placebo) compared with 11.2 for placebo [18]. Notably, lithium did not separate from placebo. These findings are consistent with a double-blind, placebo-controlled study of similar design that evaluated the efficacy of quetiapine (300 and 600 mg/day) and paroxetine (20 mg/day) as monotherapy in patients with bipolar I and bipolar II depression [39]. In the bipolar I subgroup (n ¼ 448), quetiapine 600 mg/day significantly

reduced MADRS total score from baseline to Week 8 (16.2, quetiapine 300 mg/day [95% CI ¼ 5.34 to 0.22; p < 0.05]; 16.4, quetiapine 600 mg/day [95% CI ¼ 5.60 to 0.49; p < 0.05] compared with placebo [13.4]). Both of the above studies were sufficiently large (n ¼ 328 and n ¼ 256, respectively) to provide adequate evidence for the short- and long-term use of quetiapine monotherapy for the treatment of bipolar I or II depression [18,39]. These two studies were powered to allow for a combined continuation phase, during which patients who remitted on quetiapine 300 or 600 mg/ day were randomly re-assigned to either continued treatment on quetiapine 300 mg/day or placebo and were studied for an additional 26–52 weeks. Quetiapine significantly increased the time to recurrence of depression compared with placebo (HR 0.48, 95% CI ¼ 0.29 to 0.77) [18]) (HR 0.36, 95% CI ¼ 0.21 to 0.63) [39] in patients with bipolar I or II depression. Analysis of the individual items on the MADRS revealed significant improvement of virtually all of them in the quetiapine group, indicating that the overall effect was not solely secondary to improvement in sleep. The two comparator agents in these studies, lithium and paroxetine, did not separate from placebo.

Adjunctive quetiapine To date, no randomized, controlled trials have yet examined the efficacy of adjunctive quetiapine treatment for acute bipolar depression; however, evidence for long-term efficacy in patients with bipolar I depression is provided by two randomized, double-blind, parallel group studies that investigated the use of quetiapine in combination with lithium or divalproex (Li/DVP) [40,41]. In both studies, a 12- to 36-week open-label stabilization phase was followed by a randomized treatment phase of up to 104 weeks. The primary efficacy endpoint for both studies was the time to recurrence of any mood event (mixed, mania or depression). In one study, quetiapine in combination with Li/DVP was found to be significantly more effective than placebo and Li/DVP in preventing the recurrence of any mood event and in particular a depressive episode [40]. In the other study, quetiapine in combination with Li/DVP was also significantly more effective than placebo and Li/DVP in preventing both the recurrence of any mood event and a depression event [41].

Olanzapine and olanzapine/fluoxetine combination The efficacy of olanzapine/fluoxetine combination (OFC) in comparison with lamotrigine was demonstrated in a seven-week, randomized, double-blind, parallel-group study in patients with bipolar I depression. OFC was associated with significantly greater improvement in CGI-S from baseline to Week 7 compared with lamotrigine

Pharmacological Treatment of Bipolar Depression

(1.43, OFC; 1.18, lamotrigine; p < 0.01). Furthermore, patients had statistically significantly greater improvement in MADRS total score with OFC than lamotrigine at Week 7 (14.91, OFC; 12.92, lamotrigine; p < 0.01) [42]. Tohen et al. [43] carried out a sub-analysis of data from an 8-week, placebo-controlled, randomized study that investigated the efficacy of olanzapine and OFC in patients with bipolar I depression. The aim of the analysis was to compare rates of treatment-emergent mania (defined a priori as YMRS score <15 at baseline and 15 at any subsequent visit) in patients receiving olanzapine or placebo. During the eight-week study, olanzapine and OFC were not associated with a greater risk of treatment-emergent mania compared with placebo [44]. To date, the long-term use of olanzapine or OFC in patients with bipolar depression has not been evaluated in placebo-controlled trials. The only long-term, controlled data for olanzapine plus fluoxetine in bipolar depression derive from a study evaluating the efficacy of OFC. A 25week, randomized, double-blind study compared the efficacy of OFC and lamotrigine in patients with bipolar I depression ([45]; see above). OFC was associated with significantly greater improvements in CGI-S and MADRS total scores than lamotrigine from baseline to Week 25. It is important to note the increased risk for the development of the metabolic syndrome, diabetes and cardiovascular disease incumbent in long-term treatment with olanzapine and other atypical antipsychotics. This is an important consideration in patients with bipolar disorder, a patient population already vulnerable to these major causes of morbidity and mortality.

Antidepressants There is little evidence to support the use of antidepressant monotherapy in patients with bipolar disorder, despite their common use [14]. In support of this, results from the McElroy study that investigated the efficacy of quetiapine and paroxetine for the acute treatment of bipolar depression showed that paroxetine did not significantly improve MADRS total scores at Week 8 from baseline in patients with bipolar depression (14.9, paroxetine; 13.4, placebo; p ¼ 0.313) [39], whereas quetiapine did separate from placebo as discussed above. The adjunctive use of antidepressants is a common approach to treatment of bipolar depression. A systematic review and meta-analysis of five acute, randomized, double-blind controlled trials (n ¼ 779) compared the use of antidepressants or placebo as adjuncts to a mood-stabilizer in patients with bipolar disorder and a current depressive or mixed episode. The Gijsman et al. concluded that antidepressants were a more effective adjunctive therapy than placebo, and moreover, were not associated with a higher incidence of switching to mania [46].

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In some contrast to the Gijsman analysis, the long-term use of adjunctive antidepressants in patients with bipolar I or II depression was evaluated in a large, 26-week, doubleblind, randomized, placebo-controlled study (STEP-BD). The primary outcome was durable recovery, defined as euthymia for at least 8 consecutive weeks. Adjunctive treatment with paroxetine or bupropion did not significantly increase the rate of durable recovery compared with the use of mood-stabilizers alone (23.5 and 27.3%, respectively; p ¼ 0.4). Notably, the rate of treatment-emergent affective switch in the two groups was not significantly different [47].

Imipramine and paroxetine A double-blind, randomized, placebo-controlled study investigated the use of adjunctive antidepressants in patients with bipolar I depression. Nemeroff et al. investigated the efficacy of paroxetine, imipramine or placebo in 117 outpatients stabilized on lithium therapy. Patients were randomized to receive paroxetine (mean dose, 32.6 mg/day), imipramine (mean dose, 166.7 mg/day) or placebo for 10 weeks [48]. Mean changes in HAM-D and CGI-S total score from baseline to Week 10 in the paroxetine and imipramine groups were no different to those in the placebo group. However, in the patients with subtherapeutic plasma lithium concentrations, paroxetine, but not imipramine, was effective. Imipramine, but not paroxetine, was associated with an increased switch rate into mania. Interestingly, in a smaller previous study of 27 patients with bipolar depression treated with lithium or valproate, paroxetine augmentation was equally effective to treatment with the two mood stabilizers [49]. The long-term efficacy of imipramine and lithium for the prevention of affective episodes in patients with bipolar disorder was investigated in a two-year, randomized, placebo-controlled study [20]. Imipramine had no effect on the number of depressive episodes experienced compared with placebo. Furthermore, there was no evidence of a protective effect against episodes of mania with imipramine, with 83, 67 and 12% of patients experiencing a manic episode during the last 20 months of the study with placebo, imipramine and lithium, respectively.

Fluoxetine Evidence for the use of fluoxetine as monotherapy for the acute treatment of bipolar depression is provided by the results of a 6-week, double-blind study that compared the efficacy of fluoxetine and imipramine with placebo [50]. Patients with bipolar depression (n ¼ 89) were randomized to fluoxetine (20–80 mg/day, n ¼ 30), imipramine (75–300 mg/ day, n ¼ 30) or placebo (n ¼ 29) for six weeks, with 22 patients receiving concomitant lithium during the study. Fluoxetine and imipramine were both associated with significant

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improvement in MADRS total score from baseline to Week 6 (p < 0.05 for both treatments) compared with placebo [50]. Furthermore, fluoxetine significantly improved CGI-S score at Week 6 compared with imipramine (p < 0.05).

Sertraline, bupropion and venlafaxine The efficacy of sertraline, bupropion and venlafaxine as adjunctive treatment to mood-stabilizers was investigated in a 10-week, randomized, flexible-dose trial in patients with bipolar I depression. All three antidepressant treatments were associated with comparable levels of acute response (49, 51, and 53% for bupropion, venlafaxine, and sertraline, respectively; defined as a 50% improvement in Inventory of Depressive Symptomatology (IDS) score or a decrease in Clinical Global Impression-Bipolar Disorder [CGI-BP] score of 2) and remission (34, 36, and 41% for venlafaxine, sertraline and bupropion, respectively; defined as either an IDS score 12 or CGI-BP score of 1); however, venlafaxine was associated with a significantly increased risk of switching to hypomania or mania compared with both sertraline and bupropion (29, 9, and 10%, respectively; p ¼ 0.01 venlafaxine vs. sertraline; p < 0.01 venlafaxine vs. bupropion) [51]. However, given that there was no placebo group in this study, it is not possible to determine if switch rates in the sertraline and bupropion groups were similar to what might be expected over the natural course of the disorder. Vieta et al. [52] randomized patients with bipolar I (n ¼ 44) or bipolar II (n ¼ 16) depression in a 6-week trial to augmentation with paroxetine (mean dose 32 mg/day) or venlafaxine (mean dose 179 mg/ day). The response rates were equivalent (43–48%) but the switch rate into mania was 4-fold greater in the venlafaxine group. Open studies suggested both efficacy and low switch rates with bupropion. Sachs et al. [53] reported that bupropion and imipramine exhibited equal efficacy to imipramine in the treatment of bipolar depression with low switch rates with the former agent, and Fogelson et al. [54] noted a greater than 50% switch rate with this agent.

Monamine oxidase inhibitors (MAOIs) Because the phenomenology of bipolar depression closely resembles that of an atypical depression, for example, hypersomnia, fatigue and reverse diurnal mood variation, and because MAOIs are usually effective in the treatment of atypical depression, many clinicians frequently prescribe MAOIs for the treatment refractory bipolar depression. Himmelhoch et al. [55,56] and Thase et al. [57] demonstrated the superiority of tranylcypromine over imipramine in the treatment of bipolar depression. Clearly, more double-blind controlled studies are needed in this area.

Modafinil Evidence from a recently published double-blind, placebocontrolled, randomized study showed that adjunctive modafinil is potentially an efficacious treatment for patients with bipolar I depression who respond inadequately to monotherapy with a mood stabilizer [58]. In this study, patients with bipolar I (n ¼ 64) or bipolar II (n ¼ 21) depression were randomized to receive modafinil (200 mg/day) or placebo in combination with a mood stabilizer for 6 weeks. At study endpoint, significant reductions in IDS score (p ¼ 0.047, effect size 0.47) and the CGI-BP depression severity item (p ¼ 0.009, effect size 0.63) were seen in the modafinil group compared with placebo. Furthermore, response (>50% improvement in IDS total score) and remission (final IDS total score <12) rates were significantly higher in the modafinil group compared with placebo (43.9 vs. 22.7% [p < 0.05] and 39 vs. 18%, [p ¼ 0.033], respectively) [58].

Pramipexole A 6-week, randomized, placebo-controlled trial investigated the efficacy of pramipexole monotherapy (up to 5 mg/ day) in patients with treatment-resistant bipolar I (n ¼ 15) and bipolar II depression (n ¼ 7). The primary endpoint was response to treatment, defined as >50% reduction in HAMD total score. Overall, 67% of patients who received pramipexole responded to treatment compared with 20% of patients who received placebo (p < 0.05). The change in mean HAM-D scores was greater (p ¼ 0.05) for pramipexole (48%) compared with placebo (21%). Pramipexole also significantly improved mean CGI-S score from baseline to Week 6 compared with placebo (2.4 and 0.30, respectively; p ¼ 0.01) [59].

Mifepristone A recent Cochrane systematic review has found some evidence supporting the use of glucocorticoid antagonists in the treatment of mood disorders [60]. Of these, the glucocorticoid receptor antagonist Mifepristone has the best, albeit extremely preliminary, evidence in bipolar depression. Improvements in mood and neurocognitive function were reported in a small proof of concept study in bipolar depression [61], effects that were not replicated in a similar study in schizophrenia [62]. A larger study is currently underway. Mifepristone has relatively persistent effects on cortisol levels in these patients, which raises the possibility of similarly persistent beneficial effects on mood and cognition [63].

Ethyl-eicosapentaenoic acid The efficacy of adjunctive ethyl-eicosapentaenoic acid (EPA) [1 and 2 g/day] was evaluated in a 12-week randomized,

Pharmacological Treatment of Bipolar Depression

double-blind, placebo-controlled study in 65 patients with bipolar I depression. Both doses of adjunctive EPA (combined data) significantly improved both HAM-D (3.3 points, 95% CI ¼ 6.1 to 0.2; p < 0.05; effect size 0.34) and CGI (0.79 points, 95% CI ¼ 1.27 to 0.25; p < 0.05) scores compared with placebo from baseline to the end of the study [64].

Aripiprazole Aripiprazole is classified as an atypical antipsychotic drug because of its efficacy as a monotherapy in schizophrenia and bipolar mania and lack of extrapyramidal side effects. It possesses relatively novel pharmacological properties, including partial agonism at dopamine D2/D3 receptor as well as full agonism at 5HTIA receptors. An analysis of two, identically designed, 8-week, randomized, double-blind, placebo-controlled studies in patients with bipolar I depression found that aripiprazole (flexible dose 5–30 mg/day) demonstrated a rapid onset of action (from Week 1) with significant reductions in MADRS total score compared with placebo. However, this effect was lost in the final two weeks of the trials [65]. Subsequent analysis of data from the two trials suggests that the aripiprazole doses used were not adequately determined in advance leading to high patient withdrawal, which likely contributed to the loss of statistical significance towards the end of the trials [65]. Aripiprazole has demonstrable efficacy as an adjunctive treatment to antidepressants in unipolar depression [66,67].

Pharmacological treatment of bipolar II depression In contrast to the considerable clinical data available regarding potential treatments for bipolar I depression, there is a relative dearth of clinical evidence from studies in patients with bipolar II depression [68]. This lack of clinical evidence may be a consequence of bipolar I disorder being regarded as a more severe form of illness than bipolar II depression, particularly regarding length and severity of individual depressive episodes [69–71]; however, this view may be ill-founded as patients with bipolar II disorder experience a greater frequency of episodes and a longer overall time spent in depression [70,72]. It may also be related to the lack of recognition of this subtype in the community by both patients and clinicians.

Quetiapine The efficacy of quetiapine monotherapy (300 and 600 mg/ day) for the acute treatment of patients with bipolar II depression was evaluated as part of two 8-week, randomized, double-blind, placebo-controlled studies [37,38]. In the

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bipolar II subgroup in the first study (n ¼ 182), quetiapine monotherapy was associated with a statistically significant improvement in mean MADRS total score at most assessments during the study, compared with placebo. However, the difference in MADRS total score was not significant at final assessment (Week 8) with either dose of quetiapine compared with placebo. Effect sizes were 0.39 for quetiapine 600 mg/day and 0.28 for quetiapine 300 mg/day [37]. In the second study, a significant improvement in mean MADRS total score compared with placebo was sustained from Week 1 to final assessment with quetiapine 300 mg/ day (p  0.05) and from Week 3 to final assessment with quetiapine 600 mg/day (p  0.05) in the bipolar II subgroup (n ¼ 152) [38]. A post hoc analysis of pooled data from both studies of bipolar II depression has recently been published. Quetiapine monotherapy significantly improved mean MADRS total score from the first assessment (Week 1) and at each subsequent assessment [73]. At Week 8, mean change from baseline in MADRS total score was 17.1 for quetiapine 300 mg/day (p < 0.01) and 17.9 for quetiapine 600 mg/day (p < 0.01) compared with 13.3 for placebo. Effect sizes were calculated as 0.54 for quetiapine 600 mg/day and 0.45 for quetiapine 300 mg/day. Additional data regarding the use of quetiapine for the acute treatment of bipolar II depression derive from a randomized, placebo-controlled study that evaluated the acute (eight weeks) use of quetiapine monotherapy (300 mg/day and 600 mg/day) in this patient group (n ¼ 252) [39]. At the end of the study the investigators reported a mean change in MADRS total score of 16.5 points for quetiapine 300 mg/ day, 16.3 points for quetiapine 600 mg/day, and 11.53 points for placebo. Differences in mean MADRS total score were significant for quetiapine 300 mg/day vs. placebo (95% CI ¼ 7.93 to 1.67; p < 0.05) and for quetiapine 600 mg/day vs. placebo (95% CI ¼ 8.10 to 1.85; p < 0.05). Evidence for the long-term use of quetiapine monotherapy in the treatment of bipolar II depression derives from the 26–52 week continuation phases of the Young et al. [18] and McElroy et al. [39] studies. Quetiapine significantly increased the time to recurrence of depression compared with placebo during the continuation phases of both studies in patients with bipolar I or bipolar II depression.

Pramipexole A very small six-week, double-blind, placebo-controlled study investigated the efficacy of pramipexole (up to 4.5 mg/day) in patients with bipolar II depression (n ¼ 10). The results of the study revealed a significant treatment effect with pramipexole, as shown by an improvement in total MADRS compared with placebo at Week 6 (p ¼ 0.03, 95% CI ¼ 0.104 to 2.27). Furthermore, response (defined as a >50% decrease in MADRS score from baseline) was

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experienced by 60% of patients in the pramipexole group compared with 9% in the placebo group (p ¼ 0.02) [74].

Antidepressants Another very small, nine-month, randomized, placebo-controlled, cross-over study reported significant improvement in depression severity, measured by HAM-D score and percentage of days impaired (effect sizes 1.07 and 0.85, respectively; p < 0.05), in patients with bipolar II disorder (n ¼ 10) receiving selective serotonin reuptake inhibitor (SSRI) monotherapy compared with placebo [75]. However, this study needs to be replicated in a larger sample before any conclusions regarding the efficacy of SSRIs in patients with bipolar II depression can be drawn.

Rapid cyclers Divalproex and lithium A 20-month, double-blind, parallel-group study, comparing the efficacy of divalproex and lithium for the long-term treatment of rapid-cycling bipolar disorder, has been conducted [76]. Following a 6-month, acute stabilization phase, during which patients received open-label lithium and divalproex in combination, 60 patients were randomized to receive lithium monotherapy (mean dose 1359 mg/day) or divalproex monotherapy (mean dose 1571 mg/day) for up to 20 months. No statistically significant difference between the lithium and divalproex groups was observed for the primary efficacy measure of time to treatment for a mood episode.

Lamotrigine The use of lamotrigine as a maintenance treatment in rapid-cycling bipolar disorder was investigated in a doubleblind, placebo-controlled, prophylaxis study [77]. Patients (n ¼ 324) received lamotrigine or placebo as monotherapy for six months following a preliminary, open-label stabilization phase. The primary efficacy measure was time to additional pharmacotherapy for emerging mood symptoms. No significant difference between the lamotrigine and placebo groups with respect to the primary measure was observed. However, lamotrigine was associated with a significantly greater time to premature discontinuation compared with placebo (p < 0.05). Furthermore, significantly more patients receiving lamotrigine (41%) were stable without relapse for the duration of the study compared with placebo (26%; p < 0.05) [77].

Quetiapine Evidence for the use of quetiapine monotherapy in patients with a rapid cycling disease course has been provided by a

sub-analysis of an eight-week, randomized, double-blind, placebo-controlled study [37]. Quetiapine (600 and 300 mg/ day) provided significantly greater mean reductions from baseline to Week 8 in MADRS total score than placebo (p < 0.001 for both doses) in patients with a rapid cycling disease course [78].

Antidepressants A 10-week, randomized, flexible-dose study evaluating sertraline, bupropion and venlafaxine as adjuncts to mood stabilizers investigated the impact of a patient’s rapid cycling status on the relative risk of switching into mania or hypomania [51]. In patients without rapid cycling, the risk of switching was no different with the three study medications (p ¼ 0.55); however, in patients with a rapid cycling disease course, bupropion was associated with a significantly lower risk of switching than venlafaxine (p < 0.01).

Miscellaneous High doses of thyroxine have been shown to have efficacy in rapid-cycling bipolar disorder [79]. Open studies suggest the efficacy of clozapine in treatment–refractory rapid cyclers [80,81].

Clinical recommendations From the preceding discussion it is clear that a number of key principles emerge to guide the clinician, although as ever in psychiatry we must retain the right for the individual clinician to exercise their judgement as to the best practice for any particular scenario. However, it is clear that depression is a frequent and damaging part of the lives of patients with bipolar disorder. Clinicians must be aware of this and examine all patients for depression most carefully. Furthermore, awareness of bipolar depression should be highlighted in educational materials both for the patient, family members and health care professionals. A number of evidence based treatments are now available and treatments with good supporting evidence should be prioritized over those with less, or in some cases no, supporting research evidence. The evidence base will be briefly discussed below; however, it is clearly in the interests of all (patients, families and clinicians) to support further work to strengthen the research upon which good clinical practice is based.

Conclusions Bipolar depression is a common and disabling condition with highly significant attendant costs to the patient, their families and society. Increasing evidence is available to support the efficacy of certain pharmacological agents for this mood disorder. Of these, lithium is the most venerable.

Pharmacological Treatment of Bipolar Depression

However, the evidence supporting lithium’s use (at least as monotherapy) is not strong and important negative studies have recently been reported. Although antidepressant drugs have long been used in bipolar depression, the evidence of their efficacy is not as robust as we would like, and some recent studies have been negative. However, recent large studies do support the use of some drugs, including lamotrigine and quetiapine. Much further research is needed. Larger trials could examine the efficacy of older agents, such as valproate, as well as newer agents, for example mifepristone and proof of concept studies may usher in newer agents yet. The requirement for efficacious drugs for bipolar depression is unlikely to lessen in the near future and clinicians who treat this disorder should be aware of the current evidence in order to facilitate the best clinical practice.

Financial disclosures Dr. Young has received honoraria from pharmaceutical companies, including AstraZeneca, for lecturing on this topic and has also received grant support from AstraZeneca. Dr Nemeroff serves on the Scientific Advisory Board for the American Foundation for Suicide Prevention; AstraZeneca; NARSAD, PharmaNeuroboost and CeNeRx. He serves on the Board of Directors of American Foundation for Suicide Prevention; George West Mental Health Foundation; NovaDel Pharma, Mt Cook Pharma, Inc. He owns equity or is stock holder in Corcept; Revaax; NovaDel Pharma; CeNeRx, PharmaNeuroboost, Mt Cook Pharma. He is inventor on the following patents: method and devices for transdermal delivery of lithium (US 6,375,990 B1) and method to estimate serotonin and norepinephrine transporter occupancy after drug treatment using patient or animal serum (provisional filing April, 2001).

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38. Thase, M.E., Macfadden, W., Weisler, R.H. et al. (2006) Efficacy of quetiapine monotherapy in bipolar I and II depression: a double-blind, placebo-controlled study (the BOLDER II study). J. Clin. Psychopharmacol., 26, 600–609. 39. McElroy, S., Young, A.H., Carlsson, A. et al. (2008) Doubleblind, randomized, placebo-controlled study of quetiapine and paroxetine in adults with bipolar depression (EMBOLDEN II). Poster presented at the International Society for Bipolar Disorders, Delhi and Agra, India, 27–30 January, 2008. 40. Suppes, T., Liu, S., Paulsson, B. and Brecher, M. (2007) Maintenance treatment in bipolar I disorder with quetiapine concomitant with lithium or divalproex: a North American placebo-controlled, randomized multicenter trial. Poster presented at the 46th Annual Meeting of the American College of Neuropsychopharmacology, Boca Raton, Florida, USA, 9–13 December, 2007. 41. Vieta, E., Eggens, I., Persson, I. et al. (2007) Efficacy and safety of quetiapine in combination with lithium or divalproex as maintenance treatment for bipolar I disorder. Poster presented at the 20th European College of Neuropsychopharmacology Congress, Vienna, Austria, 13–17 October, 2007. 42. Brown, E.B., McElroy, S.L., Keck, P.E. Jr et al. (2006) A 7-week, randomized, double-blind trial of olanzapine/fluoxetine combination versus lamotrigine in the treatment of bipolar I depression. J. Clin. Psychiatry, 67, 1025–1033. 43. Tohen, M., Sanger, T.M., McElroy, S.L. et al. (1999) Olanzapine versus placebo in the treatment of acute mania. Am. J. Psychiatry, 156, 702–709. 44. Keck, P.E. Jr, Corya, S.A., Altshuler, L.L. et al. (2005) Analyses of treatment-emergent mania with olanzapine/fluoxetine combination in the treatment of bipolar depression. J. Clin. Psychiatry, 66, 611–616. 45. Brown, E.B., Dunner, D.L., Adams, D.H. et al. (2006) Olanzapine/fluoxetine combination versus lamotrigine in the longterm treatment of bipolar I depression. Poster presented at the 2nd Biennial Conference of the International Society for Bipolar Disorders, Edinburgh, UK, 2–4 August, 2006. 46. Gijsman, H.J., Geddes, J.R., Rendell, J.M. et al. (2004) Antidepressants for bipolar depression: a systematic review of randomized, controlled trials. Am. J. Psychiatry, 161, 1537–1547. 47. Sachs, G.S., Nierenberg, A., Calabrese, J.R. et al. (2007) Effectiveness of adjunctive antidepressant treatment for bipolar depression. N. Engl. J. Med., 356, 1711–1722. 48. Nemeroff, C.B., Evans, D.L., Gyulai, L. et al. (2001) Doubleblind, placebo-controlled comparison of imipramine and paroxetine in the treatment of bipolar depression. Am. J. Psychiatry, 158, 906–912. 49. Young, L.T., Joffe, R.T., Robb, J.C. et al. (2000) Double-blind comparison of addition of a second mood stabilizer versus an antidepressant to an initial mood stabilizer for treatment of patients with bipolar depression. Am. J. Psychiatry, 157, 124–126. 50. Cohn, J.B., Collins, G., Ashbrook, E. and Wernicke, J.F. (1989) A comparison of fluoxetine imipramine and placebo in patients with bipolar depressive disorder. Int. Clin. Psychopharmacol., 4, 313–322. 51. Post, R.M., Altshuler, L.L., Leverich, G.S. et al. (2006) Mood switch in bipolar depression: comparison of adjunctive venlafaxine, bupropion and sertraline. Br. J. Psychiatry, 189, 124–131.

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Practical Pharmacological Maintenance Treatment of Bipolar Disorder Alan C. Swann Department of Psychiatry and Behavioral Sciences, The University of Texas Health Science Center at Houston, Houston TX, USA

Introduction Bipolar disorder is treatable, but we do not yet have curative treatments or effective measures for primary prevention. Therefore, successful maintenance treatment is the goal in bipolar disorder. Every episode prevented improves the subsequent course of illness [1] and reduces its cost [2]. We will discuss maintenance treatment in terms of the critical assessment and practical application of research findings. Our focus will be on pharmacological treatments, as nonpharmacological treatments are addressed in another chapter, but we will also address factors related to integration of pharmacological and nonpharmacological strategies.

Goals of long-term treatment What should we expect from successful treatment of a severe, life-long illness? Lack of severe symptomatic exacerbations of illness is necessary for successful maintenance treatment. Lack of episodes is, however, not sufficient for successful maintenance or optimization of quality and productivity of life [3]; yet some individuals can have impressive accomplishments and rewards despite recurrent episodes of illness [4]. Subsyndromal symptoms can be harbingers of episodes, or can be problematic in their own right [5]. Cognitive impairment may combine persistent features of bipolar disorder regardless of symptomatic status with state-dependent exacerbations in specific areas, and are potentially useful, but underused, measures of outcome [6]. Comorbidities like substance-use disorders can worsen the course of bipolar disorder and cause serious impairment in their own right [7]. Existence of social supports and rewarding employment can be considered desirable outcomes of treatment, and also can be viewed as part of a treatment strategy since they predict prolonged stability [8]. Table 1 summarizes elements of successful long-term Bipolar Disorder: Clinical and Neurobiological Foundations Edited by Lakshmi N. Yatham and Mario Maj © 2010 John Wiley & Sons, Ltd. ISBN: 978-0-470-72198-8

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treatment. Goals and means for attaining the goals interact and are interdependent. These goals are only partially related to the objectives of most treatment studies.

Adherence to and participation in treatment No matter how strong the evidence supporting a treatment is, it only works if the patient takes it. Promoting responsible participation in treatment is therefore necessary for successful maintenance pharmacotherapy. Proper monitoring of clinical state and pharmacological treatment can provide the basis for a structure, encompassing education, peer support and caregiver support, underlying responsible participation [9]. Patients commonly do not take moodstabilizing medicines [10]. While side effects and weight gain are important components of this, and important health considerations in their own right, the main reasons that patients do not take their medicine have more to do with their attitude towards and understanding of the illness and its treatment [10,11]. Interestingly, the reasons that patients gave for not taking medicine (most strongly related to their understanding of and attitude towards their illness) were quite different from the reasons assumed by their clinicians [11]. This shows how important communication and education are. The association between noncompliance and suicide highlights both the lack of opportunity for medicine to work, and failure of communication [12].

Nature of evidence: relationship to the goals of treatment Goals and outcomes We will be reviewing psychopharmacological data using diverse study designs and outcomes. Most controlled pharmacological trials focus primarily on prevention of episodes [13]. A few studies have addressed treatment effects on subsyndromal symptoms; fewer have addressed effects on cognitive function or socioeconomic outcomes.

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Table 1 Successful long-term treatment. Goal

Some mechanisms

Prevent episodes and symptoms

Primary: pharmacological Secondary: specific nonpharmacological treatments; pharmacological and nonpharmacological treatment of substance use disorders and other associated conditions; education and support of patient, caregivers and other key individuals; structure; optimization of physical health; finding the means to assure availability of treatment; treatment of concurrent illnesses Education of patient and key individuals; social skills learning; development of social networks Control of symptoms and impairments; social networking; education Judicious, yet complete, treatment of episodes and symptoms; healthy habits including exercise and protection of social and activity/sleep rhythms; someday, specific treatments Judicious psychopharmacological choices; comprehensive treatment of other medical problems; healthy habits including exercise and protection of social and activity/sleep rhythms

Enhance social adaptation Enhance occupational function Optimize cognitive function Optimize overall health

Subjects in studies Study results must be viewed in terms of their generalizability to practice. Who were the participants in the study [14,15]? Randomized trials are, by necessity, generally conducted in restricted groups. Table 2 summarizes common subject exclusions in randomized trials. These restrictions are often necessary in order to conduct trials safely and to obtain results that are interpretable. Yet they can influence responses to, and toleration of, the treatments being studied. The manner in which these criteria are applied varies across studies. We must take them into account by combining data from conventional randomized trials with other types of evidence from less restricted groups or treatment studies for the problem leading to exclusion.

Design of treatment studies Certain questions must be asked in evaluating any treatment study. Table 3 summarizes factors pertaining to the

antecedents of a subject’s participation in a study: characteristics of the subject’s course of illness, the subject’s state on entering the study and the subject’s recent and past pharmacological and nonpharmacological treatments and responsiveness [13]. To what extent can we generalize this study to our practice? How can these factors affect outcome? Factors to keep in mind include: . Polarity of index episode: There appear to be depressionprone and mania-prone forms of bipolar disorder, with potentially different courses of illness and other clinical characteristics [16]. Depression-prone patients may have a more unstable course of illness [17]. Clinical characteristics of subjects in studies of recently depressed or recently manic subjects may differ, leading to potentially different patterns of treatment response [18]. Placebo responses appeared to differ between recently depressed and recently manic in one of the few pairs of comparable studies where both were investigated [19,20]. A true prophylaxis study would begin at a time when there was no recent index

Table 2 Common exclusions from clinical trials. Exclusion

Rationale

Problem

Concurrent psychiatric diagnoses, especially substance-related

Interactions with treatment drugs; difficulty in determining what is causing symptoms and symptomatic changes; safety

Concurrent medical illness

Pharmacological interactions with study drugs; difficulty in determining causation of symptoms and changes; safety

Severity of illness

Safety; severely ill patients may be less likely to have the capacity to give informed consent

Previous treatment with study drugs

May bias outcome; safety – either because subject does not tolerate drug, or should not be randomized when an effective treatment is known

Most patients with bipolar disorder have a substance use and/or anxiety disorder; these are associated with worse outcomes [7,288] Many patients with bipolar disorder have other medical illnesses, some of which may be more common in bipolar disorder, or related to treatment toxicities [289–291] Questions of generalizability to severely ill patients, who need effective, evidence-based treatment As the number of available treatments increases, the pool and generalizability of the subject pool decreases

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Table 3 Practical design considerations in clinical trials: subject characteristics. Characteristic

Rationale

Course of illness: frequency and dominant polarity [16] Features of index episode [18] What happened before time zero? Treatment and response in index episode [13]

May influence response to specific treatments, characteristics of most likely recurrence, and potential frequency of recurrent episodes May influence effectiveness of treatments and characteristics of recurrence Effects of treatment withdrawals or dose changes before randomization; effects of responses to specific treatments, including enrichment of sample with responders to a specific treatment

episode, removing potential effects of residual symptoms or relapse into episodes that were not fully treated [13]. However, not all patients are able to enter suitable stable periods; those who do might not be amenable to the risks of entering a controlled treatment trial, and relapses/recurrences under these conditions would be less frequent, requiring more subject-years to obtain statistically usable results. . Course of illness: Bipolar disorder can vary widely in terms of the frequency of episodes and the severity of complications, such as substance-use or anxiety disorders. There is some evidence for two basic, possibly heritable, forms of the illness, where one (‘episodic-stable’) has potentially severe episodes, but the episodes are relatively infrequent, prevalence of comorbidities is relatively low and response to lithium may be relatively strong. The other more inherently unstable group may be more prone to frequent episodes, mixed states, complications like substance abuse and lithium resistance [21]. Therefore, number or frequency of previous episodes, or age of onset, can influence responses to treatments. Current data suggest that a history of many previous episodes is associated with poor response to lithium [22–25]; there is little evidence with other treatments. In terms of overall psychosocial impairment, a large number of previous episodes predicts impairment regardless of severity of an individual episode [26], confirming Kraepelin’s original observation [27]. . Previous responses to treatments: This may overlap with course of illness [21]. As more treatments become available, it is harder to find clinically typical cohorts of patients who are not:(1) atypically refractory to treatment; or (2) so mildly ill that the impact of previous treatments were small enough that they are willing to give them up to enter a randomized clinical trial. Furthermore, most new drugs resemble drugs that are already in use, and that potential subjects may have already responded or nonresponded to, potentially distorting results. This situation is ameliorated by the fact that, even for patients who are technically episode-free, current treatment outcomes still leave a lot to be desired [28].

Relevant properties of the trial itself Again, there is a complementarity between reliability or robustness of outcome measures, and generalizability to practice. General factors to consider include: . Treatment of the index episode: There are two basic alternate design strategies. In one, (‘enriched’ designs) subjects are stabilized on the drug of interest, then randomized to receive that drug or comparators. This strategy is considered less general than the alternative, since it is limited to the subgroup of patients who have responded to a specific treatment, but is closer to clinical practice, since it is certainly more coherent to continue to treat a patient with a drug that was initially effective than to switch to something else [14]. The second is a design where randomization is independent of previous treatment. This design is more general, at least in an abstract way, but is less like clinical practice and is more likely to produce negative or failed studies [13]. . Speed of cross-over to randomized treatment: Withdrawal of a successful or partially successful treatment that is more rapid than two to four weeks is associated with increased likelihood of relapse [29,30]. This appears to hold for lithium and for other mood-stabilizing treatments [31]. . Nature of comparator treatments: Placebo-controlled trials are considered the strongest evidence that a drug works, but their implementation and design are challenging, especially in maintenance studies [32]. Placebocontrolled trials have larger effect sizes and therefore need fewer subject-years to achieve statistically significant results, positive or negative. However, they have disadvantages in terms of generalizability: More severely ill subjects cannot enter placebo-controlled trials and there is published evidence that subjects of placebo-controlled trials differ clinically from subjects in trials with active comparators, and that placebo responders differ clinically and demographically from non-responders [32]. However, studies with active comparators require considerably more subject-years than placebo-controlled trials. . Study duration: A maintenance treatment study needs to be long enough to determine that recurrent episodes

Maintenance Treatment

were actually prevented by the treatments under study. Duration of published studies ranges from a few months to two years. If there is an index episode, six months is arguably inadequate time to distinguish prevention of new episodes from prevention of re-emergence of the index episode [13]. The frequency of relapse/recurrence correlates with previous episode frequency [33]. A true prophylaxis study without an index episode could presumably be conducted for a shorter time, but would require more subjects in order to obtain an adequate number of new episodes for meaningful comparisons between treatments. . Study endpoint: The endpoint of a study can range from the need to add an additional treatment to emergence of a new episode of illness. Furthermore, some studies continue after the primary endpoint, and others do not. This can distort data about relapse. For example, many studies stopped after the first relapse, which was usually manic because of the study design, thereby constraining evidence on effectiveness in preventing depressive relapse [13,34]. Designs based on time to episode or percent remaining will have the further disadvantage that information from subjects who withdrew for other reasons is lost [35]. Combining dropout from intolerance or adverse events with dropout from episodes may provide a measure closer to the true effectiveness of a drug. Table 4 summarizes different study endpoints and manners of expressing study outcomes [13]. They vary in their clinical interpretability:

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. Time until a new episode is a common endpoint. This is certainly highly relevant, but has limitations because, in a recurrent illness, the timing of a single episode may not reflect overall clinical outcome, including frequency of future episodes, over time [36]. As with all episode-based measures, this measure does not account for the substantial symptoms and impairment that can exist in the absence of a full episode. . A variant of this is time to first intervention, which is more sensitive than time to a syndromal episode. Results of studies using this method may have limited generalizability to realistic practice. Bipolar disorder is a lifelong illness. If a drug differs from placebo, as may be the case for lamotrigine, by having a few more weeks or even months before a new treatment is added – but for most patients a new treatment must be added sooner or later – might it be better just to start with two treatments, or to attempt to identify, in advance, indicators of whether or when the second treatment will be needed? . Some studies, but generally not large randomized clinical trials, have used integrated symptom measures, such as number or fraction of days symptomatic. This underscores the importance of subsyndromal symptoms and of clinical effects over time, but may underestimate the impact of severe episodes [37]. This metric has been used more in descriptive longitudinal studies than in prospective treatment evaluations [38]. . Older studies compared percentage of subjects remaining episode-free over a given period. This measure loses

Table 4 Metrics for evaluating and comparing treatments. Method

Advantages

Disadvantages

Examples

Percent episode free

The most stringent

Time to episode

Accessible; provides data on % episode free

No information about how long the average subject remains stable Defining an episode; no information about course after the episode

Time to intervention

Clinically realistic measure of need for further treatments

Lithium [231,292,293]; often a secondary measure Lithium [212]; valproate [212]; aripiprazole [294]; olanzapine [258] Lamotrigine; lithium [19,20]

Integrated severity

May overestimate recurrences; hard to control variance amongst treaters; no information about course after the intervention Misses information about the most severe aspects of the illness

Measure of real symptom severity Naturalistic [37,38] over time; addresses subsyndromal symptoms Reasons for dropout are heterogeneous Reported in most studies, Percent completing the study A rough measure of effectiveness, though rarely the and often based on case-by-case since most dropouts are due primary endpoint decisions to poor clinical response and/or poor tolerability Number needed to treat Estimates the probability that Artificially separates drug and placebo [6] a subject will benefit effects, which clinically are inseparable

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information about how long patients were actually able to remain stable, subsyndromal symptoms, what happened after the first recurrence, and realistic psychosocial impairment. . Finally, rather than, or in addition to, comparing durations of stability or percentages of subjects who remain free of episodes, some more modern studies evaluate the number needed to treat, an estimate based on the relative probability of a subject having a certain outcome [6]. An advantage of this measure is that it is portable across any outcome measure [39]. A problem is that the number needed to treat to obtain benefit versus placebo is misleading, because it assumes that one could actually dissect out the components of improvement due to placebo or active treatment, when treatment with placebo is clinically impossible.

Transition to maintenance treatment One of the most crucial aspects of long-term treatment in bipolar disorder (or any similar illness) is the transition between the acute episode and long-term treatment. Successful acute treatment substantially reduces symptomatic impairment in a matter of weeks, with initial improvement even in the first week. However, functional impairment persists for months or even for years. This transitional period, when symptoms are improved but functional impairment persists, is a critical time for most patients, as during this period there is increased pressure to function and decreased support and monitoring [40]. Documented consequences include the relatively high risk for suicide after depression [41] or arrest following mania [42] during the months after an episode.

Transition to maintenance: pharmacological management Most treatment guidelines, to the extent that they address this aspect of treatment, recommend continuing whatever treatment was effective for the acute episode [43–45]. Therefore, when initial treatments are selected or when treatments are added due to breakthrough symptoms, careful thought must be given to balancing short-term effectiveness with long-term tolerability, safety and practicality. In addition to the primary treatment, this may also hold for important supplementary treatments such as antidepressive or antipsychotic treatments. Strategies described here for the transition to maintenance treatment are also relevant for management of subsyndromal or prodromal symptoms.

After a manic episode Most evidence that rapid discontinuation of successful antimanic treatments is associated with relapse at any time during treatment is from retrospective or uncontrolled

studies [31,46]. One large randomized, placebo-controlled study demonstrated that this was the case for the period after an acute manic episode [47]. Subjects who had entered remission for an acute manic episode with a combination of olanzapine and lithium or valproate were randomized to continue on combined treatment or to have the olanzapine, which had generally been added because of inadequate response, discontinued and replaced by placebo. Subjects with olanzapine discontinued had a more rapid rate of relapse to mania. About half of subjects with olanzapine discontinuation relapsed over the first two to three months of treatment. For the remaining subjects, the survival curve was parallel to that for subjects for whom combined treatment was continued. This suggests that relatively rapid discontinuation of the added olanzapine was associated with rapid, withdrawal-like relapse in about half of the subjects, while the subjects who did not suffer this early relapse had a long-term course that was similar to subjects on combined treatment. These results strongly support the idea that, if a second treatment was needed to resolve a manic episode, this treatment should be continued for at least a few months, and then tapered slowly (if at all). Several continuation treatment studies have addressed continued improvement over 10–12 weeks after a manic episode. Subjects randomized to have risperidone or haloperidol added to lithium or valproate had better outcome 10 weeks later [48]. Of 156 original subjects, 85 entered the continuation study and only 48 finished it. Lithium and quetiapine both maintained effectiveness over a 12-week period; 72/107 subjects on quetiapine and 67/98 subjects on lithium completed the study [49]. In a similar study, lithium and haloperidol maintained effectiveness for 12 weeks [50]. Of the treatments in these studies, risperidone, haloperidol and quetiapine lack placebo-controlled evidence for longerterm efficacy; only lithium has such evidence.

After a depressive episode There is substantial evidence that, in randomized trials, antidepressant treatments do not have prophylactic efficacy in bipolar disorder [51]. However, results of randomized trials pertain to the average subject in a study, and may not apply to individual patients or subgroups. A minority of patients with bipolar disorder appear to require antidepressive treatments, in addition to mood-stabilizing treatments, for resolution of a depressive episode. Altshuler et al. addressed this in a prospective [52] and a retrospective [53] study. About 20% of subjects with bipolar depressive episodes, all receiving mood-stabilizing treatments, did not respond to mood-stabilizing treatments alone, had resolution of their depressive episodes with supplemental antidepressive treatment, and tolerated the treatment for at least 6 weeks. This group of subjects had increased likelihood of depressive relapse if antidepressive treatments

Maintenance Treatment

were discontinued within 6–12 months. It must be kept in mind that these subjects were not randomized to antidepressive treatment but were selected based on treatment response and course of illness. These results suggest strongly that the minority of patients who require antidepressive treatments for acute depressive episodes should have those treatments continued for at least 6–12 months if the treatments are tolerated and their use is consistent with the patient’s course of illness.

The need to treat residual symptoms Most criteria for improvement, response, or even remission leave a lot of room for subsyndromal symptoms. There is ample evidence that these symptoms must be treated. Subsyndromal symptoms predict relapse [5]. One study found that, with lithium or lamotrigine monotherapy, onset of prodromal symptoms after an episode was delayed for only a week compared to placebo, and predicted relapse into an episode of the original polarity [54]. During the period after recovery from the acute episode, it is important to institute collaborative monitoring of residual and emergent prodromal symptoms [55], and coping strategies for dealing with them [56].

Nonpharmacological considerations Nonpharmacological treatments are discussed in detail elsewhere in this volume. Strategies with key roles in the transition to maintenance include [40]: . First, this is the time when the collaborative, structured treatment relationship, necessary for successful treatment adherence and monitoring, is solidified [9]. . Collaborative monitoring for prodromes of episodes, and developing of pharmacological and nonpharmacological tactics for dealing with them [56,57], should be instituted during this period. Mood charting methods are very useful for this [58]. . This is the best opportunity to establish strategies that are related to education and support of the patient and caregivers. If the family or those close to the patient do not understand the illness and its need for treatment, successful treatment is difficult, if not impossible [59]. Increased burden to family members is related to poor understanding of the illness, more than to severity [60] and predicts poor outcome [61]. . Behavioural and cognitive strategies, either as supplements to pharmacological treatments of primary mood symptoms or as treatments for concurrent conditions, such as anxiety or substance-use disorders [62], can be instituted during this period. . Attention must be paid to adaptive function, including education, work and other aspects of the patient’s usual life role. This crucial period, when symptoms may be better but functional recovery is incomplete, is generally not the

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time for major life changes if they can be deferred until the patient is truly back on her feet [40]. . Perhaps the most cost-effective approach is caregiver group psychoeducation [63], where a randomized trial (n ¼ 113) showed that patients whose caregivers engaged in 12 psychoeducation group sessions had fewer relapses, and longer time to relapse, for manic or hypomanic episodes. This underscores the importance of educating and supporting caregivers and thereby reducing caregiver burden in bipolar disorder.

When is the transition to maintenance complete? If the patient is fortunate, the transition to maintenance is complete when s/he is able to handle the living and work situation that existed before the episode, without undue stress. This may, therefore, be far from the individual’s ideal adaptation. We know of no objective means to determine this. In the future it may be possible to identify and measure state-dependent neurocognitive impairments, thereby identifying the return to pre-episode function [64]. Once this point is reached, the individual is ready to embark on a stage of treatment aimed at maintaining and enhancing mood stability and enhancing adaptive and occupational functioning.

Maintenance treatment: evidence from controlled trials Studies have been designed to evaluate prevention of manic relapse, prevention of depressive relapse and prevention of either. The polarity of the most recent episode has an important impact on outcome [18]. First, there may be depression-prone and mania-prone courses of bipolar disorder, with different clinical and illness-course characteristics [16]. Accordingly, relapses are most commonly in the same direction as the most recent episode [18]. It can therefore be difficult to evaluate efficacy against relapse into the opposite polarity to the index episode, since those relapses may be less common, and they may go undetected in studies that end after the first relapse.

Placebo-controlled monotherapy studies Table 5 summarizes placebo-controlled relapse prevention or maintenance studies, published in the peer-reviewed literature, in which monotherapy with active drug was compared to placebo for at least 12 months. Evidence from this kind of trial is available for only five drugs: lithium, divalproex, olanzapine, aripiprazole and lamotrigine. In almost all cases, the treatment sample was enriched with acute responders to the study drug; in most cases, the index episode was manic. In terms of manic episodes, lithium, divalproex, olanzapine and aripiprazole were effective.

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Table 5 Evidence for prevention of depressive or manic episodes from placebo-controlled monotherapy studies. Drug

Study

N

Mo.

Manic

Depressive

Remarks

Lithium

[292] [293]

16 30

Prevented relapse

No effect Prevented relapse

No index episode Depressive index; enriched

[231] [231] [19]

40 bipolar II 35 bipolar I, 18 bipolar II 205 bipolar I 44 bipolar II 179 bipolar I

24 24 18

Prevented relapse Delayed recurrence

No effect Prevented relapse No effect

[20]

463 bipolar I

18

Delayed recurrence

No effect

Divalproex; lithium

[212]

372 bipolar I

12

Reduced relapse rate

Olanzapine

[258]

341 bipolar I

12

Aripiprazole

[295] [294] [19] [20]

161 bipolar I 24 bipolar I 179 bipolar I 463 bipolar I

6 Up to 24 18 18

No effect in entire sample. Reduced recurrence in enriched subsample Delayed recurrence and reduced rate Delayed recurrence Delayed recurrence No effect No effect

Manic index; enriched Depressive index; enriched Manic index; enriched for lamotrigine Depressive index; enriched for lamotrigine Manic index. Reduced rate for all episodes. Lithium arm not effective Manic index. Enriched

Lamotrigine

Delayed recurrence and reduced rate No effect No effect Delayed recurrence Delayed recurrence

Manic index; enriched Continuation of [295] Enriched; manic index Enriched; depressive index

Duration is in months. Positive effect: delayed time to new episode or reduced incidence of new episodes during study period. Enriched: index episode stabilized on study drug before randomization.

Lithium was effective even in two studies that were enriched for lamotrigine response [19,20]. Lamotrigine was ineffective in reducing manic recurrence in two studies, even though their designs were enriched for initial response to lamotrigine [19,20]. Lithium (in some studies), lamotrigine, divalproex and olanzapine were effective against depressive episodes. It should be noted that two of the negative studies with lithium were enriched for responders to lamotrigine [19,20]. Lithium was most effective against depression in subjects with index depressive episodes, but this may have resulted in part from study designs where early manic relapses occurred first and reduced the available pool of subjects for evaluation of depressive relapse prevention. Lithium, lamotrigine, divalproex and olanzapine were effective in reducing recurrent episodes in general.

Rapid-cycling Lamotrigine delayed the need for additional treatments compared to placebo in a six-month study of patients with rapid-cycling bipolar disorder [65]. Of 324 patients entering the study, 182 could be stabilized adequately, on multiple treatments including lamotrigine, to be randomized to lamotrigine or placebo. Overall, 41% of subjects randomized to lamotrigine versus 26% randomized to placebo were able to complete six months of randomized treatment without needing additional drugs. The effect of lamotrigine was significant in subjects with bipolar II disorder but not in subjects with bipolar I disorder [65].

Monotherapy studies with non-placebo comparators Amongst drugs with placebo-controlled trials, there have also been comparisons to other treatments. Olanzapine response was comparable to valproate for relapse in general in a 47-week study of subjects initially treated for mania with the study drug [66], and was better than lithium for mania and comparable to lithium for depression in a study of 431 recently manic subjects who were initially treated with both lithium and olanzapine and then had one or the other treatment replaced by placebo [67]. Many placebo-controlled studies have the disadvantage of early relapses on placebo due to withdrawal of active treatment. A meta-analysis of mirror-image studies, which do not have this disadvantage, found lithium to reduce relapse by 50% in patients with bipolar disorder [68]. There are several comparisons of lithium and carbamazepine, generally too small to detect any meaningful difference [69,70]. The largest was a prospective, randomized 2.5 year study of 171 subjects. Overall response to the two drugs did not differ significantly, though lithium appeared slightly better overall and significantly better in subjects with a ‘classical’ course [71]. Ironically, the ‘classical’ group (n ¼ 67) was substantially smaller than the ‘nonclassical’ group (n ¼ 104), and patient satisfaction was higher with carbamazepine than with lithium [72]. In a two-year randomized study of previously treatment-na€ıve subjects with at least two past episodes, lithium was slightly more effective in reducing episodes (12/44 with lithium and 21/50

Maintenance Treatment

with carbamazepine) but, after dropouts for intolerance, only 36% of subjects on lithium and 32% on carbamazepine completed the two years [73]. Denicoff et al. compared lithium, carbazepine and the combination in sequential one-year studies, where one year of monotherapy with each drug was followed by a year of combination treatment in 52 subjects [74]. Each drug alone was only modestly effective: on lithium, 31% of subjects had recurrent episodes, while 33% had marked improvement; with carbamazepine, 37% of subjects had recurrences, while 31% had marked improvement; on the combination, 24% had recurrences, while 55% had marked improvement [74]. Because the combination treatment phase came last, the results could have been biased in favour of combination treatment, since the more severely ill or nonresponsive subjects would have already dropped out.

Rapid-cycling Calabrese et al. compared lithium and divalproex in a 20month randomized study of patients with rapid-cycling, after initial stabilization on the combination [75]. Only 60 of the 254 subjects originally entering the study were able to be stabilized enough for randomization, even after combined treatment. Of the subjects who did not complete the stabilization phase, 76% had relapse/recurrence of depression (74% of episodes) or mania/hypomania/mixed (26% of episodes). The 60 subjects who could be randomized had similar response to lithium or divalproex, with roughly half of subjects having recurrent episodes; most recurrences were depression for either drug [75]. In their study of lithium and carbamazepine, Denicoff et al. found the combination to be significantly better than either alone in subjects with histories of rapid-cycling (28% marked improvement with lithium, 19% with carbamazepine and 56% with the combination) [74].

Combination studies Most patients with bipolar disorder eventually need more than one long-term treatment. The usual reasons for this are: (1) even at what is considered an optimal dose, monotherapy is not effective enough, especially for treating subsyndromal symptoms rather than producing mere ‘response’; and (2) that the patient gets some benefit from a drug, but is unable to tolerate what is considered an optimal dose. There is some evidence available in combination studies, but none were designed to answer these two questions. Instead, they are drug withdrawal studies where patients who have entered remission on a combination of a secondgeneration antipsychotic agent and lithium or valproate are randomized to continue on combined treatment or to have the second-generation antipsychotic discontinued. In this

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design, combinations of olanzapine [47] or quetiapine [76] with lithium or valproate were superior to lithium or valproate alone for prevention of new episodes, though the combinations also tended to have a greater side-effect burden, especially weight gain. As noted elsewhere in this chapter, combinations of lithium with carbamazepine appeared more effective than lithium alone in patients with rapid-cycling bipolar disorder [74]. Because lamotrigine may be most effective in depressionprone bipolar disorder, while drugs like lithium and valproate may be more effective in mania-prone illness, combinations of these treatments would appear reasonable. Interactions between lamotrigine and valproate are discussed below. Lamotrigine combined with lithium was well tolerated but appeared to have greater short-term than long-term effectiveness [77]. There are no published structured studies of lamotrigine and valproate, but their mechanisms are complementary [78] and the combination can be used safely if the lamotrigine dose is increased slowly [79]. Despite this paucity of evidence, combined treatments are usually necessary. In selecting combinations, factors are evidence that effects of mechanisms of drugs may be complementary, pharmacokinetic compatibility and toxicity.

Treatments for severe illness without evidence from randomized clinical trials Two treatments, electroconvulsive therapy and clozapine, have not been used in randomized clinical trials, but are considered to be effective treatments in patients who are not responding to more established treatments, or cannot take them.

Electroconvulsive treatment (ECT) When conventional treatments are ineffective or medically unsafe, long-term ECT treatment is sometimes used. Continuation and maintenance ECT have been studied retrospectively, using mirror designs in the same patients or parallel groups designs with comparable subjects not receiving continued ECT. ECT can be given for a few months after the index episode (continuation ECT) or can be given for a prolonged or indefinite period (maintenance ECT). ECT given every 10 days for an average of 10 weeks resulted in 1-year relapse rates of 33%, compared to 95% in a non-ECT comparison group [80]. One year of maintenance ECT, using mirror designs, reduced hospitalizations in 43 patients [81] and reduced time in hospital from 44 to 7% in 22 patients studied for 18 months [82]. Maintenance ECT was reported to be generally well tolerated. It may be underutilized in patients with treatment-refractory bipolar disorder or complicated medical illnesses [83].

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ECT in pregnancy and childbirth ECT is useful when more established treatments may be problematic, such as the first trimester of pregnancy. In general, ECT appears safe during pregnancy, including high-risk pregnancy [84]. A review of 300 reports over 50 years found 4 reports of premature labour, no reports of premature membrane rupture, and a few reports of transient but benign foetal arrythmias [85]. ECT in pregnancy is not free of risk; spontaneous abortion [86] and premature labour [87,88] have been reported.

Clozapine may also be beneficial in impulsivity and related problems. Clozapine reduced aggressive or impulsive aggressive behaviour in schizophrenia, independent of its effects on psychosis [100–102]. Clozapine may also reduce substance abuse [101]. Clozapine has been reported to reduce suicidal behaviour [103,104]. In a large prospective, randomized study of patients with schizophrenia, patients receiving clozapine had less suicidal behaviour than those receiving olanzapine, although other indices of clinical response were similar [105].

Clinical use and tolerability Treatment of mixed or manic states generally requires bilateral ECT [89]. Memory loss can occur during ECT; it is considered to be generally reversible, and to affect retention memory, unlike the usual impairment in acquisition memory associated with depression itself [90]. ECT can apparently be given with most psychotroic drugs if the ECT dose and seizure are monitored carefully, though it may be difficult with some anticonvulsive agents. The combination of ECT and lithium has been reported to cause prolonged seizures or persistent delirium [91]. However, one study of 31 patients given ECT plus lithium found that complications did not differ from those in 135 patients receiving ECT without lithium [92].

Toxicities and side effects Clozapine can cause weight gain, insulin resistance, and increased cholesterol and triglycerides, comparable to or greater than effects of olanzapine [106]. New-onset diabetes mellitus [107] and diabetic ketoacidosis [108] have been reported with clozapine. Clozapine has the potential for severe leucopenia or agranulocytosis in 1–2% of patients, especially during the first 6 months of treatment [109]. Therefore, periodic monitoring of complete blood counts is required for at least the first six months of treatment, with availability linked to peripheral neutrophil counts. The dose must be increased gradually, starting with 12.5–25 mg/day and increasing by 25–50 mg/day to reach the target dose, usually 300–450 mg/day for monotherapy, by about two weeks. Other more frequent side effects, including sialorrhea, antimuscarinic side effects and postural hypotension, have led to discontinuation in about 17% of patients in schizophrenia trials [110]. However, persistence in long-term naturalistic treatment is better than would be expected from a drug with its side-effect profile, probably due to the quality of the clinical response, severity of illness in those treated with it, lack of response to other treatments and, in add-on studies, the relatively low dose requirement [93]. Clozapine lowers the seizure threshold, with about 5% of clinical trial patients reporting seizures. At doses above about 400 mg, an anticonvulsant is often given concomitantly [110]. Pharmacokinetic interactions should be taken into account. Carbamazepine reduces clozapine levels, while valproate does not [111]. Neuroleptic malignant syndrome [112] and tardive dyskinesia [113] have both been reported with clozapine. Therefore, although clozapine is less likely to have these effects than other antipsychotics are, there is no antipsychotic treatment that is completely without risk for tardive dyskinesia or neuroleptic malignant syndrome.

Summary ECT is effective in the acute treatment of bipolar disorder when conventional treatment is not effective or usable. While there is less evidence, it may be effective in maintenance treatment under similar circumstances. It also may be a useful interim treatment, such as during pregnancy. However, long-term cognitive effects of ECT, especially when combined with other treatments, are a potential problem.

Clozapine Effectiveness Clozapine appears to be effective, sometimes as add-on treatment at moderate doses [93], in manic or mixed episodes not responsive to other treatments [94,95]. In two studies of patients refractory to other treatments, including clozapine or electroconvulsive treatment alone, patients tolerated and responded to combined clozapine and ECT [96,97]. The required dose of clozapine under these conditions appeared to be moderate, averaging 150–200 mg in add-on studies [93,96]. There is limited data on longer-term treatment; remissions persisted for three to five years in patients with severe dysphoric mania [94]. Clozapine has been studied for 48 months [98] to five years [94]. In a one-year randomized prospective add-on trial, subjects receiving clozapine had substantial improvement in ratings for general psychopathology, psychosis and mania compared to treatment as usual [99].

Summary In patients not responding to conventional treatments or combinations of them, clozapine can be effective in mania and severe impulsive aggression, sometimes with modest add-on doses of 100–200 mg/day. Clozapine may protect

Maintenance Treatment

against suicidal behaviour, though this effect has only been reported in schizophrenia [105]. Disadvantages include that, unlike ECT, it has little or no known antidepressive effects, and its metabolic effects are amongst the most severe of any psychotropic drug.

Treatment targets other than affective episodes Patients with bipolar disorder can suffer considerable impairment even when they are not having syndromal episodes of illness [3]. A few controlled studies have addressed endpoints other than depressive, manic, or mixed episodes. We will consider three significant problems associated with bipolar disorder: substance use, suicidal behaviour and cognitive impairment. Each of these is examined in detail in other chapters of this book; we will briefly review effects of commonly used maintenance treatments on these outcomes.

Substance/alcohol use Bipolar disorder has a higher prevalence of substance-use disorders than any other non-substance-related Axis I disorder. Substance use is associated with a more unstable course of illness, more suicide and violence, and poorer response to widely-used treatments. Yet, there is surprisingly little evidence that any treatment prevents or reduces substance or alcohol use in bipolar disorder. Unfortunately, individuals with substance use disorders are generally excluded from controlled maintenance trials. Results of

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pharmacological treatment studies for alcohol/substance use disorders in bipolar disorder are summarized in Table 6. Most of these studies were short-term; they suggest temporary additions to ongoing maintenance treatment rather than long-term preventive treatments. In some cases the treatments potentially effective in substance use treatment are also potentially useful for prevention of depressive or manic episodes. There are modestly positive results with anticonvulsants and uniformly negative results with second-generation antipsychotic agents, even when these treatments improved mood symptoms. In treatment of cocaine abuse in patients without bipolar disorder, positive results have been published with topiramate [114] and modafinil [115], with negative studies for olanzapine [116,117], risperidone [118], valproate [117] and carbamazepine [119]. For alcohol use, positive studies have been published with topiramate [120] and (for heavy drinking) valproate [121], an equivocal study with quetiapine [122], and largely negative studies with lithium (reviewed in [123]). In maintenance strategies for substance-related disorders in bipolar disorder, the mood-stabilizing treatment most supported by the overall sparse evidence is valproate. If conventional mood stabilizing treatments are not effective in reducing substance use, adjunctive topiramate may be useful; it has good evidence in either alcohol or cocaine use and should not have negative effects on mood stability. Cognitive behavioural relapse prevention therapies [124], perhaps especially group designs [125,126], are promising nonpharmacological interventions that may reduce substance use and improve adherence to pharmacological treatments. It may be important that nonpharmacological

Table 6 Treatment of substance abuse/dependence in subjects with bipolar disorder. Drug

Design

Duration

Outcome

Remarks

Citicholine [296]

Placebo-controlled, add-on n ¼ 44 Open-label, add-on, n ¼ 15 Open-label, add-on, n ¼ 30 and 32 Open-label add-on, n ¼ 17

12 wk

Reduced cocaine craving and frequency Reduced psychiatric symptoms and cocaine use Reduced psychiatric symptoms and cocaine craving No effect on measures of cocaine use; improved psychiatric symptoms No effect on abstinence; reduced heavy drinking Reduced substance use and improved psychiatric symptoms

Improved cognitive function

Valproate [297] Lamotrigine [298,299] Quetiapine [300]

Valproate [302] Lithium [303]

Quetiapine [298] Naltrexone [304]

Placebo-controlled, n ¼ 59 Placebo-controlled, n ¼ 20 Placebo-controlled add-on, n ¼ 102 Open-label, n ¼ 34

12 wk Up to 36 wk 12 wk

24 wk 6 wk

12 wk 16 wk

Reduced depressive symptoms; no effect on alcohol use Reduced psychiatric symptoms and alcohol use

Reduced cocaine use only in combined study Note Quetiapine abuse potential [301]

Adolescents with manic episodes and alcohol/ marijuana use

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strategies be aimed specifically at substance abuse in the context of bipolar disorder rather than substance use in general [127].

Suicidal behaviour Suicide in bipolar disorder is discussed in depth elsewhere in this book; we will consider aspects related to maintenance psychopharmacological treatment. Bipolar disorder carries a 20–30-fold increase in suicide mortality, regardless of age and gender; even in treated individuals, suicide mortality appears five-fold higher [128,129]. Risk for severe suicidal behaviour is increased with the combination of activation and depression, and is therefore maximal in mixed or activated depressive states [130,131], partially explaining the increased risk with substance-use disorders [130,132], since they are associated with mixed states and impulsivity [133]. Risk of suicide is also increased in patients with poor adherence to treatment [12]. The period of greatest risk is during or directly after depressive or mixed episodes [41].

Treatment effects on suicidal behaviour Suicidal behaviour appears to be reduced during lithium treatment, increasing when treatment is stopped [134,135]. In 32 controlled trials [136] and in longer-term observational studies [137], lithium reduced suicide and all-cause mortality. In patients who discontinued lithium treatment, the increased mortality generally associated with bipolar disorder returned [138]. Several factors complicate the interpretation of this evidence. None of the studies of suicide and treatment in bipolar disorder involved randomized treatments or designs that assured comparable treatment populations. Good response to lithium, and therefore the likelihood of remaining in treatment with lithium, is associated with characteristics that would be expected to confer relatively low risk for suicide: lack of mixed episodes, relatively infrequent episodes, and lack of substance abuse [21,22,25,139–141]. In naturalistic studies comparing two treatments, patients given the treatments may differ since clinicians will base treatment choice on clinical characteristics or previous response. Analyses of effects on suicidal behaviour in randomized clinical trials are complicated by the fact that potentially suicidal subjects are generally excluded from these trials. This important question should be addressed by a prospective, randomized study, designed in a manner where it is safe for a range of subjects to participate, such as the comparison of clozapine and olanzapine in schizophrenia where, other than the randomized treatments, subjects could have a wide range of treatments, including hospitalization [105]. Until such evidence is available, no other treatment has evidence for suicide prevention that is comparable to lithium.

Maintenance strategies for reducing suicide risk Components of a successful programme to minimize the risk for suicidal behaviour, which must be an integrated part of overall treatment, include: 1. vigorous preventive pharmacological mood-stabilizing treatment, especially emphasizing protection against activated depressive states, and combined with the education and support necessary to maximize adherence to treatment; 2. treatment of psychiatric comorbidities, especially substance use and anxiety disorders; 3. a supportive, collaborative treatment structure that includes education and support of caregivers or key individuals in the patient’s life, and careful and proactive monitoring, including detection and management of prodromal symptoms or of situations known to be problematic in the past [142]. It is noteworthy that, in patients who continued to take lithium but left lithium clinics, suicide mortality increased (though not to the extent of patients who also quit taking lithium [143]), emphasizing the role of structure and support. No strategy can eliminate suicide, but an integrated approach can reduce the risk for suicide and is the kind of approach that is necessary, in general, for the effective treatment of bipolar disorder.

Anxiety disorders Anxiety disorders, including generalized anxiety disorders, panic disorder and obsessive-compulsive disorders, are more prevalent in bipolar disorder than in any other axis I illness, including major depressive disorder; about half of patients with bipolar disorder have met criteria for at least one anxiety disorder [144,145]. Patients with combined bipolar and anxiety disorders, compared to those without anxiety disorder, have a stronger family history of bipolar illness, have earlier onset and are more likely to have histories of substance use disorders and of suicidal behaviour [146]. Young et al. reported that patients with bipolar who had high symptom ratings for anxiety, even if they did not meet criteria for an anxiety disorder, had a worse course of illness with increased suicidality and alcohol use behaviour, with a trend towards poorer response to lithium [147]. Yet, there is little information about treatment of anxiety disorders or anxiety in the context of bipolar disorder.

Treatment considerations The only placebo-controlled trial published to date in treating anxiety disorders in bipolar disorder was a negative trial of risperidone at 0.5–4 mg/day in patients who had generalized anxiety disorder or panic disorder in addition to bipolar disorder [148]. In placebo-controlled studies of depressive episodes in bipolar disorder, olanzapine or olanzepine-fluoxetine combination [149] and valproate [150] markedly reduced anxiety scores. In a single-blind 12-week

Maintenance Treatment

add-on study for patients who were receiving lithium and in remission, olanzapine (average dose about 7.5 mg) and lamotrigine (average dose about 100 mg) similarly reduced anxiety scores [151]. In patients without bipolar disorder, evidence of varying depth supports valproate (panic disorder), lamotrigine, risperidone and olanzapine (post-traumatic stress disorder), risperidone, olanzapine or quetiapine (refractory obsessive compulsive disorder) and many antidepressive agents [152]. In one report, open-label valproate improved symptoms of panic disorder in treatment-refractory patients with mood instability [153]. Antidepressants [154], or antidepressant withdrawal [155], have been reported to cause mood destabilization in patients with anxiety disorders who were not thought to have bipolar disorder. While there have been few reports involving subjects with bipolar disorder [156], cognitive behavioural therapies are effective against anxiety disorders in other subject groups, and their effects persist well beyond the period of treatment [157]. Given the potential for long-term effectiveness, the lack of pharmacokinetic interactions with ongoing treatments, and the lack of mood-destabilizing effects, cognitive behaviour therapy is a potentially attractive treatment for anxiety disorders in patients with bipolar disorder who are already receiving mood-stabilizing treatments.

Maintenance strategies for anxiety disorders or severe anxiety in bipolar disorder The clinician needs to be alert for the presence of anxiety disorders, which appear to be under-recognized [158]. Given the lack of direct evidence from controlled studies, the first pharmacological choice is to use treatments shown to be effective in other contexts that are also effective in bipolar disorder, without potential mood-destabilization. This would include lamotrigine, valproate and several atypical antipsychotics. Antidepressive agents have the most extensive body of supporting data and could be useful in patients with adequate mood-stabilizing treatment, especially if their previous illness course pattern is episodic-stable. Addition of nonpharmacological treatments such as cognitive-behavioural therapy has the potential for long-term effectiveness without complicating the patient’s pharmacological regime.

Using major treatments This section summarizes practical aspects of the most important maintenance treatments. Many relevant topics, including pharmacology of individual drugs, drug toxicities, pregnancy and weight gain, are treated in more detail elsewhere in this book. It is the purpose of this chapter to summarize information that is most salient in the context of maintenance treatment.

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Lithium Effectiveness Lithium, the first prophylactic treatment with demonstrated effectiveness in randomized trials, is remarkably versatile. It has been reported to reduce recurrences of mania or (possibly a less robust effect) depression [68,159,160] and to have the potential of reducing suicidal behaviour [161] (see above). While there are also negative studies with lithium (see Table 5), some of these were compromised by study design, especially studies in prevention of depressive episodes. Response to lithium appears to run in families [21,162] and to be strongest with an episodic-stable, rather than inherently unstable, course of illness [21,24]. Lithium may be less effective in patients who have had many episodes and who have concurrent substanceuse disorders or other complications of bipolar disorder [8,21–23,25,71]. Naturalistic studies suggest that some patients initially responding to lithium lose their response to lithium monotherapy over the ensuing 5–10 years; this effect is seen most in patients with many previous episodes [23,163]. However, other patients appear to have progressively better response to lithium with time, even after 10–15 years [164,165]. If it is necessary to stop lithium treatment, this should be done as gradually as possible, as multiple studies have shown that the incidence and severity of relapse (usually into the episode type resembling the first or the most recent episode) is worse if discontinuation is more rapid than two to four weeks [29,46]. This may be a general principle across long-term treatments [31]. If lithium is discontinued for any reason, there are reports of less satisfactory response, or nonreponse, when it is reinstated [166]. However, other larger studies suggest that, on average, patients who responded to lithium in the past will respond again, though response may worsen as time off lithium increases [167]. Patients should be encouraged to continue taking lithium if they respond well to it; long-term outcome with controlled lithium withdrawal was poor [168]. Practical pharmacokinetics Lithium is so simple that it is complicated. It has many cellular actions. Pharmacokinetically, a few principles are helpful in understanding its use. It is almost completely absorbed from the GI tract (some slow-release preparations may have reduced absorption if bowel transit time is too fast), reaching peak plasma concentrations in one to three hours [169]. Its half life is roughly 24 hours, so single daily dosing is potentially feasible [170]. It is distributed to all tissues. Concentrations in most tissues are lower than plasma levels becauseofa transmembrane lithium-sodium exchanger [171]. Concentrations in excitable cells, like neurons, are higher than in other tissues, because lithium enters through the voltage dependent sodium channel during electrical

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activity [172]. The concentration of lithium in excitable tissues continues to increase for hours after the plasma level has begun to decline [173], an important consideration with toxicity or overdose. Lithium is not metabolized (one would need a nuclear reactor) and has no appreciable protein binding. It is entirely excreted by the kidney, being filtered in the glomerulus, and partially reabsorbed in the proximal tubule. How much lithium is in the body at a given dose depends almost entirely on the rate of sodium delivery to the proximal tubule, because lithium and sodium compete for reabsorption [174]. Sodium is also reabsorbed in the distal tubule, but lithium basically is not. Increased sodium delivery to the proximal tubule, for instance from increased cardiac output, a proximal-tubule diuretic or increased sodium intake, reduces lithium reabsorption. If the patient is dehydrated or has low sodium stores, perhaps due to diuretic treatment, there is less sodium to compete with lithium, so more lithium is reabsorbed and the lithium level rises. As the lithium level approaches 3 mEq/L, it inhibits the action of aldosterone on the distal tubule, impairing reabsorption of sodium there (where lithium does not compete with sodium) and limiting sodium reabsorption to the proximal tubule where it must compete with increasing lithium concentrations. Therefore, the severity of lithium toxicity quickly accelerates at around this level [175].

Management and monitoring Lithium treatment requires therapeutic structure, and this can be beneficial in bipolar disorder. Suicidal behaviour increased in patients who left lithium clinics but kept taking lithium [143]. The structure inherent in successful lithium treatment promotes education about the illness and monitoring of its course [9,176,177]. Lithium levels can be useful in planning treatment, as well as in assuring safety. One study found that patients maintained on higher lithium levels (0.8–1.0 mEq/L) did better in terms of episodes and residual symptoms than those maintained on a lower level (0.4–0.6 mEq/L), though they also had more side effects [22]. Interpretation of these results, however, is complicated by the fact that subjects on the lower level had a rapid dose reduction at the beginning of the trial, possibly predisposing them to increased symptoms [30]. Another study reported that manic relapses were associated with lower lithium levels than depressive relapses were [178]. However, it must be remembered that lithium levels are state-dependent. Hypomania or mania is associated with increased catecholamine release, cardiac output, renal blood flow and lithium clearance, resulting in lower lithium levels [173,179,180]. If an incipient episode is detected early, the dose of lithium can be increased (if tolerated) and this potential problem can be prevented or reduced.

Toxicities and side effects Lithium has a varied profile of potential side effects that require systematic monitoring of its use. Even so, when used properly, lithium is potentially well tolerated and safe. Guscott and Taylor stressed the importance of education and monitoring, pointing out that many problems with lithium stem from noncompliance: not on the part of patients, but of clinicians [9]. The monitoring that is required for optimum treatment with lithium fosters communication between patient and physician, understanding of the patient’s illness, and the idea that the patient has responsibility for his health, rather than being the mere recipient of a treatment. This attitude is useful for all treatments, not just lithium. Major potential side effects and practical measures include: . Weight gain: Weight gain with lithium can be substantial, especially if combined with other treatments [181]. Weight gain must be managed prospectively, with a judicious programme of nutrition, activity and monitoring [182]. If necessary, addition of topiramate has been shown to reduce weight in patients receiving lithium or valproate without worsening depression or mania [183]. . Renal effects: Lithium treatment can result in progressive decline in renal function over time, due to interstitial nephropathy, though the average patient may have no longterm decline in renal function beyond normal ageing [184]. This usually insidious phenomenon (sometimes called ‘creatinine creep’) seems to occur in 20% or less of patients taking lithium for many years [185]. Prospective and retrospective studies based on biopsy evidence suggest that this problem is not related to duration of lithium treatment per se but is related to repeated episodes of lithium toxicity and to other drugs or medical conditions that affect the kidney [185–187]. If detected early, it appears to be reversible (or at least not to progress further) if lithium is discontinued; under these circumstances, lithium can be discontinued gradually while alternative treatment is substituted [188]. Sometimes a low dose of lithium can be continued. It is advisable to monitor renal function (at least with a creatinine level) at least yearly in healthy patients, more often if there is pre-existing illness that can affect the kidneys [189]. If creatinine starts to rise, further evaluation is warranted, and consultation with a nephrologist is advisable if creatinine rises above 1.6 mg/dl [189]. The importance of monitoring creatinine levels is underscored by a report that in patients discontinuing lithium with serum creatinine greater than 2.5 mg/dl, deterioration of renal function usually was progressive even after lithium discontinuation, but when creatinine was less than 2.5 mg/dl, renal function subsequently improved [188]. More commonly, lithium can cause a reversible, doserelated diabetes insipidus due to impairment of antidiuretic hormone action [190]. This can usually be managed by dose reduction or by addition of a low dose thiazide diuretic or

Maintenance Treatment

amiloride [191]. Over long periods, this condition may become less reversible, and may predispose to interstitial nephropathy and renal insufficiency by predisposing to episodes of lithium toxicity [186]. Single daily dosing may reduce these effects [170,186]: . Endocrine effects: The most common endocrine side effect of lithium is hypothyroidism, usually manifested first by increased thyroid stimulating hormone levels. Lithium treatment can usually be continued, with addition of thyroid hormone replacement [192]. Hyperparathyroidism can also occur during lithium treatment [193]. . Neurotoxicity: Lithium treatment can be associated with neurotoxicity [194,195], which can be insidious [196], is potentially related to elevated lithium levels [196] and is at least partially reversible [195,196]. It is associated with impaired neuromuscular conduction [194]. Its true incidence is difficult to determine; risk may be increased by combination with antipsychotic agents [197]. . Cardiac: cardiac problems are rare in lithium treatment, but the drug can cause reversible sinus node dysfunction, at toxic or nontoxic levels, in susceptible individuals [198]. This is thought to be a consequence of sodium channel blockade [199]. This effect may be more likely in patients who are also taking carbamazepine [200] or verapamil [201]. Hypothyroidism can also contribute to sinus node impairment with lithium [202]. Lithium has also been reported to cause, or contribute to, QTc prolongation [203]. . Dose-dependent symptomatic side effects [204]: Doserelated side effects should be watched closely for two reasons:(1) they can usually be managed, but, if ignored, can readily lead the patient to stop taking lithium (generally their worst consequence); and (2) they can be early signs that the lithium level is rising or has reached pre-toxic levels. Lithium can cause intention tremor, especially if given in combination with other tremor-inducing drugs such as serotonin reuptake inhibitors or anticonvulsants. If not manageable by dose adjustment of lithium or one of the other drugs, this can usually be ameliorated with betanoradrenergic blocking agents. Lithium can also cause stomach upset, which can be managed by dose adjustment, giving with food, or acid-reducing drugs; or diarrhoea, which can be managed by dose reduction or common antidiarrheal drugs.

Lithium and pregnancy [205] This is an important consideration in planning long-term treatment, since pregnancy is potentially an important part of life for at least half of patients with bipolar disorder. Long-term lithium can have substantial benefits, and pregnancy does not protect against episode recurrence if treatment is discontinued [206]. It is reasonable that a patient and her psychiatrist have clear communication about one of the most important decisions of her life. Lithium exposure

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during the first trimester can be associated with Ebstein’s anomaly, an otherwise rare heart defect that requires surgical correction. It is difficult to determine the actual incidence of this effect, since most data are from case-registry studies, which tend to over-report problems [207]. Later in pregnancy, lithium can cause side effects in the foetus, such as polyhydramnios from foetal nephrogenic diabetes insipidus [208]. During pregnancy, lithium clearance is increased due to the mother’s increased fluid volume, so lithium levels at the pre-pregnancy dose will be lower. At the time of delivery, because of the rapid drop in fluid volume, the lithium level can rise; therefore, it is recommended that a woman who is taking lithium stop lithium before going into labour (it she is fortunate enough to know this beforehand). Probably because of its lack of protein binding, the concentration of lithium in breast milk is relatively high [209]. Judicious planning in patients who benefit from lithium is therefore necessary. The period directly after childbirth is particularly risky in bipolar disorder; furthermore, ‘postpartum’ depressions often have onset during the third trimester [210].

Summary Lithium is effective for reducing recurrence of manic or depressive episodes in bipolar disorder. Although its effectiveness as a primary treatment may be greatest in patients with an episodic-stable course of illness and positive family history for lithium response [21,211], it is also an valuable secondary treatment. Beyond effects on mood episodes, lithium has beneficial effects on impulsive-aggressive behaviour and suicidal behaviour. The facts that it is not bound to plasma proteins or metabolized by the liver are favourable characteristics for combination treatments. Lithium use requires monitoring and structure, appropriate to using an effective drug to treat a complex illness.

Anticonvulsive treatments Valproate Effectiveness In a six-month, placebo-controlled study, fewer patients on divalproex than on placebo treatment had depressive or total episodes [212,213]. There were no differences in percent of patients having manic episodes or in time to recurrence. This study was unusual in that subjects were not required to be initially treated with valproate, though subjects were stabilized on valproate and/or lithium. In the subjects who were initially stabilized on valproate, time to manic recurrence was significantly longer than that for placebo [212]. Therefore, under usual clinical conditions, divalproex was effective in delaying relapse to mania or depression. In addition, one year of valproate treatment was equivalent to olanzapine in the incidence of recurrence [66].

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There is evidence suggesting that treatment with valproate might be effective in reducing cocaine use or heavy alcohol drinking in bipolar disorder.

Toxicities Valproate has been associated with liver failure [214] and with pancreatitis [215]. Liver failure is rare (one case per several thousand patients) except in infants or in patients with already compromised liver function [214]. Pancreatitis is a rare, idiosyncratic reaction to valproate, usually occurring early in treatment and generally recurring upon rechallenge [216]; a total of 24 cases were reported in the world literature up to 1991 [215]. Pancreatitis may be more likely in patients with risk factors (i.e. severe drinking) and valproate may exacerbate pancreatitis that has other causes. Valproate commonly reduces platelet counts during the acute phase of treatment (by
10% in the average patient); functionally significant thrombocytopenia is rare [217]. In a cohort of young women with seizure disorders, valproate treatment was associated with increased development of polycystic ovarian syndrome [218]. The authors attributed this to insulin resistance caused by weight gain. Results of subsequent studies in patients with bipolar disorder have been mixed [219,220]. Until there is a prospective, longitudinal study that is large enough to account for confounding factors and evaluate predictors of risk, treatment should be based on the patient’s clinical needs; weight control is important in young women at risk [220]. Pregnancy and childbirth During the first trimester, incidence of neural tube defects is increased (2–3%); this risk is possibly reduced, but certainly not eliminated, by folic acid treatment [221]. Risk is increased with valproate levels of over 70 ug/ml or doses over 1000 mg/day, and by combinations that include enzyme inducers or benzodiazepines [222]. The neural tube closes by day 28, when many women may not realize they are pregnant. Therefore, it is important to address the issue of pregnancy-associated risk proactively, as early in treatment as possible [221,223]. Generally it is recommended that women taking valproate take folic acid supplements, with increased folic acid around the time of conception if pregnancy on valproate is anticipated [224]. It is important, however, not to have a false sense of security because of folic acid treatment. The concentration of valproate in breast milk appears to be low, but this is based on a very small number of cases [209]. Valproate does not significantly affect circulating levels of oral contraceptive hormones [224]. Monitoring Trough valproate levels can be obtained about 12 hours after divalproex treatment. Theoretically, levels should be

obtained about 24 hours after treatment with the extended release form, but because of its smaller diurnal variation, it is adequate to obtain the level at the time most convenient to the patient, being sure to maintain a consistent pattern. Liver function and platelets should be monitored early in treatment. In healthy patients, thereafter it is generally adequate to monitor these parameters once or twice yearly, or when there is a change in drug regimen or medical status. Because pancreatitis is rare and sporadic, there is no utility in monitoring serum amylase routinely [225].

Summary Valproate is potentially effective in a wide range of presentations in bipolar disorder, including mixed states, rapid-cycling and patients with substance abuse. Results of maintenance studies suggest that valproate protects against recurrence under normal clinical circumstances, and the drug is also potentially effective against common complications of bipolar disorder, including substance- and impulsivity-related disorders [226]. Its main disadvantages are potential reproductive effects and weight gain. Lamotrigine Effectiveness Lamotrigine treatment delayed onset of need for additional treatments for depressive episodes in recently depressed [20] or manic [19] patients, and reduced the total incidence of recurrence [227], in two 18-month studies. It similarly delayed onset of need for additional treatment in bipolar II subjects with rapid-cycling in a 6-month study [65]. All of these studies used enrichment designs with the requirement that subjects were stabilized on combined treatments including lamotrigine and then remained stable for at least two weeks on lamotrigine monotherapy. This is a disadvantage since lamotrigine has never been demonstrated to be effective in acute manic episodes [228] or in preventing manic episodes [229], and has only limited supporting evidence in acute depression [230]. Therefore, patients maintained on lamotrigine will generally require initial treatment with other medicines instead of or in addition to lamotrigine, as well as combination treatment with a drug that is more effective for mania prevention. Lamotrigine has practical advantages in long-term preventive treatment of bipolar depressive episodes. It appears to be weight-neutral and rarely causes sedation. No other treatment has evidence for prevention of depressive episodes that is as consistent as that for lamotrigine, since lithium may be less effective in preventing depressive episodes in patients with index mania [231]. Lamotrigine monotherapy may have somewhat limited application in bipolar disorder, given its lack of effectiveness against mania. Recently manic subjects on lamotrigine

Maintenance Treatment

went 20 weeks before needing additional treatment, compared to 12 weeks on placebo or 42 weeks on lithium [19]. Recently depressed patients went 29 weeks on lamotrigine, 24 weeks on lithium or 13 weeks on placebo [20]. In subjects with rapid-cycling, 45% were able to complete 6 months without additional treatments [65]. Therefore, over a period of several months, most subjects needed additional medicine, no matter what monotherapy they had been assigned. It is attractive to consider lamotrigine for bipolar II disorder, where most patients are probably depression-prone [232]. The 18-month studies were in bipolar I subjects, and in the single study with bipolar II depression, effects of lamotrigine did not differ from placebo [233].

Toxicities Lamotrigine is a well-tolerated drug after the first 2 months of treatment. Lamotrigine, like many aromatic anticonvulsants (carbamazepine, barbiturates, diphenylhydantoin), can precipitate hypersensitivity reactions, possibly directed against a complex of the drug and a metabolizing enzyme [234,235]. These reactions can include severe rashes, including Stevens-Johnson syndrome and toxic epidermal necrolysis, as well as other systemic manifestations of hypersensitivity [236]. These reactions are unusual (generally around 0.1%), can be largely prevented by gradual initial dose escalation, and are more common in children or in individuals with known susceptibility to this kind of hypersensitivity (which appears to be genetic). When a person taking lamotrigine develops a rash, it is necessary to determine whether the rash is likely to progress to a severe hypersentivity reaction (these have substantial mortality) or is benign and self-limited (benign rashes outnumber severe hypersensitivity by 100 : 1). Lamotrigine should only be used if the rationale is unusually strong in patients who are at high risk (previous similar reaction to another drug, child/adolescent), and all patients should have careful discussions (and written material) about these hypersensitivity reactions. In clinical trials where the dose was escalated gradually, the rate of severe rash was extremely low [227]. The incidence of rash can be reduced by using gradual dose titration plus a set of dermatological precautions to protect against confounding rashes from other causes [237]. Using lamotrigine with other medicines Medicines that inhibit metabolism of lamotrigine can increase the likelihood of rash by accelerating initial concentrations of lamotrigine. The most widely used example of this in psychiatry is valproate [238]. The combination of valproate and lamotrigine is considered clinically useful because the drugs may have complementary effects on episode prevention that mirror their positive anticonvulsive interaction [78], and appears to be safe if this pharmacoki-

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netic interaction is compensated for [79]. Valproate essentially doubles steady-state lamotrigine levels by preventing its conjugative metabolism (usually the dominate pathway) [239]. Therefore, if lamotrigine is added to the regimen of a patient already taking valproate, the usual dosage schedule should be cut in half (i.e. 12.5 mg daily for 2 weeks, then 25 mg daily, etc.). If valproate is added to lamotrigine, the clinician should allow for the fact that, once the valproate level is above about 70 mcg/ml, the rate of lamotrigine metabolism will be halved. Therefore, a prudent tactic might be to double the dose interval before the first lamotrigine dose after valproate was added, and then continue at half the former dose [240,241]. Enzyme inducers, like carbamazepine, can reduce lamotrigine levels, and it is often recommended that the initial doses of lamotrigine be increased proportionately to compensate for this [241]. However, one should be cautious with this tactic, because enzyme inducers lower the concentration of unmetabolized drug, but they increase the concentrations of the drugenzyme complex that is presumably the target of the allergic reaction [235].

Lamotrigine in pregnancy There is no evidence for elevated rates of foetal malformations with lamotrigine [205]. However, one should not be complacent, because foetal complications are so widespread amongst anticonvulsants and the experience with lamotrigine is still relatively brief [242]. During pregnancy, lamotrigine clearance is increased so an increased dose may be necessary for successful treatment. Lamotrigine in the newborn can reach substantial blood levels and has a low clearance rate, though no problems have been associated with this [243]. Lamotrigine can lower circulating levels of oral contraceptive hormones, but not to the extent of more strongly enzyme-inducing anticonvulsants [242]. Summary Lamotrigine has strong supporting evidence for prevention of depressive episodes in subjects stabilized on lamotrigine [227]. It also has advantages in terms of tolerability, since weight gain and sedation are generally not encountered. It may be especially useful in treatment of depressionprone patients with bipolar disorder, generally as part of treatment combinations. Carbamazepine Effectiveness Carbamazepine has a wealth of experience in naturalistic trials and in comparisons to other treatments, generally lithium, but no long-term placebo-controlled maintenance trials. Evidence for effectiveness of carbamazepine is limited to mania. It may be most effective in patients with

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‘atypical’ features, who actually outnumber their ‘typical’ counterparts [71]. The general view that carbamazepine was especially effective in patients with rapid-cycling was not supported in a prospective 3-year randomized, sequential, counterbalanced comparison with lithium, where neither treatment alone was particularly effective over 12 months but the combination was significantly better [244].

Oxcarbazepine Oxcarbazepine is a congener of carbamazepine. Because its first metabolic step is reductive and does not undergo autoinduction as the corresponding step of carbamazepine metabolism does, oxcarbazepine has the potential for simpler pharmacokinetic interactions and a lower incidence of hypersensitivity reactions. These problems, most importantly the interaction with oral contraceptives (see below) still occur with oxcarbazepine, though possibly at lower rates. There is preliminary evidence for prophylactic effects, but current evidence is not adequate to determine its effectiveness [245]. In a small 12-month add-on study to lithium (total n ¼ 55), there were trends for improvement in depressive (p ¼ 0.085) and total (p ¼ 0.13) mood events [246]; the study was therefore not powered adequately to provide realistic evidence for the efficacy, or lack of efficacy, of oxcarbazepine added to lithium. Toxicities Carbamazepine can precipitate the anticonvulsive hypersensitivity syndrome described above for lamotrigine, possibly with a greater prevalence. The cause of the reaction is hypersensitivity to a complex of carbamazepine with arene oxidase, its initial degradative enzyme [235]. General treatment considerations are as discussed above for lamotrigine. In addition to skin rashes, a common result with carbamazepine is bone marrow suppression and aplastic anaemia [247]. While more insidious, reversible neutropenia can be detected by regular haematological monitoring during the first few weeks of treatment, the severe, more sudden onset of aplastic anaemia cannot, so patients must be educated to recognize potential early manifestations. Carbamazepinealsohashepaticandothertoxicitiesthatare similar to most other antiepileptic drugs [248]. Weight gain can occur with carbamazepine but is less than with valproate or lithium [249]. Neurological side effects, including diplopia, intention tremor and coordination difficulties, are relatively common during dose escalation or if levels are increased by pharmacokinetic interactions with added treatments [250]. Using carbamazepine with other drugs Because it induces cytochrome p450 3A4, carbamazepine lowers levels of most psychotropic drugs, including members of every drug class except lithium [251]. Carba-

mazepine can also lower levels of many other prescribed medicines, including oral contraceptives [252]. It is therefore important (as always) to be aware of all other medicines that a patient is taking, and to communicate regularly with other treating physicians to be sure they know the patient is receiving carbamazepine. These considerations apply equally well to any other enzyme-inducing drugs. Carbamazepine and valproate have a dual interaction [253]. Carbamazepine lowers valproate levels by inducing that portion of valproate metabolism that takes place through microsomal oxidation. This can be readily compensated for by monitoring valproate levels and increasing the dose. In addition, valproate, while it has little effect on circulating levels of carbamazepine, increases levels of an active metabolite, carbamazepine 10,11-epoxide, whose levels are not routinely measured [254]. Therefore, the carbamazepine dose may need to be reduced, based on clinical observation rather than blood levels.

Carbamazepine in pregnancy Carbamazepine, like many other anticonvulsants, is associated with increased incidence of neural tube defects, a problem that occurs during the first month of pregnancy [255]. Drug combinations that include enzyme inducers like carbamazepine may increase the likelihood of these effects over the individual drugs [222]. Summary Carbamazepine can be effective in reducing recurrence of mania, especially in patients who have a complicated course of bipolar disorder including comorbid substance use and an unstable course; predictors of response are complementary to predictors of lithium response [71], so the combination can be more useful than either drug alone in some patients [74,256]. It has never been demonstrated to prevent recurrence of depression. Its greatest use may be as part of treatment combinations (allowing for pharmacokinetic interactions) in mania-prone patients with complicated illness. Treatment guidelines generally consider it a secondline treatment [43,44]. Second-generation antipsychotic agents Effectiveness Aripiprazole, olanzapine, quetiapine, risperidone and ziprasidone all have been shown to be efficacious for treating depressive and/or manic episodes in bipolar disorder [257], and therefore are likely to be used for long-term treatment. Olanzapine [258] and aripiprazole [259] were effective against placebo in long-term prevention of episodes (Table 5). The long-acting injectable form of risperidone was effective for 2 years in a study of 10 patients [260]. Quetiapine plus lithium or valproate appeared more effective than

Maintenance Treatment

lithium or valproate alone in a 2-year study [76], but this study was enriched by a prolonged stabilization period on combination treatment, so it should be regarded as a quetiapine withdrawal study. In a 4-year naturalistic study of 232 patients with bipolar I or II disorder, quetiapine alone was associated with good outcome in 29%, lithium in 46%, valproate in 33% and lithium or valproate plus quetiapine in 78–80%. Rapid cycling subjects had favourable (but not as good as non-rapid cycler) outcomes with olanzapine [261] and favourable (difficult to compare with non-rapid cyclers) with aripiprazole [262]. Secondgeneration antipsychotics are heterogeneous in their toxicities and in their apparent effectiveness against acute depressive episodes [149,263–265]. Therefore one cannot assume that they would be equi-effective in the general prevention of episodes of bipolar disorder. Clozapine differs from other second-generation drugs in its spectrum of effectiveness and the nature of its supporting evidence, and was discussed separately above. While no peer-reviewed placebo-controlled monotherapy studies have been published, placebo-controlled maintenance studies of risperidone (long-acting injectable) and quetiapine, lasting at least 1 year, and a shorter study of adjunctive ziprasidone, have been conducted and the results have been presented in meetings. It is therefore safe to assume that, though toxicities and relative effectiveness against depression, mania and comorbid conditions may vary, second-generation antipsychotics in general can prevent recurrent episodes in bipolar disorder, at least in patients initially responding to these drugs. With long acting, injectable first-generation antipsychotic agents, there is evidence from mirror-design and naturalistic studies that long-acting forms of conventional antipsychotic agents can reduce manic recurrence in bipolar disorder; there is no evidence from randomized, controlled trials [266]. However, these drugs have the potential of increasing depressive symptoms and, possibly, suicidality [267].

Toxicities and side effects The most substantial problems related to second-generation antipsychotics are metabolic effects and effects on the secondary motor system: . Metabolic effects and weight gain: All second-generation antipsychotics can cause excessive weight gain, type II diabetes mellitus, or even new-onset diabetic ketoacidosis [268,269]. However, the incidence varies substantially across drugs. Olanzapine and clozapine have the highest incidence of these problems; quetiapine (note that the incidence may increase as higher doses are used) and risperidone are intermediate, and aripiprazole and ziprasidone have the lowest incidence (although undue complacency is ill-advised). These are potentially effective drugs but the decision to use them, as with all powerful

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medical treatments with significant potential toxicities, should be made judiciously. The key to management is early, proactive education, monitoring and efforts to foster reasonable nutrition and activity [270]. There should be a proactive strategy for controlling weight gain with specific strategies if a patient gains a threshold amount of weight. A first-line approach could be a nonpharmacological programme like Weight-Watchers; a second-line pharmacological approach might include a drug like topiramate [271], which has been shown to reduce weight gain with olanzapine [272], at least does not have mood-destabilizing properties, and can be effective in other concomitant problems in bipolar disorder. In addition to these effects on glucose metabolism and weight, second-generation antipsychotics can be associated with unfavourable lipid effects, including increases in cholesterol and triglycerides [273]. These should therefore be monitored during treatment, and approached using dietary and, if necessary, pharmacological treatments: . Movement disorders: All second-generation antipsychotics can cause acute drug-induced parkinsonism or akathisia; these effects may be more common in risperidone, aripiprazole and ziprasidone and less common in quetiapine [274]. The incidence may be substantially higher in clinical practice than that reported in clinical trials [275]. In addition to these dose-dependent, acute side effects, second-generation antipsychotic treatments can be associated with tardive dyskinesia, other tardive movement disorders like tardive dystonia and neuroleptic malignant syndrome [275]. Incidence varies across individual drugs, but all second-generation drugs, even clozapine [112,113], have convincing reports of tardive dyskinesia and neuroleptic malignant syndrome. Patients need to be aware of these possibilities from the start, so they can collaborate in effective monitoring and treatment.

Second-generation antipsychotics in pregnancy As noted above, effective treatment during and following pregnancy are highly important, and this need has to be balanced with the requirements for a safe pregnancy. There appears to be little evidence for foetal malformations associated with second-generation antipsychotic drugs [276]. Metabolic effects can be significant, including apparent increases in gestational diabetes and in weight of the newborn infant [277]. Gestational diabetes mellitus associated with olanzapine treatment, as with diabetes mellitus outside of pregnancy, can occur in the absence of drug-induced weight gain [278]. Antidepressive agents Antidepressive agents have never been shown to prevent depressive recurrence in bipolar disorder; there are seven negative trials [51]. In addition, mood destabilization appears greater during extended treatment than during

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single episodes [279], and their long-term use has been associated with cycle acceleration [280], loss of initial response [280,281] and the emergence of chronic irritability and dysphoria [282]. In a large prospective study, antidepressive drugs or placebo were added to ongoing moodstabilizing treatment in patients who developed depressive episodes; antidepressants were no more effective than placebo [283]. Yet, antidepressant use is common in bipolar disorder, and some patients appear to benefit. In a naturalistic study, Ghaemi and Goodwin reported that about 20% of outpatients benefited from addition of antidepressive to moodstabilizing treatments [284]. Altshuler et al. conducted retrospective (n ¼ 44) [53] and prospective (n ¼ 84) [52] studies, finding that patients in whom antidepressants were discontinued did worse than those in whom they were continued, with more depressions and without less mood instability. It must be kept in mind, however, that these patients:(1) had depressive episodes that had not responded to mood stabilizing treatments; (2) responded to antidepressants; and (3) tolerated antidepressants without mood instability for at least six weeks before they entered the study group. This produced a relatively rarified sample of less than 20% of the original subjects [52]. Furthermore,

there was no information about the patients’ course of illness, previous treatment responses or reasons for discontinuing antidepressant treatment. It is possible that patients who discontinued antidepressive treatments may have done so because of emerging problems or the loss of response that has been reported in bipolar disorder [280,281]. Withdrawal of antidepressant treatment can also result in manic episodes [285], even in patients taking moodstabilizing treatments [286]. There is not much information on the frequency, but one chart review found withdrawal mania in 6 of 73 cases [286]. Characteristics of the unstable form of bipolar disorder, or of a mania-prone course, may predict antidepressantrelated problems [287]. These characteristics include histories of substance-use disorders, a recent manic episode, and many previous episodes of illness.

Summary: practical maintenance pharmacological treatment Table 7 summarizes pharmacological drugs supported by evidence in bipolar disorder. Drugs, where evidence has not been published, are shown because they have demonstrated efficacy in other phases of the illness. In terms of the course

Table 7 Summary of maintenance pharmacological treatments. Treatment

Placebo-controlled RCT

Non-placebo or adjunctive RCT

Other uses

Remarks/course

Lithium

Mania (enriched or nonenriched) > Depression Mania (enriched only), Depression Depression (enriched)

General

Suicidality?

General

Substance abuse, anxiety Substance abuse, anxiety

Manic-prone, episodicstable, familial Unstable course?

Valproate Lamotrigine Carbamazepine Olanzapine Aripiprazole Quetiapine

Depression Mania

Antidepressants

Mania, Depression (enriched) Mania (enriched) Mania, Depression (enriched; abstract only) Mania, Depression (enriched; abstract only) Mania, Depression (injectable; abstract only) Only negative

Topiramate

None

Clozapine

None

Open label add on

Electroconvulsive treatment

None

Naturalistic

Ziprasidone Risperidone

Depression-prone Mania-prone, unstable course?

General Mania General

Mania-prone Depression-prone?

General (injectable) Positive continuation study

Anxiety Substance use, impulse-control disorders, weight control Impulsive-aggression; suicide?

Depression-prone, episodic stable course

Refractory mania or behavioural disturbances Refractory episodes, or other treatment not usable

Maintenance Treatment

presentations of bipolar disorder, results can be summarized as: 1 Mania-prone: Lithium, olanzapine, aripiprazole and valproate have the best published evidence, while quetiapine, ziprasidone and long-acting injectable risperidone have unpublished (abstract only) studies. 2 Depression-prone: Lamotrigine, valproate, lithium and olanzapine have the best published evidence, while quetiapine has unpublished (abstract only) evidence. 3 Episodic-stable vs. unstable course: Lithium response is strongest with episodic-stable illness, while valproate and carbamazepine may be effective in unstable illness, but evidence for relationships between response and course of illness is still sparse. For depressive episodes not responding to mood stabilizing treatments, antidepressive treatments may be best tolerated by patients with an episodic-stable course of illness. 4 Comorbidities and problems: a. Suicide: Lithium and clozapine may have antisuicide action (although effective prevention of activated depression and provision of a collaborative treatment structure are the most desirable general strategies); b. Substance use: Evidence supports topiramate and valproate, and cognitive-behavioural relapse prevention treatments; c. Anxiety disorders: Sparse evidence supports lamotrigine, valproate and cognitive-behavioural therapy; d. Weight gain: proactive management; topiramate is probably the best-proven pharmacological option. 5 Combination treatments: drugs with compatible pharmacokinetics and complementary mechanisms: lithium, valproate or lamotrigine with each other or with a secondgeneration antipsychotic, depending on course of illness and side-effect profile; 6 Treatment-refractory patients: clozapine (mania, impulsive-aggressiveness, suicidality); electroconvulsive treatment (depressive, mania, or mixed). Integrated nonpharmacological treatment is, for most patients, a vital part of optimal treatment; psychoeducation groups for caregivers appear to be a highly efficient strategy. In this context, collaborative, prospective monitoring of life events and prodromal or emergent subsyndromal symptoms is a vital part of treatment that can reduce recurrence of illness and provide the patient with the tools for collaborative mastery of the illness.

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Maintenance Treatment 252. Murialdo, G., Galimberti, C.A., Gianelli, M.V. et al. (1998) Effects of valproate, phenobarbital, and carbamazepine on sex steroid setup in women with epilepsy. Clin. Neuropharmacol., 21 (1), 52–58. 253. Wilder, B.J. (1992) Pharmacokinetics of valproate and carbamazepine. J. Clin. Psychopharmacol., 12 (Suppl.), 64S–68. 254. Chang, S.L. and Levy, R.H. (1986) Inhibitory effect of valproic acid on the disposition of carbamazepine and carbamazepine-10,11-epoxide in the rat. Drug Metab. Dispos., 14 (3), 281–286. 255. Jones, K.L., Lacro, R.V., Johnson, K.A. and Adams, J. (1989) Pattern of malformations in the children of women treated with carbamazepine during pregnancy. N. Engl. J. Med., 320, 1661–1666. 256. Baethge, C., Baldessarini, R.J., Mathiske-Schmidt, K. et al. (2005) Long-term combination therapy versus monotherapy with lithium and carbamazepine in 46 bipolar I patients. J. Clin. Psychiatry, 66 (2), 174–182. 257. Scherk, H., Pajonk, F.G. and Leucht, S. (2007) Second-generation antipsychotic agents in the treatment of acute mania: a systematic review and meta-analysis of randomized controlled trials. Arch. Gen. Psychiatry, 64 (4), 442–455. 258. Tohen, M., Calabrese, J.R., Sachs, G.S. et al. (2006) Randomized, placebo-controlled trial of olanzapine as maintenance therapy in patients with bipolar I disorder responding to acute treatment with olanzapine. Am. J. Psychiatry, 163 (2), 247–256. 259. Keck, P.E. Jr, Calabrese, J.R., McIntyre, R.S. et al. (2007) Aripiprazole monotherapy for maintenance therapy in bipolar I disorder: a 100-week, double-blind study versus placebo. J. Clin. Psychiatry, 68 (10), 1480–1491. 260. Malempati, R.N., Bond, D.J. and Yatham, L.N. (2008) Depot risperidone in the outpatient management of bipolar disorder: a 2-year study of 10 patients. Int. Clin. Psychopharmacol., 23 (2), 88–94. 261. Vieta, E., Calabrese, J.R., Hennen, J. et al. (2004) Comparison of rapid-cycling and non-rapid-cycling bipolar I manic patients during treatment with olanzapine: analysis of pooled data. J. Clin. Psychiatry, 65 (10), 1420–1428. 262. Muzina, D.J., Momah, C., Eudicone, J.M. et al. (2008) Aripiprazole monotherapy in patients with rapid-cycling bipolar I disorder: an analysis from a long-term, double-blind, placebo-controlled study. Int. J. Clin. Pract., 62 (5), 679–687. 263. Calabrese, J.R., Keck, P.E. Jr, Macfadden, W. et al. (2005) A randomized, double-blind, placebo-controlled trial of quetiapine in the treatment of bipolar I or II depression. Am. J. Psychiatry, 162 (7), 1351–1360. 264. Tohen, M., Vieta, E., Calabrese, J. et al. (2003) Efficacy of olanzapine and olanzapine-fluoxetine combination in the treatment of bipolar I depression. Arch. Gen. Psychiatry, 60 (11), 1079–1088. 265. Thase, M.E., Jonas, A., Khan, A. et al. (2008) Aripiprazole monotherapy in nonpsychotic bipolar I depression: results of 2 randomized, placebo-controlled studies. J. Clin. Psychopharmacol., 28 (1), 13–20. 266. El-Mallakh, R.S. (2007) Medication adherence and the use of long-acting antipsychotics in bipolar disorder. J. Psychiatr. Pract., 13 (2), 79–85.

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267. Bond, D.J., Pratoomsri, W. and Yatham, L.N. (2007) Depot antipsychotic medications in bipolar disorder: a review of the literature. Acta Psychiatr. Scand. Suppl. (434), 3–16. 268. McIntyre, R.S., Mancini, D.A., Basile, V.S. et al. (2003) Antipsychotic-induced weight gain: bipolar disorder and leptin. J. Clin. Psychopharmacol., 23 (4), 323–327. 269. Birt, J. (2003) Management of weight gain associated with antipsychotics. Ann. Clin. Psychiatry, 15 (1), 49–58. 270. Poulin, M.J., Chaput, J.P., Simard, V. et al. (2007) Management of antipsychotic-induced weight gain: prospective naturalistic study of the effectiveness of a supervised exercise programme. Aust. NZ J. Psychiatry, 41 (12), 980–989. 271. McIntyre, R.S., Mancini, D.A., 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., 4 (3), 207–213. 272. Vieta, E., Sanchez-Moreno, J., Goikolea, J.M. et al. (2004) Effects on weight and outcome of long-term olanzapinetopiramate combination treatment in bipolar disorder. J. Clin. Psychopharmacol., 24 (4), 374–378. 273. Almeras, N., Despres, J.P., Villeneuve, J. et al. (2004) Development of an atherogenic metabolic risk factor profile associated with the use of atypical antipsychotics. J. Clin. Psychiatry, 65 (4), 557–564. 274. Gao, K., Kemp, D.E., Ganocy, S.J. et al. (2008) Antipsychoticinduced extrapyramidal side effects in bipolar disorder and schizophrenia: a systematic review. J. Clin. Psychopharmacol., 28 (2), 203–209. 275. Ghaemi, S.N., Hsu, D.J., Rosenquist, K.J. et al. (2006) Extrapyramidal side effects with atypical neuroleptics in bipolar disorder. Prog. Neuropsychopharmacol. Biol. Psychiatry, 30 (2), 209–213. 276. McKenna, K., Koren, G., Tetelbaum, M. et al. (2005) Pregnancy outcome of women using atypical antipsychotic drugs: a prospective comparative study. J. Clin. Psychiatry, 66 (4), 444–449. 277. Newham, J.J., Thomas, S.H., Macritchie, K. et al. (2008) Birth weight of infants after maternal exposure to typical and atypical antipsychotics: prospective comparison study. Br. J. Psychiatry, 192 (5), 333–337. 278. Vemuri, M.P. and Rasgon, N.L. (2007) A case of olanzapineinduced gestational diabetes mellitus in the absence of weight gain. J. Clin. Psychiatry, 68 (12), 1989. 279. Post, R.M., Leverich, G.S., Nolen, W.A. et al. (2003) A reevaluation of the role of antidepressants in the treatment of bipolar depression: data from the Stanley Foundation Bipolar Network. Bipolar Disord., 5 (6), 396–406. 280. Fava, G.A. (2003) Can long-term treatment with antidepressant drugs worsen the course of depression? J. Clin. Psychiatry, 64 (2), 123–133. 281. Sharma, V. (2001) Loss of response to antidepressants and subsequent refractoriness: diagnostic issues in a retrospective case series. J. Affect. Disord., 64 (1), 99–106. 282. Ei-Mallakh, R.S. and Karippot, A. (2005) Antidepressantassociated chronic irritable dysphoria (acid) in bipolar disorder: a case series. J. Affect. Disord., 84 (2–3), 267–272.

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Rapid Cycling Bipolar Disorder: Phenomenology and Treatment Joseph F. Goldberg1 and Michael Berk2 1 2

Mount Sinai School of Medicine, New York, NY, USA Barwon Health and the Geelong Clinic, University of Melbourne, Victoria, Australia

The construct of rapid cycling has received considerable attention ever since Dunner and Fieve [1] first coined the term to describe bipolar disorder patients with a poor response to long-term lithium therapy. In its original definition – and as stillreflectedinDSM-IVTR– rapidcyclingpertainedtofouror more distinct episodes of mania or depression in a preceding 12-month period. From that definition, numerous controversies and clinical uncertainties have arisen: is rapid cycling transient (state-like) or persistent (trait-like)? Does it arise early or late in the course of bipolar disorder? Concordant with the staging model, is it a marker of the later and more refractory stageofthe disorder?Is polarity change a necessary component of rapid cycling, or is there more often proneness for a single polarity (e.g. depression) to recur with high frequency? How commonly is rapid cycling a consequence ofantidepressantuse(i.e.iatrogenic)?Howdoesrapidcycling differ from a mixed episode? How important are DSM-IV criteria for defining rapid cycling with respect to the need for duration criteria for defining a full affective episode, or for delineating newepisodes (i.e.frequent relapses within a year) from single episodes that merely wax and wane due to incomplete recovery? What is the boundary between rapid cycling and the mood lability seen in borderline personality disorder? And perhaps most essentially, what treatments are most versus least useful in the presence of rapid cycling? This chapter will attempt to address these and other related questions regarding the phenomenology and treatment of rapid cycling in bipolar disorder, with a focus on issues most relevant to practical diagnosis and management.

Controversies regarding the definition of rapid cycling Although Dunner and Fieve [1] originally defined rapid cycling based on the presence of frequent syndromes per

Bipolar Disorder: Clinical and Neurobiological Foundations Edited by Lakshmi N. Yatham and Mario Maj © 2010 John Wiley & Sons, Ltd. ISBN: 978-0-470-72198-8

year, other investigators have emphasized the clinical importance of mood oscillations per se (rather than frequent syndromes with requisite associated criteria) – thus emphasizing polarity change rather than high recurrence regardless of polarity – as a nosologically valid and clinically relevant construct. Kramlinger and Post (1996) [2] described the phenomenon of mood states that shifted in polarity over the course of weeks to days (‘ultra-rapid cycling’) to distinct mood shifts that occurred within a day (‘ultra-ultra rapid’ or ‘ultradian’ cycling). Problematic with such conceptualizations is their phenomenologic overlap with the World Health Organization (WHO) construct of mixed episodes, which can include the ‘rapid alternation (i.e. within a few hours) of hypomanic, manic and depressive symptoms’ over at least a two-week period [3]. This similarly overlaps with the mood instability that is core to the borderline construct [4]. It can be very difficult to separate out the mood lability of borderline personality organization from that of rapid cycling. This is not helped by high rates of overlapping risk factors such as sexual abuse, nor by the high rates of comorbidity that exist between the two conditions. The clinical imperative to do so is however self evident, due to the divergent treatment approaches implied by a dichotomous diagnosis. Separate from the qualitative symptoms of rapid cycling (i.e. distinct polarity changes as per DSM-IVTR vs. rapid alternations of affective symptoms per ICD-10) lies ongoing debate over the minimally relevant time duration of symptoms to constitute an ‘episode’. Maj and colleagues [5] observed high inter-rater reliability amongst psychiatrists in identifying distinct clinical states involving four or more episodes per year that included relaxed criteria for the duration of episodes. In order to clarify the controversy regarding the diagnosis of rapid cycling, the International Society of Bipolar Disorders commissioned a review of the diagnostic criteria for rapid cycling. The working group concluded that: ‘while episode cycling can be conceptualized as a dimensional phenomenon between the extremes of no cycling and

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continuous ultradian cycling, there is insufficient new evidence to modify the existing DSM-IV definition of rapid cycling in a manner that would be less arbitrary’ [6]. The staging model proposes that bipolar disorder has a characteristic trajectory, from an at-risk phase, through the prodrome, to a first episode, followed by the characteristic cycle of recurrence and relapse, which frequently shows an accelerating pattern, and the subsequent emergence of a phase of treatment resistance in a few individuals. Rapid cycling is considered to be a component of the latter, fourth stage of the disorder [8,67].

Phenomenology There is inconsistent data on the prevalence of rapid cycling in patients with bipolar disorder. An overall prevalence of 16.3%, with a range between 12 and 24% was described in a meta-analysis, which included patients consecutively admitted to an inpatient or outpatient facility without a priori selection of rapid cycling or matching with controls without rapid cycling [9]. Rapid cycling may have increased in prevalence in recent years, particularly in inpatient settings [10]. There are many explanations for this, from sampling bias (studies of patients in specialized centres), increased recognition after the inclusion of rapid cycling in the DSM-IV and the publication of key papers highlighting rapid cycling, or it may reflect a true increased prevalence, due to widespread treatment with antidepressants and greater prevalence of substance use [11]. In 1742 subjects from the National Institute of Mental Health Systematic Treatment Enhancement Programme for Bipolar Disorder (NIMH STEP-BD), the incidence of prospectively-observed rapid cycling (as defined by DSM-IV) over a two-year period was only 5% [12], in contrast to a much higher retrospectively-report